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17 pages, 3986 KB  
Article
Miniature Multi-Target Tracking in Sonar Images Using Dual Trajectory Storage Method
by Zhen Huang, Peizhen Zhang, Rui Wang, Xiaoyan Xian, Qi Wang, Jiayu Hu and Qinyu Wu
J. Mar. Sci. Eng. 2026, 14(6), 568; https://doi.org/10.3390/jmse14060568 - 19 Mar 2026
Abstract
To address the conflict between trajectory fragmentation and the trade-off between association efficiency and data integrity in underwater micro-scale multi-target sonar motion detection and tracking in video sequences, a multi-target motion detection and tracking algorithm based on a dual trajectory storage mechanism and [...] Read more.
To address the conflict between trajectory fragmentation and the trade-off between association efficiency and data integrity in underwater micro-scale multi-target sonar motion detection and tracking in video sequences, a multi-target motion detection and tracking algorithm based on a dual trajectory storage mechanism and adaptive trajectory association is proposed. The method first obtains target centroids through Gaussian mixture model foreground extraction, morphological post-processing, and connected region analysis. By employing a dual-storage structure consisting of real-time trajectories and complete trajectories, it dynamically adjusts association thresholds based on frame sampling rates to achieve adaptive distance calculation for trajectory tracking. Experimental results demonstrate that the proposed method achieves a completeness rate of 100% in recording valid trajectory point lengths. The adaptive threshold mechanism improves association accuracy to 96.07% while reducing trajectory fragmentation rate to 0.9%. The average association time is 0.28 ms per frame, enabling efficient real-time association while ensuring the integrity of motion trajectory tracking. This research contributes to enhancing real-time detection and tracking capabilities for micro-scale underwater targets and provides support for applications such as underwater security surveillance, marine resource exploration, and intelligent autonomous underwater vehicle navigation. Full article
(This article belongs to the Section Physical Oceanography)
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26 pages, 3122 KB  
Article
A 94 GHz Millimeter-Wave Radar System for Remote Vehicle Height Measurement to Prevent Bridge Collisions
by Natan Steinmetz, Eyal Magori, Yael Balal, Yonatan B. Sudai and Nezah Balal
Sensors 2026, 26(6), 1921; https://doi.org/10.3390/s26061921 - 18 Mar 2026
Viewed by 45
Abstract
Collisions between over-height vehicles and low-clearance bridges cause infrastructure damage and pose safety risks. Existing detection systems rely primarily on optical sensors, which suffer from performance degradation in adverse weather conditions. This paper presents an alternative approach based on a 94 GHz millimeter-wave [...] Read more.
Collisions between over-height vehicles and low-clearance bridges cause infrastructure damage and pose safety risks. Existing detection systems rely primarily on optical sensors, which suffer from performance degradation in adverse weather conditions. This paper presents an alternative approach based on a 94 GHz millimeter-wave radar that achieves velocity-independent height measurement. The proposed technique exploits the ratio of Doppler shifts from two scattering centers on a vehicle, specifically the roof and the wheel–road interface. This ratio depends only on the measurement geometry, as the unknown vehicle velocity cancels algebraically, enabling direct height computation without speed measurement. The paper provides a closed-form height estimation model, analyzes the trade-off between frequency resolution and geometric constancy during integration, and presents experimental validation using a scaled laboratory testbed. An optical tracking system is used solely for ground-truth validation in the laboratory and is not required for operational deployment. Results across six test cases with heights ranging from 20 cm to 46 cm demonstrate an average absolute error of 0.60 cm and relative errors below 3.3 percent. A scaling analysis for representative full-scale geometries indicates that at highway speeds of 80 km/h, integration times in the millisecond range (approximately 3–18 ms for representative 20–50 m measurement standoff) are feasible; warning distance can be extended independently by upstream radar placement. The expected advantage in fog, rain, and dust is based on established W-band propagation characteristics; dedicated adverse-weather and full field validation (including multipath, clutter, and multi-vehicle scenarios) remain future work. Full article
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12 pages, 1019 KB  
Proceeding Paper
Intelligent Drone Patrolling with Real-Time Object Detection and GPS-Based Path Adaptation
by Gurugubelli V. S. Narayana, Shiba Prasad Swain, Debabrata Pattnayak, Manas Ranjan Pradhan and P. Ankit Krishna
Eng. Proc. 2026, 124(1), 82; https://doi.org/10.3390/engproc2026124082 - 18 Mar 2026
Viewed by 86
Abstract
Background: The need for autonomous aerial surveillance originates from weaknesses in manual monitoring, such as late response, low scalability and rigid patrol plans. AI and GPS-driven smart aerial monitoring present an attractive solution for continuous adaptive wide-area surveillance. Objective: In this paper, we [...] Read more.
Background: The need for autonomous aerial surveillance originates from weaknesses in manual monitoring, such as late response, low scalability and rigid patrol plans. AI and GPS-driven smart aerial monitoring present an attractive solution for continuous adaptive wide-area surveillance. Objective: In this paper, we aim at designing and validating experimentally a low-cost drone-based unmanned autonomous mission patrolling system with waypoint navigation, real-time video backhauling, AI-based human/object detection and GPS path re-planning when an event occurs to ensure the safety of patrol missions under battery constraints. Methods: The proposed architecture combines autonomous navigation and embedded flight-control with online analog video streaming and ground-station-based computer vision processing. Object detection based on deep learning for live aerial video is used, and the proposed system’s performance is tested at different altitudes, lighting states and GPS patrol plans. Results: Experimental results show that the proposed method can obtain stable waypoint tracking with a clear real-time video downlink in patrol missions. The system is able to adaptively modify paths as a reaction to detected events and commence safe return-to-home functionality during low-battery conditions. The proposed detection model obtains a mean average precision of 87.4%, with an F1-score of 0.89 and real-time inference latency (20–25 ms per frame) that enables fast service without any interruption in practice during surveillance deployment. Conclusions: Experimental results show that the proposed method can obtain stable waypoint tracking with a clear real-time video downlink in patrol missions. The system can adaptively modify paths as a reaction to detected events and commence safe return-to-home functionality during low-battery conditions. The proposed detection model obtains a mean average precision of 87.4%, with an F1-score of 0.89 and real-time inference latency (20–25 ms per frame) that enables fast service without any interruption in practice during surveillance deployment. Full article
(This article belongs to the Proceedings of The 6th International Electronic Conference on Applied Sciences)
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33 pages, 35113 KB  
Article
Operation of a Modular 3D-Pixelated Liquid Argon Time-Projection Chamber in a Neutrino Beam
by S. Abbaslu, A. Abed Abud, R. Acciarri, L. P. Accorsi, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, C. Adriano, F. Akbar, F. Alemanno, N. S. Alex, K. Allison, M. Alrashed, A. Alton, R. Alvarez, T. Alves, A. Aman, H. Amar, P. Amedo, J. Anderson, D. A. Andrade, C. Andreopoulos, M. Andreotti, M. P. Andrews, F. Andrianala, S. Andringa, F. Anjarazafy, S. Ansarifard, D. Antic, M. Antoniassi, A. Aranda-Fernandez, L. Arellano, E. Arrieta Diaz, M. A. Arroyave, M. Arteropons, J. Asaadi, M. Ascencio, A. Ashkenazi, D. Asner, L. Asquith, E. Atkin, D. Auguste, A. Aurisano, V. Aushev, D. Autiero, D. Ávila Gómez, M. B. Azam, F. Azfar, A. Back, J. J. Back, Y. Bae, I. Bagaturia, L. Bagby, D. Baigarashev, S. Balasubramanian, A. Balboni, P. Baldi, W. Baldini, J. Baldonedo, B. Baller, B. Bambah, F. Barao, D. Barbu, G. Barenboim, P. B̃arham Alzás, G. J. Barker, W. Barkhouse, G. Barr, A. Barros, N. Barros, D. Barrow, J. L. Barrow, A. Basharina-Freshville, A. Bashyal, V. Basque, M. Bassani, D. Basu, C. Batchelor, L. Bathe-Peters, J. B. R. Battat, F. Battisti, J. Bautista, F. Bay, J. L. L. Bazo Alba, J. F. Beacom, E. Bechetoille, B. Behera, E. Belchior, B. Bell, G. Bell, L. Bellantoni, G. Bellettini, V. Bellini, O. Beltramello, A. Belyaev, C. Benitez Montiel, D. Benjamin, F. Bento Neves, J. Berger, S. Berkman, J. Bermudez, J. Bernal, P. Bernardini, A. Bersani, E. Bertholet, E. Bertolini, S. Bertolucci, M. Betancourt, A. Betancur Rodríguez, Y. Bezawada, A. T. Bezerra, A. Bhat, V. Bhatnagar, M. Bhattacharjee, S. Bhattacharjee, M. Bhattacharya, S. Bhuller, B. Bhuyan, S. Biagi, J. Bian, K. Biery, B. Bilki, M. Bishai, A. Blake, F. D. Blaszczyk, G. C. Blazey, E. Blucher, B. Bogart, J. Boissevain, S. Bolognesi, T. Bolton, L. Bomben, M. Bonesini, C. Bonilla-Diaz, A. Booth, F. Boran, R. Borges Merlo, N. Bostan, G. Botogoske, B. Bottino, R. Bouet, J. Boza, J. Bracinik, B. Brahma, D. Brailsford, F. Bramati, A. Branca, A. Brandt, J. Bremer, S. J. Brice, V. Brio, C. Brizzolari, C. Bromberg, J. Brooke, A. Bross, G. Brunetti, M. B. Brunetti, N. Buchanan, H. Budd, J. Buergi, A. Bundock, D. Burgardt, S. Butchart, G. Caceres V., R. Calabrese, R. Calabrese, J. Calcutt, L. Calivers, E. Calvo, A. Caminata, A. F. Camino, W. Campanelli, A. Campani, A. Campos Benitez, N. Canci, J. Capó, I. Caracas, D. Caratelli, D. Carber, J. M. Carceller, G. Carini, B. Carlus, M. F. Carneiro, P. Carniti, I. Caro Terrazas, H. Carranza, N. Carrara, L. Carroll, T. Carroll, A. Carter, E. Casarejos, D. Casazza, J. F. Castaño Forero, F. A. Castaño, C. Castromonte, E. Catano-Mur, C. Cattadori, F. Cavalier, F. Cavanna, S. Centro, G. Cerati, C. Cerna, A. Cervelli, A. Cervera Villanueva, J. Chakrani, M. Chalifour, A. Chappell, A. Chatterjee, B. Chauhan, C. Chavez Barajas, H. Chen, M. Chen, W. C. Chen, Y. Chen, Z. Chen, D. Cherdack, S. S. Chhibra, C. Chi, F. Chiapponi, R. Chirco, N. Chitirasreemadam, K. Cho, S. Choate, G. Choi, D. Chokheli, P. S. Chong, B. Chowdhury, D. Christian, M. Chung, E. Church, M. F. Cicala, M. Cicerchia, V. Cicero, R. Ciolini, P. Clarke, G. Cline, A. G. Cocco, J. A. B. Coelho, A. Cohen, J. Collazo, J. Collot, H. Combs, J. M. Conrad, L. Conti, T. Contreras, M. Convery, K. Conway, S. Copello, P. Cova, C. Cox, L. Cremonesi, J. I. Crespo-Anadón, M. Crisler, E. Cristaldo, J. Crnkovic, G. Crone, R. Cross, A. Cudd, C. Cuesta, Y. Cui, F. Curciarello, D. Cussans, J. Dai, O. Dalager, W. Dallaway, R. D’Amico, H. da Motta, Z. A. Dar, R. Darby, L. Da Silva Peres, Q. David, G. S. Davies, S. Davini, J. Dawson, R. De Aguiar, P. Debbins, M. P. Decowski, A. de Gouvêa, P. C. De Holanda, P. De Jong, P. Del Amo Sanchez, G. De Lauretis, A. Delbart, M. Delgado, A. Dell’Acqua, G. Delle Monache, N. Delmonte, P. De Lurgio, R. Demario, G. De Matteis, J. R. T. de Mello Neto, A. P. A. De Mendonca, D. M. DeMuth, S. Dennis, C. Densham, P. Denton, G. W. Deptuch, A. De Roeck, V. De Romeri, J. P. Detje, J. Devine, K. Dhanmeher, R. Dharmapalan, M. Dias, A. Diaz, J. S. Díaz, F. Díaz, F. Di Capua, A. Di Domenico, S. Di Domizio, S. Di Falco, L. Di Giulio, P. Ding, L. Di Noto, E. Diociaiuti, G. Di Sciascio, V. Di Silvestre, C. Distefano, R. Di Stefano, R. Diurba, M. Diwan, Z. Djurcic, S. Dolan, M. Dolce, M. J. Dolinski, D. Domenici, S. Dominguez, S. Donati, S. Doran, D. Douglas, T. A. Doyle, F. Drielsma, D. Duchesneau, K. Duffy, K. Dugas, P. Dunne, B. Dutta, D. A. Dwyer, A. S. Dyshkant, S. Dytman, M. Eads, A. Earle, S. Edayath, D. Edmunds, J. Eisch, W. Emark, P. Englezos, A. Ereditato, T. Erjavec, C. O. Escobar, J. J. Evans, E. Ewart, A. C. Ezeribe, K. Fahey, A. Falcone, M. Fani’, D. Faragher, C. Farnese, Y. Farzan, J. Felix, Y. Feng, M. Ferreira da Silva, G. Ferry, E. Fialova, L. Fields, P. Filip, A. Filkins, F. Filthaut, G. Fiorillo, M. Fiorini, S. Fogarty, W. Foreman, J. Fowler, J. Franc, K. Francis, D. Franco, J. Franklin, J. Freeman, J. Fried, A. Friedland, M. Fucci, S. Fuess, I. K. Furic, K. Furman, A. P. Furmanski, R. Gaba, A. Gabrielli, A. M Gago, F. Galizzi, H. Gallagher, M. Galli, N. Gallice, V. Galymov, E. Gamberini, T. Gamble, R. Gandhi, S. Ganguly, F. Gao, S. Gao, D. Garcia-Gamez, M. Á. García-Peris, S. Gardiner, A. Gartman, A. Gauch, P. Gauzzi, S. Gazzana, G. Ge, N. Geffroy, B. Gelli, S. Gent, L. Gerlach, A. Ghosh, T. Giammaria, D. Gibin, I. Gil-Botella, A. Gioiosa, S. Giovannella, A. K. Giri, V. Giusti, D. Gnani, O. Gogota, S. Gollapinni, K. Gollwitzer, R. A. Gomes, L. S. Gomez Fajardo, D. Gonzalez-Diaz, J. Gonzalez-Santome, M. C. Goodman, S. Goswami, C. Gotti, J. Goudeau, C. Grace, E. Gramellini, R. Gran, P. Granger, C. Grant, D. R. Gratieri, G. Grauso, P. Green, S. Greenberg, W. C. Griffith, K. Grzelak, L. Gu, W. Gu, V. Guarino, M. Guarise, R. Guenette, M. Guerzoni, D. Guffanti, A. Guglielmi, F. Y. Guo, A. Gupta, V. Gupta, G. Gurung, D. Gutierrez, P. Guzowski, M. M. Guzzo, S. Gwon, A. Habig, L. Haegel, R. Hafeji, L. Hagaman, A. Hahn, J. Hakenmüller, T. Hamernik, P. Hamilton, J. Hancock, M. Handley, F. Happacher, B. 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Mavrokoridis, I. Mawby, F. Mayhew, T. McAskill, N. McConkey, B. McConnell, K. S. McFarland, C. McGivern, C. McGrew, A. McNab, C. McNulty, J. Mead, L. Meazza, V. C. N. Meddage, A. Medhi, M. Mehmood, B. Mehta, P. Mehta, F. Mei, P. Melas, L. Mellet, T. C. D. Melo, O. Mena, H. Mendez, D. P. Méndez, A. Menegolli, G. Meng, A. C. E. A. Mercuri, A. Meregaglia, M. D. Messier, S. Metallo, W. Metcalf, M. Mewes, H. Meyer, T. Miao, J. Micallef, A. Miccoli, G. Michna, R. Milincic, F. Miller, G. Miller, W. Miller, A. Minotti, L. Miralles Verge, C. Mironov, S. Miscetti, C. S. Mishra, P. Mishra, S. R. Mishra, D. Mladenov, I. Mocioiu, A. Mogan, R. Mohanta, T. A. Mohayai, N. Mokhov, J. Molina, L. Molina Bueno, E. Montagna, A. Montanari, C. Montanari, D. Montanari, D. Montanino, L. M. Montaño Zetina, M. Mooney, A. F. Moor, M. Moore, Z. Moore, D. Moreno, G. Moreno-Granados, O. Moreno-Palacios, L. Morescalchi, C. Morris, E. Motuk, C. A. Moura, G. Mouster, W. Mu, L. Mualem, J. Mueller, M. Muether, A. Muir, Y. Mukhamejanov, A. Mukhamejanova, M. Mulhearn, D. Munford, L. J. Munteanu, H. Muramatsu, J. Muraz, M. Murphy, T. Murphy, A. Mytilinaki, J. Nachtman, Y. Nagai, S. Nagu, D. Naples, S. Narita, J. Nava, A. Navrer-Agasson, N. Nayak, M. Nebot-Guinot, A. Nehm, J. K. Nelson, O. Neogi, J. Nesbit, M. Nessi, D. Newbold, M. Newcomer, D. Newmark, R. Nichol, F. Nicolas-Arnaldos, A. Nielsen, A. Nikolica, J. Nikolov, E. Niner, X. Ning, K. Nishimura, A. Norman, A. Norrick, P. Novella, A. Nowak, J. A. Nowak, M. Oberling, J. P. Ochoa-Ricoux, S. Oh, S. B. Oh, A. Olivier, T. Olson, Y. Onel, Y. Onishchuk, A. Oranday, M. Osbiston, J. A. Osorio Vélez, L. O’Sullivan, L. Otiniano Ormachea, L. Pagani, G. Palacio, O. Palamara, S. Palestini, J. M. Paley, M. Pallavicini, C. Palomares, S. Pan, M. Panareo, P. Panda, V. Pandey, W. Panduro Vazquez, E. Pantic, V. Paolone, A. Papadopoulou, R. Papaleo, D. Papoulias, S. Paramesvaran, J. Park, S. Parke, S. Parsa, S. Parveen, M. Parvu, D. Pasciuto, S. Pascoli, L. Pasqualini, J. Pasternak, G. Patel, J. L. Paton, C. Patrick, L. Patrizii, R. B. Patterson, T. Patzak, A. Paudel, J. Paul, L. Paulucci, Z. Pavlovic, G. Pawloski, D. Payne, A. Peake, V. Pec, E. Pedreschi, S. J. M. Peeters, W. Pellico, E. Pennacchio, A. Penzo, O. L. G. Peres, Y. F. Perez Gonzalez, L. Pérez-Molina, C. Pernas, J. Perry, D. Pershey, G. Pessina, G. Petrillo, C. Petta, R. Petti, M. Pfaff, V. Pia, G. M. Piacentino, L. Pickering, L. Pierini, F. Pietropaolo, V. L. Pimentel, G. Pinaroli, S. Pincha, J. Pinchault, K. Pitts, P. Plesniak, K. Pletcher, K. Plows, C. Pollack, T. Pollmann, F. Pompa, X. Pons, N. Poonthottathil, V. Popov, F. Poppi, J. Porter, L. G. Porto Paixão, M. Potekhin, M. Pozzato, R. Pradhan, T. Prakash, M. Prest, F. Psihas, D. Pugnere, D. Pullia, X. Qian, J. Queen, J. L. Raaf, M. Rabelhofer, V. Radeka, J. Rademacker, F. Raffaelli, A. Rafique, A. Rahe, S. Rajagopalan, M. Rajaoalisoa, I. Rakhno, L. Rakotondravohitra, M. A. Ralaikoto, L. Ralte, M. A. Ramirez Delgado, B. Ramson, S. S. Randriamanampisoa, A. Rappoldi, G. Raselli, T. Rath, P. Ratoff, R. Ray, H. Razafinime, R. F. Razakamiandra, E. M. Rea, J. S. Real, B. Rebel, R. Rechenmacher, J. Reichenbacher, S. D. Reitzner, E. Renner, S. Repetto, S. Rescia, F. Resnati, C. Reynolds, M. Ribas, S. Riboldi, C. Riccio, G. Riccobene, J. S. Ricol, M. Rigan, A. Rikalo, E. V. Rincón, A. Ritchie-Yates, D. Rivera, A. Robert, A. Roberts, E. Robles, M. Roda, D. Rodas Rodríguez, M. J. O. Rodrigues, J. Rodriguez Rondon, S. Rosauro-Alcaraz, P. Rosier, D. Ross, M. Rossella, M. Ross-Lonergan, T. Rotsy, N. Roy, P. Roy, P. Roy, C. Rubbia, D. Rudik, A. Ruggeri, G. Ruiz Ferreira, K. Rushiya, B. Russell, S. Sacerdoti, N. Saduyev, S. K. Sahoo, N. Sahu, S. Sakhiyev, P. Sala, G. Salmoria, S. Samanta, M. C. Sanchez, A. Sánchez-Castillo, P. Sanchez-Lucas, D. A. Sanders, S. Sanfilippo, D. Santoro, N. Saoulidou, P. Sapienza, I. Sarcevic, I. Sarra, G. Savage, V. Savinov, G. Scanavini, A. Scanu, A. Scaramelli, T. Schefke, H. Schellman, S. Schifano, P. Schlabach, D. Schmitz, A. W. Schneider, K. Scholberg, A. Schroeder, A. Schukraft, B. Schuld, S. Schwartz, A. Segade, E. Segreto, A. Selyunin, C. R. Senise, J. Sensenig, S. H. Seo, D. Seppela, M. H. Shaevitz, P. Shanahan, P. Sharma, R. Kumar, S. Sharma Poudel, K. Shaw, T. Shaw, K. Shchablo, J. Shen, C. Shepherd-Themistocleous, J. Shi, W. Shi, S. Shin, S. Shivakoti, A. Shmakov, I. Shoemaker, D. Shooltz, R. Shrock, M. Siden, J. Silber, L. Simard, J. Sinclair, G. Sinev, Jaydip Singh, J. Singh, L. Singh, P. Singh, V. Singh, S. Singh Chauhan, R. Sipos, C. Sironneau, G. Sirri, K. Siyeon, K. Skarpaas, J. Smedley, J. Smith, P. Smith, J. Smolik, M. Smy, M. Snape, E. L. Snider, P. Snopok, M. Soares Nunes, H. Sobel, M. Soderberg, H. Sogarwal, C. J. Solano Salinas, S. Söldner-Rembold, N. Solomey, V. Solovov, W. E. Sondheim, M. Sorbara, M. Sorel, J. Soto-Oton, A. Sousa, K. Soustruznik, D. Souza Correia, F. Spinella, J. Spitz, N. J. C. Spooner, D. Stalder, M. Stancari, L. Stanco, J. Steenis, R. Stein, H. M. Steiner, A. F. Steklain Lisbôa, J. Stewart, B. Stillwell, J. Stock, T. Stokes, T. Strauss, L. Strigari, A. Stuart, J. G. Suarez, J. Subash, A. Surdo, L. Suter, A. Sutton, K. Sutton, Y. Suvorov, R. Svoboda, S. K. Swain, C. Sweeney, B. Szczerbinska, A. M. Szelc, A. Sztuc, A. Taffara, N. Talukdar, J. Tamara, H. A. Tanaka, S. Tang, N. Taniuchi, A. M. Tapia Casanova, A. Tapper, S. Tariq, E. Tatar, R. Tayloe, A. M. Teklu, K. Tellez Giron Flores, J. Tena Vidal, P. Tennessen, M. Tenti, K. Terao, F. Terranova, G. Testera, T. Thakore, A. Thea, S. Thomas, A. Thompson, C. Thorpe, S. C. Timm, E. Tiras, V. Tishchenko, S. Tiwari, N. Todorović, L. Tomassetti, A. Tonazzo, D. Torbunov, D. Torres Muñoz, M. Torti, M. Tortola, Y. Torun, N. Tosi, D. Totani, M. Toups, C. Touramanis, V. Trabattoni, D. Tran, J. Trevor, E. Triller, S. Trilov, D. Trotta, J. Truchon, D. Truncali, W. H. Trzaska, Y. Tsai, Y.-T. Tsai, Z. Tsamalaidze, K. V. Tsang, N. Tsverava, S. Z. Tu, S. Tufanli, C. Tunnell, J. Turner, M. Tuzi, M. Tzanov, M. A. Uchida, J. Ureña González, J. Urheim, T. Usher, H. Utaegbulam, S. Uzunyan, M. R. Vagins, P. Vahle, G. A. Valdiviesso, E. Valencia, R. Valentim, Z. Vallari, E. Vallazza, J. W. F. Valle, R. Van Berg, D. V. Forero, A. Vannozzi, M. Van Nuland-Troost, F. Varanini, D. Vargas Oliva, N. Vaughan, K. Vaziri, A. Vázquez-Ramos, J. Vega, J. Vences, S. Ventura, A. Verdugo, M. Verzocchi, K. Vetter, M. Vicenzi, H. Vieira de Souza, C. Vignoli, C. Vilela, E. Villa, S. Viola, B. Viren, G. V. Stenico, R. Vizarreta, A. P. Vizcaya Hernandez, S. Vlachos, G. Vorobyev, Q. Vuong, A. V. Waldron, L. Walker, H. Wallace, M. Wallach, J. Walsh, T. Walton, L. Wan, B. Wang, H. Wang, J. Wang, M. H. L. S. Wang, X. Wang, Y. Wang, D. Warner, L. Warsame, M. O. Wascko, D. Waters, A. Watson, K. Wawrowska, A. Weber, C. M. Weber, M. Weber, H. Wei, A. Weinstein, S. Westerdale, M. Wetstein, K. Whalen, A. J. White, L. H. Whitehead, D. Whittington, F. Wieler, J. Wilhlemi, M. J. Wilking, A. Wilkinson, C. Wilkinson, F. Wilson, R. J. Wilson, P. Winter, J. Wolcott, J. Wolfs, T. Wongjirad, A. Wood, K. Wood, E. Worcester, M. Worcester, K. Wresilo, M. Wright, M. Wrobel, S. Wu, W. Wu, Z. Wu, M. Wurm, J. Wyenberg, B. M. Wynne, Y. Xiao, I. Xiotidis, B. Yaeggy, N. Yahlali, E. Yandel, G. Yang, J. Yang, T. Yang, A. Yankelevich, L. Yates, U. Yevarouskaya, K. Yonehara, T. Young, B. Yu, H. Yu, J. Yu, W. Yuan, M. Zabloudil, R. Zaki, J. Zalesak, L. Zambelli, B. Zamorano, A. Zani, O. Zapata, L. Zazueta, G. P. Zeller, J. Zennamo, J. Zettlemoyer, K. Zeug, C. Zhang, S. Zhang, Y. Zhang, L. Zhao, M. Zhao, E. D. Zimmerman, S. Zucchelli, V. Zutshi, R. Zwaska and On behalf of the DUNE Collaborationadd Show full author list remove Hide full author list
Instruments 2026, 10(1), 18; https://doi.org/10.3390/instruments10010018 - 17 Mar 2026
Viewed by 187
Abstract
The 2x2 Demonstrator, a prototype for the Deep Underground Neutrino Experiment (DUNE) liquid argon (LAr) Near Detector, was exposed to the Neutrinos from the Main Injector (NuMI) neutrino beam at Fermi National Accelerator Laboratory (Fermilab). This detector is a prototype of a new [...] Read more.
The 2x2 Demonstrator, a prototype for the Deep Underground Neutrino Experiment (DUNE) liquid argon (LAr) Near Detector, was exposed to the Neutrinos from the Main Injector (NuMI) neutrino beam at Fermi National Accelerator Laboratory (Fermilab). This detector is a prototype of a new modular design for a liquid argon time-projection chamber (LArTPC), comprising a two-by-two array of four modules, each further segmented into two optically isolated LArTPCs. The 2x2 Demonstrator features a number of pioneering technologies, including a low-profile resistive field shell to establish drift fields, native 3D ionization pixelated imaging, and a high-coverage dielectric light readout system. The 2.4-tonne active mass detector is flanked upstream and downstream by supplemental solid-scintillator tracking planes, repurposed from the MINERvA experiment, which track ionizing particles exiting the argon volume. The antineutrino beam data collected by the detector over a 4.5 day period in 2024 include over 30,000 neutrino interactions in the LAr active volume—the first neutrino interactions reported by a DUNE detector prototype. During its physics-quality run, the 2x2 Demonstrator operated at a nominal drift field of 500 V/cm and maintained good LAr purity, with a stable electron lifetime of approximately 1.25 ms. This paper describes the detector and supporting systems, summarizes the installation and commissioning, and presents the initial validation of collected NuMI beam and off-beam self-triggers. In addition, it highlights observed interactions in the detector volume, including candidate muon antineutrino events. Full article
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20 pages, 2312 KB  
Article
Effect-Directed Extraction of Grape Pomace: Optimizing Antioxidant and Antibrowning Efficacy
by Ignacio Cabezudo, Maximiliano Campero, Andrea M. Escalante and Ricardo L. E. Furlan
Processes 2026, 14(6), 925; https://doi.org/10.3390/pr14060925 - 14 Mar 2026
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Abstract
The increasing interest in valorizing agricultural by-products has positioned grape pomace as a rich source of bioactive compounds. This study developed an effect-directed extraction (EDE) approach guided by bioactivity quantification on thin layer chromatography (TLC). Twelve grape pomaces were screened based on antioxidant [...] Read more.
The increasing interest in valorizing agricultural by-products has positioned grape pomace as a rich source of bioactive compounds. This study developed an effect-directed extraction (EDE) approach guided by bioactivity quantification on thin layer chromatography (TLC). Twelve grape pomaces were screened based on antioxidant and tyrosinase inhibitory properties. Using hydroalcoholic solvent (ethanol:water, 1:1), the two most promising sources (Malbec from San Rafael) were subjected to response surface methodology (RSM) to optimize extraction of anti-browning and antioxidant compounds visualized as TLC spots. Temperature and time were optimized (76 °C, 45 min), and samples were analyzed using TLC coupled with DPPH and laccase inhibition bioautography. Antioxidant compounds showed retention factor values on TLC plates of 0.37 and 0.75 (DPPH/ABTS-active), while laccase inhibition occurred at Rf 0.35, coinciding with the primary tyrosinase inhibition zone. However, subsequent bioassay-guided HPLC fractionation and HRMS/MS analysis revealed that tyrosinase and laccase inhibitions are mediated by distinct compounds within this bioactive zone, highlighting a synergistic multi-target effect in the optimized extract that is retained throughout the process. The primary tyrosinase inhibitor at Rf ~0.35 was tentatively elucidated as an acylated anthocyanin, consistent with malvidin-3-O-(p-coumaroyl)glucoside. Optimized extracts were evaluated on Pink Lady apple slices at different timepoints. The browning index was reduced by 25% versus the control at 15 h, confirmed by significantly lower ΔE values (p < 0.05). The process requires only food-grade solvents and conventional equipment, facilitating scale-up for grape pomace generated worldwide. Validating the EDE strategy, this TLC-guided approach successfully tracked and preserved the primary anti-tyrosinase activity from the crude waste matrix down to the tentatively identified molecule, contributing to circular economy objectives in the wine industry. Full article
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21 pages, 14144 KB  
Article
Optimization of Formation Parameters for Single-Pass/Cross-Track Interferometry Through the Harmony Mission
by Federica Cotugno, Andreas Theodosiou, Björn Rommen, Michele Manunta, Riccardo Lanari, Maria Salvato, Francesca Pelliccia and Alfredo Renga
Remote Sens. 2026, 18(6), 877; https://doi.org/10.3390/rs18060877 - 12 Mar 2026
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Abstract
In the framework of Harmony, the 10th ESA Earth Explorer mission, this paper presents a general methodology to optimize the formation parameters relevant to the single-pass, cross-track interferometry (XTI) configuration. The proposed method considers the requested height sensitivity and the maximum allowable temporal [...] Read more.
In the framework of Harmony, the 10th ESA Earth Explorer mission, this paper presents a general methodology to optimize the formation parameters relevant to the single-pass, cross-track interferometry (XTI) configuration. The proposed method considers the requested height sensitivity and the maximum allowable temporal lag and derives the formation parameters for an optimal coverage over different ranges of latitudes by leveraging the relative eccentricity and inclination vector formalism. Our approach addresses the problem of interferometric coherence through the wavenumber support alignment method which is able to take into account the specific geometry of XTI in Harmony, which is a long-baseline multistatic configuration with large squint angles. The analysis is completed by an estimate of the propellant budget, required to maintain the optimized formation, which can be used as a further trade-off parameter within the mission design process. The results indicate that the passively stable helix configuration (with relative eccentricity and inclination phase angles set to 90°) provides a robust solution at equatorial and mid-latitude regions with perpendicular baselines up to the order of 1 km and temporal lag below 10 ms. Conversely, for high-latitude and polar regions, two alternative strategies are identified, revealing a trade-off between enhanced interferometric performance and increased formation maintenance requirements. For polar regions, a first strategy adopts relative eccentric and phase angles of 10°, achieving satisfactory performance across most latitudes, whereas an alternative approach retains the value of 90° and optimizes the formation specifically for high latitudes. These two options result in distinct station-keeping demands since the former strategy requires a ΔV budget about two orders of magnitude higher, while the latter remains within a ΔV range that is typical for missions of the considered class. Full article
(This article belongs to the Special Issue Multi-Satellite SAR Missions in Earth Orbit: Programs and Studies)
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17 pages, 800 KB  
Article
Association of Vericiguat with Improvement in Functional Abilities and Comprehensive Geriatric Assessment in Elderly Patients with Worsening Heart Failure
by Giuseppe Armentaro, Maria Rosangela Scarcelli, Giandomenico Severini, Carlo Alberto Pastura, Velia Cassano, Francesco Maruca, Laura Francesca Marincola, Gianluca Cortese, Valentino Condoleo, Sofia Miceli, Raffaele Maio, Maurizio Volterrani, Cristiana Vitale, Giuseppe Massimo Claudio Rosano and Angela Sciacqua
Pharmaceuticals 2026, 19(3), 466; https://doi.org/10.3390/ph19030466 - 12 Mar 2026
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Abstract
Background: Elderly patients with heart failure with reduced ejection fraction (HFrEF) who experience worsening heart failure (wHF) remain at high residual risk despite optimal medical therapy (OMT), and data on cognitive function and comprehensive geriatric assessment (CGA) in this setting are lacking. [...] Read more.
Background: Elderly patients with heart failure with reduced ejection fraction (HFrEF) who experience worsening heart failure (wHF) remain at high residual risk despite optimal medical therapy (OMT), and data on cognitive function and comprehensive geriatric assessment (CGA) in this setting are lacking. This study evaluated the association between 12-month treatment with vericiguat and changes in cardiac, functional and geriatric parameters in elderly patients with recent wHF. Methods and results: In this single-center prospective observational study, 55 patients (45 men, mean age 76.4 ± 5.1 years) with HFrEF on OMT and a recent episode of wHF were treated with vericiguat and followed for 12 months. Clinical assessment, CGA and echocardiography including speckle-tracking were performed at baseline, 6, and 12 months. At 12 months, the mean vericiguat dose was 5.5 ± 2.9 mg/day. NT-proBNP levels decreased from 980 (467–2106) to 654 (274–1762) pg/mL (p < 0.0001), while left ventricular ejection fraction increased from 36.8 ± 3.1% to 43.4 ± 5.7% (p < 0.0001). Global longitudinal strain improved from −9.2 ± 1.7% to −11.5 ± 2.1% (p = 0.008), with parallel improvements in right ventricular function and pulmonary pressures. Cognitive performance improved (MMSE 25.1 ± 1.7 to 26.2 ± 2.1 points, p < 0.0001), as did depressive symptoms (GDS 7.8 ± 2.0 to 5.4 ± 1.6 points, p < 0.0001), physical performance (SPPB 6.7 ± 1.1 to 8.4 ± 0.9 points, p < 0.0001), and gait speed (0.70 ± 0.10 to 0.83 ± 0.06 m/s, p < 0.0001). Conley score decreased from 5.2 ± 2.3 to 2.4 ± 1.8 points (p < 0.0001), suggesting a lower risk of falls. Loop diuretic and MRA use were significantly reduced during follow-up. Conclusions: In this elderly HFrEF cohort with recent wHF on contemporary OMT, 12-month treatment with vericiguat was associated with consistent improvements in cardiac structure and function, biomarkers, and multidimensional geriatric status. These hypothesis-generating findings support the integration of CGA into future controlled studies of vericiguat in frail older patients with HFrEF. Given the observational design and lack of a control group, causal inference is not possible. Full article
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27 pages, 9034 KB  
Article
A Comparison of Optimisation Algorithms for Electronic Polarisation Control in Quantum Key Distribution
by Matt Young, Haofan Duan, Stefano Pirandola and Marco Lucamarini
Appl. Sci. 2026, 16(5), 2568; https://doi.org/10.3390/app16052568 - 7 Mar 2026
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Abstract
Polarisation encoding is widely used in fibre-based Quantum Key Distribution (QKD), but random birefringence in optical fibres causes the transmitted states to drift, requiring active compensation at the receiver. Electronic Polarisation Controllers (EPCs) are commonly used for this purpose, yet the relationship between [...] Read more.
Polarisation encoding is widely used in fibre-based Quantum Key Distribution (QKD), but random birefringence in optical fibres causes the transmitted states to drift, requiring active compensation at the receiver. Electronic Polarisation Controllers (EPCs) are commonly used for this purpose, yet the relationship between their control voltages and the resulting polarisation transformation is highly nonlinear and difficult to model. While optimisation algorithms are frequently employed to align and stabilise polarisation states, their comparative performance has not been systematically studied in realistic QKD settings. In this work, we benchmark four optimisation algorithms for electronic polarisation control, using both a numerical model and a 50 km fibre-based experimental setup. We evaluate each algorithm in terms of convergence time, failure rate, and stability, under both initial alignment and continuous drift compensation scenarios. Coordinate Descent achieved the fastest average alignment time (2.1 ms in simulation; 34.6 s experimentally), while Simulated Annealing delivered perfect reliability. We further propose a hybrid control strategy that combines fast initial alignment with high-reliability realignment. This approach was validated over a continuous 2 h QKD simulation with real fibre drift, demonstrating robust polarisation control without manual intervention. Our results provide guidance for algorithm selection in practical QKD deployments and suggest a pathway to resilient, autonomous polarisation tracking in long-distance quantum networks. Full article
(This article belongs to the Special Issue Quantum Communication and Quantum Information)
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25 pages, 15027 KB  
Article
Characterization of Local and Long-Distance Ice Floe Motion in the Yellow River Using UAV–GPS Joint Observations
by Chunjiang Li, Jiaqi Dai, Yupeng Leng, Xiaohua Hao, Weiping Li, Shamshodbek Akmalov, Xiangqian Li, Zhichao Wang, Han Gao, Xiang Fu, Shengbo Hu and Yu Zheng
Remote Sens. 2026, 18(5), 823; https://doi.org/10.3390/rs18050823 - 6 Mar 2026
Viewed by 251
Abstract
Understanding the motion parameters of floating ice is very important for characterizing the ice water dynamics of rivers during freezing periods. Due to the low spatiotemporal resolution of satellite images, limited observation range of unmanned aerial vehicles, and deformation of shore-based camera images, [...] Read more.
Understanding the motion parameters of floating ice is very important for characterizing the ice water dynamics of rivers during freezing periods. Due to the low spatiotemporal resolution of satellite images, limited observation range of unmanned aerial vehicles, and deformation of shore-based camera images, it is difficult to simultaneously quantify the translational and rotational motion characteristics of floating ice and long-distance transportation. This study used the unmanned aerial vehicle GPS joint observation method to observe and obtain various motion parameters such as local translation, rotation, and long-distance transportation in the curved section of the upper reaches of the Yellow River and the straight section of the middle reaches of the Yellow River during the winter of 2024–2025 under conditions of ice density of 50–90%. The velocity field obtained by the drone shows an average ice velocity of 1.27 m/s at the bend and 1.18 m/s in the straight section, with lateral velocity gradients of −0.245 to 0.050 s−1 and −0.141 to 0.222 s−1, respectively. The angular velocity of a single floating ice block is 0.008–0.016 rad/s at bends and 0.010–0.036 rad/s in straight sections. The angular velocity is positively correlated with the local shear strength, and the rotation direction is consistent with the sign of the velocity gradient. GPS tracking provides long-distance transportation trajectories, and the average difference between the speeds obtained by GPS and drones is 0.10 m/s, confirming the reliability of speed estimation based on drones. These results indicate that integrated unmanned aerial vehicle GPS observation can quantitatively characterize local floating ice movement and long-distance floating ice transport behavior, providing on-site parameters for river ice water dynamics research and hazard assessment, and has the potential to be applied to rivers in other cold regions. Full article
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36 pages, 805 KB  
Article
Real-Time Embedded NMPC for Autonomous Vehicle Path Tracking with Curvature-Aware Speed Adaptation and Sensitivity Analysis
by Taoufik Belkebir, Hicham Belkebir and Anass Mansouri
Automation 2026, 7(2), 44; https://doi.org/10.3390/automation7020044 - 6 Mar 2026
Viewed by 338
Abstract
Local path tracking is a critical challenge for autonomous vehicles, requiring precise trajectory following under nonlinear dynamics, strict constraints, and real-time execution. While Nonlinear Model Predictive Control (NMPC) has emerged as a leading approach, many existing methods decouple velocity planning from tracking, lack [...] Read more.
Local path tracking is a critical challenge for autonomous vehicles, requiring precise trajectory following under nonlinear dynamics, strict constraints, and real-time execution. While Nonlinear Model Predictive Control (NMPC) has emerged as a leading approach, many existing methods decouple velocity planning from tracking, lack formal stability guarantees, or do not demonstrate feasibility on embedded platforms. We present a unified NMPC framework that integrates curvature-aware velocity adaptation directly into the cost function. The controller makes use of cubic spline paths, recursive feasibility constraints, and Lyapunov-based terminal costs to ensure stability. The nonlinear optimization problem is implemented in CasADi and solved using IPOPT, with warm-starting and efficient discretization techniques enabling real-time performance. Our approach has been validated in the CARLA simulator across a variety of urban scenarios, including straight roads, intersections, and roundabouts. The controller achieves a mean cross-track error of 0.10 m on straight roads, 0.44 m on roundabouts, and 1.36 m on tight intersections, while maintaining smooth control inputs and bounded actuator effort. A curvature-aware cost term yields a 14.4% reduction in lateral tracking error compared to the curvature-unaware baseline. Benchmarking results indicate that the Raspberry Pi 5 outperforms the NVIDIA Xavier AGX by 1.5–1.6×, achieving mean execution times of 38–45 ms across all scenarios. This demonstrates that advanced NMPC can run in real time on low-cost consumer hardware ($80 vs. $700). Systematic ablation studies reveal the critical role of state weighting (Q) and input regularization (R): removing Q degrades tracking by 10% and destabilizes control effort (+54% acceleration, +477% steering), while omitting R induces oscillatory behavior with +907% acceleration effort. Euler integration provides no computational benefit (+8% solver time) while degrading accuracy by 25%, confirming RK4 as strictly superior. Sensitivity analysis via Latin Hypercube Sampling identifies the prediction horizon (N) and discretization timestep (Δt) as dominant parameters. Per-scenario Pareto analysis yields a balanced operating point (N=15, Δt=0.055 s) used for all primary evaluations, while a global sweep identifies a robust alternative (N=12, Δt=0.086 s) suitable for general deployment tuning. This framework bridges the gap between spline-based local planning and stability-guaranteed NMPC, offering a simulation-validated, real-time solution for embedded autonomous driving research. Future work will focus on hardware-in-the-loop and full-vehicle deployment, integration with high-level decision-making, and learning-enhanced MPC. Full article
(This article belongs to the Section Robotics and Autonomous Systems)
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22 pages, 3339 KB  
Article
Particle Velocity Measurement in Battery Thermal Runaway Jets Using an Enhanced Deep Learning and Adaptive Matching Framework
by Xinhua Mao, Zhimin Chen, Mengqi Zhang, Jinwei Sun and Chengshan Xu
Batteries 2026, 12(3), 90; https://doi.org/10.3390/batteries12030090 - 6 Mar 2026
Viewed by 222
Abstract
High-speed solid particles ejected during battery thermal runaway pose severe safety threats, yet their velocity measurement is hindered by high density, microscopic size, and intense glare. This study proposes a non-intrusive velocimetry framework that integrates an enhanced single-stage object detector with a structural [...] Read more.
High-speed solid particles ejected during battery thermal runaway pose severe safety threats, yet their velocity measurement is hindered by high density, microscopic size, and intense glare. This study proposes a non-intrusive velocimetry framework that integrates an enhanced single-stage object detector with a structural similarity matching algorithm. The detector incorporates specialized feature extraction modules and a high-resolution layer to identify microscopic targets in extreme environments, while the matching algorithm employs adaptive direction constraints to ensure precise trajectory tracking. Experimental validation demonstrates that the framework achieves a mean average precision of 92.7% and supports real-time processing. The method successfully quantifies a three-stage velocity evolution in battery failure events, identifying a peak particle speed exceeding 120 m/s. These findings provide critical kinematic data for optimizing battery safety structures and modeling fire propagation mechanisms. Full article
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26 pages, 46386 KB  
Article
Predicting Car-Engine Manufacturing Quality with Multi-Sensor Data of Manufacturing Assembly Process
by Xinyu Yang, Qianxi Zhang, Junjie Bao, Xue Wang, Nengchao Wu, Qing Tao, Haijia Wu and Li Liu
Sensors 2026, 26(5), 1651; https://doi.org/10.3390/s26051651 - 5 Mar 2026
Viewed by 265
Abstract
Car engine quality control is fundamentally hindered by extremely high-dimensional, noisy, and imbalanced multi-sensor data. To overcome these challenges, this paper proposes an edge-deployable diagnostic and predictive framework. First, a Sparse Autoencoder (SAE) maps over 12,000 distributed manufacturing parameters into a robust latent [...] Read more.
Car engine quality control is fundamentally hindered by extremely high-dimensional, noisy, and imbalanced multi-sensor data. To overcome these challenges, this paper proposes an edge-deployable diagnostic and predictive framework. First, a Sparse Autoencoder (SAE) maps over 12,000 distributed manufacturing parameters into a robust latent space to filter instrumentation noise. Second, for defect classification, a Class-Specific Weighted Ensemble (CSWE) tackles extreme class imbalance by aggressively penalizing majority-class bias, improving defect interception recall by 7.72%. Third, for transient performance tracking, an Adaptive Regime-Switching Regression (ARSR) replaces manual phase selection with unsupervised regime routing to dynamically weight local experts, reducing relative prediction error by 12%. Rigorously validated across three diverse public datasets (NASA C-MAPSS, AI4I, SECOM) and a physical H4 engine assembly line, the framework achieves an ultra-low inference latency of 80±3 ms, practically reducing the engine rework rate by 7.2%. Full article
(This article belongs to the Section Industrial Sensors)
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22 pages, 5226 KB  
Article
Sequential Anaerobic–Aerobic Treatment of Paint Wastewater: Performance and LC–MS Pollutant Transformation
by E. S. Manju and Basavaraju Manu
ChemEngineering 2026, 10(3), 38; https://doi.org/10.3390/chemengineering10030038 - 5 Mar 2026
Viewed by 243
Abstract
Paint manufacturing wastewater contains complex mixtures of solvents, resins, surfactants, pigments, and polymeric additives that result in high chemical oxygen demand (COD), toxicity, and poor biodegradability. Conventional physicochemical treatment provides limited removal of dissolved organics, and the pollutant-level behavior of paint effluents during [...] Read more.
Paint manufacturing wastewater contains complex mixtures of solvents, resins, surfactants, pigments, and polymeric additives that result in high chemical oxygen demand (COD), toxicity, and poor biodegradability. Conventional physicochemical treatment provides limited removal of dissolved organics, and the pollutant-level behavior of paint effluents during biological treatment remains insufficiently characterized. This study addresses this gap by evaluating a sequential anaerobic–aerobic batch process treating three distinct synthetic paint wastewater samples. This study is a comparative investigation of sequential biological treatment across multiple paint wastewater variants, combined with high-resolution LC–MS to track compound-level transformations. Treatment performance was assessed through COD removal, biogas generation, pH and redox behavior, and LC–MS profiling of organic contaminants. The anaerobic stage achieved 70–95% COD removal depending on wastewater type. Aerobic polishing increased overall removal efficiencies, while PWW3 exhibited reduced stability during extended operation. LC–MS analysis showed substantial decreases in the number and intensity of chromatographic peaks and demonstrated degradation of phthalates, glycol ethers, organophosphate plasticizers, and solvent-derived compounds. The study provides integrated performance- and pollutant-level assessment of sequential anaerobic–aerobic treatment of paint wastewater and demonstrates the influences of wastewater heterogeneity in biological degradation pathways. Full article
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26 pages, 4269 KB  
Article
Age-Related Differences in Thigh Biarticular Agonist–Antagonist Coordination During 50 m Sprinting: A Phase-Specific Analysis of sEMG and Ground Reaction Force Using Phase Mean Comparisons and Linear Mixed-Effects Models
by Kanta Yokota and Hiroyuki Tamaki
Appl. Sci. 2026, 16(5), 2439; https://doi.org/10.3390/app16052439 - 3 Mar 2026
Viewed by 217
Abstract
Background: Age-related differences in neuromuscular coordination during multi-joint tasks are reported, but phase-specific evidence during maximal sprinting is limited. Aim: The aim of this study was to investigate phase-specific age differences in agonist–antagonist coordination of the biarticular thigh muscles during 50 [...] Read more.
Background: Age-related differences in neuromuscular coordination during multi-joint tasks are reported, but phase-specific evidence during maximal sprinting is limited. Aim: The aim of this study was to investigate phase-specific age differences in agonist–antagonist coordination of the biarticular thigh muscles during 50 m sprinting. Methods: Thirty-eight healthy trained track athletes (Adults: n = 21, age = 23.32 ± 2.98 years; Adolescents: n = 17, age = 13.65 ± 0.76 years) performed maximal 50 m sprints over force plates. Bilateral rectus femoris (RF) and biceps femoris (BF) sEMG and ground reaction forces were recorded; each stride was segmented into seven phases, and an RF–BF co-contraction index (CCI) was calculated per phase. Between-group differences in phase mean CCI were tested (α = 0.05) and quantified with Hedges’ g. Speed- and frequency-dependent modulation of CCI was evaluated using linear mixed-effects models (LME; random intercepts for participant) with Frequency × Group and Speed × Group interaction terms; ordinary least squares (OLS) fits on stride cycle-level group means were descriptive. Linear and single-breakpoint segmented models were compared using the corrected Akaike information criterion (AICc) and Akaike weights. Results: Adolescents showed higher CCI in contact (right: Adults 0.09 ± 0.05 vs. Adolescents 0.13 ± 0.07, g = 0.68; left: Adults 0.08 ± 0.04 vs. Adolescents 0.12 ± 0.06, g = 0.84) and propulsive phases (right: Adults 0.08 ± 0.05 vs. Adolescents 0.13 ± 0.08, g = 0.68; left: Adults 0.07 ± 0.04 vs. Adolescents 0.12 ± 0.07, g = 0.84; p < 0.05 for both legs in both phases). LME identified Frequency × Group interactions in the stride cycle (ΔSlope = 0.10, p < 0.001) and late swing (ΔSlope = 0.12, p < 0.05) and a Speed × Group interaction in mid swing (ΔSlope = 0.01, p < 0.05). Mid swing showed a positive CCI–speed/frequency relationship in both groups, whereas across most other phases Adults downregulated CCI as speed/frequency increased while Adolescents tended to increase CCI. Model selection supported phase-dependent single-breakpoint patterns, with breakpoints around 2.19–2.21 Hz and 6.11–9.51 m·s−1 in Adults and around 2.11 Hz and 7.13–7.59 m·s−1 in Adolescents. Conclusions: Maximal sprinting revealed phase-specific age differences in BF–RF co-contraction and its scaling with speed/frequency, which may help guide age-informed monitoring and training considerations in developing athletes. Full article
(This article belongs to the Special Issue Biomechanics and Human Movement Analysis in Sport)
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16 pages, 2695 KB  
Article
The Impact of Mitral Valvular Etiology on Left Atrial Functional Recovery After the Maze Procedure: A Comparison Between Mitral Stenosis, Mitral Regurgitation and Non-Mitral Valve Disease
by Woo Sung Jang, Jung Uk Woo and Kyungsub Song
J. Clin. Med. 2026, 15(5), 1856; https://doi.org/10.3390/jcm15051856 - 28 Feb 2026
Viewed by 204
Abstract
Background: Although the concomitant Maze procedure successfully restores sinus rhythm in patients with valvular atrial fibrillation, it remains unclear whether electrical restoration translates into uniform functional recovery across different valvular etiologies. To address this issue, we compared the long-term left atrial (LA) [...] Read more.
Background: Although the concomitant Maze procedure successfully restores sinus rhythm in patients with valvular atrial fibrillation, it remains unclear whether electrical restoration translates into uniform functional recovery across different valvular etiologies. To address this issue, we compared the long-term left atrial (LA) mechanical recovery between patients with mitral stenosis (MS) and mitral regurgitation (MR) after the Maze procedure. Methods: This retrospective study included 211 patients who underwent the Maze procedure concomitant with valvular surgery and maintained sinus rhythm after 1 year. Patients were stratified into three groups, namely MS (n = 51), MR (n = 98), and non-mitral (n = 62) serving as a reference. LA function was evaluated using speckle-tracking echocardiography at baseline, immediately postoperatively, and at 1 year. Primary outcomes were changes in LA reservoir (LASr), LA conduit (LAScd), and LA contractile (LASct) strains. Results: At 1-year follow-up, the non-mitral reference group exhibited the best LA function, followed by the MR group, whereas the MS group showed the most impaired values (p < 0.001). Analysis of functional recovery revealed a mechanistic divergence, i.e., although the improvement in passive stiffness (LAScd) was comparable between the MS and MR groups (p = 0.42), the recovery of active contractile strain (LASct) was significantly superior in the MR group compared to the MS group (p < 0.05). The MS group failed to regain effective atrial contraction despite successful rhythm control. Conclusions: Although the Maze procedure successfully restored sinus rhythm, functional recovery varied significantly by etiology. The superior recovery in patients with MR was driven by the restoration of active atrial contraction, whereas patients with MS exhibited persistent mechanical dysfunction attributed to irreversible myocardial structural remodeling, despite similar improvements in compliance. Therefore, electrical success does not guarantee functional success, particularly in patients with MS. Full article
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