Search Results (224,306)

The Internet of Things (IoT) has transformed multiple industries, providing significant potential for automation, efficiency, and enhanced decision-making. The incorporation of IoT and data analytics in smart grid represents a groundbreaking opportunity for the energy sector, delivering substantial advantages in efficiency, sustainability, and customer empowerment. This integration enables smart grids to autonomously monitor energy flows and adjust to fluctuations in energy demand and supply in a flexible and real-time fashion. Statistical analytics, as a fundamental component of data analytics, provides the necessary tools and techniques to uncover patterns, trends, and insights within datasets. Nevertheless, it is crucial to address privacy and security issues to fully maximize the potential of data analytics in smart grids. This paper makes several significant contributions to the literature on secure, privacy-aware aggregation schemes in smart grids. First, we introduce a Fog-enabled Secure Data Analytics Operations (FESDAO) scheme which offers a distributed architecture incorporating robust security features such as secure aggregation, authentication, fault tolerance and resilience against insider threats. The scheme achieves privacy during data aggregation through a modified Boneh-Goh-Nissim cryptographic scheme along with other mechanisms. Second, FESDAO also supports statistical analytics on metering data at the cloud control center and fog node levels. FESDAO ensures reliable aggregation and accurate data analytical results, even in scenarios where smart meters fail to report data, thereby preserving both analytical operation computation accuracy and latency. We further provide comprehensive security analyses to demonstrate that the proposed approach effectively supports data privacy, source authentication, fault tolerance, and resilience against false data injection and replay attacks. Lastly, we offer thorough performance evaluations to illustrate the efficiency of the suggested scheme in comparison to current state-of-the-art schemes, considering encryption, computation, aggregation, decryption, and communication costs. Moreover, a detailed security analysis has been conducted to verify the scheme’s resistance against insider collusion attacks, replay attack, and false data injection (FDI) attack. Full article

The surface treated by laser phase transformation hardening exhibits superior hardness, enhanced wear resistance, and refined grain structure. In this study, both single-track and two-track laser phase transformation hardening processes were numerically simulated, with the simulation accuracy being verified experimentally. Furthermore, the optimal overlap rate for laser two-track overlay was predicted based on the simulation results. An S355J2G3 metal block specimen was used as a case, numerical simulations of the phase transformation coupled with the temperature field on the specimen’s surface under laser irradiation were carried out using SYSWELD2019 software. The surface temperature distribution and the evolution of phase volume fractions were analyzed. Additionally, the changes in the temperature field within the softening zone and the distribution of tempering structures resulting from two-track laser overlay were examined. The discrepancy between experimental and simulated results for the hardening layer width was approximately 10%, while the error rates for the hardening layer depth and the tempering softening zone were below 5% and 10%, respectively. Based on simulations conducted with varying overlap rates, the flatness metric produces the best results at 50% overlap under these laser processing parameters. Full article

Background and Objectives: This study aimed to evaluate the treatment outcomes of adults with pulmonary drug-susceptible tuberculosis (DS-TB) in Lithuania over 22 years, and to examine associations between treatment outcomes, various risk factors, and temporal trends. Materials and Methods: A retrospective cohort analysis was conducted using data from the National Tuberculosis Information System from 2000 to 2021. A total of 18,697 adult patients with DS-TB were included. Patients were grouped into three time periods: Period I (2000–2007), Period II (2008–2015), and Period III (2016–2021). Treatment outcomes were categorized as successful (treatment completed with recovery) or unsuccessful (patients who encountered treatment failure, died during treatment, or converted to drug-resistant tuberculosis). Associations with individual risk factors, including smoking, alcohol use, comorbidities, and sociodemographic variables, were analyzed. Results: Treatment success rates improved steadily across the study periods: 82.3% in Period I, 84.4% in Period II, and 87.6% in Period III. Mortality rates declined over time but remained substantial: 17.1%, 15.2%, and 12.0% in Periods I, II, and III, respectively. Non-lethal treatment failures decreased slightly (0.6%, 0.4%, and 0.4%). Multivariate analysis identified significant associations between treatment failure and multiple risk factors, including low BMI, male gender, unemployment, homelessness, smoking, alcohol and substance use, and comorbid conditions such as cancer, cardiovascular disease, chronic lung disease, diabetes mellitus, HIV, and renal failure. Conclusions: Treatment outcomes for DS-TB in Lithuania have improved over the past two decades; however, certain modifiable risk factors—such as low BMI, homelessness, substance use, and comorbidities—remain strongly linked to treatment failure. To further improve outcomes, targeted interventions such as nutritional support, housing programs, and integrated addiction services should be prioritized for high-risk groups within national TB control efforts. Full article

Path navigation for mobile robots critically determines the operational efficiency of warehouse logistics systems. However, the current QR (Quick Response) code path navigation for warehouses suffers from low operational efficiency and poor dynamic adaptability in complex dynamic environments. This paper introduces a deep reinforcement learning and hybrid-algorithm SLAM (Simultaneous Localization and Mapping) path navigation method for Mecanum-wheeled robots, validated with an emphasis on dynamic adaptability and real-time performance. Based on the Gazebo warehouse simulation environment, the TD3 (Twin Deep Deterministic Policy Gradient) path planning method was established for offline training. Then, the Astar-Time Elastic Band (TEB) hybrid path planning algorithm was used to conduct experimental verification in static and dynamic real-world scenarios. Finally, experiments show that the TD3-based path planning for mobile robots makes effective decisions during offline training in the simulation environment, while Astar-TEB accurately completes path planning and navigates around both static and dynamic obstacles in real-world scenarios. Therefore, this verifies the feasibility and effectiveness of the proposed SLAM path navigation for Mecanum-wheeled mobile robots on a miniature warehouse platform. Full article

In this paper, we proposed a novel method for grinding trajectory planning on large-curved forgings to improve grinding performance and grinding efficiency. Our method consists of four main steps. Firstly, we conducted simulations and analyses on the contact state and contact pressure between the grinding tool and curved workpieces, and explored different grinding methods. Based on the Preston equation, a material removal model was established to analyze the grinding force. Secondly, we proposed an adaptive impedance control method based on grinding force analysis, which can control the contact force indirectly by adjusting the end position of the robot. To address the inability of impedance control to adjust impedance parameters in real time, a control strategy involving online estimation of environmental position and stiffness is adopted. Based on the Lyapunov asymptotic stability principle, an adaptive impedance control model is established, and the effectiveness of the adaptive algorithm is verified through simulation. Thirdly, Position correction is realized through gravity compensation of the grinding force and discretization of the impedance control model. Subsequently, a dynamic trajectory adjustment strategy is proposed, which integrates position correction for the current grinding point and position compensation for the next grinding point, to achieve the force control objective in the grinding process. Finally, a constant force grinding experiment was conducted on large-curvature blades using a robotic automatic grinding system. The grinding system effectively removed the knife marks on the blade surface, resulting in a surface roughness of 0.5146 µm and a grinding efficiency of approximately 0.89 cm²/s. The simulation and experimental results indicate that the smoothness and grinding efficiency of the blades are superior to the enterprise’s existing grinding technology, verifying the feasibility and effectiveness of our proposed method. Full article

The present study examined the impact of adding methionine (Met) and its conjugated form (Met-Met) on Cornu aspersum snails. The primary focus was on the animals’ growth performance, the chemical composition of their carcass (whole body without the shell), the mineral profile, and the mechanical properties of their shells. In two experiments conducted under controlled laboratory conditions, diets supplemented with varying levels of Met addition (0.3, 0.6, 1.4 g/kg feed) were used, and the effects of free methionine, Met-Met and their mixture (1.4 g/kg feed) were compared. The study incorporated measurements of body weight, shell width, and mortality of snails. Analyses encompassing protein, fat, sulphur amino acids, glutathione levels, oxidative stress indices (DPPH, TAC, TBARS), and macro- and micronutrient content of carcass and shells were conducted. The findings demonstrated that adding 1.4 g Met/kg feed significantly enhanced the shells’ weight gain (+56% vs. Control), shell weight (+56%) and crushing force (+135%). Furthermore, an increase in the Met content of the carcass was observed (+18%), along with elevated carcass Ca (+28%) and P (+30%) and higher shell Ca (+12%) and Zn (+87%), alongside reduced carcass Fe (−38%) and Cu (−19%). In Experiment II, the Met-Met group exhibited the highest carcass weight (+16% vs. Control), the greatest carcass-to-body weight ratio, and the highest proportion of mature individuals (+27%). Moreover, Met-Met supplementation improved Cu absorption and retention in the carcass (+19%). Also, the results suggest that the conjugated form of methionine may improve Cu absorption and storage in the carcass (+19%). The study’s findings indicate that methionine addition, especially in Met-Met form, can substantially impact the efficiency of C. aspersum farming, enhancing both the productivity outcomes and the quality of the product. That is particularly important in increasing the shell’s mechanical resistance and the carcass’s nutritional value. Full article

The paper presents a comprehensive evaluation of certain main parameters and the performance of microjet series models from the same engine manufacturer, AMT Netherlands, under various operating regimes. The study was performed through a percentage-based analysis of a series of actual values extracted from a set of charts, from which a specific database was created. The database comprised data sourced from official specification sheets issued by the manufacturer. The studied engines shared the same technical turbomachinery design, comprising a single shaft, one centrifugal compressor rotor, one axial turbine rotor stage, and a convergent jet nozzle, but differed in thrust class, ranging from 167 to 1569 N. Parameter and performance ratios were calculated to analyze the variation patterns within each engine and across different engines. The study refers to the variation analysis of thrust, fuel flow, exhaust gas temperature, and specific fuel consumption relative to engine speed, from idle to maximum regime. It presents the actual percentage values alongside polynomial functions that characterize the variations in engine parameters through which the analysis can be conducted. Full article

The persistent conflict between strength and electrical conductivity in copper-based materials presents a fundamental limitation for next-generation high-performance applications. Graphene, with its unique two-dimensional architecture and exceptional intrinsic characteristics, has become a promising reinforcement phase for copper matrices. This comprehensive review synthesizes recent advancements in graphene–copper composites (CGCs), focusing particularly on structural design innovations and scalable manufacturing approaches such as powder metallurgy, molecular-level mixing, electrochemical deposition, and chemical vapor deposition. The analysis examines pathways for optimizing key properties—including mechanical strength, thermal conduction, and electrical performance—while investigating the fundamental reinforcement mechanisms and charge/heat transport phenomena. Special consideration is given to how graphene morphology, concentration, structural quality, interfacial chemistry, and processing conditions collectively determine composite behavior. Significant emphasis is placed on interface engineering strategies, graphene alignment, consolidation control, and defect management to minimize electron and phonon scattering while improving stress transfer efficiency. The review concludes by proposing research directions to resolve the strength–conductivity paradox and broaden practical implementation domains, thereby offering both methodological frameworks and theoretical foundations to support the industrial adoption of high-performance CGCs. Full article

This review provides an overview of existing accident prevention methods by monitoring the persons’ physiological state, observing movements, and physiological parameters. Firstly, different physiological parameters monitoring systems are introduced. Secondly, various systems dealing with position recognition on pressure sensing mats are presented. We conduct an in-depth literature search and quantitative analysis of papers published in this area and focus independently of the application (drivers, office and wheelchair users, etc.). Quantitative information about the number of subjects, investigated scenarios, sensor types, machine learning usage, and laboratory vs. real-world works is extracted. In posture recognition, most works recognize at least forward, backward, left and right movements on a seat. The remaining works use the pressure sensing mat for bedridden people. In physiological parameters measurement, most works detect the heart rate and often also add respiration rate recognition. Machine learning algorithms are used in most cases and are taking on an ever-greater importance for classification and regression problems. Although all solutions use different techniques, returning satisfactory results, none of them try to detect small movements, which can pose challenges in determining the optimal sensor topology and sampling frequency required to detect fine movements. For physiological measurements, there are lots of challenges to overcome in noisy environments, notably the detection of heart rate, blood pressure, and respiratory rate at very low signal-to-noise levels. Full article

This study documents the first-ever recorded occurrence of alluvial gold in the foreland region of the Eastern Carpathians, specifically within the Moldavian Platform, Romania, and presents the morphological analysis and the chemical composition of the newly discovered alluvial gold. A total of 115 gold particles, with a combined weight of approximately 0.50 g, were collected from three distinct sites within the Baia region, near Falticeni town. The native gold grains exhibit average length and width ranging from 3.93 mm to 2.50 mm in location #1, 0.43 mm to 0.30 mm in location #2, and 1.01 mm to 0.56 mm in location #3, respectively. The gold grains are rounded to sub-rounded and display discoidal to subdiscoidal shapes. Traces of the original quartz gangue are occasionally retained on their surfaces. The morphological analysis and the presence of quartz attached to the gold grains suggest a short transportation distance. Quantitative electron probe microanalysis conducted on 16 gold grains yields a silver (Ag) content between 0.56 wt% to 6.19 wt%. The primary source of the alluvial gold remains unidentified. We suggest that this could be orogenic gold type deposit. Full article

The advancement of onshore and offshore wind turbines depends on the experimental validation of new technologies, novel component designs, and innovative concepts. However, full-scale models are typically very expensive, have limited functionality, and are difficult to adapt to diverse research needs. To address this shortcoming, this article presents the design of a low-cost, modular 3D-printed small prototype of a wind turbine. It includes a multi-hollow platform for marine environments configuration and stabilization, the turbine tower, and three blades with active pitch control, not always included in wind turbine prototypes. The modular tower design allows for easy height extensions, while the rotor incorporates custom blades optimized for the prototype geometry and experimental setup. Tests were conducted to evaluate the system’s operational response and verify the proper functioning of the assembled components at various wind speeds and blade pitch angles. The results confirm that the rotor speed with the prototype’s onshore configuration is highly pitch-dependent, reaching a maximum efficiency of approximately 5°. The tower displacement, measured with an IMU, remained within a narrow range, oscillating around 2° and reaching up to 4° at higher wind speeds due to elastic deflections of the PLA structure. These results, consistent with the prototype scale, validate its usefulness in capturing essential aerodynamic and structural behaviors of the wind turbine. They also demonstrate its relevance as a new tool for experimental studies of wind turbines and open up new research, validation, and control possibilities not considered in previous developments by incorporating blade pitch control. Full article

Japanese Encephalitis (JE) is a mosquito-borne viral infection that causes acute brain inflammation. First identified in Japan in 1871, the disease gained renewed global attention in 2025 after emerging in a non-endemic region, raising significant healthcare concerns. Vaccination remains the most effective strategy for preventing outbreaks. However, low- and middle-income countries (LMICs) face considerable challenges in implementing vaccination programs due to geographical, economic, and regulatory barriers. Most existing studies on JE vaccines (JEVs) have been conducted in higher-income countries, leaving critical gaps in data on efficacy and safety in LMIC settings. Furthermore, uncertainties surrounding cost-effectiveness make funding decisions more complex. This narrative review evaluates the current evidence on JE vaccination in LMICs, based on a literature search in PubMed and ScienceDirect covering 2005–2025. The review examines vaccine efficacy, safety, cost-effectiveness, and policy implementation. Findings show that JEVs demonstrate high efficacy and strong safety profiles, with mild adverse effects, most commonly fever. The live attenuated SA 14-14-2 vaccine (LAJEV) is particularly cost-effective, offering substantial economic benefits by reducing healthcare expenditures in endemic regions. To ensure sustainability, vaccination programs in LMICs require tailored policies and targeted financial support. Policy frameworks must be adapted to local contexts, enabling focused, effective, and equitable implementation. Full article

Shanlan rice, a unique drought-resistant rice germplasm resource in Hainan Province, China, holds significant potential for rice genetic improvement and breeding innovation. However, its genetic diversity and significance in rice breeding remain inadequately explored. This study conducted a comprehensive analysis of phenolic acid profiles and antioxidant properties in the brown rice of 84 Shanlan rice accessions. It was revealed that colored Shanlan rice accessions exhibited significantly higher total phenolic content (249.00–2408.33 mg gallic acid equivalents per 100 g of rice flour (mg GAE/100 g)) and antioxidant capacity (DPPH: 680.39–809.63 micromoles of Trolox equivalent per 100 g (μmol TE/100 g); ABTS: 529.93–1917.77 μmol TE/100 g) compared to white-grained varieties. High-performance liquid chromatography (HPLC) analysis identified eight phenolic acids in the bound fractions, among which the sinapic acid (55.08 μg/g) and vanillic acid (11.72 μg/g) were predominant, accounting for over 60% of total bound phenolic acid content. A genome-wide association study (GWAS) identified 84 significant loci associated with these phenolic-related traits. A major quantitative trait locus (QTL) on chromosome 7 for free phenolic content, total phenolic content, flavonoids, and DPPH activity was co-located at the Rc gene locus, a key regulator of red pericarp pigmentation and proanthocyanidin biosynthesis. Haplotype analysis identified ten haplotypes in Rc, with the haplotype H002 showing the highest antioxidant capacity. Another QTL on chromosome 11 was associated with p-coumaric, vanillic, and sinapic acids, although no significant difference was observed in haplotype analysis. These results highlight Rc as a key genetic factor underlying antioxidant properties in rice, while other loci require further validation. This research provides a foundation for breeding health-benefit, drought-tolerant rice cultivars using Hainan’s unique germplasm. Full article

Internal waves play a critical role in material transport, vertical mixing, and energy dissipation within stratified aquatic systems. Their dynamics are strongly modulated by thermal stratification and surface meteorological forcing. This study examines the influence of interannual meteorological variability from 1980 to 2010 on internal wave behavior using a series of numerical simulations in Lake Biwa in Japan. In each simulation, air temperature, wind speed, or precipitation was perturbed by ±2 standard deviations relative to the climatological mean. Power spectral analysis of simulated velocity fields was conducted for the surface, thermocline, and bottom layers, focusing on super-inertial (6–16 h), near-inertial (~16–30 h), and sub-inertial (>30 h) frequency bands. The results show that higher air temperatures intensify stratification and enhance near-inertial internal waves, particularly within the thermocline, whereas cooler conditions favor sub-inertial wave dominance. Increased wind speeds amplify internal wave energy across all layers, with the strongest effect occurring in the high-frequency band due to intensified wind stress and vertical shear, while weaker winds suppress wave activity. Precipitation variability primarily affects surface stratification, exerting more localized and weaker impacts. These findings highlight the non-linear, depth-dependent responses of internal waves to atmospheric drivers and improve understanding of the coupling between climate variability and internal wave energetics. The insights gained provide a basis for more accurate predictions and sustainable management of stratified aquatic ecosystems under future climate scenarios. Full article

Background. The existing literature highlights a lack of comparative studies between subtypes of cholangiocarcinoma (CC) and the impact of misclassification on the epidemiological parameters. Methods. A retrospective study was conducted to evaluate the surgical outcomes. The authors used Poisson regression with modified errors to calculate the risk ratios (RR) and reported post-estimation marginal effects. Coefficient estimates, variance inflation factors, and Pearson’s goodness-of-fit test statistics were used to check for multicollinearity and model fit, respectively. We also performed a reclassification analysis by modeling Klatskin tumors (PCC) as extrahepatic (ECC), reclassifying them as intrahepatic (ICC), and comparing the corresponding changes in estimates. Results. Regression analysis revealed an increased risk of death in patients with ICC (RR = 2.05, 95% CI 1.11–3.78) and PCC (RR = 2.03, 95% CI 0.97–4.24) compared to those with DCC. When PCC was analyzed as an ECC, the ICC revealed an RR of 1.52 (95% CI 0.84–2.73). Further reclassification of PCC showed an RR of 2.04 for ICC (95% CI: 1.53–3.53). The adjusted marginal effects saw a reduction in the death probability for both ICC and ECC. However, post hoc analyses revealed insufficient evidence for differences between the reclassified models. Conclusions. Patients with DCC had slightly better prognosis compared to ICC and PCC. We found no differences in survival between ICC and ECC (combining DCC and PCC). The decrease in mortality risk due to reclassification in both groups was not confirmed statistically. Future studies should focus on statistical evidence when referring to the Will Rogers phenomenon, instead of inferring from raw comparisons. Full article