Search Results (348)

Reliable motion classification is essential for practical prosthetic-hand control. Unintended activations caused by ambiguous motions, unknown motions, or non-target body movements can degrade controllability and compromise user safety. Mechanical-sensing approaches are attracting attention as alternatives or complements to surface electromyography, and tactile-sensor-based methods represent one such direction. However, despite extensive studies on prosthetic control, systematic investigations of computationally lightweight motion-rejection strategies remain limited. This study investigates rejection mechanisms to improve the robustness of polyvinylidene fluoride (PVDF) tactile-sensor-based prosthetic control. The proposed approach selectively withholds outputs for misclassified and non-target inputs. We compare three mechanisms: (1) one-class support vector machine (OCSVM) outlier detection, (2) entropy-based rejection using a multilayer perceptron (BPNN-Entropy), and (3) a parameter-free decision-consistency check for one-vs-rest support vector machines (SVMs) that withholds classification when the output sign pattern is inconsistent (one-vs-rest reject option (OvR-RO); proposed). Performance is evaluated for three sources of unintended activation: ambiguous target trials (retrospectively defined), unknown motions excluded from training, and non-target body movements. The results show that OvR-RO achieves a favorable balance between rejection rate and rejection precision for ambiguous motions, while maintaining responsiveness. Overall, explicitly rejecting misclassified and non-target motions is effective for enhancing robustness in tactile-sensor-based prosthetic control. Full article

Background: The combination of hepatic arterial infusion chemotherapy (HAIC) with immune checkpoint inhibitors (ICIs) and anti-angiogenic agents represents a potential therapeutic strategy for advanced hepatocellular carcinoma (HCC). This study aimed to compare the efficacy and safety of triple therapies combining HAIC with ICIs and either bevacizumab or tyrosine kinase inhibitors (TKIs) in these patients. Methods: This retrospective single-center study enrolled 65 consecutive patients with advanced HCC who received HAIC combined with ICIs plus either bevacizumab (bevacizumab group, n = 31) or TKIs (TKIs group, n = 34) between June 2021 and June 2023. Primary endpoints included progression-free survival (PFS), objective response rate (ORR), duration of response (DOR), and safety profiles. Results: The bevacizumab group demonstrated significantly prolonged median PFS (10.9 vs. 7.4 months, p = 0.001) and higher ORR (83.9% vs. 61.8%, p = 0.047) compared with the TKIs group. DOR was longer in the bevacizumab group (7.9 vs. 5.3 months, p = 0.008). Median overall survival (OS) was not reached in the bevacizumab group versus 22.6 months in the TKIs group. Grade 3–4 adverse events occurred in 67.7% of the bevacizumab group and 73.5% of the TKIs group, with distinct toxicity profiles. Gastrointestinal hemorrhage (45.2%) and gastric ulcer (22.6%) predominated in the bevacizumab group, whereas the TKIs group exhibited more hepatic enzyme elevations (aspartate aminotransferase, 67.6%; alanine aminotransferase, 61.8%), proteinuria (29.4%), diarrhea (26.5%), hand-foot syndrome (20.6%), and reactive cutaneous capillary endothelial proliferation (11.8%). Conclusions: Bevacizumab-containing triplet therapy was associated with improved tumor control and delayed progression compared to TKIs-based regimens in advanced HCC. The higher bleeding risk in the bevacizumab group highlights the necessity of standardized baseline evaluation and adequate preventive measures. Full article

(1) Background: Subclinical neck pain is mild-to-moderate neck pain that has not yet been treated, and where individuals experience pain-free days. Alterations in sensorimotor integration, motor control, proprioception, and cerebellar inhibition have been observed in individuals with subclinical neck pain. Upregulation of the cervico-ocular reflex is documented in subclinical neck pain, with no difference in the gain of the vestibulo-ocular reflex. Vestibulo-ocular reflex gain adaptation and associated differences in visuo-motor control have not been successfully measured in this population. This study aims to investigate the vestibulo-ocular reflex gain adaptation and visuo-motor control in individuals with subclinical neck pain. (2) Methods: 30 right-hand-dominant participants (19 healthy controls: 10 male and 9 female; 16 subclinical neck pain: 6 male and 10 female) aged 18 to 35 performed an eye tracking task. Participants were seated 90cm away from a monitor and instructed to hold their gaze on a stationary or moving target projected onto a screen while performing active head rotations. Trials were divided into 12 blocks (pre-adaptation, 10 adaptation, and post-adaptation) for a total of 192 trials. During adaptation, the target would move at increasing speeds during each block, increasing by 10% of active head velocity up to a maximum of 100%. (3) Results: The subclinical neck pain group demonstrated significantly higher total saccades (p = 0.006, ƞ² = 0.240) and overt catch-up saccades (p = 0.041, ƞ² = 0.141) than the healthy control group. (4) Conclusion: Subclinical neck pain alters the visual–vestibular interaction. Full article

Background/Objectives: Conventional next-generation sequencing (NGS) workflows often require more than two weeks to complete, delaying treatment decisions and limiting access to precision oncology in community settings. This report aimed to demonstrate the feasibility of performing rapid, comprehensive cell-free DNA (cfDNA)-based genomic profiling by introducing a fully automated NGS workflow in a community hospital environment. Case Presentation: A postoperative patient with pancreatic ductal adenocarcinoma and liver metastasis underwent cfDNA-based liquid biopsy using plasma collected in PAXgene^® Blood ccfDNA Tubes. Gene analysis was performed using the Oncomine Precision Assay GX5 on the Ion Torrent Genexus™ System (Thermo Fisher Scientific). Three pathogenic hotspot mutations—KRAS G12R, TP53 M246I/M246K, and GNA11—and one copy number gain in PIK3CA were identified, whereas no variants were detected in a healthy volunteer control. The total turnaround time from plasma separation to report generation was approximately 27 h, requiring only 40 min of total hands-on time. Discussion: This rapid, automated workflow enabled comprehensive cfDNA analysis within a clinically practical timeframe, overcoming key limitations of conventional multi-step NGS workflows that typically require external sample shipment and specialized personnel. The results confirm the technical feasibility of conducting high-quality molecular testing in a regional hospital setting. Conclusions: This report demonstrates that fully automated cfDNA-based NGS can achieve clinically meaningful genomic profiling within 27 h in a community hospital. This advancement addresses the time and cost barriers of traditional NGS analysis and represents a significant step toward promoting precision medicine in community healthcare. Full article

This paper introduces a lightweight and accessible interaction system for treadmill-based video games, relying solely on facial tracking via a smartphone’s front camera. The system enables real-time estimation of running cadence and directional control through natural head movements, providing an immersive and hands-free gaming experience. A key contribution is the implementation of a FFT-based cadence estimation method that achieves accuracy errors below 5% using only 128 frames, enabling real-time feedback. Preliminary evaluations with 11 participants demonstrate that the FFT-based approach outperforms traditional peak detection in both accuracy and robustness across multiple running speeds. These results position the system as a practical, efficient, and scalable solution for fitness-oriented human–computer interaction, with promising implications for digital health and exergaming. Full article

The metabolism of polyunsaturated fatty acids (PUFAs) is a broad research field, and the products identified so far offer potential medical and industrial applications. Epoxy fatty acids (EpFAs) act as lipid mediators that modulate renal function, angiogenesis, vascular dilatation and inflammation; moreover, they regulate monocyte aggregation and are involved in cardiovascular and metabolic diseases. On the other hand, EpFAs are precursors of environmentally friendly products for the plastics industry, in which the grade of epoxidation of the compounds gives the polymeric material different advantageous characteristics. The controlled chemical synthesis of poly epoxidized PUFAs is challenging as the reactions are non-selective. In contrast, the biosynthetic route based on cytochrome P450 monooxygenases and lipoxygenases is highly selective but ineffective due to the instability of the enzymes in cell-free systems. Fungal unspecific peroxygenases (UPOs, EC 1.11.2.1) with P450-like activity offer a suitable alternative for the selective synthesis of EpFAs from PUFAs. Here we demonstrate that a recombinant unspecific peroxygenase from Aspergillus niger (rAniUPO) is able to sequentially epoxidize eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) to 14,15-17,18 diepoxyeicosatrienoic acid (14,15-17,18 diEpETrE) and 16,17-19,20-diepoxydocosatetraenoic acid (16,17-19,20 diEpDTE), respectively, while arachidonic acid is transformed into 13-hydroxy-14,15-epoxyeicosatrienoic acid (14,15-hepoxilin B₃). Optimal production for these oxygenated derivatives (up to 15 mg) was achieved using 2 mM hydrogen peroxide as the co-substrate. The obtained molecules were identified using high-resolution mass spectrometry and their structure was verified by NMR. Our results demonstrate the suitability of UPOs for the synthesis of EpFAs that can be used in medical research and industrial applications. Full article

Current upper-limb rehabilitation robots primarily focus on training tasks involving free movements or static interactions with rigid objects. These paradigms lack simulation of complex object manipulation tasks encountered in daily life, thereby limiting the training of patients’ high-level sensorimotor integration capabilities. To address this gap, this study proposes an innovative robotic rehabilitation training system designed for functional occupational therapy. Specifically, the task of transporting a water cup was abstracted into a cup–ball system integrated with a robotic arm. The ball was modeled as a point mass, and kinematic and dynamic analyses of the system were conducted. A visual tracking method was employed to monitor the ball’s motion and calculate its slosh angle. Owing to the impaired fine motor control in stroke patients, a sloshing suppression control strategy integrating exponential filtering, feedforward force compensation, and impedance control was proposed to prevent the ball from spilling. Experiments validated the effectiveness of the proposed method. The results indicated that with full compensation, the oscillation rate of the ball was significantly reduced, and the smoothness of the hand force was markedly improved. This study presents an effective method for addressing dynamic uncertainty in rehabilitation robot training, thus significantly improving the functional relevance of the training. Full article

Immobilization of yeast cells represents a significant advance in alcoholic fermentation. Compared to traditional methods that rely on the use of free cells, immobilized systems enable higher cell density, easier separation and reuse of biocatalysts, and improved fermentation control, all while maintaining cellular activity. The choice of immobilization material plays a key role in performance. Natural polymers such as alginate provide biocompatibility, but the main drawback is their insufficient mechanical strength. On the other hand, synthetic polymers offer greater durability but raise concerns regarding food safety and cost. Three-dimensional (3D) bioprinting is emerging as a promising solution, enabling the design of structural, customizable matrices with precise cell positioning and tunable physical properties. Traditional materials are undergoing reengineering as bioinks, while new synthetic and hybrid materials are being developed to overcome the limitations of conventional carriers. These innovations combine biocompatibility with mechanical stability and functional adaptability for industrial use. Although the application of 3D bioprinting to produce such carriers has shown promising progress, challenges remain in scalability, process integration, and long-term stability under industrial fermentation conditions. For these reasons, continued interdisciplinary research is necessary to further develop advanced techniques for immobilizing yeast cells for use in alcoholic fermentation. Full article

This paper proposes a sub-sampling phase-locked loop (SSPLL) that combines a time-to-digital converter (TDC)-free digital coarse loop with a high-gain analog SSPD fine loop. The coarse loop follows a counter-assisted, frequency-domain DPLL framework with an auxiliary FLL, enabling wide capture range and fast initial acquisition. Precise fractional-N operation without a TDC is achieved by reusing the fine loop delta–sigma modulator (DSM) and digital-to-time converter (DTC) in the coarse loop: the DSM maps the frequency control word (FCW) fraction to a variable integer sequence for integer-domain fractional synthesis, while the DTC aligns reference clock to the nearest oscillator edge to cancel DSM-induced quantization error. An LMS-based DTC gain calibration is enabled in the coarse loop, and its calibrated gain is handed off to the fine loop, stabilizing loop switching despite the narrow locking range of the SSPD. Constraining arithmetic to the integer path eliminates a need of TDC and simplifies hardware, improving area efficiency while preserving accurate frequency/phase alignment. Simulations in 28 nm CMOS over 4–5 GHz with a 104 MHz reference demonstrate 177-fs RMS jitter, −245.6 dB FoM, 0.146-mm² active area, and 8.94 mW power, validating wide capture, low in-band phase noise, and robust coarse-to-fine handover. Full article

Background/Objectives: The purpose of the study is to determine and compare the accuracy and efficiency of two dynamic navigation systems (DNS)—Navident (ClaroNav, Canada) and X-Guide (Nobel Biocare, Switzerland)—vs. a free-hand (FH) approach in performing endodontic microsurgery (EMS) on human cadavers. Methods: a total of 119 roots of six cadavers were randomly divided into three groups (Navident/X-Guide/FH). The cadavers’ jaws were scanned pre-operatively with computed tomography. The DICOM data were uploaded and digitally managed with software interfaces for registration, calibration, and virtual planning of EMS. Osteotomy was performed under DNS control and using a dental operating microscope (FH control group). Post-operative scans were taken with same settings as preoperative. Accuracy was then determined by comparing pre- and post-scans of coronal and apical linear, angular deviation, angle, length, and depth of apical resection. Efficiency was determined by measuring the procedural time of osteotomy, apicectomy, retro-cavity preparation, the volume of substance, and cortical bone loss, as well as iatrogenic complications. Outcomes were also evaluated in relation to different operators’ skill levels. Descriptive statistics and inferential analyses were conducted using R software (4.2.1). Results: DNS demonstrated better efficiency in osteotomy and apicectomy, second only to FH in substance and cortical bone loss. Both DNS approaches had similar accuracy. Experts were faster and more accurate than non-experts in FH, apart from resection angle, length and depth, and retro-cavity preparation time, for which comparison was not statistically significant. The Navident and X-guide groups had similar trends in increasing efficiency and accuracy of EMS. All complications in the FH group were performed by non-experts. The X-guide group demonstrated fewer complications than the Navident group. Conclusions: Both DNS appear beneficial for EMS in terms of accuracy and efficacy in comparison with FH, also demonstrating the decreasing gap of skill expertise between experts and novice operators. Through convenient use X-guide diminishes the level of iatrogenic complications compared to Navident. Full article

Products such as toothpaste tablets align with the concept of sustainable cosmetic production. The aim of this study was to evaluate the physical and functional properties of toothpaste tablets with different formulations—with and without fluoride, surfactants, and dried herbs. The following parameters were determined: friability (using a shaking method), compressive strength (using a tensile testing machine), colour parameters (spectrophotometrically), pH, and foaming capacity. The study results showed that tablet durability is closely dependent on the formulation. Tablets made with commonly used ingredients (control sample) had the highest breaking force (55.24 N). Tablets without fluoride had the lowest friability (1.46%). Optical tests showed that different formulations affected tablet brightness and colour saturation. The largest changes were observed for samples containing dried herbs—ΔE > 5. The tablets with clove added had improved foam quality, which is important from a functional perspective. The disintegration time of the tablets was significantly shorter for the modified formulation samples. The study results indicate that the developed tablets, especially the control and fluoride-free samples, are sufficiently hard and durable. The tablets with added herbal ingredients, on the other hand, exhibit good foaming and dissolving properties and are waterless products without preservatives. Full article

This paper describes a small, quasi-experimental, mixed method study investigating teacher and child outcomes for a preschool data science intervention condition compared to a business-as-usual comparison condition. The intervention included both hands-on activities and a free digital tool called the Preschool Data Toolbox to engage young children in foundational data science activities. The intervention activities aligned with a learning blueprint that articulated a set of early childhood data science learning goals based on K-12 computer science and early mathematics standards. The intervention supports teachers to implement foundational data science investigations using an intuitive tablet app that scaffolds the DS process through structured and open-ended instructional experiences. Findings from classroom observations, teacher surveys, and interviews indicate high feasibility and engagement, with teachers reporting ease of use, developmental appropriateness, and positive impacts on children’s data acumen and math skills (n = 217). After controlling pre-test scores, children who participated in the intervention demonstrated statistically higher post-test scores (p = 0.001) compared to those in the comparison group, highlighting the effectiveness of the program in fostering early STEM skills. The study underscores the potential of developmentally appropriate DS experiences to foster early learning, support teacher confidence, and prepare children for future academic success, while highlighting the need for further research and professional development to scale such interventions effectively. Full article

Campylobacter hepaticus is the etiological agent of Spotty Liver Disease (SLD), a newly emerging bacterial disease of laying hens resulting in significant mortality and production losses primarily in free-range systems. Although its economic impact continues to grow, the molecular basis of C. hepaticus pathogenesis remains poorly understood. In this study, we conducted transcriptomic profiling of C. hepaticus in three host-relevant conditions, exposure to chicken bile, infection of a chicken liver hepatocellular carcinoma (LMH) cell line, and isolation from liver lesions of naturally infected chickens. Through RNA-seq analysis, we found unique gene expression signatures in each environment. In the bile, C. hepaticus exhibited differential expression of 412 genes, with upregulation of genes related to motility, cell envelope remodeling, glycosylation, nitrate respiration, and multidrug efflux systems, indicating a stress-adaptive, metabolically active lifestyle. In LMH, on the other hand, 125 genes were differentially expressed, primarily reflecting downregulation of motility, oxidative stress response, chaperones, and core metabolic processes, suggesting that these cells adopt a less active, intracellular dormant lifestyle. Transcriptomic analysis of C. hepaticus isolated from the liver identified 26 differentially expressed genes, featuring selective upregulation of genes associated with nitrate respiration, sulfur metabolism, and pyridoxal 5’ phosphate homeostasis, alongside downregulation of the major outer membrane porin (momp), stress response chaperones (dnaK, groL), and genes involved in oxidative stress defense and energy production. Furthermore, the immune evasion-related gene cmeA and a glycosyltransferase gene were found to be highly upregulated. This study presents the first in-depth transcriptomic exploration of C. hepaticus in multiple host relevant niches. Our findings reveal niche-specific gene expression profiles and highlight metabolic and structural adaptations that enable C. hepaticus to survive during bile exposure, persist within host cells, and contribute to liver pathology. These insights provide a basis for identifying novel virulence determinants and may inform the development of targeted interventions, including vaccines or antimicrobial therapy, to control SLD in commercial poultry operations. Full article

This paper introduces a gesture-controlled conversational interface driven by a local AI model, aimed at improving accessibility and facilitating hands-free interaction within digital environments. The technology utilizes real-time hand gesture recognition via a typical laptop camera and connects with a local AI engine to produce customized learning materials. Users can peruse educational documents, obtain topic summaries, and generate automated quizzes with intuitive gestures, including lateral finger movements, a two-finger gesture, or an open palm, without the need for conventional input devices. Upon selection of a file, the AI model analyzes its whole content, producing a structured summary and a multiple-choice assessment, both of which are immediately saved for subsequent inspection. A unified set of gestures facilitates seamless navigating within the user interface and the opened documents. The system underwent testing with university students and faculty (n = 31), utilizing assessment measures such as gesture detection accuracy, command-response latency, and user satisfaction. The findings demonstrate that the system offers a seamless, hands-free user experience with significant potential for usage in accessibility, human–computer interaction, and intelligent interface design. This work advances the creation of multimodal AI-driven educational aids, providing a pragmatic framework for gesture-based document navigation and intelligent content enhancement. Full article

Arthritis and arthrosis are prevalent joint diseases that cause pain and disability, and their early diagnosis is crucial for preventing irreversible damage. Conventional diagnostic methods such as X-ray, ultrasound, and MRI have limitations in early detection, prompting interest in alternative techniques. This work presents the design and clinical evaluation of a prototype device for non-invasive early diagnosis of arthritis (inflammatory joint disease) and arthrosis (osteoarthritis) using infrared thermography and deep neural networks. The portable prototype integrates a Raspberry Pi 4 microcomputer, an infrared thermal camera, and a touchscreen interface, all housed in a 3D-printed PLA enclosure. A custom Flask-based application enables two operational modes: (1) thermal image acquisition for training data collection, and (2) automated diagnosis using a pre-trained ResNet50 deep learning model. A clinical study was conducted at a university clinic in a temperature-controlled environment with 100 subjects (70% with arthritic conditions and 30% healthy). Thermal images of both hands (four images per hand) were captured for each participant, and all patients provided informed consent. The ResNet50 model was trained to classify three classes (healthy, arthritis, and arthrosis) from these images. Results show that the system can effectively distinguish healthy individuals from those with joint pathologies, achieving an overall test accuracy of approximately 64%. The model identified healthy hands with high confidence (100% sensitivity for the healthy class), but it struggled to differentiate between arthritis and arthrosis, often misclassifying one as the other. The prototype’s multiclass ROC (Receiver Operating Characteristic) analysis further showed excellent discrimination between healthy vs. diseased groups (AUC, Area Under the Curve ~1.00), but lower performance between arthrosis and arthritis classes (AUC ~0.60–0.68). Despite these challenges, the device demonstrates the feasibility of AI-assisted thermographic screening: it is completely non-invasive, radiation-free, and low-cost, providing results in real-time. In the discussion, we compare this thermography-based approach with conventional diagnostic modalities and highlight its advantages, such as early detection of physiological changes, portability, and patient comfort. While not intended to replace established methods, this technology can serve as an early warning and triage tool in clinical settings. In conclusion, the proposed prototype represents an innovative application of infrared thermography and deep learning for joint disease screening. With further improvements in classification accuracy and broader validation, such systems could significantly augment current clinical practice by enabling rapid and non-invasive early diagnosis of arthritis and arthrosis. Full article