Search Results (1,775)

Background: Approximately half of U.S. adults have ≥1 cardiovascular disease (CVD) risk factors. Exercise is universally recommended as a first-line lifestyle therapy to prevent and treat CVD. Objective: We will conduct a feasibility and pilot efficacy randomized controlled trial to test the usability and user satisfaction of an evidence-based digital health tool we developed for physicians—the Prioritizes Personalizes Prescribes EXercise algorithm (P3-EX)—to treat patients with CVD risk factors (ClinicalTrials.gov: NCT07238556). Methods: We will recruit 24 physicians who do not prescribe written exercise prescriptions (ExRx) from two local CT hospitals. Physicians will recruit two patients each (N = 48); both patients must have CVD risk factors. Each physician will deliver a P3-EX ExRx to one patient (n = 24) and the Physical Activity Vital Sign ExRx to the other patient (n = 24) in a random sequence crossover design. Physicians and patients will rate the feasibility and acceptability of each ExRx method using validated questionnaires. Patients will perform their ExRx for 12 weeks and complete an exercise diary to monitor exercise adherence with weekly virtual oversight by Research Assistants. Before and after the exercise intervention, we will measure patient CVD risk factors and physical activity levels via accelerometry. Results: This trial has received Institutional Review Board approval (E-HHC-2025-0198) and will begin in January 2026, with findings published in 2027. Conclusions: This protocol provides the scientific rationale and methodology to test P3-EX within a real-world clinical setting, to inform the feasibility of using P3-EX as a digital health support tool by physicians, and preliminary efficacy of P3-EX to improve patient cardiovascular health and physical activity levels. Full article

Background/Objectives: Medication incidents remain a significant concern in hospital settings. Integrated medication systems, regarding organized processes, policies, technologies and professional practices are designed to enhance patient safety; however, their safety performance is still suboptimal. The use of valid and reliable instruments to assess hospital medication system safety can be a valuable resource for health care management. The aim of this study was to describe the development and psychometric validation of the Hospital Medication System Safety Assessment Questionnaire (HMSSA-Q) for assessing the safety of hospital medication systems and its processes in Portugal. Methods: The HMSSA-Q was developed through a literature review and two rounds of expert panel consultation. Following consensus, a pilot methodological study was conducted in 95 Portuguese hospitals. Construct validity was assessed using principal component factor analysis, and reliability was evaluated through internal consistency (Cronbach’s alpha). Results: The instrument is theoretically structured into five predefined domains/subscales: Organizational Environment, Safe Medication Prescribing, Safe Medication in Hospital Pharmacy, Safe Medication Preparation and Administration, and Information and Patient Education. Principal component analyses performed separately for each domain supported their internal structure. The overall scale showed excellent internal consistency (Cronbach’s α = 0.97), with Cronbach’s alpha values for the domains ranging from 0.86 to 0.94. Conclusions: The HMSSA-Q is a valid and reliable instrument for assessing the safety of hospital medication systems and has the potential to serve as an innovative management tool for improving patient safety. Full article

Background/Objectives: Adults with intellectual disability (ID) experience high rates of psychiatric comorbidity but often face diagnostic challenges and treatment barriers, leading to inappropriate psychotropic medication use. This study examined the extent to which specialized psychiatric assessment and improved diagnostic accuracy had an impact on medication management and clinical outcomes in adults with ID and co-occurring psychiatric disorders. Methods: This observational retrospective study analyzed medical records from 25 adults with ID who underwent specialized psychiatric assessment at a community-based service in Italy between January 2023 and January 2024. Psychopathological diagnoses were established according to Diagnostic Manual—Intellectual Disability, Second Edition (DM-ID2) criteria, based on clinical observation and a comprehensive assessment using validated instruments. Clinical outcomes were assessed using a psychometric tool encompassing multiple psychopathological and behavioral dimensions. Data on psychotropic prescriptions and side effects were also collected. Non-parametric analyses were performed, with significance set at α = 0.05. Results: The proportion of patients with a psychiatric diagnosis increased from 32% to 96% after specialized assessment (p < 0.001), with notable rises in depressive (0% to 32%), bipolar (8% to 36%), anxiety (4% to 24%), and impulse control (0% to 16%) disorders. First-generation antipsychotic prescriptions decreased (from 36% to 8%, p = 0.023), while antidepressant use increased (from 12% to 52%, p = 0.004). The mean number of side effects per patient declined from 1.6 to 0.5 (p < 0.001), particularly the elevated prolactin level and psychomotor retardation. Significant improvements were observed in symptom intensity and frequency across multiple domains, including aggression, mood disturbances, and compulsions (p < 0.001). Conclusions: In this single-center retrospective study, specialized psychiatric assessment was associated with improved diagnostic accuracy, medication management, and clinical outcomes in adults with ID. The increase in psychiatric diagnoses likely reflects improved identification, addressing key challenges in precision diagnosis for people with neurodevelopmental disorders. Although the overall number of prescribed medications remained stable, optimization of treatment regimens reduced first-generation antipsychotic use and related adverse effects. These findings indicates that access to specialized assessment and precision diagnosis could improve psychopharmacological interventions and outcomes for this vulnerable population, but larger, multi-center and longer-term studies are needed to confirm these results. Full article

This paper formulates a control framework grounded in prescribed performance control (PPC) and combined with a dynamic error modulation function. The proposed framework addresses the control challenges of DC–DC boost converters under sudden power variations caused by constant power loads (CPLs). A sine kernel-based prescribed performance function with smoothly decaying characteristics is designed to form a dynamic performance boundary that gradually tightens as the system state evolves. Furthermore, to effectively eliminate the restriction of traditional PPC on the system’s initial state, a time-varying modulation function is introduced. This function dynamically scales the tracking error, thereby improving the system’s adaptability at the initial state. A neural network disturbance observer (NNDO) is employed to approximate and compensate for unknown nonlinearities and external disturbances, thereby enhancing system robustness and adaptability. Consequently, a prescribed performance controller that integrates dynamic error modulation and a dual-channel NNDO is proposed. The proposed controller not only guarantees that the tracking error satisfies the prescribed performance constraints but also avoids the computation of high-order derivatives. Simulation results demonstrate that the proposed method maintains bounded convergence of the tracking error and achieves smooth voltage regulation during CPL variations. The results further exhibit excellent dynamic response and steady-state performance. Full article

Although PINNs have demonstrated strong predictive capabilities in forward problems, their performance in inverse problems remains inadequate, largely due to unquantifiable noise encountered during the multi-parameter identification of prestressed concrete beams. Experimental measurements are often noisy, sparse, or asymmetric, while numerical or analytical models, although physically consistent, are typically approximate and lack regularization from well-defined multi-fidelity data. To address this limitation, this paper proposed a multi-fidelity data and prior-enhanced physics-informed neural network (MF-rPINN), which integrates multi-fidelity data with physics prior relational constraints to guide parameter identification using only sparse experimental observations. The MF-rPINN architecture is designed to enforce consistency between each training iteration and a prescribed set of experimental measurements, while embedding the second-order displacement function into the loss function. Experimental results demonstrate that the proposed MF-rPINN achieves accurate parameter identification even under noisy and incomplete observations, owing to the combined regularization effects of governing physical laws and the second-order displacement prior. The minimum relative errors of the elastic modulus are −6.49% and −9.32% under different and identical loading conditions, respectively, while the minimum relative errors of the prestress force are 0.65% and 4.51%. Compared with classical analytical approaches, MF-rPINN exhibits superior robustness and is capable of predicting continuous displacement fields of prestressed concrete beams while simultaneously identifying prestress force and elastic modulus. These advantages highlight the potential of MF-rPINN as a reliable surrogate modeling tool for practical engineering applications. Full article

Script Concordance Tests (SCTs) assess clinical reasoning under uncertainty. While construction guidelines exist, the feasibility of collaborative development approaches and educators’ real-time experiences remain underreported. This feasibility study explores how medical educators construct SCTs collaboratively and their perceptions of the process. Four UK-based medical educators developed SCTs for prescribing in older adults during a three-hour workshop involving observation with a think-aloud approach, followed by a post-workshop focus group. Data were analysed using Braun and Clarke’s thematic analysis, Tuckman’s group development informed observation analysis, and an inductive approach for the focus group. Educators created seven vignettes (30 items) in 127 min, averaging 18 min per vignette. Observation revealed small-team role specification (lead, scribe, challenger) and three themes: content development, quality checks, and team dynamics. The team progressed rapidly through Tuckman’s stages, spending most of the time in the performing stage. Focus group analysis revealed four themes: design features, perceived utility, group dynamics and best-practice recommendations. This study demonstrates the feasibility of collaborative SCT development through structured teamwork. Educators perceived SCTs as practical, as valuing effective team dynamics and clear role distribution. Findings can provide practical insights for institutions implementing SCT development, emphasising practice sessions and appropriately sized collaborative teams. Full article

Achieving high-precision motion control for hydraulic manipulators presents a challenging task. Addressing the issue of low motion control accuracy caused by the strong electromechanical-hydraulic coupling characteristics of hydraulic manipulator systems, this paper innovatively introduces an RBF neural network and an Actor–Critic reinforcement learning architecture within a performance-based control framework designed using the inverse method. This approach enables dual compensation for both internal uncertainties and external disturbances within the manipulator, thereby enhancing the system’s control performance. First, within the control architecture, the performance function ensures system transient performance while employing an RBF neural network to estimate and compensate for internal unmodeled errors caused by mechanical coupling and hydraulic parameter uncertainties. Stability proofs are used to derive the network weight update rate. Second, a disturbance compensator is designed based on reinforcement learning. Deployed into the controller through offline training and online adaptation, it compensates for external system disturbances, further improving control accuracy. Finally, comparative and ablation experiments conducted on a hydraulic manipulator testbed demonstrate the effectiveness of the disturbance compensator. Compared to PID control, the proposed approach achieves a 60–65% improvement in control accuracy. Full article

Pneumatic separation can exhibit unstable performance when the feed composition fluctuates while operating parameters remain fixed. This work investigates a perception-informed airflow regulation approach, demonstrated on a representative fibrous–granular mixture case study. We propose LGDNet, a lightweight visual ratio estimation network (0.08 M parameters) built with Ghost-based operations and learned grouped channel convolution (LGCC), to estimate mixture composition from dense images. A dedicated 21-class dataset (0–100% in 5% increments) containing approximately 21,000 augmented images was constructed for training and evaluation. LGDNet achieves a Top-1 accuracy of 66.86%, an interval accuracy of 74.10% within a $\pm 5\%$ tolerance, and an MAE of 4.85, with an average inference latency of 28.25 ms per image under the unified benchmark settings. To assess the regulation mechanism, a coupled CFD–DEM simulation model of a zigzag air classifier was built and used to compare a regime-dependent airflow policy with a fixed-velocity baseline under representative prescribed inlet ratios. Under high impurity loading ($r=70\%$), the dynamic policy improves product purity by approximately 1.5 percentage points in simulation. Together, the real-image perception evaluation and the mechanism-level simulation study suggest the feasibility of using visual ratio estimation to inform airflow adjustment; broader generalization and further on-site validation on real equipment will be pursued in future work. Full article

This study presents the development and high-fidelity finite element modelling of an innovative hybrid railway carbody structure, designed to achieve a substantial reduction in mass while maintaining the required mechanical performance under service conditions. The proposed concept integrates a traditional aluminium frame with an advanced honeycomb sandwich panel, joined through adhesive bonding to ensure structural continuity, compensate for thermal effects, and minimize over constraining stresses. Detailed numerical simulations were conducted to evaluate both the static and dynamic behaviour of the structure under the most demanding load cases prescribed by standards. Modal analysis showed excellent agreement with the original carbody, with variations in the first natural frequency about 3%, while a change in the nature of the corresponding eigenvector was observed. Static simulations under maximum vertical loading confirmed comparable stiffness and stress distributions. Localised stress peaks increased by approximately 19%; the corresponding material utilization factor remained below unity, demonstrating that the structure operates safely within its allowable limits. The introduction of the sandwich panel enabled a mass saving of approximately 60% in the replaced components, corresponding to 3.9% if referred to the whole structure. The results validate the structural feasibility and mechanical reliability of the proposed hybrid concept, laying the foundations for the subsequent experimental phase and for refining its predictive accuracy and industrial applicability. Full article

Background: Obesity alters metabolic, inflammatory, and immune responses, and acute exercise may affect these parameters differently according to body composition. This study investigated the acute effects of Spartacus exercise on metabolic, inflammatory, and immune markers in adolescent girls with overweight/obesity and normal weight. Methods: In this non-randomized clinical study, sixteen girls with overweight/obesity (BMI: 31.17 ± 3.85 kg/m²) and fourteen normal-weight girls (BMI: 21.93 ± 0.99 kg/m²) performed an intermittent running test (15 s effort, 15 s passive recovery), starting at 7 km·h⁻¹ with 1 km·h⁻¹ increments every 3 min until exhaustion. Blood samples were collected at rest (T0), immediately post-exercise (T1), and 30 min post-exercise (T2). CRP and ESR were assessed at baseline to characterize participants’ inflammatory status, while glucose and leukocyte subpopulations were evaluated to investigate acute exercise responses. Results: Fasting glucose, lipid profile (TC, TG, HDL-C, LDL-C), inflammatory markers (CRP, ESR), and leukocyte subpopulations were assessed. Significant group effects were observed for all metabolic and inflammatory markers, reflecting higher baseline values in participants with overweight/obesity compared with normal-weight participants (p < 0.05). Significant effects of time were found for glucose and leukocytes (p < 0.001), indicating acute exercise-induced changes, along with significant time × group interactions. Participants with overweight/obesity showed greater and more prolonged increases in glucose, total leukocytes, and neutrophils, whereas normal-weight girls returned to baseline within 30 min. Conclusions: Acute high-intensity intermittent exercise induces transient metabolic and immune responses in adolescents, with amplified and prolonged effects in those with obesity. These findings highlight the importance of considering body composition when prescribing exercise programs. Full article

Background: Benzodiazepines (BZDs) are commonly prescribed for anxiety, insomnia, and muscle relaxation, but concerns remain regarding their potential long-term cognitive effects. Prior reviews have reported inconsistent associations between BZD use and cognitive risk, often limited by methodological heterogeneity and unresolved biases. Objective: This systematic review critically evaluates the evidence on BZD exposure and cognitive outcomes, with a specific focus on study design, potential biases, and other factors of methodological heterogeneity. Methods: Following PRISMA 2020 guidelines, we searched PubMed and Google Scholar for studies published between 2010 and 2025. The final search was conducted on 1 July 2025. Eligible studies assessed cognitive performance or incident dementia in community-dwelling adults with regard to BZD use. One reviewer independently screened titles, abstracts, and full texts to determine the eligibility of each study. The other two reviewers participated in the inclusion and exclusion decisions. Any disagreements were resolved by consensus among all three reviewers to minimize bias. No statistical data handling, data conversions, or missing imputation was conducted, as this review did not include quantitative synthesis or meta-analysis. Results: Of 79 references screened by titles, abstracts, and full texts, seventeen articles met the inclusion criteria for this review. Participants in the cohort studies were mostly older adults and cognitively healthy at baseline, while those from case–control studies were dementia patients and their matched controls. Overall, findings remain inconsistent, with five studies reporting an association between BZD use and cognition in the entire cohort, six reporting effects only in specific contexts or subgroups, and six finding no evidence at all. Potential contributing factors to this variability include protopathic bias, operational definitions of BZD exposure, and whether analyses were stratified by factors such as sex, drug half-life, or dose. Conclusions: Due to inconsistencies among findings and limitations in study design rigor, the current review cannot determine whether BZDs independently raise cognitive risk. Future research should adopt more rigorous study designs, with particular attention to addressing protopathic bias, and clarify limitations related to the operational definition of BZD. In addition, our findings support the need for further investigation of BZD association with vulnerable populations, including those with sex-specific susceptibility, low socioeconomic status, and exposure to high-risk prescribing practices. Full article

Background: Rotator cuff-related shoulder pain (RCRSP) is a prevalent musculoskeletal disorder treated by physiotherapists. Although international guidelines support active, exercise-based management, little is known about current physiotherapy practices in Cyprus. Aim: To investigate physiotherapy management practices for RCRSP in Cyprus, assess adherence to recommended clinical guidelines, and compare findings with practices in other countries. Methods: A cross-sectional online survey was conducted among Cypriot physiotherapists between June and July 2024. An English case vignette-based questionnaire, adapted from validated international surveys, examined demographics, clinical reasoning, treatment preferences, and guideline adherence. Descriptive statistics summarised responses; chi-square tests and logistic regression identified associations between demographics and clinical decisions. Content analysis was performed on open-ended responses. Results: A total of 143 physiotherapists completed the survey. Most adhered to guideline-recommended care, with 99.3% (n = 142/143) prescribing exercise and 100% (n = 143/143) providing patient education. Conservative management was preferred, with 64.3% (n = 91/143) not recommending imaging, 72.0% (n = 103/143) not recommending injections, and 73.4% (n = 104/143) not recommending surgical referrals. Significant associations were found between special interest in shoulder conditions and recommendations for surgery (χ² = 4.937, p = 0.026) and injections (χ² = 9.143, p = 0.002). Physiotherapists recommending surgery were nearly seven times more likely to suggest MRI (Exp(B) = 6.944, p < 0.001). Conclusions: Cypriot physiotherapists predominantly use exercise and education for the management of RCRSP, aligning closely with international recommendations. Conservative strategies were favoured, with limited use of imaging, injections, and surgical referrals. However, variation in clinical decision-making, particularly regarding referrals and imaging, indicates partial adherence to best practice and highlights opportunities for enhanced guideline implementation and targeted clinical training. Full article

Background: Sitting and standing with conventional hip–knee–ankle–foot (HKAF) prostheses are demanding tasks for hip disarticulation (HD) amputees due to the passive nature of current prosthetic hip joints that cannot assist with moment generation. This study developed a sitting and standing control strategy for a motorized hip joint and evaluated whether providing active assistance reduces the intact side demand of these activities. Methods: A dedicated control strategy was developed and implemented for a motorized hip prosthesis (Power Hip) compatible with existing prosthetic knees, feet, and sockets. One HD participant was trained to perform sitting and standing tasks using the Power Hip. Its performance was compared with the participant’s prescribed passive HKAF prosthesis through measurements of ground reaction forces (GRFs), joint moments, and activity durations. GRFs were collected using force plates, kinematics were captured via Theia3D markerless motion capture, and joint moments were computed in Visual3D. Results: The Power Hip enabled more symmetric limb loading and faster stand-to-sit transitions (1.22 ± 0.08 s vs. 2.62 ± 0.41 s), while slightly prolonging sit-to-stand (1.69 ± 0.49 s vs. 1.22 ± 0.40 s) compared to the passive HKAF. The participant exhibited reduced intact-side loading impulses during stand-to-sit (4.97 ± 0.78 N∙s/kg vs. 15.06 ± 2.90 N∙s/kg) and decreased reliance on upper-limb support. Hip moment asymmetries between the intact and prosthetic sides were also reduced during both sit-to-stand (−0.18 ± 0.09 N/kg vs. −0.69 ± 0.67 N/kg) and stand-to-sit transitions (0.77 ± 0.20 N/kg vs. 2.03 ± 0.58 N/kg). Conclusions: The prototype and control strategy demonstrated promising improvements in sitting and standing performance compared to conventional passive prostheses, reducing the physical demand on the intact limb and upper body. Full article

The Infectious Diseases Society of America (IDSA) guidelines for community-acquired pneumonia (CAP) recommend pneumococcal urinary antigen testing (UAT) for a subset of inpatients admitted with pneumonia. Despite this, UAT testing is frequently performed on inpatients who do not meet the official IDSA criteria, and current evidence regarding antibiotic de-escalation in UAT-positive cases remains inconclusive. To explore this further, we conducted a retrospective cohort study examining antibiotic de-escalation patterns among hospitalized CAP patients who underwent UAT over a 60-day period during peak respiratory illness season (November and December, 2023). Patients with positive UAT results were compared to those who had negative UAT; the primary outcome was whether a positive UAT impacted antibiotic de-escalation prescribing. A total of 268 patients were analyzed—235 UAT-negative and 33 UAT-positive. Both groups were comparable in terms of disease severity, underlying health conditions, and readmission rates. Empiric therapy targeting Pseudomonas aeruginosa (P. aeruginosa) and methicillin-resistant Staphylococcus aureus (MRSA) was used in 40% of patients (36% in the UAT-positive group and 46% of the UAG-negative group). The use of atypical coverage, MRSA coverage, or anti-pseudomonal β-lactams was frequently de-escalated in both cohorts (p < 0.05); however, the UAT-positive group had significantly shorter durations of anti-pseudomonal therapy (p = 0.03) and anti-MRSA therapy (p = 0.02). Despite this, the UAT-positive group was more commonly given fluoroquinolones, such as levofloxacin or moxifloxacin, over narrow-spectrum β-lactams for final antibiotic coverage (p = 0.021). Overall, positive UAT appeared to support earlier discontinuation of anti-MRSA and anti-pseudomonal antibiotics; however, it did not impact fluoroquinolone use. Future antimicrobial stewardship efforts may benefit from promoting greater use of narrow-spectrum β-lactams in these patients. Full article

Steel fiber-reinforced concrete (SFRC) can exhibit markedly improved mechanical performance when the fibers are preferentially aligned along the principal tensile stress directions. One method of aligning steel fibers is using magnetic methods. However, most existing magnetic alignment techniques rely on solenoids and are restricted to one-dimensional alignment and relatively small specimen sizes. This paper presents a novel planar magnetic orientation device capable of producing arbitrary two-dimensional fiber layouts and demonstrates its applicability from laboratory-scale proof-of-concept tests to large high-performance fiber-reinforced concrete (HPFRC) structural elements. The concept is first verified on transparent ultrasound gel specimens, where image analysis confirms fiber orientation in the prescribed angles. The method is then applied to small prismatic HPFRC specimens (40 mm × 40 mm × 160 mm) with fiber contents of 0.5%, 1.0%, and 1.5%, exposed to different magnetic field intensities (80 mT–140 mT). Flexural tests show increases in average flexural strength compared to non-oriented reference specimens, with 100 mT providing the most efficient alignment for the investigated mixture. A non-destructive electromagnetic method based on the measurement of the quality factor Q of a coil correlates well with flexural strength. Finally, the device is integrated with an industrial robot and used to orient fibers in large HPFRC slabs (1000 mm × 410 mm), achieving an average increase in flexural tensile strength of about 64% relative to non-oriented slabs. The results demonstrate that planar magnetic orientation is a promising approach for tailoring fiber layouts in SFRC structural elements and for enabling automated, programmable manufacturing. Full article