Search Results (538)

This study investigated the effects of applying the abdominal draw-in maneuver (ADIM) and manual resistance (MR), separately and in combination, during prone hip extension (PHE) on muscle activity and anterior pelvic tilt. Twenty-four healthy adult males performed PHE under three randomized conditions: ADIM, MR, and ADIM combined with MR. Electromyography was used to measure gluteus maximus (GM), erector spinae (ES), internal oblique (IO), and hamstring activity, while anterior pelvic tilt angle was assessed using a gyroscopic sensor. Repeated-measures ANOVA revealed significant differences across conditions (p < 0.05). Post hoc analysis showed that GM and IO activity were significantly greater in the ADIM combined with MR condition than in either ADIM or MR alone, with MR also producing higher values than ADIM (p < 0.05). ES activity was lowest in the ADIM condition, while ADIM combined with MR produced lower ES activity than MR (p < 0.05). The GM/ES ratio was highest in ADIM combined with MR compared with the other conditions (p < 0.05). Anterior pelvic tilt angle was significantly smaller in both the ADIM and ADIM combined with MR conditions compared with MR (p < 0.05). These findings suggest that combined ADIM with MR induces strong IO contraction and enhances lumbopelvic stability, leading to substantially increased GM activity. Full article

Hospital design greatly influences patient recovery. Evidence indicates that daylight enhances recovery, but hospital designs in Erbil need further optimization of window configurations to provide sufficient daylight. This suboptimal design can result in longer patient stays, negatively affecting recovery outcomes. The study aims to develop a localized daylight optimization model for inpatient hospital rooms in Erbil via integrating window size, shape, and orientation to enhance patient well-being and recovery. This is accomplished through a mixed-method approach: qualitatively, a hypothetical case study has been analyzed using drawings in Revit, and quantitatively, daylighting analysis is conducted using IES-VE 2024 software for a hypothetical inpatient room case study. Results show that orientation has the most significant impact on daylight parameters. Regarding window size and aspect ratio, horizontal window ratios significantly exceeded vertical ratios (p = 0.001), emphasizing the importance of aspect ratio in optimizing daylight distribution. However, window placement did not have a statistically significant effect on illuminance levels (p = 0.182). The study concludes that window orientation and size substantially influence daylighting in hospital patient rooms. It also evaluates alternative configurations—including variations in window size, proportion, orientation, and placement—to explore potential daylighting improvements achievable in similar urban and climatic environments. Full article

To address information isolation and incomplete parameter extraction among multi-modal data (e.g., drawings, text, and tables) in the operation and maintenance stage of buildings, this paper proposes a multi-modal data parsing, automatic parameter extraction, and standardized integration method oriented toward 3D modeling. First, by employing vector element parsing and layer semantic analysis, the method enables structured extraction of key component geometry from architectural drawings and improves modeling accuracy via spatial topological relationship analysis. Second, by combining regular expressions, a domain-specific terminology dictionary, and a BiLSTM-CRF deep learning model, the extraction accuracy of unstructured parameters from architectural texts is significantly improved. Third, a multi-scale sliding window and geometric feature analysis are used to achieve automatic detection and parameter extraction from complex nested tables. Regarding the experimental setup: the drawings consist of a large-scale collection of DXF files stratified and randomly split into train/val/test with an approximate 8:1:1 ratio; the text set includes 1550 PDF-derived specification fragments (8:1:1 split); and the tables cover typical door/window, structural, and electrical schedules (also split ~8:1:1). F1 scores use micro-F1 (instance-level aggregation), and 95% confidence intervals and their computation are described in the main text. Experimental results show that the F1 scores for wall line, wall, and column recognition reach 98.1%, 84.9%, and 92.2%, respectively, while the F1 scores for door and window recognition are 74.3% and 76.2%. For text parameter extraction, the proposed PENet model achieves a precision of 83.56% and a recall of 86.91%. For the table task, the parameter extraction recalls for doors/windows and structure are 95.0% and 96.7%, respectively. The proposed method enables efficient parameter extraction and standardization from multi-modal architectural data, demonstrates significant advantages in handling heterogeneous data and improving modeling efficiency, and provides practical technical support for the digital reconstruction and intelligent management of existing buildings. Full article

The mental health of young adults is a widespread and growing concern in many communities, impacting social sustainability. At the same time, there is growing evidence of the value that nature can provide towards improving health and wellbeing. However, there is little research on the scale of the monetized value of relevant wellbeing benefits from nature exposure. Nature prescribing draws on the growing base of evidence about nature and its health and wellbeing connections, with medical practitioners and/or allied health workers providing a prescription to selected patients to participate in a program that offers interventions intended to improve participant health and/or wellbeing, using a nature setting. This paper is the first to undertake a cost–benefit analysis of nature prescribing, involving a program aimed to improve the wellbeing of young adults with mild to moderate mental illness in regional/rural Victoria, Australia. The evaluation demonstrates that a curated, group-based nature exposure program can yield significant improvement in levels of life satisfaction and mental health in this cohort. Paired sample comparisons and multiple regression analyses suggest that the program produced an increase in mean participant life satisfaction scores of ~0.7 units, measured using Personal Wellbeing Index scores. A project benefit–cost ratio of over four resulted from this. Mental health, as measured by Kessler scale scores, also showed solid improvement, and loneliness was reduced. The unique contributions of nature and of the group-based delivery mode to the measured benefits were not identifiable but the combined effect was evident, improving participants’ likelihood of social inclusion, a major social sustainability goal. Furthermore, the solid program benefit–cost ratios indicate an economically sustainable program, which uses an environmental platform (nature) for its delivery. This links all three triple bottom line sustainability outcomes to this program. Topping up group-based nature exposure, after completion of the six-session, two-hours-per-session program, was important for many participants to sustain benefit levels. Participants emphasized the importance of the program being delivered by trained professionals. Achieving involvement of a suitably sized project comparison or control group through the 8-month program evaluation period to follow-up proved challenging, which somewhat weakens the power of the evaluation findings. Full article

Background: The change over time of certain inflammatory markers, such as the neutrophil–lymphocyte ratio (NLR) and systemic inflammatory response index (SIRI), is a prognostic factor in many cancers, including breast cancer. This study retrospectively evaluated how a 12-week intensive exercise program might have influenced both the NLR and SIRI in women with breast cancer. Methods: Two institutional review board-approved prospective clinical trials, EXERT-BC (NCT05747209, 2 November 2022) and EXERT-BCN (NCT05978960, 31 July 2023), were retrospectively assessed. Complete blood count (CBC) values performed before and after participation in a 12-week intensive resistance program were analyzed post hoc. Blood tests were ordered as part of routine clinical care and not pre-specified by either study protocol. Participants who had blood work more than four months from study intake or completion were excluded. Additionally, those undergoing active systemic therapy or with underlying inflammatory conditions were also excluded. The NLR and SIRI values were analyzed via the Mann–Whitney test, with pair-wise assessment of pre- and post-intervention values via the Wilcoxon signed-rank test. Results: Out of 84 participants, 21 people met the inclusion criteria. Roughly 70% had either ductal carcinoma in situ (DCIS) or early-stage breast cancer. The average blood draw was taken within two months of study intake and outtake. After the 12-week structured exercise program, there was an associated reduction in both the NLR (2.26 [IQR, 1.70–4.22] to 1.99 [1.44–2.62]; ΔNLR = −0.27, W = 47.0, p = 0.016) and SIRI (1.23 [0.82–1.64] to 0.80 [0.59–1.45]; ΔSIRI = −0.43, W = 48.0, p = 0.018). Of those who saw their inflammatory markers improve, roughly two thirds showed a clinically relevant improvement. Conclusions: Completion of a 12-week intensive resistance exercise program was associated with a statistically improved NLR and SIRI. The small sample size and retrospective nature limit the broader application of these findings. The results, however, provide a genesis for prospective validation examining the potential benefit exercise might have on the NLR and SIRI in women with breast cancer. Full article

The escalating demand for sustainable development in the built environment necessitates the integration of innovative, system-based assessment tools. This study investigates the role of energy efficiency (EE) within a nature-inspired sustainability assessment framework, drawing from biomimicry principles to evaluate green building practices in South Africa. Grounded in the ethos of nature’s efficiency, such as closed-loop energy systems, passive energy use, efficiency through form and function, and decentralised and localised energy generation, this study identifies and prioritises key EE criteria, including efficient energy management, renewable energy optimisation, passive heating, ventilation and air conditioning (HVAC) systems, and energy-saving technologies. Using the Analytic Hierarchy Process (AHP), this research engaged 38 highly experienced, practising, and registered construction professionals to perform pairwise comparisons of EE criteria. Results revealed that efficient energy management (29.8%) emerged as the most significant factor, followed closely by energy-saving equipment (26.4%), with strong expert consensus (consistency ratio = 0.03). The findings reflect a convergence of ecological wisdom and industry expertise, suggesting that nature’s design strategies offer a compelling roadmap for achieving sustainable energy performance in buildings. This study reinforces the applicability of biomimicry in shaping context-specific sustainability metrics and informs the development of adaptive, ecologically aligned certification frameworks. This study recommends the integration of these EE criteria into building rating systems, fostering interdisciplinary collaboration, and scaling nature-based frameworks to inform global sustainability practice. By bridging theory and application, this study advances a regenerative approach to construction that aligns with the UN Sustainable Development Goals and long-term environmental resilience. Full article

Background/Objectives: Disparities in multiple myeloma (MM) survival occur based on factors like genetics, age, race, income level, and access to healthcare. The impact of age at diagnosis on MM survival is not fully understood and continues to draw research attention. This study explores the link between age at diagnosis and survival outcomes using data from the University of Arkansas Medical Sciences Myeloma Center Database (MMDB). Methods: Kaplan–Meier curves and Cox models were used to analyze the data. The log-transformed age variable strongly predicted survival. Results: The analysis found survival curves showing that patients in lower age brackets tend to have better survival profiles. Thus, for example, those in the oldest category (>70) showed the steepest decline, while the youngest age category (under 40) had better survival. Spline functions identified a non-linear relationship between age and survival. The likelihood ratio test, Wald test, and log-rank score test confirmed that the overall model was statistically significant, indicating that the spline-based approach effectively captured the relationship between age and survival. Further analysis using a stratified Cox model by age group showed significant risk differences. Patients aged 50–59, 60–69, and over 70 all had higher risks of death compared to younger patients, with those over 70 having a 3.3 times greater risk. Conclusions: In conclusion, the study confirmed that age at diagnosis has a significant association with survival outcomes for MM patients. Full article

Based on the perspective of multi-stage dynamic competition, this study constructs a discrete dynamic model of price competition between the “direct sales” and “resale” channels in cross-border e-commerce (CBEC) under three blockchain deployment modes. Drawing on nonlinear dynamics theory, the Nash equilibrium of the system and its stability conditions are examined. Using numerical simulations, the effects of factors such as the channel price adjustment speed, tariff rate, and commission ratio on the dynamic evolution, entropy, and stability of the system under the empowerment of blockchain technology are investigated. Furthermore, the impact of noise factors on system stability and the corresponding chaos control strategies are further analyzed. This study finds that a single-channel deployment tends to induce asymmetric system responses, whereas dual-channel collaborative deployment helps enhance strategic coordination. An increase in price adjustment speed, tariffs, and commission rates can drive the system’s pricing dynamics from a stable state into chaos, thereby raising its entropy, while the adoption of blockchain technology tends to weaken dynamic stability. Therefore, after deploying blockchain technology, each channel should make its pricing decisions more cautiously. Moderate noise can exert a stabilizing effect, whereas excessive disturbances may cause the system to diverge. Hence, enterprises should carefully assess the magnitude of disturbances and capitalize on the positive effects brought about by moderate fluctuations. In addition, the delayed feedback control method can effectively suppress chaotic fluctuations and enhance system stability, demonstrating strong adaptability across different blockchain deployment modes. Full article

This observational retrospective study aimed to examine the association between team behaviour during periods of one-goal leads and subsequent match outcomes while accounting for team level and match location. All matches (n = 380) of the English Premier League (EPL) during the season 2023/24 were analyzed. Team behaviour was evaluated by shots every 10 min during a one-goal lead (SP10MDOGL), a time-normalized indicator of offensive activity that reflects a team’s strategic orientation while protecting a narrow lead. Mixed effects multinomial logistic regression was used to establish the association between SP10MDOGL and the match outcome. Results indicated that increased SP10MDOGL was strongly associated with a higher likelihood of both drawing (Odds ratio (OR) = 2.37, 95% confidence interval (CI) = 1.29–4.33; Cohen’s d (d) = 0.47) and winning (OR = 3.38; 95%CI = 1.93–5.92; d = 0.67) compared to losing. This association remained consistent across high-, intermediate-, and low-level teams regardless of whether they played at home or away. These findings suggest that maintaining an offensive approach through an increased number of shots during a one-goal lead is associated with a higher likelihood of securing positive match outcomes within the elite-level football context, such as the EPL. Soccer coaches should consider implementing proactive offensive strategies when protecting a narrow lead, regardless of their team level and match location. Full article

The immiscibility of most polymers leads to poor interfacial adhesion in blends, a critical challenge that often limits the mechanical performance of polymer composites. This research introduces shape-forming elements (SFEs), a novel class of coextrusion dies designed to create additional geometric complexity and control over interfacial architecture. Specifically inspired by Julia Set and T-Square fractals, SFEs were simulated, prototyped, and found to be effective in coextrusion of different-colored polymer clays. The SFEs were employed to coextrude architected composites consisting of a liquid crystalline polymer (Vectra A950) and a cycloaliphatic polyamide (Trogamid CX7323). Mechanical testing revealed a strong positive correlation between the draw ratio and both the tensile modulus (adjusted R² = 0.94) and tensile stress at break (adjusted R² = 0.84). However, experimental cross-sections significantly differed from simulation results. These discrepancies were attributed to interfacial instabilities caused by material incompatibility between the two polymers and potential moisture-induced defects. This finding highlights critical challenges that arise during practical processing, emphasizing the importance of addressing polymer compatibility and moisture management to realize the full potential of SFEs in designing advanced polymer composites with targeted properties. Full article

Biodegradable polymers offer a promising solution to the growing issue of global microplastic pollution. To effectively replace conventional plastics, it is essential to develop strategies for tuning the properties of biodegradable polymers without relying on additives. Biaxial stretching promotes anisotropic crystallization in polymer domains, thereby altering the mechanical performance of polymer blends. In this study, we employed a design of experiment (DoE) approach to investigate the effects of biaxial stretching at three drawing temperatures (T_ds) and draw ratios (λs) on a biodegradable blend of poly(lactic acid) (PLA) and poly(butylene adipate-co-terephthalate) (PBAT), aiming to optimize both the strength and ductility. The DoE analysis revealed that the composition, the λ, the interaction between the λ and composition, and the interaction between the T_d and composition significantly affect the elongation at break (ε_Break). For the stress at break (σ_Break), the most influential factors were the interaction between the λ and PLA concentration; a three-way interaction among the λ, PLA, and T_d; the T_d; the λ; and finally the PLA concentration alone. The optimal ε_Break and σ_Break were achieved at a λ = 5 × 5 and T_d = 110 °C, with a composition of 10% PLA and 90% PBAT. The stretched samples exhibited higher crystallinity compared to the pressed samples across all compositions. This work demonstrates that in addition to the composition, the processing parameters, such as the λ and T_d, critically influence the mechanical properties, enabling performance enhancements without the need for compatibilizers or toxic additives. Full article

The emigration of highly skilled individuals has become a critical concern for many countries amid increasing global labor mobility. This study employs the Improved Fuzzy Step-Wise Weight Assessment Ratio Analysis (IF-SWARA) method within a fuzzy multi-criteria decision-making (FMCDM) framework to identify and prioritize the key drivers of skilled migration. Drawing on opinions from sixteen Turkish emigrants currently residing abroad, the study captures firsthand perspectives on the structural factors influencing their migration decisions. The results indicate that the most influential factors are workplace conditions, living standards, and academic standards. These findings underscore the multifaceted nature of brain drain and highlight the necessity for comprehensive policy approaches that address both push and pull dynamics. By systematically ranking these determinants, the study contributes to the growing body of evidence-based research on international human capital flows. Full article

This study aims to examine the implementation of digital education at SDN Cicurug Caringin and SDIT Nabawi, Sukabumi Regency, with a focus on opportunities, challenges, and gaps in the use of technology for learning at the elementary school level. Using a qualitative approach and a comparative case study design, this study explores the application of digital education in two different contexts, namely in rural areas (SDN Cicurug Caringin) and urban areas (SDIT Nabawi). Data were collected through in-depth interviews with four teachers, two principals, eight students, and four parents, as well as direct observation in both schools. The analysis techniques used are data reduction, data presentation, and conclusion drawing, with Miles and Huberman’s interactive analysis procedures. The results of the study show that SDN Cicurug Caringin faces significant infrastructure constraints, such as a student-computer ratio of 1:15, limited internet connection, and low digital literacy of parents due to their simple socio-economic background. On the other hand, SDIT Nabawi has succeeded in utilizing digital platforms such as Let’s Read to increase students’ interest in reading, although it is limited by teaching time and lack of TPACK (Technological Pedagogical Content Knowledge) training for teachers. The main gaps found between the two schools are unequal access to technology, limited teacher capacity to integrate technology, and low parental support in assisting children in digital learning. This study provides empirical evidence that the success of digital education is highly dependent on adequate infrastructure, TPACK-based training for teachers, and parental involvement in digital literacy. The recommendations included infrastructure improvements, TPACK training for teachers, and the implementation of digital literacy workshops for parents to reduce disparities and improve learning outcomes. Full article

Background: Huntington’s disease (HD) causes progressive motor dysfunction, with chorea as its hallmark symptom. Vesicular monoamine transporter 2 (VMAT 2) inhibitors (tetrabenazine, deutetrabenazine, valbenazine) are established symptomatic therapies, while dopamine stabilizers (pridopidine, ordopidine) are emerging therapies, but their net benefit and safety remain uncertain. Methods: Seven databases were searched through May 2025 following PRISMA guidelines. Random effects meta-analyses calculated mean differences (MDs) for the Unified Huntington Disease Rating Scale total motor score (UHDRS TMS) and total maximal chorea score (TMC), plus risk ratios (RRs) for adverse events (AEs). Trial Sequential Analysis (TSA) applied a Lan DeMets O’Brien Fleming α spending function with 80% power. Results: Seven randomized trials (1431 participants) met inclusion criteria. VMAT 2 inhibitors significantly improved motor outcomes versus placebo (UHDRS TMS: MD −3.80, 95% CI −5.76 to −1.83; TMC: MD −3.05, 95% CI −3.84 to −2.26; both I² = 0%). Dopamine stabilizers produced no meaningful change (UHDRS TMS: MD −0.98, 95% CI −2.48 to 0.51; I² = 32%). Neither class increased total AEs (VMAT 2: RR 1.21, 95% CI 0.99 to 1.48; dopamine stabilizers: RR 1.05, 95% CI 0.92 to 1.20; both I² = 0%). TSA confirmed robust evidence for VMAT 2 benefits on TMC but indicated additional data are required to verify dopamine stabilizer effects on UHDRS TMS. Trial sequential analysis confirmed the reliability of VMAT2 for TMC; however, the sample size was insufficient to draw conclusions about the effects of dopamine stabilizers on UHDRS TMS or their safety outcomes, indicating that additional data are needed. Conclusions: VMAT-2 inhibitors may suggest potential improvements in motor symptoms in Huntington’s disease, while current evidence does not demonstrate a significant benefit of dopamine stabilizers. The safety profiles of both treatments appear generally comparable to placebo. Further rigorous and long-term studies are required to better establish their efficacy and safety. Full article

The acquisition of plant ecological indicators, such as leaf area index and leaf area density values, typically relies on labor-intensive field sampling and measurements, which are often time-consuming and hinder large-scale application. As different plant ecological indicators are closely related to plants’ geometric characteristics, the development of dynamic correlation and prediction methods for relevant indicators has become an important research topic. However, existing 3D plant models are mainly used for visualization purposes, which cannot accurately reflect the plant’s growth process or geometric characteristics. This study presents a workflow for parametric 3D plant modeling and ecological indicator analysis, integrating dynamic plant modeling, indicator calculation, and microclimate simulation. With the established plant model, a method for calculating and analyzing ecological indicators, including the leaf area index, leaf area density, aboveground biomass, and aboveground carbon storage, was then proposed. A method for exporting the model-generated data into ENVI-met v.5.0 to simulate the microclimate environment was also established. Then, by taking Daijia Lake Park as an example, this study utilized site planting construction drawings and field survey data to perform parametric modeling of 21,685 on-site trees from 65 species at three different growth stages using Blender v.4.0 and The Grove plugin v.10. The generated plant model’s accuracy was then verified using the 3D IoU ratio between the models and on-site scanned point cloud data. Plant ecological indicators at various stages were then extracted and exported to ENVI-met for microclimate analysis. The workflow integrates the simulation of plant growth dynamics and their interactions with environmental factors. It can also be used for scenario-based predictions in planting design and serves as a basis for urban green space monitoring and management. Full article