Background: Telemonitoring systems in cardiology have shown potential in improving chronic cardiovascular disease (CVD) management. This study aims to evaluate the impact of telemonitoring, mainly through mobile applications, on patient outcomes such as self-care, blood pressure control, quality of life, and hospitalization. Methods: We systematically reviewed studies assessing telemonitoring methods for patients with chronic CVD. The analysis included studies from various geographic regions and healthcare settings, focusing on qualitative outcomes without performing a meta-analysis. Results: Telemonitoring was found to aid in maintaining blood pressure and significantly enhance self-care abilities. Improvements in quality of life were observed in some studies, though results varied. Most studies indicated telemonitoring could effectively manage blood pressure and reduce hypertension-related complications. However, the heterogeneity of interventions and outcomes measured across trials posed challenges for a comprehensive meta-analysis. Conclusions: Integrating telemonitoring systems into routine care can significantly improve disease management and patient outcomes for chronic CVD patients. Future research should standardize telemonitoring interventions and outcome measures, conduct long-term studies, and evaluate the cost-effectiveness of these systems. Greater blindness in future randomized controlled trials and more studies on atrial fibrillation are also necessary. Significant potential exists for telemonitoring to improve patient outcomes and assist in managing chronic illnesses.

Multiple imputation by chained equations (MICE) is a popular and well-researched statistical approach to account for missing data in empirical research. However, applying the technique requires researchers to set dozens of smaller and larger parameters to build an adequate imputation model before estimating the analytical model of interest. It is somewhat unclear how severely small and potentially arbitrary decisions influence the quality of the produced findings. The current study tests this empirically using a simulation approach with datasets with low and high shares of missing data points that are missing at random (MAR). For each of the two specifications, 4,200 simulations are conducted where multiple parameters are randomly varied to create a diverse range of potential imputation models. The results demonstrate that even random imputation models can significantly reduce bias compared to listwise deletion since more than 90% of all simulations give less biased results. All minor decisions taken together explain between 11% and 21% of the variation in the statistics of interest. The most substantial influence on this variation is due to the selection of the imputation algorithm within MICE. These findings demonstrate that almost any imputation model, even those built with little care, will often result in a higher quality than applying listwise deletion, as long as critical assumptions, such as MAR and the avoidance of severe misspecifications, hold.

Regression models are highly popular in empirical research and come in many different forms to fit virtually any distribution, variable, or research question. Usually, these models also compute how much variation in the outcome variable can be explained by all predictors, which is relevant to understanding whether the predictors are, in sum, able to explain the outcome or whether other potentially unobserved factors are more relevant. This aspect is crucial for interventions and policy as even statistically significant regression coefficients can be meaningless if they have little influence on the outcome overall. Besides having a measurement to judge the overall goodness of fit, ranking predictors by their relative importance is also relevant. For such analyses, it is necessary to decompose the total explanatory power of a model and partition it so that each explanatory variable is assigned a share. This enables the computation of a predictor variable's absolute and relative influence. Dominance analysis is a statistical approach to achieve this goal.

Lean body mass (LBM) is correlated with powerlifting performance in athletes competing in different bodyweight classes. However, it remains unknown whether changes in LBM are correlated with performance changes in powerlifters preparing for a competition. Aim of the study was to investigate the changes in LBM and performance in powerlifters preparing for a competition. Eight male powerlifters (age 31.7±9.8years, height 1.77±0.06m, weight 99.2±14.6kg) and three female powerlifters (age 32.7±16.3years, height 1.54±0.06m, weight 66.6±20.9kg), participated in the study. Athletes followed individualized periodized training programs for 12 weeks aiming to maximize their performance for the national championship. Maximum strength (1-RM) in squat, bench press, and deadlift, body composition, grip strength, anaerobic power, quadriceps’ cross sectional area and vastus lateralis muscle architecture were measured before and after the training period. Significant increases were found after the training period in squat (5.8±7.0%, P

Semi-Interlocking Masonry (SIM) represents an innovative building system developed at the Centre for Infrastructure Performance and Reliability at The University of Newcastle, Australia. This system employs a unique approach to interlocking mortar-less engineered masonry panels constructed from SIM units. These units are designed to offer substantial energy dissipation capacity, primarily attributed to the friction occurring on the sliding bed joints between the units within the panel during seismic events. The primary aim of this study is to evaluate the viability of incorporating semi-interlocking masonry as infill panels in the construction of multi-storey buildings across diverse geographical locations with varying seismic conditions in Australia. To assess the feasibility of SIM panels in different conditions (according to Australian Standard AS1170) in Australia, a comprehensive analysis using Strand7 is conducted on a three-storey structure incorporating traditional masonry infill panels and SIM panels. The comparison of displacement and base shear capacities is carried out in response to seismic events across various scenarios in different locations within Australia. The insights gained from this comparative analysis contribute valuable information regarding the viability of implementing SIM as a contemporary construction material.

Deep Eutectic Solvents (DESs) show promising abilities for the delamination of multilayer packaging films that are used in food packaging and in pharmaceutical blister packs. Due to the complexity of their structure, the recycling of these materials is a challenging task, leading to the easiest or cheapest option, landfilling. Towards the development of ‘green’ solvents for the efficient waste management and recycling, the conducted research focuses on the preparation of a range of hydrophobic and hydrophilic DES based on carboxylic acids. Also, their chemical and physical characterization, such as DSC, rheometer and density measurements, was followed for the determination of their properties. The laminate packaging waste products that were tested were Al/PE, PE/Al/PET, Al/PE/paper and PVC/PE/Al. Different batches of solvent systems were tested based on various naturally derived aliphatic and aromatic organic compounds as well as amino acids. The separated films were collected and studied further for the examination of the delamination extend. Results showed full or partial delamination of some materials as well as challenges of solvent systems. Variables such as temperature, agitation rate, mixing time and solvents ratios were monitored and collected during the design of experimental process. The results showed that the used DESs can offer an efficient, low-energy, affordable and green option for the delamination tested packaging materials.

The literature offers limited information on the effect of obesity on the rate of force development, a critical parameter for mobility in older adults. The objectives of this study were; to explore the influence of obesity on RFD in older adults and to examine the association between this neuromuscular parameter and walking speed. 42 older adults were classified into two groups: the control group (CG, n=22; age=81.13±4.02 years; Body mass index (BMI)=25.13±3.35 kg/m²), and the obese group (OG, n=20; age=77.71±2.95 years; BMI=34.46±3.25 kg/m²). Walking speed (m/s) was measured using the 10-meter walking test. Neuromuscular parameters of the plantar flexors were evaluated during a maximal voluntary contraction test using a dynamometer. The RFD was calculated from the linear slop of the force – time curve in two phases: from the onset of the contraction to 50 ms (RFD50-100) and from 100 to 200 ms (RFD100-200). The gait speed was lower in the OG compared to the CG (p

This paper presents a new semi-explicit algorithm for parameters estimation in a time-fractional generalization of dual-phase-lag heat conduction model with the Caputo fractional derivatives. It is shown that this model can be derived from a general linear constitutive relation for the heat transfer by conduction when the heat conduction relaxation kernel contains the Mittag-Leffler function. The model can be used to describe heat conduction phenomena in a material with power-law memory. The proposed algorithm of parameters estimation is based on the time integral characteristics method. The explicit representations of the thermal diffusivity and the fractional analogues of the thermal relaxation time and the thermal retardation are obtained via a Laplace transform of the temperature field and utilized in the algorithm. An implicit relation is derived for the order of fractional differentiation. In the algorithm, this relation is resolved numerically. An example illustrates the proposed technique.

Microscopic vision plays an important role in automated micro-assembly. However, some uncertain factors in the assembly process, such as occlusion and stains can lead to the mistakes of feature extraction. Herein, to solve the problem, the deep learning techniques are introduced into the feature recognition tasks, focusing on the attention mechanism and visualizing CNNs for DL-based microscopic vision. The main contributions are summarized as follows: The CBAM attention mechanism is combined with the YOLOv5 algorithm to improve the accuracy and robustness of feature extraction. The micropart feature occlusion experiment results show that at 70% occlusion degree, YOLOV5-CBAM can reach 97.9% [email protected], which is 4.6% higher than the original one. Visualization analysis of DL-based model is conducted using Grad-CAM to make the decision result more transparent and avoid potential visual detection risks during assembly. The heatmap matching degree between GT area and high-light area is increased by 27.81% on average, which further verify the effectiveness of attention mechanism in micropart feature localization. Additionally, micropart surface stain and droplet quality classification models based on ResNet50 are trained to replace the manual sorting. The visual results are consistent with human eye discernment and judgement, confirming the reliability of parts and droplets sorting.

Poor perinatal mental health can have significant and lasting impacts on a woman’s overall health and the well-being of her children and family. From conception, a baby's behavior, appearance, aversions, and interests can be influenced by the prenatal environment. Thus, the quality of prenatal care is crucial. Factors such as maternal stress, environmental conditions, cravings, mood swings, hormonal changes, and emotional experiences during pregnancy can profoundly affect the baby’s behavior once born. The baby's interaction with the external world begins from conception, not just at birth. For instance, maternal depression can negatively affect both the mental and physical health of the infant. Therefore, fostering a supportive environment for expectant mothers is essential for their health and that of their unborn child. Promoting the mother’s well-being through happiness and comfort is critical.This review paper aims to synthesize current research on maternal-fetal attachment during pregnancy, its evolution, and its postpartum effects on the mother-infant relationship. It will explore how these dynamics change over time, both during pregnancy and after delivery, to provide a comprehensive understanding of the factors influencing attachment and related outcomes. As Alan Soufre, a famous developmental psychologist would state, "Attachment would begin before birth. The mother’s emotional state can shape the child’s development trajectory long before the child is born."

Among earth’s microbial populations are the genes, functional capacities, generational memory and sentient cognition that enable microorganisms to adapt and thrive in the full range of ecological conditions found on planet earth. In prior sequential publications, we considered fundamental properties (e.g., use of and responses to sound, light, vibrations) and features of microorganisms that cause them to be critical co-partners of human and other holobionts as well as the potential benefits for humanity that can be gained by fully applying quantum-related and novel capacities of microbial life. In this narrative review we: 1) discuss key concepts concerning a microbially-enhanced and sustainable future, and 2) focus on electric- and magnetic- based features of microorganisms that make them pivotal for myriad benefits ranging from beyond pharma-based health and wellness to free- and/or renewable energy and restorative agriculture to improved human networking. While the benefits are many, the risks posed by hazardous electric or magnetic field exposures to both holobionts and microbial communities are significant. This review concludes that microbes and their remarkable capacities offer both humanity and the planet a much brighter future if we reverse the demonization of microbes and wanton microbiome degradation that has predominated much of the past century.

Dynamic systems which underly controlled systems are expected to increase in complexity as robots, devices, and connected networks become more intelligent. While classical stable systems converge to a stable point (a sink), another type of stability is to consider a stable path rather than a single point. Such stable paths can be made of saddles which draw in trajectories from certain regions, and then push the trajectory toward the next saddle point. These are chains of saddles are called stable heteroclinic channels (SHCs), and can be used in robotic control to represent time sequences. While we have previously shown that each saddle is visualizable as a trajectory waypoint in phase space, how to increase the fidelity of the trajectory was unclear. In this paper, we hypothesized that the waypoints can be individually modified to locally vary fidelity. Specifically, we expected that increasing the saddle value (ratio of saddle eigenvalues) causes the trajectory to slow to more closely approach a particular saddle. Combined with other parameters that control speed and magnitude, a system expressed with an SHC can be modified locally, point by point, without disrupting the rest of the path, supporting their use in motion primitives. However, even more complex trajectory shape modifications are possible. While some combinations can enable a trajectory to better reach into corners, other combinations can rotate, distort and round the trajectory in the region of a corner. In our example, modifying select saddle values produced a 32% decrease in the trajectory error of a complex trajectory produced using this system. This is an effect not visible in previous 1D studies, that can lead to different learnable and tunable representations of dynamic systems.

Isothermal interrupted hot compression tests of 5754 aluminum were conducted on Gleeble-3500 thermo-mechanical simulator at temperature 350 °C and 450 °C, strain rate 0.1 s-1 and 1s−1. These tests simulated flat rolling to investigate how softening behaviors respond to controlled parameters, such as deformation temperature, strain rate and delay times. This data allowed the parameters for the hot rolling process to be optimized. The delay times during interrupted compression vary between 5s and 60s. The dynamic softening at each pass and metadynamic recrystallization at the intervals of deformation passes were analyzed in detail. 0.2% offset yield strength is applied to calculate the softening fraction undergoing metadynamic recrystallization. A kinetic model was developed to describe metadynamic recrystallization behaviors of the hot deformed 5754 aluminum alloy. Furthermore, the time constant for 50% recrystallization was expressed as functions related to the temperature and the strain rate. The experimental and calculated results were found to be in close agreement, which verified the developed model.

A comprehensive modeling framework for the thermoforming of polymer matrix woven laminate composite was developed. Two numerical indicators, the slip path length and traction magnitude, have been identified to be positively correlated to matrix smearing and wrinkling defects. The material model has been calibrated with picture-frame experimental results, and the prediction accuracy for intra-ply shear and thickness distribution were examined with measurements on the physically formed parts. Finally, a parametric study was conducted to determine the relationship between various process parameters and the quality of the formed part. For the trapezoidal part, orienting the laminate at 45-degrees to the mold axis reduces the likelihood of matrix smear and wrinkling defects. Although this laminate orientation yielded a greater spatial variation of part thickness, the thickness deviation is lower than that for the 0-degree orientation case. Higher forming rates were found to result in more defects due to increased slip path lengths and traction magnitudes. Optimal forming speeds should balance rapid shaping within the operating temperature window while avoiding tear. It was discovered that shallower molds benefit from faster ramp rates, while deeper molds require slower rates to manage extensive shearing, stretching, and bending. Faster forming rates lead to smaller thickness increases at high intra-ply shear regions, indicating a shift from intra-ply shear to out-of-plane bending due to the visco-plastic effect of the molten laminate, and can negatively impact part quality. Lastly, it was shown that a well-conceived strategy using darts could improve the part quality by reducing the magnitude of the defect indicators.

The vast array of interconnected microbes across earth’s ecosystems and within holobionts has been called the “Internet of Microbes.” Research into the fundamental microbial properties has demonstrated that bacteria and archaea are masters of energy and information collection, storage, transformation, and dissemination using both “wired” and wireless (at a distance) capacities. These features suggest that microbes are quantum entangled within and between earth’s holobionts, and that specific tools affecting energy and information functions could provide an effective strategy for managing microbial populations. Microbes use four critically important microbial networking functions (sound, light, electricity, and magnetism). This narrative review focuses on microbial management based on two of the four: sound and light (as well as related vibrations). These are examined as: 1) tools for managing microbial populations, 2) tools to support new technologies, and 3) tools for healing humans and other holobionts. Given microbial sensitivity to sound, light, and vibrations, it is critical that microbial populations and microbe-laden holobionts are protected from potentially damaging exposures. We conclude that sound, light, and vibrations are useful therapeutic tools that can help support useful microbial populations and help to address ongoing challenges of holobiont disease.

The digital model of airborne frequency selective surface radomes (AFSSRs) is the basis of design, simulation analysis, manufacturing, and other related research of AFSSRs. This paper proposes a rapid modeling method of AFSSRs based on dynamic customizable primitives. Firstly, a layered digital model construction scheme of AFSSR is presented based on the typical radome wall structure. Then, according to the characteristics of various surface configurations and complex wireframe information of AFSSRs, the dynamic primitives are raised to express the boundary and contour information of all kinds of radomes. Focusing on the undevelopable characteristics of the aero-dynamic shape surface of the AFSSR, the arrangement solution and mapping method for frequency selective elements on undevelopable surfaces are proposed. Furthermore, the imple-mentation logic of this method on the creation of each layer model and the assembly of the whole machine model is introduced. Finally, according to this method, a rapid modeling system (RMS) is established, and the modeling effect and efficiency of the RMS are demonstrated and compared, which verifies the feasibility and effectiveness of this method.

Polyphenols and fermentable fibers have shown favorable effects on gut microbiota composition and metabolic function. However, few studies have investigated whether combining multiple fermentable fibers or polyphenols may have additive beneficial effects on gut microbial states. Here, an in vitro fer-mentation model, seeded with human stool combined from 30 healthy volunteers, was supplemented with blends of polyphenols (PP), dietary fibers (FB) or their combination (PPFB) to determine influence on gut bacteria growth dynamics and select metabolite changes. PP and FB blends independently lead to significant increases in the absolute abundance of select beneficial taxa, namely Ruminococcus bromii, Bifidobacterium spp., Lactobacillus spp. and Dorea spp. Total short chain fatty acid concentrations, relative to non-supplemented control (F), increased significantly with PPFB and FB supplementation, but not PP. Indole and ammonia concentrations decreased with FB and PPFB supplementation, but not PP alone while increased antioxidant capacity was only evident with both PP and PPFB. These findings demonstrated that, while the independent blends displayed selective positive impacts on gut states, combination of both blends provided an additive effect. The work outlines the potential of mixed substrate blends to elicit a broader positive influence on gut microbial composition and function to build resiliency toward dysbiosis.

The rheological properties of a polyamide (PA) resin with low crystallinity were modified by melt-mixing it with a small amount of an alternative a-olefin–maleic anhydride copolymer as a reactive compound. Because PA has a low melting point, rheological characterization was performed over a wide temperature range. Owing to the reaction between PA and the alternative a-olefin–maleic anhydride copolymer, the blend sample behaved as a long-chain branched polymer in the molten state. The thermo-rheological complexity was obvious owing to large flow activation energy values in the low modulus region. The primary normal stress difference under steady shear was greatly increased in the wide shear rate range, leading to a large swell ratio at capillary extrusion. Furthermore, strain hardening in the transient elongational viscosity, which is responsible for favorable processability, was clear. Because this is a simple modification method, it will be widely employed to modify the rheological properties of various polyamide resins.

The performance of OpenFOAM in strong scaling tests on HPC systems with AMD EPYC processors exhibits a pronounced superlinear speedup. Simple test cases show superlinear speedups of over 300%, which significantly impacts the efficient use of computing resources. With the last generation of HPC architectures, a superlinear speedup of about 10% to 20% was well expected and accepted by CFD users. The measured superlinear speedup is much more pronounced and withstands the communication overhead to even larger scales. A detailed performance analysis of OpenFOAM follows, employing various High-Performance Computing (HPC) architectures, including AMD, ARM and Intel systems. The performance metric FVOPS (Finite VOlumes solved Per Second) is introduced to compare the performance of Computational Fluid Dynamics (CFD) applications when varying the grid size, as occurs in a strong scaling test. The achievable FVOPS depends on various factors, including the simulation type, boundary conditions, and especially the grid size of a use case. Analysing FVOPS on a single node level with varying grid size shows a significant difference in performance and cache utilization, which explains the large superlinear speedups seen in the strong scaling tests. Furthermore, FVOPS can be used as a simple benchmark to determine the optimal number of grid elements per rank to simulate a given use case at peak efficiency on a given platform, resulting in time, energy, and cost savings. The FVOPS metric also facilitates the direct comparison between different HPC architectures. The tests using AMD, ARM, and Intel processors show a peak in performance when employing around 10,000 grid elements per core. The presence of a large L3 cache on AMD processors is particularly advantageous, as indicated by L3 cache miss rates observed on AMD EPYC processors. Our results suggest that future HPC architectures with larger caches and higher memory bandwidth would benefit the CFD community.

Mutual exclusion algorithms are at the heart of concurrent, distributed/parallel, real-time and operating systems. It is well-known that such algorithms are very difficult to analyze and in the literature different conjectures about starvation-freedom and the number of by-passes (also said the overtaking factor), which in turn affects the (hopefully) bounded waiting time that a process competing for entering the critical section has to suffer before accessing the shared resource, have been formulated for specific algorithms. This paper proposes a novel modelling approach based on Timed Automata and the Uppaal toolset, which proves effective for studying all the properties of a mutual exclusion algorithm for N≥2 processes, by exhaustive model checking. Although the approach, as already confirmed by similar experiments reported in the literature, is not scalable due to state explosion problems, and can be practically applied until N≤5, it is of great value for revealing true properties of analyzed algorithms. For dimensions N>5 the statistical model checker of Uppaal can be used which, although based on simulations, can confirm properties by estimations and probabilities. The paper describes the proposed modelling and verification method and applies it to several mutual exclusion algorithms, thus retrieving known properties but also showing new results about properties often studied only by peer-review and intuitive reasoning.

Background/Objectives: Concurrent opioid (OPI) and benzodiazepine (BZD) use may exacerbate falls/fractures risk compared to no use or use alone. Yet, patients may need concurrent OPI-BZD use for co-occurring conditions (e.g., pain and anxiety). Therefore, we examined the association between longitudinal OPI-BZD dosing patterns and subsequent injurious falls risk. Methods: We conducted a retrospective cohort study including non-cancer fee-for-service Medicare beneficiaries initiating OPI and/or BZD in 2016-2018. We identified OPI-BZD use patterns during the 3 months following OPI and/or BZD initiation (i.e., trajectory period) using group-based multi-trajectory models. We estimated time to first injurious fall within 3 months post-trajectory period using inverse-probability-of-treatment-weighted Cox proportional hazards models. Results: Among 622,588 beneficiaries (age≥65=84.6%, female=58.1%, White=82.7%; having injurious falls=0.45%), we identified 13 distinct OPI-BZD trajectories: Group(A):Very-low OPI-only (early discontinuation)(44.9% of the cohort); (B):Low OPI-only (rapid decline)(15.1%); (C):Very-low OPI-only (late discontinuation)(7.7%); (D):Low OPI-only (gradual decline)(4.0%); (E):Moderate OPI-only (rapid decline)(2.3%); (F):Very-low BZD-only (late discontinuation)(11.5%); (G):Low BZD-only (rapid decline)(4.5%); (H):Low BZD-only (stable) (3.1%); (I):Moderate BZD-only (gradual decline)(2.1%); (J):Very-low OPI (rapid decline)/Very-low BZD (late discontinuation)(2.9%); (K):Very-low OPI (rapid decline)/Very-low BZD (increasing)(0.9%); (L):Very-low OPI (stable)/Low BZD (stable)(0.6%); and (M):Low OPI (gradual decline)/Low BZD (gradual decline)(0.6%). Compared with Group(A), 6 trajectories had increased 3-month injurious fall risks: (C): HR, 95%CI=1.78, 1.58-2.01; (D): 2.24, 1.93-2.59; (E): 2.60, 2.18-3.09; (H): 2.02, 1.70-2.40; (L): 2.73, 1.98-3.76; and (M): 1.96, 1.32-2.91. Conclusions: Our findings suggest that 3-month injurious fall risk varied across OPI-BZD trajectories, highlighting the importance of considering both dose and duration when assessing fall risks of OPI-BZD use among older adults.

Objectives: To compare the effects of high-velocity resistance training to slow-velocity re-sistance training on neuromuscular and functional parameters and to analyze the relationship between changes in walking speed and improvements in neuromuscular parameters following intervetions. Methods: 40 participants were randomly assigned to either a high-speed resistance training group (GHS, n = 18; age = 80.41 ± 10.12 years; BMI = 23.81 ± 3.45 kg/m²) or a low-speed resistance training group (GLS, n = 22; age = 82.89 ± 5.32 years; BMI = 23.81 ± 3.45 kg/m²). Before and after the interventions, gait speed (m/s) was assessed using a 10-minute walking test, and relative maximal force (Relative F max, N/kg) was evaluated during maximal voluntary isometric con-traction of the plantar flexors. From the force-time curve, early (0 – 50 ms) and late (100 – 200 ms) rates of force development (RFD) were extracted from the linear slopes (Δ force / Δ time). Results: Gait speed significantly improved in both groups (p < 0.05). However, the improvement was more pronounced in the GHS compared to the GLS (p < 0.05). Relative Fmax showed a more significant increase in the GLS than in the GHS (p < 0.05). Moreover, a significant 10% increase in early RFD in the GLS and a 20.1% increase in the GHS were observed (p < 0.05). The improvement in early RFD was greater in the GHS (p < 0.05). Additionally, late RFD improved significantly only in the GHS (+20.4%, p < 0.05). Conclusion: High-velocity resistance training appears particularly effective in improving the ability to rapidly generate force, which is essential for many daily activities re-quiring explosive movements and quick responses.

As a representative of Exponential Organizations, MI went from obscurity to the Fortune 500 in just ten years. Mi's success is inextricably linked to its outstanding business model. This paper summarizes the elements of MI's business model from four perspectives: value proposition, value creation, value delivery, and value capture, as well as its measures for developing into an exponential organization. Expecting to provide theoretical references for the transformation and upgrading of manufacturing organizations.

The geodesics on a relativistic manifold are given by the well-known equation involving the Christoffel coefficients. This equation can be solved numerically step by step and transposed into a quantization. We study here the effect of this quantization on the Schwarzschild spacetime, more precisely in the Kruskal-Szekeres map.

Accurate measurement of pedaling kinetics and kinematics is vital for optimizing rehabilitation, exercise training, and understanding musculoskeletal biomechanics. Pedal reaction force, the main external force in cycling, is essential for musculoskeletal modeling and closely correlates with lower limb muscle activity and joint reaction forces. However, sensor instrumentation like 3-axis pedal force sensors is costly and requires extensive post-processing. Recent advancements in machine learning (ML), particularly neural network (NN) models, provide promising solutions for kinetic analyses. In this study, an NN model was developed to predict radial and mediolateral forces, providing a low-cost solution to study pedaling biomechanics with stationary cycling ergometers. Fifteen healthy individuals performed a 2-minute pedaling task at two different self-selected (58±5 rpm) and higher (72±7 rpm) cadences. Pedal forces were recorded using a 3-axis force system. The dataset included pedal force, crank angle, cadence, power, and participants' weight and height. The NN model achieved an inter-subject normalized root mean square error (nRMSE) of 0.15±0.02 and 0.26±0.05 for radial and mediolateral forces at high cadence, respectively, and 0.20±0.04 and 0.22±0.04 at self-selected cadence. The NN model's low computational time suits real-time pedal force predictions, matching the accuracy of previous ML algorithms for estimating ground reaction forces in gait.

This article explores the significant parallels between big tobacco companies and major social networking sites regarding their influence on public health and society. While acknowledging the fundamental differences in their products and services, the paper scrutinises both industries through five primary lenses: addiction, misinformation, lack of regulation, harm to public health, and youth targeting. Both industries exhibit addictive characteristics, have faced criticism for the spread of misinformation, operate with limited regulation and transparency, and have raised concerns about targeting young demographics. Moreover, the potential harm to public health is a significant concern, with tobacco leading to well-established physical health issues. At the same time, excessive social media use has been linked to psychological harm, particularly among young users. The comparison underscores the necessity for greater regulation and oversight of social media companies, highlighting the urgent need for more comprehensive policies to mitigate potential harm and safeguard public health in the digital age.

Variability is the predisposition of phenomena to assume different values over time. Variability is higher when the differences of cases from each other are larger or diverge from a specific value, such as arithmetic mean. This study focuses on the variability of research topics within and between research fields to explain, whenever possible, how the variability shapes the structure and dynamics of technological trajectories. Analysis of variability here applies the entropy and variance decomposition on main research fields in quantum technologies. Empirical evidence shows that variability in research topics is inversely proportional to the age of research fields. Inductive implications are that higher variability in research topics of recent scientific fields is due to uncertain dynamics that generates a heterogeneity of different technological trajectories some of them can growth and develop towards fruitful directions others can be dismissed. Hence the variability seems to be one of the drivers that shapes technological evolution and can provide policy and managerial implications to improve the scientific and technological forecasting that may support appropriate decisions of R&D investments towards promising research fields and technologies.

The volume of vehicular traffic in large cities has increased in recent years, the devices that collect vehicular GPS data such as cameras, GPS receivers and others generate millions of records at every instant of time generating problems in processing and storage of these data which becomes important for researchers. Intelligent Transportation Systems perform vehicle monitoring and control by collecting GPS trajectories, this large volume of information is necessary to have an optimal storage process. Its processing by means of compression techniques and simplification algorithms allow to reduce the necessary storage space. This paper presents a GPS trajectory simplification algorithm that considers noise reduction, point simplification and analysis of road network information. The results obtained on two data sets from the cities of California and Beijing are satisfactory, achieving a higher compression ratio without affecting data quality

The epidermal cells on the surface of the cotton ovules undergo differentiation to produce fibers, which are single-celled hair-like protrusions resembling the plant trichomes. The initiation of these unicellular fibers from the cotton ovule surface is a complex and tightly regulated process. The initiation step is the cell fate-determining stage, which leads to the commitment of cells that eventually developed into fibers, thus becomes the most crucial phase in fiber development. The in-depth knowledge of molecular regulation is a prerequisite to get a clear view of the fiber initiation process's genetic and epigenetic control. The identification and functional validation of cotton fiber initiation-related genes, few fibreless mutants, transcription factors, microRNAs, epigenetic regulators, as well as the elucidation of the role of phytohormones as signaling molecules, has played a significant role in understanding the cotton fiber initiation process at the molecular level. This review focuses on the comprehensive information regarding the genetic and epigenetic regulation of cotton fiber initiation. Thus, the review will provide readers insight into mechanistic details that operate during cotton fiber initiation.

Background/Objectives: The primary life-threatening complication in Spinal-bulbar muscular atrophy (SBMA) is ventilatory failure, which results from the weakening of the bulbar and respiratory muscles. However, systematic studies assessing respiratory function over the long-term have not been performed. The present study analyzes the longitudinal patterns of respiratory function tests over a follow-up of 11 years, aiming to identify any potential, sustained decline during this time. Furthermore, we explored possible correlations between respiratory function tests and clinical and biochemical serum indices. Methods: We collected data from 9 genetically confirmed SBMA patients and conducted spirometric measurements twice a year for eleven years. The spirometric data included maximum inspiratory pressure (MIP), maximum expiratory pressure (MEP), and forced vital capacity (FVC)]. Additionally, we measured serum biochemical indices and SBMA functional rating scale (SBMAFRS) for clinical analysis. Results: All three respiratory function tests showed a descending trend. A major decrease was observed for MEP (52%) and MIP (42%), while this was minor for FVC (25%). SBMAFRS score correlated with the three pulmonary function tests. MIP and MEP correlated with creatine phosphokinase and creatinine levels, and FVC correlated with serum level of transaminases. Conclusions: This longitudinal study shows a progressive decline of spirometric data throughout life in patients with SBMA. Spirometric measures relative to maximal strength of the respiratory muscles (MIP and MEP) may have a better predictive value for pulmonary and muscular decline than FVC.

The Global Carbon Budget is the cumulative carbon emissions that human activities can generate while limiting the global temperature increase to less than 2°C. On this basis, most countries ratified the Paris Agreement 2015, pledging to reduce national emissions and the impacts of climate change. The European Union has planned to reduce emissions by 80% of their 1990 value by 2050 but such a target needs to be coupled with a further constraint on the cumulative greenhouse gases released along the path to 2050. The aim and the novelty of this study are to propose, for the first time, a carbon budget for the European Union, which represents the most significant physical characteristic to assess the feasibility of current EU-28 greenhouse gas reduction objectives under the goals of the 2015 Paris treaty

The effects of rare earth Ce on the microstructure and properties of cast pure copper were investigated through thermodynamic calculations, XRD analysis, mechanical testing, metallographic microscopy, and scanning electron microscopy (SEM). The experimental results demonstrate that the reaction between rare earth Ce and oxygen as well as sulfur in copper exhibits a significantly negative Gibbs free energy value, indicating a strong thermodynamic driving force for deoxidation and desulfurization reactions. Ce is capable of removing trace amounts of O and S from copper. Moreover, the maximum solid solubility of Ce in Cu falls within the range of 0.009% to 0.01%. Furthermore, Ce can refine columnar grains while enlarging equiaxed grains in as-cast copper.Upon addition of rare earth Ce, the tensile strength increased by 8.45%, elongation increased by 12.1%, and microhardness rose from 73.5HV to 81.2HV-an increase of 10.5%. Overall, rare earth Ce has been found to enhance both the microstructure and mechanical properties of cast pure copper.

(1) Background: The aim of the research was to present and emphasize the importance of magnetic resonance imaging (MRI) in diagnosing Achilles tendon (AT) ruptures by presenting case reports. (2) Materials and Methods: The sample of respondents included 7 patients (4 males and 3 females, 2 athletes and 5 non-athletes), aged 25 to 58 years, with AT injuries, who were examined and treated at the Institute for Treatment and Rehabilitation "Niška Banja", Niš, Serbia. Ankle examinations with MRI were conducted using the Esaote O-scan 0.3 T machine. The examinations were performed without the application of a paramagnetic contrast agent and without the use of anesthesia. Results: The MRI method's sensitivity and overall diagnostic accuracy were excellent, with 100% true positives. In our study, the method accurately detected the presence, location, and severity of AT injuries in all cases. MRI is an important and reliable method for detecting AT injuries, classifying them, monitoring the course of recovery, and assessing the effects of therapy. Conclusions: An unrecognized or delayed diagnosis of an AT injury can lead to chronic changes. Timely diagnosis (clinical examination, ultrasonography, magnetic resonance imaging) and appropriate treatment (conservative or operative) enable patients to return to normal activities, including sports. Unfortunately, the use of MRI is limited by restricted access and the cost of the examination.

Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) are prevalent neurodevelopmental disorders with distinct diagnostic criteria but significant overlap in symptoms and comorbidity. This article explores the relationship between ADHD and ASD, examining their common neurodevelopmental origins, shared features, and distinct trajectories. Both disorders are highly heritable, with genetic studies identifying shared genetic variants and neurobiological abnormalities. Environmental factors, including prenatal and perinatal exposures, also contribute to their etiology. Despite these commonalities, ADHD and ASD exhibit distinct developmental trajectories, cognitive profiles, and long-term outcomes. Understanding the interplay between these disorders is crucial for developing effective diagnostic and treatment strategies. Future research should focus on elucidating the underlying mechanisms and developing targeted interventions for individuals with comorbid ADHD and ASD.

The precise mathematical description of gaze patterns is still an unsettled matter of debate. This can, consequently, affect the analysis of this type of data in its practical applications. In this scope, we show evidence that a Lévy-flight description of eye-gaze trajectories is not only appropriate but its scale invariant properties are remarkably useful to assist in diagnosing children with Attention Deficit and Hyperactivity Disorder (ADHD), alongside with the usual cognitive tests. Using this picture, we find that the distribution of the characteristic exponent of Lévy-flights statistically is different in children with ADHD. Furthermore, we observe that these children deviate from a strategy that is considered optimal for searching processes, in contrast to non-ADHD children. We focus on the case where both eye-tracking data and data from a cognitive test are present and show that the study of gaze patterns in children with ADHD can help in identifying this condition. Since eye-tracking data can be gathered during cognitive tests without needing extra time-consuming specific tasks, we argue that it is in prime position to provide assistance in the arduous task of ADHD diagnosing.

Introduction: It may be feasible to detect episodic memory change in preclinical Alzheimer’s disease (AD) to indicate navigational risks and AD prior to mild cognitive impairment. The establishment of episodic memory signatures may allow for biomarker mapping to inform diagnostic research and practiceMethods: Retrospective longitudinal mixed methods and cross-sectional effect size, to compare group differences, are applied to the Craft-21 memory scores from the preclinical years of persons who later developed AD (pre-AD) dementia , n = 175 with 112 females and 63 males. Their scores are compared to cognitively normal controls (non-AD) n = 6,814 with 4,232 females and 2,582 males. Pre-AD and non-AD groups are further analyzed by biological sex. The dataset is from the National Alzheimer’s Coordinating Center funded by NIA/NIH Grant U24 AG072122. Results: The pre-AD episodic memory scores decreased an average of -.510, p < .001 versus (vs.) the non-AD annual increase by .127, p < .001. The first Cohen’s d = .482 and last Cohen’s d = 976, p < .001. The pre-AD females had an average annual decreased of -.762, p < .001 vs. non-AD females increase of .117, p < .001. The first Cohen’s d = .576 and last Cohen’s d = 1.133, p <.001. The pre-AD males increased every year by .185, p = .996 vs. the non-AD males annual increase of .185, p < .001. The first Cohen’s d = 1.054 decreased by the last year to Cohen’s d = .680, p <.001Discussion: Distinct decline in episodic memory occurs for pre-AD females, but there is not a significant change in pre-AD males. However, the effect size difference between both pre-AD and non-AD groups suggests biomarker mapping in conjunction with memory trajectories may be feasible to determine potential navigational risks as well as biological and cognitive preclinical AD.

It is well known that the photon trajectories follow a curved path in a gravitational field. We explore here the gravitational bending of electric field lines. It seems that the electric field lines of a charge, supported in a gravitational field, follow exactly the trajectories of photons emitted isotropically from a source situated at the charge location. From a detailed examination of the electrostatic field of a charge accelerated uniformly in the instantaneous rest frame, exploiting the strong principle of equivalence, one can determine the bending of the electric field lines of a charge in a gravitational field. The fraction of electric field lines crossing a surface, stationary above or below the charge in the gravitational field, is shown to be exactly similar to the fraction of photon trajectories, emitted from a source placed at the charge location, intersecting that surface. On the other hand, for a freely falling charge in the gravitational field there is no such bending of electric field lines. The field lines continue to extend in radial straight lines from the instantaneous 'present' position of the charge, as do the trajectories of photons streaming away from the instantaneous position of a freely falling source in the gravitational field. The electric field configuration of a freely falling charge in the gravitational field is shown to be exactly the same as that of a charge moving uniformly in an inertial frame with velocity equal to the instantaneous ``present'' velocity of the freely falling charge.

Variable flow emitters are a new type of emitter for underground drip irrigation that are used in locations where soil moisture is difficult to transport to the surface, which leads to crop emer-gence difficulties. The flow channel structure parameters of emitters affect the hydraulic per-formance of the emitter and its anticlogging ability. In this study, the variable flow emitter at the conventional low–flow water supply stage is taken as the research object. A combination of CFD numerical simulation of a two–phase flow of water and sand and clear water testing of test samples is applied to study the influence laws of 10 groups of variable flow emitter structural combinations on the effluent flow rate (q), flow index (x), particle passage rate and flow field inside the flow channel. The results show that the Realizable k–ε turbulence model can be used to simulate the flow field inside the variable flow emitter flow channel. The nRMSE between the measured and simulated values of q is 11.23%, and the relative error between the measured and simulated values of x is 4.66%, which gives a high simulation accuracy. The polar analysis shows that the tooth angle A has the smallest effect on the effluent flow rate q0.1 under 0.1 MPa, x, and particle passage rate of the variable flow emitter. The depth of the flow channel D, the spacing of the teeth B, and the height of the teeth E have a different order of precedence in the influence of the three indices, which are D > B > E > A, B > E > D > A, and E > B > D > A, respectively. The value of particle passage rate is positively correlated with the mean flow velocity (v) and the mean turbulent kinetic energy (k) in the flow channel, and particle passage rate tends to increase and then decrease with the increase of x. The retention time (t) of the particles in the flow channel is closely related to the magnitude of v and k. Three multivariate linear regression equations (R2 = 0.883 ~ 0.995) were constructed for q0.1, x, and particle passage rate versus the flow channel structural parameters. Using the scipy.optimize.minimize function in Python, we de-termined the three optimal combinations of flow channel structural parameters corresponding to better hydraulic performance: q0.1 is 1.5 or 2 L/h (objective function y = min x), better clogging resistance (y = max particle passage rate), and both (y = min (0.5 x - 0.5 particle passage rate)). The research results can provide a ref-erence for the optimal design of variable flow emitters.

The one-dimensional MoS₂/carbon nanofibers (1D MoS₂/CNFs) are synthesized by electrospinning using exfoliated MoS₂ nanosheets and polyacrylonitrile as raw materials. The exfoliated MoS₂ nanosheets with size of about 150 nm are encapsulated in carbon nanofibers, and the free-standing MoS₂/CNFs can be easily cut into flexible tablet and directly used as binder-free anode for lithium storage. The resultant 1D MoS₂/CNFs exhibit a very high reversible capacity of 700 mAh g^-1 at 100 mA g^-1 after 50 cycles, high rate capacity (450 mAh g^-1 at 1000 mA g^-1 after 200 cycles) and good cycle stability.

In recent years, artificial intelligence technology has seen increasingly widespread application in the field of intelligent manufacturing, particularly with deep learning offering novel methods for recognizing geometric shapes with specific features. In traditional CNC machining, computer-aided manufacturing (CAM) typically generates G-code for specific machine tools based on existing models. However, the tool paths for most CNC machines consist of a series of collinear motion commands (G01), often resulting in discontinuities in the curvature of adjacent tool paths, leading to machining defects. To address these issues, this paper proposes a method for CNC system machining trajectory feature recognition and path optimization based on intelligent agents. This method employs intelligent agents to construct models, analyze the key geometric information in the G-code generated during CNC machining, and uses the MCRL deep learning model incorporating linear attention mechanisms and multiple neural networks for recognition and classification. Path optimization is then carried out using mean filtering, Bezier curve fitting, and an improved novel adaptive coati optimization algorithm (NACOA) according to the degree of unsmoothness of the path. Taking the optimization of a gear model’s process file as an example, the effectiveness of the proposed method is verified. The research results indicate that the CNC system machining trajectory feature recognition and path optimization method based on intelligent agents can significantly enhance the smoothness of CNC machining paths, reduce machining defects, and has substantial application value.

With the proliferation of locating devices, more and more raw spatial trajectories are formed, and many works enrich these raw trajectories with semantics, and mine patterns from both raw and semantic trajectories, but access control of spatial trajectories is not considered yet. We present a multi-policy secure model for semantic spatial trajectories. In our model, Mandatory Access Control, Role Based Access Control and Discretionary Access control are all enforced, separately and combined, and we represent the model semi-formally in Ontology Web Language.

Glass cleaning is one of the major cleaning tasks in malls, offices, and modern households where the human workforce is still used for cleaning. Manual cleaning on façade glasses is a less safe, tedious, ineffective, and complex process. With the advancement of robot technology, it is possible to use robots for glass cleaning to facilitate mankind and improve cleaning efficiency. This work presents the development of a vacuum-type glass cleaning robot for façade cleaning and its performance analysis. The developed square-shaped robot is controlled by an Arduino Mega microcontroller, equipped with vacuuming and cleaning technology. An adhesion mechanism on the wheels makes the robot move forward and backward on the glass. The robot runs on a 24-volt DC with a power rating of 75 watts. There are ultrasonic sensors to detect obstacles and help the robot navigate. The robot uses a random-walk mechanism and works continuously for 90 minutes effectively. The performance of the robot has been analyzed in terms of coverage area, repeatability, and dust collection efficiency.

Currently, the use of recycled waste plastic in road construction is not just considered ecofriendly but also considered advantageous for improving road performance over time. This research explores using recycled plastic bags, made of low-density polyethylene (LDPE), in asphalt mixtures to improve road performance and manage waste. The study aims to assess the effects of incorporating different amounts of shredded waste plastic into asphalt mixes and determine the optimal percentage. The aggregate used was obtained from Sargodha quarry Pakistan and asphalt used was 60/70 grade obtained from national refinery limited Pakistan. Using the Marshall mix design, the optimum bitumen content (OBC) was found to be 4.5% of the asphalt mix weight. Thirty samples were tested with waste plastic proportions of 6%, 8%, 10%, 12%, and 14% of OBC weight, along with a standard mix. Tests on stability, bulk density, flow, and air voids showed that a 10% plastic content significantly enhances asphalt performance, increasing stability by around 25%. The study recommends using 10% plastic by OBC weight in asphalt mixes for better performance and suggests further research on optimal incorporation techniques of waste materials in asphalt mixtures.

We investigated preschool-aged children’s understanding of early fractional tasks and how that performance correlates with fine motor skills and use of gestures while counting. Participants were 33 preschoolers aged 4 to 5 in two Southeastern public elementary schools. Children were tested individually in an interview-like setting. Mathematics tasks were presented in a paper and pencil format and the Grooved Pegboard test assessed fine motor skills. Finally, utilization of gestures was evaluated by taking a behavioral rating of the child’s hand morphology, accuracy of gestures, and synchrony of gestures and spoken word while performing a counting task. Results indicate performance on fractional reasoning tasks significantly predicts both fine motor ability and accuracy of gestures.

A general consensus is that the conventional linear modalities guarantee no industrial sustenance in long run for many obvious reasons. This is where the topicality of circularity has been accentuated for the last two decades or so in socio-political arena. However, anecdotal evidence suggests that the emphasis given to circularity in the construction industry is relatively low. Tackling this issue essentially warrants a rigorous co-production of integrated knowhow preferably beyond sectorial boundaries. The present study sheds light on interdisciplinary approaches taken to deal with the slowness in transmuting circularity into construction sector. A comprehensive literature survey was undertaken to understand this phenomenon at policy, firm and site level. The analysis included one hundred twenty-eight (128) articles published in high impact journals between 2003 and 2024. Eighty seven (87) gaps in terms of theory, knowledge, practice, method, empiricism and policy were observed. Forty four (44) thematic sub-clusters have the potential of empirical research. A new framework was finally proposed to scaffold the systemic transition towards a circular construction sector. On a practical level, the study offer valuable insights and instruments for the industry personnel to gauge the efficacy of their own circular approaches and initiatives.

Increasing research has indicated a strong association between identity functioning and eating disorder (ED) symptomatology. However, a detailed investigation of identity throughout ED treatment is lacking. The present longitudinal study examined identity in inpatients with an ED and explored its co-development with ED symptomatology throughout treatment. At admission (Wave 1), 110 women with an ED (Mage=21, SD=6.08, range:14-45) participated, of whom 83.64% participated during treatment (Wave 2) and 55.45% at discharge (Wave 3). Questionnaires on identity synthesis, identity confusion, identity processes, and ED symptomatology were completed. Latent growth curve modeling was used to address the research questions. Throughout treatment, a decrease in identity confusion and an increase in identity synthesis and adaptive identity processes were found. Accordingly, increases in identity synthesis and identification with commitment were related to general decreases in drive for thinness and body dis-satisfaction. Similarly, such decreases in ED symptoms were related to general decreases in identity confusion and ruminative exploration. The present study points to an increase in identity functioning throughout treatment, and longitudinal associations between identity functioning and ED symptomatology were found. Helping the patient to decrease ruminative exploration and to increase identification with previously made life commitments seem important in ED treatment.

The dynamics of a low-energy charged particle in an axis-symmetric magnetic field is known to be a regular superposition of periodic–although possibly incommensurate–motions. The projection of the particle orbit along the two non-ignorable coordinates (x,y) may be expressed in terms of each other: y=y(x), yet–to our knowledge–such a functional relation has never been directly produced in literature, but only by way of a detour: first, equations of motion are solved, yielding x=x(t),y=y(t), and then one of the two relations is inverted, x(t)→t(x). In this paper we present a closed-form functional relation which allows to express coordinates of the particle’ orbit without the need to pass through the hourly law of motion.

Athlete’s heart is characterised by structural, functional, and electrical remodelling. During an exercise session, the heart increases the use of oxygen, which is associated with decreased vascular resistance in the lungs’ circulation. Left ventricular hypertrophy is an echocardiographic modification especially met in endurance athlete’s heart. Moreover, left atrial dilatation represents another important characteristic of endurance athletes. Electrical modulation in the athletic heart induces neurological modifications leading to sinus arrhythmia, bradycardia, early repolarisation, and first-grade atrioventricular (AV) blocks. Athletes' nutritional status involves the assimilation of macronutrients such as proteins, carbohydrates, and fats. Depending on the duration of physical exercise, ATP can be obtained in aerobic or anaerobic conditions. This systematic review aims to find correlations between different evaluative methods of cardiac adaptation and present the metabolism in performance athletes.

A binary biomass-based solid electrolyte film (LSE) was successfully synthesized through the incorporation of lignin nanoparticles (LNP) with sodium alginate (SA). The impact of the mass ratio of SA to LNP on the microstructure, porosity, electrolyte absorption capacity, ionic conductivity, and electrochemical properties of the LSE was thoroughly investigated. The results indicated that as the proportion of SA increased from 5% to 15% LNP, the pore structure of the LSE became increasingly uniform and abundant. Consequently, enhancements were observed in porosity, liquid absorption capacity, ionic conductivity, and overall electrochemical performance. Notably, at a SA amount of 15% LNP, the ionic conductivity of resultant LSE-15 was recorded at 14.10 mS cm1, with porosity and liquid absorption rates reaching 308% and 58.4%, respectively. LSE-15 was employed as a solid electrolyte, while LNP-based carbon aerogel (LCA) served as the two electrodes in the construction of a symmetric all-solid-state supercapacitor (SSC). The SSC device demonstrated exceptional electrochemical storage capacity, achieving a specific capacitance of 197 F g1 at 0.5 A g1, along with maximum energy and power density of 27.33 W h kg1 and 4998 W kg1, respectively. Furthermore, the SSC device exhibited highly stable electrochemical performance under extreme conditions, including compression, bending, and both series and parallel connections. Therefore, the development and application of the binary biomass-based solid electrolyte film in supercapacitors represent a promising strategy for harnessing high-value biomass resources in the field of energy storage.

The extensive utilization of drones has led to numerous scenarios that encompass both advantageous and perilous outcomes. By using deep learning techniques, it is aimed to reduce the dangerous effects of drone use through early detection of drones.The state of the art of the study is evaluation of deep learning approaches such as pre trained YOLOv8 drone detection for security issues. In this study, dataset collected by Mehdi Özel for a UAV competition are sourced from GitHub. These images are labeled using Roboflow, and the model is trained on Google Colab. To enhance model performance, dataset augmentation techniques including rotation and blurring are implemented. Following these steps, a significant precision value of 0.946, a notable recall value of 0.9605 and a considerable precision-recall curve value of 0.978 are achieved, surpassing many popular models such as Mask CNN, CNN, and YOLOv5.

Background: Recent reports on the national temporal trends of sepsis-related mortality in the United States (US) suggested outcome improvement in several race and ethnicity groups. However, it is unknown whether national data reflect state-level trajectories. Methods: We used the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research Multiple Cause of Death dataset to identify all decedents with sepsis in the US during 2010-2019. Negative binomial regression models were fit to estimate national and state-level trends of age-adjusted sepsis-related mortality rates within race and ethnicity groups. Results: There were 1,852,610 sepsis-related deaths in the US during 2010-2019. Nationally, sepsis-related mortality rates decreased among Blacks and Asians, were unchanged among Hispanics and Native Americans, and rose among Whites. The percent of states with similar trends were 30.0% among Blacks, 32.1% among Asians, 74.3% among Hispanics, 75.0% among Native Americans, and 66.7%% among Whites, while trending in opposite direction from 3.6% among Asians to 15.0% among Blacks. Conclusions: National trends in sepsis-related mortality in the US did not represent state-level trajectories in race and ethnicity groups. Gains in sepsis outcomes among race and ethnicity groups at the national level were not shared equitably at the state level.

Gesture recognition technology has been quickly developed in the field of human-computer interaction. The multiple-input multiple-output (MIMO) radar has been widely adopted in gesture recognition because of its notable spatial resolution. In this work, a highly accurate MIMO radar-based hand gesture recognition algorithm with very low complexity is proposed. To make the proposed system applicable in the industry and work well even when the size of the training data is limited, we applied several low-complexity adaptive signal processing methods to extract features and reduce the noise effect. First, spectrum analysis is applied to range-Doppler maps (RDMs) and a cell-averaging constant false alarm rate (CA-CFAR) with mirror filters is applied to improve the robustness to noise. Afterward, the features related to the distance, speed, direction, and the elevation angle of the moving object are determined by the proposed adaptive signal analysis techniques and the random forest is applied for classification. The proposed system has the capability to precisely distinguish and identify eight motions, including waving, moving to the left or right, patting, pushing, pulling, and rotating clockwise or anticlockwise, with an accuracy of 95%. Experiments demonstrate the capability of the proposed hand gesture recognition system to classify different movements precisely.

Introduction: We describe the clinical features and inpatient trajectories of older adults hospitalized with COVID-19, and explore relationships with frailty. Methods: This retrospective observational study included older adults admitted as an emergency to a University Hospital who were diagnosed with COVID-19. Patient characteristics and hospital outcomes, primarily inpatient death or death within 14 days of discharge, were described for the whole cohort and by frailty status. Associations with mortality were further evaluated using Cox Proportional Hazards Regression (Hazard Ratio [HR], 95% Confidence Interval). Results: 214 patients (94 women) were included of whom 142 (66.4%) were frail with a median Clinical Frailty Scale (CFS) score of 6. Frail compared to non-frail patients were more likely to present with atypical symptoms including new or worsening confusion (45.1% vs 20.8%, p<0.001) and were more likely to die (66% vs 16%, p=0.001). Older age, being male, presenting with high illness acuity and high frailty were independent predictors of death and a dose-response association between frailty and mortality was observed (CFS 1-4: reference; CFS 5-6: HR 1.78, 95% CI 0.90, 3.53; CFS 7-8: HR 2.57, 95% CI 1.26, 5.24). Conclusions: Clinicians should have a low threshold for testing for COVID-19 in older and frail patients during periods of community viral transmission and diagnosis should prompt early advanced care planning.

Recent advance in electric propulsion systems have demonstrated that these engines can be used for for long-duration interplanetary voyages. Constant specific impulse engine described as a thrust-limited engine is an example of this type of engine, processing the ability to operate at a constant level of impulse. The determination of minimum-fuel, planar heliocentric Earth-to-Mars low-thrust trajectories of spacecraft using a constant specific impulse is discussed considering the first-order necessary conditions derived from Lawden’s primer vector theory. The minimum-fuel low-thrust Earth-to-Mars optimization problem is then solved in two-dimensional, heliocentric frame using both indirect and direct methods. In the indirect method, two-point-boundary-value problems are derived to solve boundary value problems for ordinary differential equations. In the direct method, a general-purpose optimal control software called GPOPS-II is adopted to solve these optimal control problems. Numerical examples using two different optimization methods are presented to demonstrate the characteristics of minimum-fuel planar low-thrust trajectories with on-off-on thrust sequences at three chosen flight times and available maximum powers. The results are useful for broad trajectory search in the preliminary phase of mission designs.

The strong competition in the automotive industry has required manufacturers to implement lean production, both with methods and techniques specific to Industry 4.0. At the same time, universities must provide graduates with specific skills for applying these new production methods and techniques. In this context, a Lean Learning Factory was developed in the Pitesti University Center, which allows students to learn, experiment, and research, in an environment similar to that of enterprises, the new Lean Manufacturing methods and techniques, and Industry 4.0. The research presented in this study had as its objective identifying the minimum number of repetitions necessary to train operators who serve two differently organized workstations, one classic, the other including digital techniques, but on which the same assembly operation is performed. Several indicators were considered in the analysis, such as the number of errors, the number of stops, the effective duration of the work cycle, and the percentage ratio between the standard duration of cyclical activities and the effective duration of the work cycle. The evolution of these indicators was mathematically modelled by regression functions, using the least squares method. The obtained results also highlight the usefulness of applying the DOJO method as a Lean manufacturing-specific learning technique and the efficiency of implementing digital techniques in work organization.

The amount of solar energy produced is directly proportional to the surface area of solar panels exposed to sun rays. To increase the productivity of solar panels, a number of techniques are proposed by curving the surface or protruding the panel surface to maximise the surface area, e.g. Protruding panel surfaces with shapes such as pyramidal, cone, spherical cap, sinusoidal wavy curve, etc. These techniques are analysed to determine whether the panel surface area increases. The geometrical design analysis showed that, depending on the chosen surface curving method, the panel can achieve a remarkable increase in surface area.The system advisor model was used to assess a sample of solar cells with standard measurements of 6 by 6 inches that were organised in a zigzag pattern with different angles of inclination (10°, 15°, 20°, 25°, 30°, and 35°). Overall, the maximum power pump and annual AC energy performance increase by 1.4%, 4.2%, 6.8%, 10.8%, 14.9%, and 21.6%, respectively, over a one-year period of productivity. However, by applying the concept of solar panel efficiency degradation due to tilting solar panels at an angle by Mamun et al. (2022), for each 5° increase in tilt angle beyond the ideal 10°, the efficiency decreases by approximately 0.76%. In conclusion, the overall efficiency is greater than that of standard flat solar panels, provided the tilt angle is within a reasonable range.

Dipole antennas, fundamental components in wireless communication systems, have garnered significant attention due to their versatility and efficiency across various applications. This literature review explores the performance analysis of dipole antennas, focusing on recent advancements and methodologies from 2019 to 2024. Employing a systematic approach, the review synthesizes findings from multiple databases, emphasizing peer-reviewed studies that delve into dipole antenna designs and applications. Through meticulous data extraction, key parameters influencing dipole antenna performance, such as material properties and operating frequency, are identified and analyzed. Results highlight the widespread utilization of dipole antennas in wireless communication systems, including indoor positioning, mobile communication, and antenna calibration, among others. Discussions underscore the evolution of dipole antennas in base station environments and their role in filtering applications. The review concludes by emphasizing the continued relevance and evolution of dipole antennas, showcasing their adaptability and potential across diverse wireless communication contexts.

Precision agriculture is a farm management technology that involves sensing and then responding to the observed variability in the field. Remote sensing is one of the tools of precision agriculture. The emergence of small unmanned aerial vehicles (sUAV) have paved the way to accessible remote sensing tools for farmers. This paper describes the comparison of two popular off-the-shelf sUAVs: 3DR Iris and DJI Phantom 2. Both units are equipped with a camera gimbal attached with a GoPro camera. The comparison of the two sUAV involves a hovering test and a rectilinear motion test. In the hovering test, the sUAV was allowed to hover over a known object and images were taken every second for two minutes. The position of the object in the images was measured and this was used to assess the stability of the sUAV while hovering. In the rectilinear test, the sUAV was allowed to follow a straight path and images of a lined track were acquired. The lines on the images were then measured on how accurate the sUAV followed the path. Results showed that both sUAV performed well in both the hovering test and the rectilinear motion test. This demonstrates that both sUAVs can be used for agricultural monitoring.

The fundamental question in the field of sensor research is new directions of scientific fields, which play a vital role in the progress of science and technology. This study confronts this question here by developing a bibliometric analysis, which endeavors to explain the evolution of sensor research and new technologies that are critical to science and society. The database of Scopus concerning scientific documents and patents is used for statistical and computational analyses in these topics. Results suggest that emerging technological trajectories in sensors are wireless sensor networks, wearable sensors and biosensors. Main characteristics of these growing research fields and technologies in sensors are described for fruitful implications of research and innovation policy directed to science advances and technological change in society.

The Ituri-Epulu-Aru landscape (IEAL) is experiencing deforestation and forest degradation. This deforestation is at the root of many environmental disturbances in a region characterized by endemism in biodiversity. This article focuses on the triangulation of spatialized prospective scenarios in order to identify future trajectories based on the knowledge of historical dynamics through the diachronic analysis of three satellite images (2003-2010-2014-2016). The scenarios were de-signed in a supervised model implemented in the DINAMICA EGO platform. The three scenarios Business-As-Usual (BAU), Rapid Economic Growth (REG) and Sustainable Management of the Environment (SME), extrapolating current trends, show that by 2061 this landscape will always be dominated forests (+ 84%). Old-growth forests occupy 74.2% of the landscape area in the BAU scenario, 81.4% in the SEM scenario and 61.2% in the REG scenario. The SEM scenario gives hope that restoration and preservation of biodiversity priority habitats is still possible if policy makers become aware of it.

Ammonium ion is a chemical species that is found in abundance in natural waters, whether underground or surface, but also in wastewater resulting from agricultural and industrial activities. Even if the removal of the ammonium ion from water has been studied for a very long time, it has been found that its removal is far from being solved. In this study, we evaluated the performance of the ammonium ions adsorption process on two adsorbents, zeolite clinoptilolite, ZR, (manufacturer Zeolite Develop-ment SRL, Rupea, Brasov, Romania) and the other granular activated carbon type Norit GAC 830 W. In the first step the paper presents the mineralogical (XRD) and structural (SEM and EDX) characterization of the ZR and determination of the pH zero-point charge, pHZPC, for all the adsorbents. Studies were carried out in equilibrium and kinetic conditions. The efficiency of the adsorbent was investigated in different experimental conditions by varying the initial concentration, particle size, temperature, pH, ionic strength and contact time. The mathematical models and parameters specific to the adsorption isotherms that best describe the experimental results were identified. Langmuir, Freundlich, Temkin and Dubinin-Radushkevich mathematical models were used for comparison. The Langmuir isotherm proved to be the most appropriate to describe the adsorption of ammonium ions on all types of adsorbents used. The adsorption capacity of ammonium ion from synthetic solutions, at 20 °C, pH = 6.09, for the range of initial concentrations 0 - 50 mg/L for Rupea Zeolite is in the range of 10.46 mg/g -12.34 mg/g and for granular activated carbon GAC W830 is 16.64 mg/g. It was found that the increase in temperature and pH have a positive effect on the adsorption capacity of the ammonium ion on the studied adsorbents, and the ionic strength determines the decrease in the adsorption capacity. Kinetic models were also identified that best describe the experimental processes. In this sense, pseudo first order, pseudo second order, intraparticle diffusion and the Elovich model were used. The results of the investigation showed that second-order kinetics governs the adsorption process on ZR zeolites and pseudo-first order for activated carbon.

: TiAl6V4 alloy is widely used in selective laser melting and direct laser melting. In turn, works devoted to the issue of how the track stacking scheme affects the value of mechanical properties is not enough. The influence of the Ti6Al4V alloy track trajectories on the microstructure and mechanical properties during direct laser deposition is studied in this article for the first time. The results were obtained on the influence of «parallel» and «perpendicular» technique of laying tracks in direct laser synthesis. All studied samples have a microstructure typical of the hardened two-phase condition titanium. It is shown that the method of laying tracks and the direction of load application during compression testing relative to the location of the tracks leads to a change in the ultimate strength of the Ti-6Al-4V alloy from 1794 to 1910 MPa. The plasticity of the Ti-6Al-4V alloy obtained by direct laser alloying can vary from 21.3 to 33.0% depending on the direction of laying the tracks and the direction of the compression test. The hardness of alloys varies in the range from 409 to 511 HV and depends on the method of laying the tracks and the direction of hardness measurements.

In recent years, there has been an increasing interest in adopting novel sensing technologies for the continuous monitoring of structural systems. In this respect, Micro-Electro-Mechanical System (MEMS) sensors are widely used in several applications, including Structural Health Monitoring (SHM). Thanks to their significantly lower cost, ease of installation on the structure, and lower power consumption, they enable extensive, pervasive, and battery-less monitoring systems. This paper presents an innovative high-performance device for SHM applications, based on a low-noise triaxial MEMS accelerometer, providing a guideline and insightful results about the opportunities and capabilities of these devices. Sensor nodes have been designed, developed, and calibrated to meet structural vibration monitoring and modal identification requirements. These components include a protocol for reliable command dissemination through the network and data collection, and improvements to software components for data pipelining, jitter control, and high-frequency sampling. Devices were tested in the lab using shaker excitation. Results demonstrate that MEMS-based accelerometers are a feasible solution to replace expensive piezo-based accelerometers. Deploying MEMS is promising to minimize sensor node energy consumption. Time and frequency domain analysis show that MEMS can correctly detect modal frequencies, useful parameters for damage detection. The acquired data from the test bed were used to examine the functioning of the network, data transmission, and data quality. The proposed architecture has been successfully deployed in a real case study to monitor the structural health of the Marcus Aurelius Exedra Hall within the Capitoline Museum of Rome. The performance robustness was demonstrated and the results showed that the wired sensor network provides dense and accurate vibration data for structural continuous monitoring.

The purpose of this study is to examine the match-related performance (scores and penalties) of the athletes in the Junior EJC (European Judo Championship) and U23 EJC categories before and immediately after the Covid-19 quarantine, according to gender and weight category groups. Our sample was based on the junior and U23, male and females, 2019-2020 Junior European Judo Championships and 2019-2020 U23 European Judo Championships. A total of 1431 matches in these tournaments were analyzed: male (n=812) and female (n=619). The main findings of this study showed that most matches in both the male and female categories resulted in ippon (2019-2020 average: 64,35% for Junior male, 70,55% for U23 male and 69,3% for Junior female, 64,4% for U23 female). No significant differences (p &gt; 0.05) were observed between gender and age groups concerning the match scores. In the formation phase of the technique, considerations of high- and low-intensity actions, and analysis of the speed of athletes during matches in official competitions can help to better understand the dynamics of the variability of movements in judo matches. In addition, suggestions are presented to be applied to athletes in different age categories who are on the way to become Olympic athletes.

As air traffic demand grows, robust, data-driven anomaly detection methods are required to ensure that aviation systems become safer and more efficient. The terminal airspace is identified as the most critical airspace for both individual flight-level and system-level safety and efficiency. As such, developing data-driven anomaly detection methods to analyze terminal airspace operations is paramount. With the expansion of ADS-B technology, open-source flight tracking data has become more readily available to enable larger-scale analyses of aircraft operations. This paper makes a distinction between spatial metrics in ADS-B trajectory data and energy metrics derived from ADS-B trajectory data. Motivated by the limited number of approaches that simultaneously consider both spatial and energy metrics, this paper introduces the concepts of spatial anomalies and energy anomalies. In particular, it proposes a novel, unified framework for detection of spatial and energy anomalies in ADS-B trajectory data (and associated derived metrics). The framework consists of three main parts - a data processing procedure, a spatial anomaly detection method, and an energy anomaly detection method. The framework is demonstrated utilizing four months of ADS-B trajectory data associated with arrivals at San Francisco International Airport, and the relationship between the spatial and energy anomalies in this terminal airspace is explored. The results that stem from the implementation of this framework indicate that if an aircraft is spatially not conforming to an identified set of air traffic flows representing standard spatial operations, then this aircraft is more likely to experience non-conformance to standard operations in its energy metrics. Aviation operators, such as air traffic controllers, may benefit from this observation, as it may factor into decision-making in instances where there is the potential to instruct an aircraft to spatially deviate from standard operations. Additionally, this research revealed underlying differences between trajectories that are spatially nominal yet energy-anomalous and those trajectories that are spatially anomalous and energy-anomalous. Focusing solely on energy anomaly detection does not provide insight into potential spatial-related decisions that may have been made to result in off-nominal energy behavior.

The “NWCSAF High Resolution Winds (NWC/GEO-HRW)” software is developed by the EUMETSAT’s “Satellite Application Facility on support to Nowcasting and very short range forecasting (NWCSAF)”, inside its stand-alone software package for calculation of meteorological products with geostationary satellite data (NWC/GEO). The whole NWC/GEO software package can be obtained after registration at the NWCSAF Helpdesk, www.nwcsaf.org. It is easy to get, install and use. The code is easy to read and fully documented. And in the NWCSAF Helpdesk, users find support and help for its use. “NWCSAF High Resolution Winds” provides a detailed calculation of Atmospheric Motion Vectors (AMVs) and Trajectories, locally and in near real time, using as input NWP model data and geostationary satellite image data. The latest version of the software, v2018, is able to process MSG, Himawari-8/9, GOES-N and GOES-R satellite series images, so that AMVs and Trajectories can be calculated all throughout the planet Earth with the same algorithm and quality. In the “2014 and 2018 AMV Intercomparison Studies”, “NWCSAF High Resolution Winds” has shown to be one of the two best AMV algorithms for both MSG and Himawari-8/9 satellites. And the “Coordination Group for Meteorological Satellites (CGMS)” has recognized in its “2012 Meeting Report”: 1. “NWCSAF High Resolution Winds” fulfills the requirements to be a portable stand-alone AMV calculation software due to its easy installation and usability. 2. It has been successfully adapted by some CGMS members and serves as an important tool for development. It is modular, well documented, and well suited as stand-alone AMV software. 3. Although alternatives exist as portable stand-alone AMV calculation software, they are not as advanced in terms of documentation and do not have an existing Helpdesk. Considering this, a full description and validation of the “NWCSAF/High Resolution Winds” is shown here for the first time in a peer-reviewed paper. The procedure to obtain the software for operational meteorology and research is also explained.

This paper aims to assess whether the financial performance of Portuguese companies that publish sustainability reports (SR) differs from the financial performance of companies that do not publish SR. We use two methodological procedures. First, we conducted a univariate analysis to test the differences in the financial performance according to the disclosure of SR. Second, we conducted a multivariate analysis using a multiple linear regression that explains financial performance by the disclosure of SR, as well as control variables such as sector, size, leverage, growth, and liquidity. Findings indicate that financial performance of companies that disclose SR does not significantly differ from the financial performance of companies that do not disclose SR. The results are robust to both methodological procedures, as well as to the sample split by sectors.

The existing methods of oil palm Fresh Fruit Bunch (FFB) evacuation from in-field to temporary collection point which typically apply medium to large tractors, often result in unexpected soil compaction. Meanwhile, smaller size equipment indicates low working capacity and unable to perform direct unloading to collection bin. This paper addresses the challenge of FFB evacuation by focusing on preventing soil compaction, increasing working capacity and enabling direct unloading to collection bin. For this purpose, a 6x6WD transporter prototype with a scissor lift mechanism was developed. With the design, the transporter could evacuate FFB in both steep mineral terrain and low ground pressure peatland, able to carry FFB with capacity of 750 kg and provide direct unloading into collection bin. The average field working capacity of the transporter was found to be 15 tons day-1. This research offers insights for future designs of medium-sized FFB transporters with advanced unloading mechanisms.

Continuous-flow microwave heating stands out for its ability to rapidly and uniformly heat substances, making it widely applicable in chemical production. However, in practical applications, the permittivity of the heated liquid changes dramatically as the reaction progresses, affecting the efficiency and uniformity of continuous-flow heating. Herein, this work presents a novel microwave heating device based on coaxial structure for high-performance heating. Our approach commenced with the development of a multi-physical field model, incorporating a spiral polytetrafluoroethylene (PTFE) as a water channel and the coaxial waveguide as a container was established. The analysis shows that the uniform distribution of the sectional electric field of electromagnetic waves in the TEM mode within the coaxial structure can enhance heating uniformity. Then, a continuous-flow microwave heating system for different liquid loads was established, and experimental measurements were conducted. The heating efficiency for all loads exceeded 90%, which basely matched the simulation results, validating the accuracy of the model. Finally, the heating efficiency and uniformity under different permittivity loads were analyzed, as well as the impact of channel radius on heating efficiency. The device demonstrated high heating efficiency and stable heating uniformity across different loads. This continuous-flow microwave device is suitable for chemical research and production, contributing to the promotion of microwave energy applications in the chemical industry.

Abstract: Background: Restless Legs Syndrome /Willis-Ekbom disease (RLS/WED) has occasionally -but not consistently- been associated with cognitive, and most notably, language and executive impairment. The present study was conducted to investigate the cognitive trajectories of older individuals with RLS/WED. Methods: Participants were drawn from the randomly selected, older (>64 years), population-based HELIAD cohort. Individuals without dementia, with available neuropsychological evaluations at baseline and follow-up were considered for potential eligibility. A comprehensive assessment examining five principal components of cognition (memory, visuo-spatial ability, attention, executive function, and language) was administered to the partici-pants. Generalized estimating equations analysis was used to examine the unadjusted and adjusted (for critical factors and covariates) effects of RLS/WED on cognition over time. Results: A total of 1003 predominantly female, older (72.9 ±4.9 years) partici-pants, with follow-up evaluations after a mean of 3.09 ±0.85 years and without demen-tia at baseline and follow-up were included in the present study. Among them, 81 were diagnosed with RLS/WED at baseline. Global cognition, memory, attention, executive and visuo-perceptual skills did not differ between those with and without RLS/WED. However, the RLS/WED group performed worse on language at baseline by 0.249 of a standard deviation, while demonstrating a mitigated language decline over time, by 0.063 of a standard deviation. The unadjusted models yielded similar results. Conclu-sions: Our findings were indicative of a baseline language disadvantage among older individuals with RLS/WED, but the initial discrepancy tends to dissolve over time.

Education outside the classroom (EOtC) can be beneficial for students. The relationship between biological stress markers and sedentary behavior (SB) plus physical activity (PA) is insufficiently evaluated in school settings. This exploratory study aims to evaluate the association between students’ cortisol, plus circulating cell-free deoxyribonucleic acid (cfDNA) levels, and their SB, light PA (LPA) and moderate-to-vigorous PA (MVPA) during outdoor and indoor classes in different seasons. We assessed data from an education outside the classroom (EOtC) program (n = 48; intervention group [IG], n = 37; control group [CG], n = 11). We sampled data on 3 school-days in three seasons (fall, spring, and summer) in normal teaching indoors (CG) and outdoor lessons (IG) in the forest. SB and PA were evaluated by accelerometry, and cortisol and cfDNA levels by saliva samples. The compositional data analysis approach analyzed SB and PA. Fitted Bayesian hierarchical linear models evaluated the association between cortisol and cfDNA, and SB/LPA/MVPA. A steady decline of cortisol in the outdoor setting is associated with relatively high levels of LPA. SB and MVPA tended to exhibit a similar effect in the indoor setting. CfDNA is positively associated with a relatively high amount of SB in the IG, the same association is likely for LPA and MVPA in both groups. LPA seems to support a healthy cortisol decrease in children during outdoor lessons. The relevance of SB/PA as a composition in relation to students stress response in school should be emphasized. This study facilitates the formulation of straightforward and directed hypotheses for further research.

The review scrutinizes the currently performed research on the new methods for enhancing bituminous binder performance through radiation and radical grafting of polymer modifers of bitumen. It investigates innovative methods, including using waste polymers as modifiers, and applying radiation for polymer grafting, to overcome challenges like high costs, low aging resistance and storage stability issues, of which separation of phases polymer/bitumen is the most significant obstacle. These advanced modification techniques promise sustainability through the decrease of the carbon footprint of transportation systems by improving the properties and durability of binders. Additionally, the review discusses the parameters and mechanistic aspects from a scientific perspective, shedding light on the underlying processes that contribute to the improved performance of modified bituminous binders.

Seedling establishment is often a critical bottleneck to revegetation of mine tailings and similar substrates with a low capacity to retain water and plant nutrients. Biochar and deactivated yeast are potential sustainable, low-cost materials with high nutrient- and water-holding capacity that could be used in this context as seed coatings to aid in seedling establishment on challenging sub-strates. We conducted a greenhouse study to assess the effectiveness of biochar and deactivated yeast, applied alone in a factorial combination, as seed coatings, on the germination, establish-ment, and early growth of white clover (Trifolium repens) and purple prairie clover (Dalea pur-purea). Coated seeds were applied to a mine tailing, a coarse granitic sand, and potting soil mix substates; seedling establishment and growth were monitored over 75 days. Results indicate strong interactive effects of seed coatings with species and substrate. Biochar coatings enhanced seedling establishment of Trifolium, with biochar or biochar plus yeast coatings giving the best results. In some cases, these effects persisted throughout the experiment: biochar coatings resulted in a ~5-fold increase in Trifolium biomass at harvest for plants in the potting soil mix but had neutral effects on sand or tailings. Biochar seed coatings also enhanced Dalea germination in some cases, but benefits did not persist. Our results indicate that biochar-based seed coatings can have lasting effects on plant growth well beyond germination, but also emphasize highly spe-cies-specific responses that highlight the need for further study of broader patterns and mecha-nisms.

High dimensional datasets are highly likely to have redundant, irrelevant, and noisy features that negatively affect the performance of the classification algorithms. Selecting the most relevant features and reducing the dimensions of datasets by removing the undesired features is a dimensional reduction technique called Feature Selection (FS). In this paper, we propose an FS approach based on the Black Hole Algorithms (BHO) with a mutation technique called MBHO. Generally, BHO contains two major phases. At the exploitation phase, a set of stars are modified based on some rule and according to some objective function, the best star is selected as the black hole which attracts other stars. Furthermore, when a star gets closer to the event horizon, it will be swallowed and a new one will be randomly generated in the search space which thus is the exploration phase. However, randomness may cause the algorithm to fall into the trap of local optima, and to overcome such complications, inversion mutation is used. Furthermore, we modify a widely utilized objective function in most of the proposed works for wrapper feature selection by combining two new terms that are based on the correlation among the selected subset of features and the features and the classification label. We also utilize a transfer function, known as the V2 transfer function, to convert continuous values into discrete ones to enhance search. We assess our approach via extensive evaluation experiments using fourteen benchmark datasets. We benchmark the performance of a wrapper FS approach called Binary Cuckoo Search (BCS), and three filter-based FS approaches (namely Mutual Information Maximisation (MIM), Joint Mutual Information (JMI), and minimum Redundancy Maximum Relevance (mRMR)). Our evaluation has shown that the proposed model is an effective approach for FS, in selecting better features that enhance the performance metrics on the classifiers. Thus, MBHO can be utilized as one alternative to the existing state-of-art-approaches. We release the source codes of our implementation for the community to build on with new methods and datasets.

The human eye is a vital source of collecting information worldwide via daily observation. The computer science area recognizes it in research as a human-computer interaction. Human blink is an integral part of this observation as a research topic. Several studies have been conducted on eye blinking and left-right eye movements. Previous studies conducted on the eye blink consider the availability of hardware devices high in the budget, high Precision, and low light expo-sure, unlike our study, which uses low-budget devices as simple as a webcam and more versatile usable techniques, incredibly both dim and high light to name a few. This study offers the observational approach via ResNet101v2, VGG-19, and Convolution Neural Network (CNN) architectures. Outperforming both VGG-19 and CNN in this study, ResNet101v2 achieves an impressive accuracy of 98.2%. In contemporary times, deep learning in AI is taking an advanced form. This study attempts to provide a new insight into the real-world implementation of the eye blink.

The emerging wireless energy transfer technology enables sensor nodes to maintain perpetual operation. However, maximizing the network performance while preserving short charging delay is a great challenge. In this work, a Wireless Mobile Charger (WMC) and a Directional Charger (DC) are deployed to transmit wireless energy to the sensor node to improve the network's throughput. To the best of our knowledge, this is the first work to optimize the data sensing rate and charging delay by joint scheduling of MC and DC. We prove we can transmit maximum energy to each sensor node to obtain our optimization objective. In our proposed work, a DC selects a total horizon of equipped with DCs, which selects the horizon of each specific area with based on its antenna orientation. DC's orientation is scheduled for each time slot. Furthermore, multiple MCs are used to transmit energy for sensor nodes which cannot be covered by DCs. We divided the Rechargeable Wireless Sensor Network into several zones via the Voronoi diagram. We deployed a static DC and one MC charging location in each zone to provide wireless charging service jointly. We obtain the optimal charging location of MCs in each zone by solving Mix Integral Programming for energy transmission. The optimization objective of our proposed research is to sense maximum data from each sensor node with the help of maximum energy. The lifetime of each sensor network can increase, and the end delay can be maximized with joint energy transmission. Extensive simulation results demonstrate that our RWSNs are designed significantly to improve network lifetime over the baseline method.

Emotional intelligence may help nurses to cope with demanding work environments. Although it is well known that emotional intelligence is positively related to work performance literature on nurses is limited. The aim of our study was to examine the impact of emotional intelligence on work performance in a sample of nurses in Greece. We conducted a cross-sectional study in Greece. We collected data from a convenience sample of nurses during January 2024. We measured emotional intelligence with the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), and work performance with the Individual Work Performance Questionnaire (IWPQ). We created multivariable linear regression models adjusted for sex, age, educational level, and work experience. We found that the four streams of emotional intelligence (i.e. well-being, self-control, emotionality, sociability) increases nurses’ work performance. In particular, we found a positive relationship between well-being and task performance and contextual performance. Similarly, there was a positive relationship between self-control and task performance. Additionally, sociability increased task performance and contextual performance. Moreover, emotionality and sociability reduced counterproductive work behavior. Our multivariable models identified a positive impact of emotional intelligence on nurses’ work performance. Nurses managers and healthcare organizations should adopt appropriate interventions to improve nurses’ emotional intelligence.

Shape memory alloys (SMA) are becoming a more important factor in actuation technology. Due to their unique features, they bring the potential to safe weight, installation space and reduce energy consumption. The system integration of the generally small diameter NiTi wires is an important cornerstone for the emerging technology. Crimping, a common method for the mechanical and electrical connection of SMA wires, has several drawbacks when it comes to miniaturization and high force outputs. For high force applications for example, multiple SMA wires in parallel are needed to keep actuation frequencies high, while scaling up the actuation force. To meet these challenges, the proposed study deals with the development of a resistance welding process for manufacturing NiTi wire bundles. The wires are welded to sheet metal substrate, resulting in promising functional properties and high joint strengths. The welding process benefits from low cost, easy to control parameters and good automation potential. A method for evaluating the resistance welding process parameters is presented. With these parameters in place, a manufacturing process for bundled wire actuators is discussed and implemented. The welded joints are examined by peel tests, microscopy, and fatigue experiments. The performance of the manufactured bundle actuators is demonstrated by comparison to a single wire with the same accumulated cross-sectional area.

A novel nano-laminated GdB2C2 material was successfully synthesized using GdH2, B4C, and C via an in-situ solid state reaction approach for the first time. The formation mechanism of GdB2C2 was revealed based on the microstructure and phase evolution investigation. A purity of 96.4 wt. % GdB2C2 was obtained at a low temperature of 1500 ℃, while a near full pure GdB2C2 can be obtained at a temperature over 1700 ℃. The as-obtained GdB2C2 presented excellent thermal stability at high temperature of 2100 ℃ in Ar atmosphere due to the stable frame work formed by the high covalent four-members and eight-members B-C rings in GdB2C2. The minimum reflection loss value (RLmin) of -47.01 dB with an effective absorption bandwidth (EAB) of 1.76 GHz at a thickness of 3.44 mm was obtained for the GdB2C2 synthesized at 1500 ℃. The possible EMWA mechanism could be ascribed to the nano-laminated structure and appropriate electrical conductivity, which facilitated to the good impedance matching, remarkable conduction loss, interfacial polarization as well as multiple interface reflection and scattering. The as-obtained GdB2C2, with excellent EMWA performance as well as remarkable ultra-high temperature thermal stability, could be a promising candidate for the EMWA materials applications in extreme ultra-high temperatures.

Rapid urbanisation and city expansion worldwide have significantly increased impervious surfaces such as roads, buildings, and pavements. These impervious surfaces impede water infiltration into the ground, resulting in escalated surface runoff during rainfall. This has been exacerbated by climate change and heightened precipitation levels, resulting in recurrent annual flooding. Conventional drainage systems are now insufficient to cope with the amplified surface runoff, contributing to the escalating flood occurrences. Sustainable urban drainage systems such as green roofs, swales, and permeable pavements were developed as modern flood control techniques to replace the traditional drainage system approach by optimising resource utilisation and developing novel and more productive technologies. While most SUD techniques are sustainable in design, construction, and operation, permeable pavements are considered one of the least sustainable SUD techniques. This has garnered considerable attention from researchers who have been studying the design of a more sustainable permeable pavement system by utilising sustainable and recycled materials. This paper reviews the performance of permeable pavements systems using findings from extensive reviews and analyses of scientific publications on permeable pavements. It introduces a future solution and design of permeable pavements using recycled materials. The study will consist of two permeable pavement systems, one incorporating recycled materials in its layers and the other using traditional construction materials. The data collected from both systems will be compared to determine their performance.

Circadian rhythm (CR) influences various physiological functions, including physical and cognitive performance, which fluctuate throughout the day. The present study aimed to investigate the combined and separate effects of CR and physical fatigue on cognitive and physical performance. A sample of 18 amateur athletes was subjected to a series of tests at three different times of the day: morning, afternoon, and evening. Fatigue was induced following isokinetic concentric exercise combined with a 20-minute treadmill run, followed by assessments of selected physical and cognitive tasks. Repeated measures ANOVA did not reveal an interaction between CR and fatigue in cognitive performance (p &gt; 0.05). However, a significant main effect of fatigue was observed in visual reaction time (VisRT) across all three time points. Moreover, peak torque (PT) and peak torque fatigue index (PTFI) showed significant differences between the three times of the day, peaking in the evening. Although we found no interaction between CR and physical fatigue state on selected cognitive parameters at the three times of day, a separate effect of fatigue on cognitive performance was identified. Additionally, physical parameters exhibited peak values occurring in the evening hours. Future research should further explore underlying mechanisms that potentially influence cognitive performance at different times of the day.

A lead zirconate titanate [PZT;Pb(Zr_0.52Ti_0.48)O₃] layer embedded infrared (IR) detector decorated with wavelength-selective plasmonic crystals has been investigated for high-performance non-dispersive infrared (NDIR) spectroscopy. A plasmonic IR detector with an enhanced IR absorption band has been designed based on numerical simulations, fabricated by conventional microfabrication techniques, and characterized with a broadly tunable quantum cascade laser. The enhanced responsivity of the plasmonic IR detector at specific wavelength band has improved the performance of NDIR spectroscopy and pushed the limit of detection (LOD) by an order of magnitude. In this paper, a 13 fold enhancement in the LOD of a methane gas sensing using NDIR spectroscopy is demonstrated with the plasmonic IR detector.

Three-dimensional V₂O₅ hollow structures have been prepared through a simple synthesis strategy combining solvothermal treatment and a subsequent thermal annealing. The V₂O₅ materials are composed of microspheres 2–3 μm in diameter and with a distinct hollow interior. The as-synthesized V₂O₅ hollow microspheres, when evaluated as a cathode material for lithium-ion batteries, can deliver a specific capacity as high as 273 mAh·g⁻¹ at 0.2 C. Benefiting from the hollow structures that afford fast electrolyte transport and volume accommodation, the V₂O₅ cathode also exhibits a superior rate capability and excellent cycling stability. The good Li-ion storage performance demonstrates the great potential of this unique V₂O₅ hollow material as a high-performance cathode for lithium-ion batteries.

A low-cost bio-mass-derived carbon substrate has been employed to synthesize MoS₂@carbon composites through a hydrothermal method. Carbon fibers derived from natural cotton provide a three-dimensional and open framework for the uniform growth of MoS₂ nanosheets, thus constructing hierarchically coaxial architecture. The unique structure could synergistically benefit fast Li-ion and electron transport from the conductive carbon scaffold and porous MoS₂ nanostructures. As a result, the MoS₂@carbon composites, when served as anodes for Li-ion batteries, exhibit a high reversible specific capacity of 820 mAh g^-1, high-rate capability (457 mAh g^-1 at 2 A g^-1), and excellent cycling stability. The superior electrochemical performance makes the MoS₂@carbon composites to be low-cost and promising anode materials for Li-ion batteries.

Background/Aim: Stool gluten immunogenic peptides (GIP) determination is now considered a valuable tool for detecting dietary lapses in treated celiac disease (CeD) patients. Our study aims to explore the diagnostic performance of a qualitative lateral flow immunoassay point-of-care test (LFIA/PoCT) compared with a qualitative enzyme-linked immunosorbent assay (ELISA) for detection of stool GIP. Methods: The study is a post hoc analysis of stool samples collected in the real-life conditions from a cohort of gluten-free diet-treated CeD patients. Stool GIP was measured in µg/g of stool using an ELISA kit (iVYLISA GIP S®, Biomedal SL). For the qualitative evaluation of stool GIP, a LFIA/PoCT test (GlutenDetect®; Biomedal S.L) was employed, which reported results as positive or negative. The LFIA/PoCT performance was evaluated against ELISA, considered as the gold standard. GIP concentrations

As the demand of heating and air conditioning is increasing day by day due to getting a comfortable life, for that reason, the market for heat pump and air conditioning systems or both, is seeing a steady increase in low global warming potential. All researchers on heat pump and air conditioning systems are searching for environmentally friendly refrigerants. However, a significant number of contemporary refrigerants (HCFCs) have the potential to cause global warming and ozone depletion, such as those found in heat pump air conditioning systems. Using more environmentally friendly refrigerants, including hydrocarbon and blend refrigerant mixtures, is one way to lower GWP and Ozone depletion potential. This study examines the performance of several alternative refrigerants, including R32, R134A, R410A, R22, and R290. In order to examine the performance of R290, theoretical and simulation results are compared on various refrigerants while taking into account a number of performance parameters, including the refrigerant energy efficiency ratio, mass flow rate, coefficient of performance, cooling capacity, and compressor work for one ton of refrigeration (1TR) air conditioners. One player with a very low GWP is R290. However, the only drawback is that it can catch fire and is hazardous to use in split-type commercial heat pump air conditioning applications. The environmental and thermo physical properties of HC-290 are significantly better than those of other materials, according to theoretical and simulation studies utilizing Cool Pack software, hence it is a viable replacement.

Yoga promotes acceptance, compassion, physicality, active postures, mental and emotional awareness, and spiritual benefits. It involves breath techniques, postures, and body locks, maintaining balance and strength. It's based on ethical principles. Beyond simple performance, swimming is a catalyst for overall well-being. Complementarily, yoga serves as an invaluable adjunct for swimmers, enhancing flexibility, strength, and body awareness - a triad essential to aquatic excellence. The confluence of yoga and swimming, particularly through the practice of aqua yoga asanas, presents a new paradigm for both athletes and non-performers alike. Athletes who embrace the harmonious fusion of swimming and yoga unearth the potential for achieving not just athletic mastery but also a more balanced and fulfilling lifestyle. This blend provides a route not only to enhance performance in the water but also to elevate the overall quality of life. We examined the feasibility of incorporating yoga and swimming practice into Romanian subjects' lifestyles, designing a factor analysis in SmartPLS software, based on an online survey. The study assesses the participants' knowledge of yoga's theory and philosophy, as well as their perceptions of the swimming practice's benefits for social and health issues. According to our study, Romanian participants practice yoga and swimming as often as possible to reduce stress, improve concentration for work-related tasks, and improve joint elasticity, balance, and muscular tone. Thus, Yoga and swimming are substitutes for other approaches in prevention and therapy.

The performance of the presurgical test (preSurg) for temporal lobe epilepsy (TLE) was evaluated via video-electroencephalography (VEEG), electroencephalography (EEG), 99mTc-HmPAO single-photon emission tomography (SPECT) and 1.5 T magnetic resonance imaging (MRI) in a group of 112 men (37.0 ± 1.1 years) and 106 women (39.7 ± 1.1 years) operated on for TLE. The epileptic zone (EZ) was adequately identified to determine whether the patient reached an Engel I grade (EI) at least one year postop. Accuracy was evaluated by the coefficient α, ranging from 3 (when result = EZ) to 2 (result in the same hemisphere as the EZ), 1 (noninformative result) or 0 (EZ in the contralateral hemisphere). The simplicity of diagnosis was defined as the number of preSurg surgeries needed to identify the EZ. EI was obtained in 85.8% of patients even though 42.2% of patients had noninformative MRI results. For preSurg α was (mean ± SEM) = VEEG (2.83 ± 0.04) &gt; MRI (2.14 ± 0.08) &gt; EEG (1.87 ± 0.09) &gt; SPECT (1.71 ± 0.09). The accuracy (combination of sensitivity and specificity) was calculated as follows: VEEG (0.797) &gt; MRI (0.518) &gt; EEG (0.446) &gt; SPECT (0.360). The likelihood positive ratio was greater, and the likelihood negative ratio was lower for VEEG. The most relevant factor for the regression model was VEEG (3.106) &gt; MRI (2.558) &gt; EEG (1.905), and the factors were not significantly related to SPECT. EZs in EI patients with low simplicity were identified mainly by VEEG. A very good postoperative outcome can be obtained even in TLE patients with no lesions on MRI. The VEEG is the most reliable preSurg test and may be the only reliable test for patients with very low simplicity (i.e., difficult).single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

Using density functional theory (DFT), the density of states of NH4V3O8 (NVO) was analyzed pre and post-oxygen defects (Od) formation. The findings revealed a reduced bandgap in NVO after Od introduction, emphasizing the role of Od in enhancing conductivity of the material, thus improving its electrochemical attributes. Through the water bath method, both NVO and its oxygen-deficient counterpart, (NH4)2V10O25⸱8H2O (NVOd), were synthesized as potential cathode materials for aqueous zinc-ion batteries (AZIBs). Experimental outcomes resonated with DFT predictions, highlighting the beneficial role of oxygen defects in boosting electrical conductivity. Notably, the refined material displayed a remarkable capacity of 479.3 mAh g-1 at 0.1 A g-1, underscoring its promise for advanced energy storage solutions.

The aim was to identify if surface electromyography (sEMG) parameters are indicative of post-activation potentiation (PAP)/post-activation performance enhancement (PAPE), in terms of twitch potentiation and voluntary performance. Three databases were used in March 2024, with the following inclusion criteria: (a) original research, assessed in healthy human adults, (b) sEMG parameters were measured. The exclusion criteria were: (a) studies with no PAP/PAPE-protocol, (b) non-randomized control trials. The following data were extracted: study characteristics/demographics, PAP/PAPE-protocols, sEMG parameters, twitch/performance outcomes, and study findings. A modified physiotherapy evidence database (PEDro) scale was used for quality assessment. Fifteen randomized controlled trials (RCTs), with a total of 199 subjects were included. The M-wave amplitude (combined with a twitch torque outcome) was shown to generally be indicative of PAP. The sEMG amplitude (in some muscles) were found to be indicative of PAPE during ballistic movements, while a small decrease in the MdF (in certain muscles) were shown to reflect PAPE. Changes in the Hmax/Mmax ratio were found to contribute (temporally) to PAP, while the H-reflex amplitude was shown to be neither indicative of PAP nor PAPE. This review provides preliminarily findings suggesting that certain sEMG parameters could be indicative of PAP/PAPE. However, future research is warranted.

The relationship between the structure characteristics and performances of coal based hydrogenation isomeric base oil (CTL) and metallocene catalyzed coal based polyalphaolefin (mPAO) base oil was clarified here. CTL and mPAO were compared with typical petroleum based and natural gas based commercial API Class III and IV base oils. Pressurized differential scanning calorimetry (PDSC), Rotary Bomb Oxidation Test (RBOT) and four-balls friction tester were used to evaluate the oxidation stability and lubrication performance of base oils under different working conditions. The sensitivity of different base oils to typical antioxidants and extreme pressure antiwear agents was compared. Specially, the composition and structure of CTL base oil are obviously different from GTL and mineral base oil. The coal-based CTL and mPAO base oils exhibit commendable viscosity-temperature properties, characteristics, coupled with low-temperature fluidity, fire safety, and minimal evaporation loss. The lubricating properties, oxidation stability and the sensitivity to extreme pressure antiwear agents of CTL are close to those of similar base oils. But the sensitivity of CTL to typical antioxidants is relatively poor. Besides, compared with commercial PAO base oil, mPAO has lower isomerization degree and fewer isomerization types. The oxidation stability and sensitivity to typical antioxidants of mPAO base oil are comparable with those of commercial PAO base oil, while its lubrication performance and sensitivity to typical extreme pressure antiwear agents are significantly better than those of commercial PAO base oil.

In this paper, a novel permanent magnet-assisted synchronous reluctance machine (PMASynRM) with rare-earth PMs and ferrite magnets is proposed. The performance of PMASynRM is discussed with respected to the different magnet ratio of rare-earth PMs and ferrite magnets. Some characteristics including the flux density, output torque, cogging torque, output power, power factor, torque ripple, loss, efficiency, and demagnetization are calculated by 2-D finite element analysis (FEA). The analysis results show that the excellent performance can be obtained by using hybrid magnet of rare-earth PMs and ferrite magnets with the suitable magnet ratio, and provide some desirable cost-performance trade-off.

The iron roughneck is an automated equipment utilized for the connection and removal of drilling tools. This paper presents the design of an integrated iron roughneck, providing a detailed introduction to its clamp body structure, along with an analysis of its structural characteristics and performance requirements. The study delves into the integration mode and working characteristics of the clamping mechanism and spin buckle mechanism for the integrated upper clamp body structure of the iron roughneck. Additionally, this paper conducts an in-depth theoretical study on the spin buckle mechanism. Firstly, it analyzes the actual working condition of the spin buckle roller from two perspectives: contact theory and rolling friction theory, determining the structural form of the spin buckle roller. Secondly, it investigates the relative displacement between the spin buckle mechanism and the drilling tool, proposing a design method for the floating device mounted on the spin buckle roller and establishing the kinematic equation of the spin buckle roller under the influence of the floating device. Furthermore, the kinematic equations of the spin buckle roller under the influence of the floating device are established. Finally, a dynamics simulation experiment is performed to simulate the working process of the spin buckle mechanism under actual working conditions, analyzing the dynamics and kinematics of the spin buckle mechanism and obtaining the relevant parameter curves of the spin buckle mechanism and drilling tools. Through data comparison and analysis, the correctness of the theoretical analysis results and the rationality of the performance and structure of the spin buckle mechanism are verified.

This study investigates the impact of intellectual capital on the sustainable performance of banks in Saudi Arabia, focusing on the period from 2012 to 2022. Utilizing data from ten major Saudi banks, the research examines how different components of intellectual capital—Human Capital Efficiency (HCE), Structural Capital Efficiency (SCE), and Capital Employed Efficiency (CEE)—influence key financial performance indicators such as Return on Equity (ROE) and Net Profit Margin (NPM). The study is grounded in the resource-based view of the firm, which suggests that a firm’s internal resources can provide a sustainable competitive advantage. The analysis employs panel data techniques, including fixed and random effects models, to assess the relationships between intellectual capital components and bank performance while controlling for variables like bank size, financial leverage, GDP growth, inflation, and the impact of the COVID-19 pandemic. The findings reveal that intellectual capital significantly enhances bank performance in Saudi Arabia, with human capital efficiency showing the most decisive influence on ROE and NPM. Structural capital and capital employed efficiency also contribute positively but vary in their impact on different performance measures. This research contributes to the theoretical and practical understanding of the role of intellectual capital in promoting sustainable banking practices. It underscores the importance of strategic management of intellectual capital in enhancing financial performance and achieving sustainability goals, particularly in the context of Saudi Arabia's Vision 2030. The study's insights are relevant for bank managers and policymakers who leverage intellectual capital for economic diversification and sustainable development.

Proper Post-Activation Performance Enhancement helps to improve athletic performance. This study aimed to investigate the effects of two different velocity loss (VL), 10%VL and 20%VL, on post-activation performance enhancement (PAPE) in 20m sprint performance among sprint athletes. Twenty-four male sprint athletes (100m sprint time: 10.96±0.15 s) were recruited. A randomized crossover experimental design was used for traditional group (TG), 10%VL, and 20%VL interventions. Sprint tests were conducted at the 4th, 8th, 12th, and 16th minutes after the intervention. Two-way repeated measures ANOVA revealed an interaction effect between group and time on 20m sprint performance (F=2.817, p=0.037, partial η²=0.585). Simple effect analyses showed significant differences compared to baseline at the 4th minute for the 20%VL group (P&lt;0.05). Cohen's d values indicated improvement in 10m sprint times at the 8th minute of the rest interval for all three intervention groups (TG: ES=-0.270, 10%VL: ES=-0.038, 20%VL: ES=-0.279). Improvement in 20m sprint times was observed at the 4th minute for the 20%VL group (ES=-0.296) and at the 16th minute for the 10%VL group (ES=-0.276). Compared to traditional PAPE schemes based on 1RM, PAPE schemes based on velocity loss (20%VL) can better induce PAPE effects in sprint athletes.

Over the years, researchers have been studying the effect of weather and context data on the transport mode choice. The majority of these works are based on survey data, however the accuracy of their findings relies on how respondents give accurate and honest answers. In this paper, the potential of using GPS trajectories as an alternative to travel surveys in studying the impact of weather and context data on transport mode choices is investigated in Beijing city. In the analysis, we apply both descriptive and statistical models such as the MNL and MNP models. Our findings indicate that temperature has the most prominent effect among weather conditions. For instance, for temperatures greater than 25 °C, the walking share increases by 27% and the bike share reduces by 21%, which is line with the results from several survey studies. In addition, the evidence of government policy on transport regulation is revealed when the air quality becomes hazardous as people are encouraged to use environmentally friendly travel mode choices such as the bike instead of the bus and car, which are known CO2 emitters. Moreover, due to a series of traffic restrictions introduced by the Beijing government during the 2008 summer Olympics, a decrease of 17.5% in the car share and an increase of 13% and 10% in the walking and bus shares, respectively are observed. These findings provide a scientific basis for effective transport regulation and planning purposes.

A large body of evidence has linked unhealthy eating patterns with an alarming increase in obesity and chronic disease worldwide. However, existing methods of assessing dietary intake in nutritional epidemiology rely on food frequency questionnaires or dietary records that are prone to bias and selective reporting. Herein, metabolic phenotyping was performed on 42 healthy participants from the Diet and Gene Intervention (DIGEST) pilot study, a parallel two-arm randomized clinical trial that provided complete diets to all participants. Matching urine and plasma specimens were collected at baseline and following 2 weeks of provision of either a Prudent or Western diet with a weight-maintaining menu plan designed by a dietician. Targeted and nontargeted metabolite profiling was conducted using three complementary analytical platforms, where 80 plasma metabolites and 84 creatinine-normalized urinary metabolites were reliably measured (CV < 30%) in the majority of participants (> 75%) after implementing a rigorous data workflow for metabolite authentication with stringent quality control. We classified a panel of metabolites with distinctive trajectories following 2 weeks of food provisions when using complementary univariate and multivariate statistical models. Unknown metabolites associated with contrasting dietary patterns were identified with high resolution MS/MS and/or co-elution after spiking with authentic standards. Overall, 3-methylhistidine and proline betaine concentrations increased consistently after participants were assigned a Prudent diet (q< 0.05) in both plasma and urine samples with a corresponding decrease in the Western diet group. Similarly, creatinine-normalized urinary imidazole propionate, hydroxypipecolic acid, dihydroxybenzoic acid, and enterolactone glucuronide, as well as plasma ketoleucine and ketovaline increased with a Prudent diet (p< 0.05) after adjustments for age, sex and BMI. In contrast, plasma myristic acid, linoelaidic acid, linoleic acid, a-linoleic acid, pentadecanoic acid, alanine, proline, carnitine and deoxycarnitine, as well as urinary acesulfame K increased among participants following a Western diet. Most metabolites were also correlated (r > ±0.30, p< 0.05) to changes in average intake of specific nutrients from self-reported diet records reflecting good adherence to assigned food provisions. Our study revealed robust biomarkers sensitive to short-term changes in habitual diet for accurate monitoring of healthy eating patterns in free-living populations, which is required for validating evidence-based public health policies for chronic disease prevention.

Vertical-axis wind turbines (VAWTs) are receiving more and more attention as they involve simple design, cope better with turbulence and are insensitive to wind direction which has a huge impact on the cost since the yaw mechanism is not needed. However, VAWTs still suffer from low conversion efficiency. As a results tremendous efforts are exerted to improve its efficiency which mainly focus on two methods regardless of whether the study is a CFD simulation or a field test or lab test experiment. An active approach which involves the modification of the rotor itself such as the blade design, angle, trailing and leading edges, inner blades, chord thickness, contra-rotating rotor, etc. While the second approach involves passive techniques where the flow is directed to optimally face the downwind rotor by mounting a guiding vane such as a diffuser or other shapes at the upwind position of the rotor. Among all techniques undertaken, the CRWT rotor technique seems to be the most effective with an output even comparable to that of Horizontal Axis Wind Turbines (HAWT), while the Savonius rotor received more attention compared to other designs of VAWTs. Apart from technological issues, it was also suggested that geographical issues such as proper site siting of the wind turbine rotor at a particular location where a uniform flow could be guaranteed is of paramount importance to ensure an effective conversion capacity of wind turbines.

Establishing systemic communications between the project plan, stakeholders, and the organization through integrated management meets stakeholders' demands and managerial expectations in project-oriented organizations. Performance assessment can be defined as a control system in any company that reviews its daily operations and evaluates how well it has achieved its goals. This study aims to investigate the impact of an integrated project management system on the financial performance of the Organization for Renovation, Development, and Equipment of Schools. This applied research is descriptive-analytical. The statistical population comprises 2,700 employees of the organization, with a sample size of 340 individuals examined. The reliability of the designed questionnaire was confirmed by experts in the organization using Cronbach's alpha (α=0.91). Data were analyzed using SPSS version 20 and AMOS 18 software through descriptive statistics and confirmatory factor analysis. The results indicate that the seven dimensions of the integrated project management system (cost management, quality management and continuous control, change management, systems and information management, human resources management, interaction and communication management, procurement management) have a positive and significant impact on the financial performance of the Organization for Renovation, Development, and Equipment of Schools.

Until now, crystalline NiCo2S4 and its composites have demonstrated improve performances in supercapacitor applications, compared to their oxide analogous, due to their relatively higher electrical conductivity, and multifaceted redox reaction. However, amorphous phase materials have recently shown promise in electrochemical energy storage systems. In this work, urea-assisted amorphous NiCo2S4 on nickel foam (referred to as aNCS) with high nitrogen atom% content, was obtained via hydrothermal method. In comparison to the crystalline NiCo2S4 (referred to as cNCS), aNCS exhibited superior electrochemical performance with specific capacitance of ~3506 F g-1 which is higher than cNCS specific capacitance of ~2185 F g-1 at 2 A g-1. Additionally, aNCS in two-electrode asymmetry supercapacitor exhibited specific capacitance and energy density of ~196 F g-1 and 56 Wh kg-1, respectively.