State-of-the-art augmented-reality (AR) glasses record their position and orientation in space, enabling measurements and analyses of clinical gait-and-balance tests. This study’s objective was to evaluate concurrent validity and test-retest reliability for common clinical gait-and-balance tests in people with Parkinson’s disease: the Five Times Sit-To-Stand (FTSTS) and Timed Up-and-Go (TUG) tests. Position and orientation data was collected in 22 participants with Parkinson's disease using HoloLens 2 and Magic Leap 2 AR glasses, from which test-completion durations and durations of distinct sub-parts (e.g., sit-to-stand, turning) were derived and compared to reference systems and over test repetitions. Regarding concurrent validity, for both tests an excellent between-systems agreement was found for position and orientation time series and test-completion durations. Between-systems agreement for FTSTS (sub-)durations were all excellent, while TUG turning sub-durations were excellent (turn 1) and moderate (turn 2). Regarding test-retest reliability, the within-system test-retest variation in test-completion times and sub-durations was always much greater than the between-systems variation, implying that these (sub-)durations may be derived interchangeably from AR and reference-system data. In conclusion, AR data are of sufficient quality to evaluate gait and balance in people with Parkinson's disease, with valid quantification of test-completion durations and sub-durations of distinct FTSTS and TUG sub-parts.

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The Upper Hunter Valley is a major coal mining area in New South Wales (NSW), Australia. Due to the ongoing increase of mining activities, PM10 (air-borne particle with an aerodynamic diameter less than 10 micrometres) pollution has become a major air quality concern in local communities. The early part of this study identified two air quality subregions in the valley. This paper aims to provide a holistic summarisation of the relationships between elevated PM10 pollution in two subregions and the local- and synoptic-scale meteorological conditions for spring and summer, when PM10 pollution is relatively high. A catalogue of twelve synoptic types and a set of six local meteorological patterns have been quantitatively derived and linked to each other using the self-organising map (SOM) technique. The complex meteorology-air pollution relationships have been visualised/interpretated on the SOM planes for two representative locations. It was found that the influence of local meteorological patterns differed significantly for mean PM10 levels vs the occurrence of elevated pollution events and between air quality subregions. In contrast, synoptic types showed generally similar relationships with mean vs elevated PM10 pollution in the valley. Two local meteorological patterns, the hot-dry-northwesterly wind conditions and the hot-dry-calm conditions, were found most PM10 pollution conducive in the valley when combined with a set of synoptic counterparts. These synoptic types are featured with the influence of eastward migrating continental high pressure system and westerly troughs, or a ridge extending northwest towards coastal northern NSW or southern Queensland from the Tasman Sea. The method and results can be used in air quality research for other locations of NSW, or similar regions elsewhere.

The COVID-19 pandemic has triggered seismic shifts in how we work, and organizations behave. It has caused many organizations to transition from an office-centric culture to more flexible ways of working. This shift is necessitated by health conditions and the need for controls. It is also driven by the assumption that remote work or working from home offer a certain assurance of safety for employees against the threat of infection in highly vulnerable office conditions. The shift to remote work has so far been mainly experimental as most businesses continue to learn about what works and what doesn’t. There is also the assumption that all that matters for the efficient operability of a remote work regime is the availability and effectiveness of computing technologies and internet connectivity. Thus, once those supplies are in place remote work is expected to be fully functional and without problems. As learning continues about what works and what doesn’t, it has also become increasingly clear that beyond the threat of covid-19 and the relative safety that individual homes may offer, there are other vulnerabilities which are ignored or underestimated in the process. In most instances, the home environment of the employee, the conditions under which employees operate from home and the health and safety such environments provide (or not) are either ignored or underestimated in discussions around remote work practices. This paper highlights remote work as an emergent practice while exploring associated, but ignored, health and safety issues in employee homes.

During the COVID-19 pandemic, the spread of the SARS-CoV-2 virus forced many individuals to confront their mortality and worry about losing loved ones also because social distancing policies often made it impossible to say goodbye. Those not directly experiencing loss were inundated with information about COVID-19-related deaths through various media, leading to vicarious grief. This study aims to explore the long-term effects of direct and vicarious mourning on people's mental health during the COVID-19 pandemic. A sample of 171 adults (65% female) aged 19 to 66 years (mean age = 25.8, SD = 8.57) voluntarily participated in an online survey assessing self-reported psychological measures of complicated grief, anxiety, stress, depression, dispositional neuroticism, and situational anxiety using the Fear of COVID-19 Scale. MANOVA tests revealed that individuals experiencing direct mourning had extremely severe scores for anxiety, stress, and fear of COVID-19, while those without personal losses had moderate scores. Participants reporting high media exposure had higher scores for depression and stress. In line with Terror Management Theory, the study supported that people during the COVID-19 pandemic engaged more in proximal defenses than distal ones, taking health-protective measures, experiencing increased anxiety levels toward SARS-CoV-2 infection, and feeling more distressed. Additionally, vicarious mourning was more strongly associated with depression due to emotional empathy with others. The discussion also addresses the strengths and limitations of the study.

Over the last two decades, a considerable amount of equipment has been acquired (spreaders, seeders, sprayers, among others) to respond to the challenges of Precision Agriculture (PA) concept. Most of this equipment has been purchased at a high cost. However, many of them, despite still being functional and equipped with sensors, actuators, and electronic processing units capable of adjusting to variations in speed, have become obsolete in terms of communication, and incompatible with new monitoring and control systems based on the “Isobus” protocol. This work aims to present a solution for updating the control system (“Ferticontrol”) of a “Vicon RS-EDW” spreader with variable rate application (VRA), making it compatible with the “InCommand” system from “Ag Leader”. The solution includes low-cost “Arduino” and “Raspberry Pi” microcontrollers and open-source software. The development shows that it is possible to implement a solution that is accessible to farmers in general. It also provides a niche business opportunity for young researchers to set up small technology-based enterprises associated with universities and research centers. These partnerships guarantee permanent innovation and represent a decisive step towards modern, technological, competitive, and sustainable agriculture.

Wounds are an increasing global concern, mainly due to a sedentary lifestyle, frequently associated to the occidental way of life. The current prevalence of obesity in western societies, leading to an increase in type II diabetes, and an elderly population, are also a key factor associated to the problem of wounds healing. Therefore, it stands essential to find wound dressing systems allowing reestablishing the skin integrity in the shortest possible time and with the lowest cost, avoiding further damage and promoting patients´ well-being. Wounds can be classified into acute or chronic, depending essentially on the duration of the healing process, which is associated with. It depends on the extent and depth of wound, localization, level of infection and on the patient health status. For each kind of wound and respective healing stage there is a more suitable dressing. The aim of this review was to focus on the possible wound dressing management, aiming the more adequate healing approach for each kind of wound.

The Upper Hunter Valley is a major coal mining area containing approximately 40% of the currently identified total coal reserves in New South Wales (NSW), Australia. Due to the ongoing increase of mining activities, PM10 (air-borne particle with an aerodynamic diameter less than 10 micrometres) pollution has become a major air quality concern in local communities. This paper summarises the spatial and temporal variability modes of PM10 pollution in the region, based on long-term multi-site monitoring data and the application of the rotated principal component analysis (RPCA) and wavelet analysis techniques. RPCA identified two distinct air quality clusters/subregions in the valley, one in the west/northwest, the other in the southeast. Wavelet analysis revealed the annual cycle to be most persistent temporal mode of PM10 variability in both subregions, with intermittent signals observed at time scales of around 120, 30~90 and under 30 days. How these variation modes are related to the effects of local PM10 emissions and the influence of meteorology at different time scales deserves further attention in future work. The findings will be used in air quality reporting and forecasting in NSW. The methodology and results can also be useful for air quality research in similar regions elsewhere.

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 > 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.

Staphylococcus aureus is a gram-negative bacterium that causes superficial and deep infections that can be mild or potentially fatal. Recently, the bacterium has gained significant attention due to the increased incidence of multidrug-resistant (MDR) strains that make treatment with antibiotics dif-ficult. Owing to the MDR strains, alternative therapies such as antimicrobial photodynamic therapy (PDT) have emerged as good options to treat non-systemic infections. PDT combines a photosensi-tiser (PS) with light and oxygen to generate free radicals that destroy bacterial structures such as the plasma membrane, matrix, and genetic material. This systematic review aimed to identify the ef-fectiveness of PDT delivered using different types of hydrogels for treating wounds, burns, and contamination by S. aureus. This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Bibliographic research was conducted using the PubMed, Web of Science, and Scopus databases. Only full articles published in English between 2013 and 2024 from any country of origin (without restrictions) were included. The research was carried out from 15 June 2023 to 15 June 2024 and did not use any automatic biblio-graphic search tool. The articles collected were identified using keywords and selected using in-clusion and exclusion criteria in accordance with the PRISMA protocol. Seven articles were in-cluded that presented a good set of evidence associated with the use of PDT against S. aureus in in vitro and in vivo studies. To conclude, PDT can effectively complement antimicrobial therapy against S. aureus, in the healing of wounds and burns. The effectiveness of this technique depends on the PS used, hydrogel type, and lesion location. Some studies have already demonstrated the ef-fectiveness of PDT but most were in vitro and a few in vivo. Further studies are required to demonstrate the safety and efficacy of PDT delivered via hydrogels in in vivo models of bacterial infection.

Off-grid electrification planning increasingly recognizes the importance of productive use of electricity (PUE) to promote community value creation and (financial) project sustainability. To ensure a sustainable and efficient integration in the community and energy system, PUE assets must carefully be evaluated to match both the community needs and the residential electricity demand patterns. We propose a novel methodology interlinking qualitative interviews, statistical analysis, and energy system modelling to optimize decision-making for PUE integration in off-grid energy systems in rural Madagascar by aligning relevant PUE effectively with anticipated residential electricity demand patterns based on socio-economic determinants of the community. We find that a possible contribution of the PUE to reducing the electricity costs depends signifi-cantly on three factors: 1. the residential electricity consumption patterns that are influenced by the socio-economic composition of the community, 2. the degree of flexibility of i) PUE assets and ii) operational preferences of the PUE user, and 3. the capacity of community members to finance and operate PUE assets. Our study demonstrates that significant cost reductions for PUE-integrated off-grid energy systems can be achieved by applying our proposed methodology. When matching PUE and residential consumption patterns, the integration of PUE assets in residential community energy system can reduce the financial risk of operators, provided the PUE enterprise operates reliably and sustainably. We highlight that the consideration of local value chains and co-creation approaches are essential to ensure the energy system is addressing the community’s needs, creates value for the community, enhances the project´s financial sustainability, and is achieving the overall objectives of decentralized energy system planning.

ObjectivesIn increasingly stressful times, many people are increasingly turning to fast food, neglecting to drink enough fluids and often forgoing regular exercise. The fast tempo of everyday life leaves little room for healthy habits, such as cooking at home, which means that a conscious and balanced diet takes a back seat.MethodsA descriptive pilot study was conducted to investigate the effects of an eight-week intervention program. This program included the daily intake of breakfast, cooking at home, adequate fluid intake and daily physical activity. The aim of the study was to evaluate the effects of these measures on the participants' body weight and general health.Results During the 56-day intervention, there was a steady trend towards weight reduction, and at the end of the intervention phase, a significant weight reduction in the test person could be observed. At the end of the intervention, the participant was still 45 years old, measured a body weight of 73.4 kg, which represents a BMI of 25.1 and is classified as slightly overweight. ConclusionThe results of the pilot study demonstrate clearly that the health mix of regular cooking at home, a daily breakfast, a daily physical activity session and sufficient fluid intake can be an effective booster for weight loss in adults. This combination has not only led to a significant reduction in body weight, but has also shown that simple, everyday measures can have a profound effect on health.

Several Lung diseases can result in lung damage structural changes, with lung transplantation as a only therapeutic option when the disease reaches an advanced progression, unfortunately, the success of lung transplantation is limited. In this context, lung bioengineering is considered a potential therapeutic alternative and the current approach is based on the use of the natural extracellular matrix (ECM) of the decellularized lung. The use of undifferentiated cells to seed an ECM can be a more practical strategy for lung bioengineering but the sterilization of the organ for this recellularization process is still a challenge. In this sense, Low-Level Laser Therapy (LLLT) can emerge as a potential treatment alternative. Therefore, the objective of this study was to verify if LLLT, can optimize lung recelularization with mesenchymal stem cells by cytokine modulation. For this, we decellularized lungs from C57BL/6 mice perfusing SDS 1% via pulmonary artery, sterilized with LLL (660nm, 100mW, 30s). Whole lung scaffolds were recellularized: (1) Recellularized Lung (2) Recellularized Lung + LLLT. Mesenchymal stem cells derived from human tooth pulp (DPSc) were seeded into lungs and incubated for 24 hours at 37ºC, 5% CO₂, in a bioreactor-like conditions, maintaining CPAP at 20cmH2O, 90% O2, and LLL at wavelength of 808nm, 100mW, 30s. Culture medium were analyzed at 24 hours. H&E, immunostaining, SEM and ELISA assay were performed. We produced viable biological scaffolds absent of DNA content, preserving glycosaminoglycans and collagen I, III and IV, fibronectin, laminin and elastin and lung structure (SEM). The levels of IL-6 and IL-8 were stable during the 24 hours of culture. IFN-γ levels showed significant difference in the DPSc and DPSc+LLLT group in the 24-hour evaluation. The levels of IL-10 decreased after LLLT. These findings highlight LLLT's role in cytokine regulation and contamination prevention during lung recellularization with mesenchymal stem cells. Overall, these results demonstrated that LLLT's modulated cytokine levels and could prevent contamination during the lung recellularization process with mesenchymal stem cells, offering promise for enhanced therapeutic strategies in lung bioengineering.

Human induced climate change led to the recognition of Community-Based Adaptation (CBA) as one of the remedies in building adaptive capacity and resilience of communities. It recognizes the resources and the skills as well as the agency of communities in shaping the optimal strategy. CBA interventions are vital in addressing community needs and contextual specificities, enable participatory and inclusive engagement and thereby facilitate more profound adaptation impacts. Agent-based modelling (ABM) harbors the potential to be the ideal tool to support developing of tailored adaptation strategies while considering capacities, resources, skills, priorities, needs and the cultural context of local communities. ABM allows to capture the complex relationships among various components within community decision making on CBA actions, the CBA actions themselves and the environment. There exist plenty of tools, however they provide for varying degrees of freedom in agent definition, sensitivity analysis, scalability, experiment design and output analysis to name a few. A set of required key criteria for CBA modelling is developed and all available ABM modelling and simulation tools are assessed for their suitability for CBA. NetLogo emerges as the most fitting tool for incorporating and handling the special features of CBA. It is closely followed by GAMA and Envision. The article provides insights and guidance to researchers and practitioners in selecting ABM tools aligned with the specific requirements of their CBA simulations and projects.

Climate simulations in West Africa have been attributed with large uncertainties. Global climate projections are not consistent with changes in observations at the regional or local level of the Niger basin, making management of hydrological projects in the basin uncertain. This study evaluates the potential of using the quantile mapping bias correction to improve the Coupled Model Intercomparison Project (CMIP5) outputs for use in hydrology impact studies. Rainfall and temperature projections from 8 CMIP5 Global Climate Models (GCM) were bias corrected using the quantile mapping approach. Impacts of climate change was evaluated with bias corrected rainfall, temperature and potential evapotranspiration (PET). The IHACRES hydrological model was adapted to the Niger basin and used to simulate impacts of climate change on discharge under present and future conditions. Bias correction significantly improved the accuracy of rainfall and temperature simulations compared to observations. Nash coefficient (NSE) for monthly rainfall comparisons of 8 GCMs to the observed was improved by bias correction from 0.69 to 0.84. The standard deviations among the 8 GCM rainfall data were significantly reduced from 0.13 to 0.03. Increasing rainfall, temperature, PET and river discharge were projected for all GCMs used in this study under the RCP8.5 scenario. These results will help improving projections and contribute to the development of sustainable climate change adaptation strategies.

The extent of access to energy of displaced populations in settlements and camps in Africa is largely 14 unknown. A multitude of contextual factors, such as the location and the characteristics of housing, 15 the legal status, the socio-cultural background, and the availability of humanitarian and public ser- 16 vices impact the living conditions and the needed energy services. Limitations in accessing energy 17 services have direct, multilayered, and far-reaching implications, including impacts on health, nu- 18 trition, education, protection, and livelihood. The objective of this article is to contribute to a more 19 comprehensive overview of the current state of energy access in displacement contexts on the Afri- 20 can continent by identifying and utilizing existing data. After a screening of the vast and various 21 available information, setting up of a database, consolidating the gathered data as well as assessing 22 the quality through a quality assessment method, the currently available information is visualized 23 and discussed. Considerable differences in the access to electricity for displaced persons across the 24 countries are found. For both electricity and clean cooking, the availability for displaced persons 25 ranges from nearly no access at all up to an access rate of 100%. More strikingly, the results also 26 show that besides South Africa and countries in the Maghreb region, the access to both clean cook- 27 ing and electricity for displaced persons is very low. At the same time, the fragmented data availa- 28 bility, the poor data quality, and the questionable expediency of available data allows neither solid 29 theoretical conclusions nor planning of effective practical implementation measures. Novel inter- 30 disciplinary research, conceptual frameworks and indicators are needed for the purpose of compa- 31 rability and consistency. Future research has the potential to more comprehensively capture the 32 current state of access to energy in displacements contexts and in a next step to examine how energy 33 is interwoven in the lives of displaced people to derive a set of more detailed context-sensitive en- 34 ergy indicators. It is essential that the concerned persons, the displaced persons themselves are in- 35 cluded in the research in a meaningful way.

In the past two decades, several floods have affected people and their properties in Burkina Faso, with the unprecedented flooding occurring in Ouagadougou in September 2009. So far, most studies have focused on Ouagadougou and surrounding localities and have paid little attention to other flood-prone regions in Burkina Faso. Specifically, there is a data and knowledge gap about the flood risk in the Haut-Bassins region, which in turn hampers the development of mitigation strategies and risk reduction measures in communities. This study demonstrates how data collected at the household level can be used to understand flood risk and its components at the village level in this data-scarce region. Using an indicator-based method, we analyze both flood risk and flood risk perception at the village level. Moreover, we determine the factors influencing flood risk perception at the household level using an ordered logit model. We find that 12 out of the 14 villages considered, experience high levels of flood risk. The management of runoff from the nearest urban areas and poorly designed civil engineering infrastructures, such as roads, were highlighted by the households as significant factors that increase their vulnerability. Hence, dependencies in space and between urban and rural areas may play a substantial role in modifying risk. The perceived flood risk consistently exceeds the estimated flood risk, with an insignificant positive correlation between both risk indices. Regression results indicate that flood risk perception is mainly influenced by informational and behavioral factors of the households. The findings of this study can provide valuable information to municipal and regional authorities involved in disaster risk management in the study area. Moreover, the method is transferable to other data-scarce regions

According to current forecasts, global heating is likely to exceed 2,8°C by the end of the century. This makes substantial adaptation measures necessary to secure a broad basis for livelihoods provision and the conservation of biodiversity. While the implementation of top-down and technocratic adaptation efforts is the majority, related adaptation shortcomings of socio-economic and ecological nature are becoming more and more apparent. Community-based adaptation (CBA) with its participatory, inclusive and needs-based bottom-up approach offers a promising and powerful alternative. This article uses a semi-systematic literature review approach to screen the current literature and identify core issues of CBA. Linking communality, locality, multidimensionality, power imbalances, transformative potential, localisation, the triad of adaptation metrics and adaptation with nature to corresponding potential actions for practical implementations provides a more holistic conceptualisation and broadens the horizons for further learnings, research and improved application.

Monitoring training load, recovery, and wellness in maturation ages is even more relevant than in adulthood, especially during congested schedules. The objective of this study was to quantify and describe the differences in external and internal load, recovery, and perceived wellness in elite under-16 female players during a period of three competitions in seven days, based on their participation during matches. An observational design was used to quantify external load (total distance, high-speed distance, and PlayerLoad), internal load (differential sRPE), as well as recovery and wellness of 18 international under-16 players during a development tournament. The external load pattern of the starting players was undulating, with matches showing the highest internal load values compared to training sessions and non-starters. Non-starters players (whether training or matches) showed similar external load and differential sRPE values throughout the tournament (p>0.05). Starting players experienced higher internal load than non-starters during matches (p<0.037), without differences between training sessions (p>0.05). No changes were seen in wellness or recovery (all p-values >0.05), except for non-starters in session 3 compared to session 7 (p=0.024). Starting players had more weekly total minutes (p=0.018), differential sRPE (breath: p=0.002; leg: p=0.002; cognitive: p=0.003), total distance (p=0.003), and PlayerLoad (p=0.008) than non-starters. Our results indicate differing load patterns between starters and non-starters, which do not affect wellness and recovery differently. Starters accumulate more weekly total load. Coaches can use these findings to guide decisions and load compensations in high competition contexts for young female soccer players.

Since the 1960s, the countries of sub-Saharan Africa have been affected by an urban crisis due to the demographic explosion in cities and the resulting land pressures. These have resulted in the proliferation of spontaneous housing areas which question the future of urban vegetation and its degree of inclusion in city planning. To analyze the state of knowledge on the research already carried out on the development of urban landscape, particularly in sub-Saharan Africa, a literature review on urban forestry covering the period 1998-2022 was carried out in order to better orient future research works for a greater consideration to urban forestry and their contributions in combating the adverse effects of climate change. Out of a set of 110 scientific papers selected, 50 were considered relevant because of their direct link with urban forestry. From the analysis of this papers, a classification of the articles according to 05 themes was carried out. These are: management of green spaces in urban areas, functions of trees in an urban environment, development of urban forestry, characterization of urban tree flora and financing of urban forestry. Thus, “function of trees in an urban environment and the characterization of urban tree flora” are the most addressed respectively at 42% and 28%. “Financing urban forestry” is practically not addressed (2%). The analysis of the 50 selected articles reveals a significant geographic concentration of urban forestry research. Countries like South Africa, Kenya, and Ghana are more represented in the literature, while vast regions in Central and Western Africa (e.g., Democratic Republic of Congo, Chad, and Niger) have minimal or no documented research on urban forestry. Future research should address these underrepresented themes, as they are crucial for the long-term sustainability of urban forestry projects. Particularly, research on financing mechanisms is essential to unlock sustainable funding sources for urban forestry, a critical barrier to its expansion.

Understanding the dynamics of Organic Carbon mineralization is fundamental in forecasting biosphere to atmosphere Net Carbon Ecosystem Exchange (NEE). With this perspective, we developed 3D-CMCC-PSM, a new version of the hybrid Process Based Model 3D‐CMCC FEM where also heterotrophic respiration (R_h) is explicitly simulated. The aim was to quantify NEE as a forward problem, by subtracting Ecosystem Respiration (R_eco) to Gross Primary Productivity (GPP). To do so, we developed a simplification of the Soil Carbon dynamics routine proposed in DNDC [1]. The method calculates decomposition as a function of soil moisture, temperature, state of the organic compartments, and relative abundance of microbial pools. Given the pulse dynamics of soil respiration, we introduced modifications in some of the principal constitutive relations involved in phenology and littering sub-routines. We quantified the model structure related uncertainty in NEE, by running our training simulations over 1000 random parameter-sets extracted from parameters distributions expected from literature. 3D-CMCC-PSM predictability was tested on independent time series for 6 Fluxnet sites. The model resulted in daily and monthly estimations highly consistent with the observed time series. It showed lower predictability in Mediterranean ecosystems, suggesting that it may need further improvements in addressing evapotranspiration and water dynamics.

Some studies investigated the relationship between frequency domain analysis of heart rate variability and the cognitive performance at the Stroop task. We propose a combined assessment also of trunk mobility in 72 healthy women to investigate the relationship between cognitive, cardiac and motor variables based on a principal component analysis. We also assessed the change on this result after an intervention of two months aiming at improving the perception-action link. At baseline, the PCA correctly identified 3 components: one related to cardiac variables, one to trunk motion and one to the performance of Stroop task. After the intervention, only two components were found with trunk symmetry and range of motion, accuracy and time to complete the Stroop task and low frequency heart rate variability aggregated in a single component by PCA. It suggested that this protocol was effective in investigating the embodied cognition and we defined this approach as “embodimetrics”.

Pandemics, and other risk-related contexts, require dynamic changes in behavior as situations develop. Human behavior is influenced by both explicit (cognitive) and implicit (intuitive) factors. In this study, we used psychological distance as a lens to understand what influences our decision-making with regards to risk in the context of COVID-19. The study was based on the rationale that our relational needs are more concrete to us than the risk of the virus. First, we explored the impact of social-psychological distance on participants’ risk perceptions and behavioral willingness. As hypothesized, we found that close social relationships of agents promoted willingness to engage in risky behavior. In the second phase, we tested an intervention designed to increase the concreteness of information about virus transmission as a mechanism to mitigate the bias of social influence. We found that the concreteness intervention resulted in significantly reduced willingness to engage in risky behavior. As such, communications aimed at changing the behavior of citizens during times of increased risk or danger, should consider conceptually concrete messaging when communicating complex risk, and hence may provide a valuable tool in promoting health-related behavior.

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.

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.

1. Background: The global COVID-19 lockdowns are unique psychological factors, requiring adjustment and coping. This illustrative, South African case study investigated the influence the COVID-19 lockdown context would have on meditation and physical activity. As these were lifestyle patterns the null hypothesis was of no change. 2. Method: The methodology consisted of quantitative and qualitative phases. The quantitative phase was an empirical, case study review of data from the author’s HeartMath and Fitbit electronic devices, as from 9 November 2019 to 31 July 2021. This consisted of coherence and achievement data from the HeartMath Inner Balance application (app), as well as distance and activity data from the Fitbit app. The qualitative phase consisted of the selection and illustration of meditation sessions documented over lockdown. 3. Results: The highly significant increases in physical activity and meditation coherence and achievement collectively indicated significant health promotion over the COVID-19 Lockdown period. Subtle energetic, experiential descriptions of meditation apprehensions resonated and supported these quantitative findings. 4. Conclusions: COVID-19 lockdown has meant transformation, humility, and reordering of priorities. The meditation descriptions amplified information from the HeartMath and Fitbit electronic devices, together co-creating conscious, embodied, relationship science for discussion, instruction, and further research.

In this paper, a seamless connection between sensor technology and machine learning (ML) has been presented which has wide applicability in rehabilitation and physical medicine. The intent is to identify an ML algorithm which has a better performance, easy to deploy, and has less training time and consumes less computational resources. In short, we propose an algorithm which maximizes the synergy between a sensor and ML by maximizing classification performance and easy to do implementation, which is robust in computational power and lower in resource consumption. The premise of the work is to show the important considerations for evaluating ML algorithms for Upper-limb activity recognition for Physical medicine and rehabilitation field.

Improving performance and promoting sustainability in women's handball are key objectives to maximize the potential of female players and ensure the long-term viability of the sport. In this context, training with Olympic movements and their derivatives improves the development of strength, power, and speed, which are determinants of performance in team sports. The aim of this study was to determine if training with Olympic movements produces significant improvements in jumping, throwing, sprinting, and change of direction performance in women handball players. Twenty-one female handball players participated in the study (10 for the control group and 11 for the intervention group). Age ranged from 15 to 17 years. All participants performed four assessment tests (Abalakov Test, throw test, 20-meter Sprint and V-Cut Test) to determine jump height, throwing speed, running speed, and change of direction ability. Measurements were carried out before and after the intervention. For six weeks, the control group performed the strength work established by the club twice a week while the intervention group additionally performed training with Olympic movements. Significant differences (p &lt;0.05) were found between the pre and post measurement of the control group and the intervention group in jump height, throwing speed and running speed, being higher in the intervention group. For the change of direction, no significant differences were found. Between groups, significant differences were observed at the end of the intervention for jump height and running speed. The conclusion of this study was that, by training with Olympic movements, in addition to regular training, could produce greater improvements in jumping performance, throwing speed and running speed in female handball players.

Daily maximum surface air temperature (Tamax) is a crucial factor for understanding complex land surface processes under rapid climate change. Remote detection of Tamax has widely relied on the empirical relationship between air temperature and land surface temperature (LST), a product derived from remote sensing. However, little is known about how such a relationship is affected by the high heterogeneity in landscapes and dynamics in seasonality. This study aims to advance our understanding of the roles of land cover and seasonal variation in the estimation of Tamax using the MODIS (Moderate Resolution Imaging Spectroradiometer) LST product. We developed statistical models to link Tamax and LST in the middle and lower reaches of the Yangtze River in China for five major land-cover types (i.e., forest, shrub, water, impervious surface, cropland, and grassland) and two seasons (i.e., growing season and non-growing season). Results show that the performance of modeling the Tamax-LST relationship was highly dependent on land cover and seasonal variation. Estimating Tamax over grasslands and water bodies achieved superior performance; while uncertainties were high over forested lands that contained extensive heterogeneity in species types, plant structure, and topography. We further found that all the land-cover specific models developed for the plant non-growing season outperformed the corresponding models developed for the growing season. Discrepancies in model performance mainly occurred in the vegetated areas (forest, cropland, and shrub), suggesting an important role of plant phenology in defining the statistical relationship between Tamax and LST. For impervious surfaces, the challenge of capturing the high spatial heterogeneity in urban settings using the low-resolution MODIS data made Tamax estimation a difficult task, which was especially true in the growing season.

At the end of the dry season in early March to early April each year, extensive agricultural biomass waste burnings occur throughout insular mainland Southeast Asia. During this biomass burnings period, smoke aerosols blanket the whole regions and were transported and dispersed by predominant westerly and south westerly winds to southern China, Taiwan and as far southern Japan and the Philippines. The extensive and intense burnings coincided with some wildfires in the forests due to high temperature making the region one of the global hot spots of biomass fires. In this study, we focus on the effect of pollutants emitted from biomass burnings in March 2019 at the height of the burnings period to the exposed population and their health impact. The Weather Research Forecast- Chemistry (WRF-Chem) model was used to predict the PM2.5 concentration over the simulating domain and health impacts are then assessed on the exposed population in the four countries of Southeast Asia, namely Thailand, Laos, Cambodia and Vietnam. Using the health impact based on log-linear concentration response function and Integrated Exposure Response (IER), the results show that at the peak period of the burnings from 13 to 20 March 2019, Thailand experienced the highest impact, with an estimated 2170 premature deaths. Laos, Vietnam, and Cambodia followed, with estimated mortalities of 277, 565, and 314 deaths respectively. However, when considering the impact per head of population, Laos exhibited the highest impact, followed by Thailand, Cambodia, and Vietnam. The results highlight the significant health impact and associated economic cost of agricultural waste burnings in Southeast Asia at the end of the dry season. And hence policy makers should take these into account to design measures to reduce the negative impact of widespread burnings on exposed population in the region.

Succinic semialdehyde dehydrogenase (SSADH) is a mitochondrial enzyme involved in the catabolism of the neurotransmitter γ-amino butyric acid. Pathogenic variants in the gene encoding this enzyme cause SSADH deficiency, a developmental disease manifesting as hypotonia, autism and epilepsy. SSADH deficiency patients usually have family-specific gene variants. Here, we describe a family exhibiting four different SSADH variants, Val90Ala, Cys93Phe, and His180Tyr/Asn255Asp (a double variant). We provide a structural and functional characterization of these variants and show that Cys93Phe and Asn255Asp are pathogenic variants that affect the stability of the SSADH protein. Due to impairment of the cofactor NAD+ binding, these variants show a highly reduced enzyme activity. However, Val90Ala and His180Tyr exhibit normal activity and expression. The His180Tyr/Asn255Asp variant exhibits a highly reduced activity as a recombinant species, is inactive and shows a very low expression in eukaryotic cells. A treatment with substances that support protein folding by either increasing chaperone protein expression or by chemical means was not capable of increasing the expression of the pathogenic variants of the SSADH deficiency patient. However, stabilization of the folding of pathogenic SSADH variants by other substances may provide a treatment option for this disease.

Enhancement of orthodontic tooth movement (OTM) through local administration of biofunctional molecules has become increasingly significant, particularly for adult patients seeking aesthetic and functional improvements. This comprehensive systematic review analyzes the efficacy of various biofunctional molecules in modulating OTM, focusing on the method of administration and its feasibility, especially considering the potential for topical application. A search across multiple databases yielded 36 original articles of experimental human and animal OTM models, which examined biofunctional molecules capable of interfering with the biochemical reactions that cause tooth movement during orthodontic therapy, accelerating the OTM rate through their influence on the bone metabolism (Calcitriol, Prostaglandins, Recombinant human Relaxin, RANKL and RANKL expression plasmid, growth factors, PTH, osteocalcin, vitamin C and E, biocompatible reduced graphene oxide, exogenous thyroxine, sclerostin protein, a specific EP4 agonist (ONO-AE1-329), carrageenan and herbal extracts). The results indicated a variable efficacy in accelerating OTM, with Calcitriol, Prostaglandins (PGE1 and PGE2), RANKL, growth factors and PTH, among others, showing promising outcomes. PGE1, PGE2 and Calcitriol experiments had statistically significant outcomes in both human and animal studies, and, while other molecules underwent only animal testing, they could be validated in the future for human use. Notably, only one of the animal studies explored topical administration, which also suggests a future research direction. This review concluded that while certain biofunctional molecules demonstrated potential for OTM enhancement, the evidence is not definitive. The development of suitable topical formulations for human use could offer a patient-friendly alternative to injections, emphasizing comfort and cost-effectiveness. Future research should focus on overcoming current methodological limitations and advancing translational research to confirm these biomolecules' efficacy and safety in clinical orthodontic practice.

Buttonweed (Cotula coronopifolia) is native to South Africa but invasive in wetlands in Europe, North America, and Australasia, where it excludes native plants. Despite being dry-fruited, field studies suggest migratory waterbirds can disperse its seeds via gut passage (endozoochory), aiding its expansion. To explore the potential for endozoochory in different regions and habitats, we collected seeds from six populations in Spain, Sweden, and the UK. Germination was tested under different salinity levels (0, 5, 10, 15 g/L) and simulated gut passage treatments: scarification, acidification, or both. No germination occurred at 15 g/L. Higher salinity reduced and delayed germination, but full gut passage treatment increased germinability and accelerated germination. Scarification or acid treatment alone resulted in intermediate germination patterns. There were significant salinity x population and gut passage x population interactions on germinability. The acceleration effect of gut passage on germination was stronger at 5-10 g/L than at 0 g/L. This study highlights how migratory birds can facilitate the spread of alien plants introduced by humans. Non-classical endozoochory by waterbirds is an understudied mechanism for the long-distance dispersal of dry-fruited alien plants. Further research on C. coronopifolia, including population genetics, is necessary to understand dispersal mechanisms and facilitate management strategies.

To increase the calculation speed of the computational fluid dynamics (CFD) based simulation for the gas-solid flow in fluidized beds, a Markov chain model (MCM) is developed to simulate the particle movement in a two-dimensional (2D) circulating fluidized bed (CFB) riser. As a statistic model, the MCM takes the CFD-discrete element method (DEM) results as samples to calculate the transition probability matrix of particles, which can describe the macroscopic regularities of the particle movement and guide the numerical simulation of the particle motion based on the Monte Carlo method. The particle distribution snapshots, residence time distribution (RTD) and mixing obtained from both the CFD-DEM and the MCM are compared. Results show that the computational speed of the MCM is faster than that of the CFD-DEM by about 2 orders of magnitude, and the difference of the mean particle residence time calculated by the two models is less than 2%. Besides, the MCM can well describe the time-averaged particle mixing compared to the CFD-DEM.

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

Background: Regular moderate-vigorous intensity exercise is recommended for adults as it can improve longevity and reduce health risks associated with a sedentary lifestyle. However, there are barriers to achieving intense exercise that may be addressed using virtual reality (VR) as a tool to promote exercise intensity and adherence, particularly through visual feedback and competition. The purpose of this work is to compare visual feedback and competition within fully-immersive VR to enhance exercise intensity and user experience of exercise for young adults; and to describe and compare visual attention during each of the conditions. Methods: Young adults (21- 34 years old) bicycled in three 5-minute VR conditions (visual feedback, self-competition and competition against others). Exercise intensity (cycling cadence and % of maximum heart rate) and visual attention (derived from a wearable eye tracking sensor) were measured continuously. User experience was measured by an intrinsic motivation questionnaire, perceived effort and participant preference. A repeated measures ANOVA with paired t-test post-hoc tests was conducted to detect differences between conditions. Results: Participants exercised at a higher intensity and had higher intrinsic motivation in the two competitive conditions compared to visual feedback. Further, participants preferred the competitive conditions and only reached a vigorous exercise intensity during self-competition. Visual exploration was higher in visual feedback compared to self-competition. Conclusion: For young adults bicycling in VR, competition promoted higher exercise intensity and motivation compared to visual feedback.

Research on fall and movement detection with wearable devices has witnessed promising growth. However, there are few publicly available datasets, all recorded with smartphones, that prevent authors to evenly compare their new proposals. Here, we present a dataset of falls and activities of daily living (ADL) acquired with a self-developed device composed of two types of accelerometer and one gyroscope. It consists of 19 ADL and 15 fall types performed by 23 young adults, 15 ADL types performed by 14 healthy and independent participants over 62 years old, and data from one participant of 60 years old that performed all ADL and falls. These activities were selected based on a survey and a literature analysis. We test the dataset with widely used feature extraction and a simple to implement threshold based classification, achieving up to 96~\% of accuracy in fall detection. An individual activity analysis demonstrates that most errors coincide in a few number of activities where algorithms could be focused on. Finally, validation tests with elderly people significantly reduced the fall detection performance of the tested features. This validates findings of other authors and encourages to develop new strategies with this new dataset as benchmark.

Drought negatively affects the growth and development of barley. To explore the genetic variation in barley under drought stress, ten breeding genotypes were tested using polyethylene glycol-6000 to simulate drought conditions. We observed that drought stress adversely affected germination-related traits across all barley genotypes and this impact varied between genotypes, suggesting genotype-specific drought tolerance. The drought tolerance index was an ideal criterion for selecting drought-tolerant genotypes as it well characterized the gradient responses of barely genotypes to drought stress. Based on this indicator, genotype OB1878-ON-50 is recommended as a significant germplasm resource for breeding programs under lower precipitation conditions due to its superior tolerance to drought stress.

(1) Background: Alzheimer’s Disease (AD) accounts for 70% of dementia cases and with no effective pharmacological treatments, new rehabilitation methods are needed. Motor activities and transcranial direct current stimulation (tDCS) have shown promise in stabilizing and enhancing cognitive functions. Objective: We want to investigate the effects of combined motor or cognitive activity with tDCS on cognitive functions in AD patients. (2) Methods: Patients with mild or moderate AD were randomized into four groups: motor activity or cognitive activity associated with anodic or sham tDCS (MotA, MotS, CogA, CogS). They received two weeks of treatment (45 minutes, 5 days/week), with the first 15 minutes using 2mA tDCS on the dorsolateral prefrontal cortex. Cognitive assessments were conducted pre-treatment (T0), post-treatment (T1), and one week after (T2). (3) Results: Twenty patients were included. Mann-Whitney test showed significant improvements in anodic groups (MotA+CogA) in the global cognitive status (p=.042), in selective attention (p=.012), and sustained attention (p=.012) at T1, but not at T2. In addition, MotA improved in the Picture Recognition Test (p=.027) and in sustained attention (p=.047) at T2. (4) Conclusion: Combined motor or cognitive activity with anodic tDCS could slow cognitive decline in AD patients, with notable improvements in global cognitive state and attention at T1.

The Vu Gia - Thu Bon River Basin (VG-TB) is confronting numerous challenges related to water security (WS), particularly in the face of the impacts of climate change. These challenges manifest in salinity intrusion, altered rainfall patterns, and reduced water supply in downstream areas. To assess the current state of water security in the basin, the study employed statistical analysis methods, Process Analysis Method (PAM), SMART, and Analytic Hierarchy Process (AHP) to develop a comprehensive Assessment Framework for Water Security (AFWS) in the VG-TB. The AFWS encompasses five key dimensions, 17 indicators, and 28 variables, aligning with the UN-Water definition of water security and addressing the Sustainable Development Goal 6 (SDG6) criteria for global water sustainability. It also adheres to the Asian Development Bank's (ADB) approach to water security assessment as outlined in the Asian Water Development Outlook (AWDO) reports. This allows for the computation of a comprehensive Water Security Index (WSI) for specific regions, serving as a foundation for decision-making and policy formulation aimed at enhancing water security in the context of climate change and facilitating sustainable basin development in the future.

The agronomic characteristics of Cenchrus purpureus were assessed through a randomized block experimental design with seven accessions (Taiwan grass, King grass, Elephant grass, Merkeron, CT-115, Purpule grass and Maralfalfa) as treatments and four replications research was carried out at the Instituto Tecnológico Superior de Tantoyuca, in 2019 and 2020, under rainfed conditions. Sowing density was established at 36 tillers in 25 m2. Green and dry matter yield, daily rates of dry matter accumulation in leaves, leaf/stem ratio, height, leaf area index and cutting frequency were assessed. Rainfall amount, temperature, relative humidity and global radiation levels were recorded to assess their effect on the evaluated variables. One-way ANOVA and multivariate analysis techniques, such as multiple linear regression (MLR), Clustering, and Principal component analysis (PCA) with the Statistica V7 software, were used. The leaf area index was greatest (p &lt; 0.05) on the dry season. Green and dry matter yield were greatest in Maralfalfa (p &lt; 0.05). Variation in the results is attributed to weather phenomena; nonetheless, Elephant grass and Maralfalfa showed the highest yields. Quality parameters must be evaluated to identify those grasses with the best attributes.

This study presents PlanteSaine, a novel mobile application powered by Artificial Intelligence (AI) models explicitly designed for maize, tomato, and onion farmers in Burkina Faso. Agriculture in Burkina Faso, like many developing nations, faces substantial challenges from plant pests and diseases, posing threats to both food security and economic stability. PlanteSaine addresses these challenges by offering a comprehensive solution that provides farmers with real-time identification of pests and diseases. Farmers capture images of affected plants with their smartphones, and PlanteSaine's AI system analyzes these images to provide accurate diagnoses. The application's offline functionality ensures accessibility even in remote areas with limited internet connectivity, while its messaging feature facilitates communication with agricultural authorities for guidance and support. Additionally, PlanteSaine includes an emergency alert mechanism to notify farmers about pest and disease outbreaks, enhancing their preparedness to deal with these threats. An AI-driven framework, featuring an image feature extraction phase with EfficientNetB3 and an artificial neural network (ANN) classifier, was developed and integrated into PlanteSaine. The evaluation of PlanteSaine demonstrates its superior performance compared to baseline models, showcasing its effectiveness in accurately detecting diseases and pests across maize, tomato, and onion crops. Overall, this study highlights the potential of PlanteSaine to revolutionize agricultural technology in Burkina Faso and beyond. Leveraging AI and mobile computing, PlanteSaine provides farmers with accessible and reliable pest and disease management tools, ultimately contributing to sustainable farming practices and enhancing food security. The success of PlanteSaine underscores the importance of interdisciplinary approaches in addressing pressing challenges in global agriculture

The progress in markerless technologies is bringing clinicians tools to rapidly evaluate tests such as Timed Up and Go (TUG) without compromising the time of the assessment, yet it raises questions about the potential trade-off in accuracy compared to traditional marker-based systems, suggesting that the precision of these evaluations is not yet conclusively established. The OpenCap system is an easy tool to process 3D kinematics with two iPhone cameras placed in front of the subject. Previous research has primarily focused on walking and movement towards the cameras with the subject facing the cameras (WF) and thus has been unable to disentangle the differences in the movement directions. We have compared the OpenCap system with a standard marker-based system for both walking directions. In OpenCap, we found significantly worse results capturing walking facing away from the cameras (RW). Compared to the marker-based system, our findings indicate troubles measuring kinematic parameters but provide good accuracy in measuring spatial-temporal parameters. These insights pave the way for refining markerless assessment technologies, potentially enhancing their utility in clinical settings.

Asymmetry plays a major role in biology at all scales. This can be seen examining the helix of DNA, the fact that the human heart is on the left side, or that most people use their right hand. A single protein such as Myosin 1D can induce helical motion in another molecule. This causes cells, organs, and even entire bodies to twist in a domino effect, causing left-right behaviour. More in general, athlete movements are often asymmetric and, during the physical rehabilita-tion after injury the asymmetry is visually discernible. Herein we review the molecular basis of movement asymmetries and report on the available knowledge on the few therapeutics inves-tigated so far such as meloxicam. From a more rehabilitative perspective, it is very important to use effective methods to control the process of resolving the injury-related movement asym-metry through the complex use of specialized exercises, measurements and gait analysis which all can provide useful information on the effectiveness of rehabilitation plans. If for each athlete the normal range of asymmetry is known, the asymmetry can be treated individually and the evolution can be monitored over time. Appropriate measures should be taken if the movement asymmetry is outside this range. In addition, genetic, physiological, and psychological factors relevant to athlete health should be considered in the process of assessing and improving exer-cise asymmetry as we also discuss in this review. The main proposal of this work is that move-ment asymmetries in athletes should be treated individually, taking into account the athlete’s genetics, physical condition, and previous injuries.

The definition of UTC in 1972 balanced the needs of the time and frequency community for a universal time scale that was traceable to the definition of frequency in the SI system of units with the needs of the astronomical community for a time scale that was closely linked to UT1, a time scale related to the rotation of Earth. The balance between these two considerations has changed very significantly since 1972, and there is widespread agreement that the method of relating UTC to UT1 should be changed by increasing the maximum tolerance between the two scales to more than the current limit of 0.9 s. I propose to realize this decision by means of an algorithmic adjustment process based on the variation in the length of the day over the previous centuries. I use these historical data to extrapolate the length of the day for a century into the future, and to compute a periodic rate adjustment to UTC based on this extrapolation. The adjustment process will not use time steps. The magnitude of the periodic rate adjustment will be re-considered every century, but the basic adjustment algorithm will not change. I suggest a maximum tolerance between UT1 and UTC that is large enough to absorb the irregular and unpredictable variations in the length of the day with respect to the long-term average increase in this value but plays no role in determining the parameters of the adjustment process that is proposed. I also propose that the adjustment be implemented at 12 UTC on 1 January since that is closest to a universal holiday in all time zones.

This paper, from the perspective of Mode 3 of knowledge production, takes the important carrier of knowledge, scientific research papers, as the research object. The mainstream databases (SCIE and SSCI) are chosen as the data sources. Firstly, bibliometric methods are applied to analyze the cooperation status among the main bodies of paper production, including authors and their affiliated institutions, countries, and disciplines; secondly, the Analytic Hierarchy Process (AHP) is used to construct a comprehensive evaluation model for the state of research cooperation in carbon neutrality. Based on the evaluation model, the cooperation characteristics of different disciplinary fields and the relationship between paper cooperation status and high-impact research papers are comparatively analyzed. At the same time, an analysis is conducted on the support from the government, the sponsorship from enterprises, and the participation of the public in the process of paper production. Finally, some suggestions are put forward on how to build an innovative ecosystem for carbon neutrality research from the perspective of Mode 3 of knowledge production.

The prevention, mitigation and treatment of movement impairments, ideally, requires early diagnosis or identification. As the human movement system has physiological and functional redundancy, movement limitations do not promptly arise at the onset of physical decline. A such, prediction of movement limitations is complex: it is unclear how much decline can be tolerated before movement limitations start. Currently, the term ‘homeostatic reserve’ or ‘physiological reserve’ is used to refer to the redundancy of the human biological system, but these terms do not describe the redundancy in the muscle architecture of the human body. The result of functional redundancy is compensation. Although compensation is an early predictor of movement limitations, clear definitions are lacking and the topic is underexposed in literature. The aim of this article is to provide a definition of compensation and emphasize its importance. Compensation is defined as an alteration in the movement trajectory and/or altering muscle recruitment to complete a movement task. Compensation for capacity is the result of a lack in neuromusculoskeletal reserve, where reserve is defined as the difference between the capacity (physiological abilities of the neuromusculoskeletal system) and the task demand. Compensation for movement objectives is a result of a shift in weighting of movement objectives, reflecting changing priorities. Studying compensation in biomechanics requires altered protocols in experimental set-ups, musculoskeletal models that are not reliant on prescribed movement, and inclusion of alternative movement objectives in optimal control theory.

Panel data of our interest consist of a moderate number of panels, while the panels contain a small number of observations. An estimator of common breaks in panel means without a boundary issue for this kind of scenario is proposed. In particular, the novel estimator is able to detect a common break point even when the change happens immediately after the first time point or just before the last observation period. Another advantage of the elaborated change point estimator is that it results in the last observation in situations with no structural breaks. The consistency of the change point estimator in panel data is established. The results are illustrated through a simulation study. As a by-product of the developed estimation technique, a theoretical utilization for correlation structure estimation, hypothesis testing, and bootstrapping in panel data is demonstrated. A practical application to non-life insurance is presented as well.

In healthy ageing, capacity declines in the neural, muscular, and skeletal systems, and each system decline has its effect on the execution of complex motor tasks. This decline in capacity can result in the inability to stand up (sit-to-stand, sit-to-walk), which is a key movement for independence. The mechanisms leading to mobility limitations or inabilities are complex, overlapping, and interdependent and the complementary fields of biomechanics, motor control, and physiology need to be combined to understand these mechanisms. The aim of this review is to provide an overview of the current knowledge of age-related compensation in standing up and to consider the limitations of these results when analysing standing up in daily life using the Capacity, Reserve, Movement Objectives, and Compensation (CaReMoOC) framework that combines biomechanics, motor control, and physiology. A literature search was performed in the search engine Scopus, using the keywords and their synonyms: strateg*(approach, technique, way) AND, sit-to-walk OR sit-to-stand OR rise (raise, arise, stand, stand-up) AND chair (seat). Inclusion criteria were: biomechanics or motor control on sit-to-stand or sit-to-walk in healthy and/or frail adults (<60y) and elderly (>60y), and/or osteoarthritis patients as a specific case of ageing related decline. The review shows that movement compensations in standing up manifest as changes in planned trajectory (Compensation by Selection) and in muscle recruitment (Compensation by Reorganisation). However, as most studies in the literature typically use standardized experimental protocols where movement compensation is restricted, these studies cannot be directly translated to functional tasks, such as the mobility of the elderly in their homes, communities, and clinic. Compensation must be included in future studies in order to facilitate clinical translation. Specifically, future studies in the standing up task should 1) determine the effect of varying arm use strategies (e.g., armrests, knees, chair, cane) on trunk and both lower limb and upper limb joint loading, 2) analyse control strategies in elderly people, 3) determine the biomechanical implications of asymmetry, and 4) incorporate assessments of age-related physical and neural decline as well as changes in psychological priorities.

This bibliographic study addresses key aspects related to fishing, product safety, and climate change in the Adriatic Sea region. The examination of product safety focuses on the assessment of contaminants originating from human activities such as industry, mining, agriculture, and household waste disposal. The contamination of the aquatic environment has emerged as a pressing global concern, extending to the Adriatic subbasin. Aquatic organisms, including fish, are prone to accumulating pollutants directly from polluted water sources and indirectly through the food web. The bio-accumulation of potentially hazardous substances, particularly heavy metals, pesticides, PCBs, PAHs, and antibiotic resistance in aquatic organisms, poses a significant threat to human health. Climate change effects will deplete our seafood supply in terms of quantity and safety owing to negative consequences such as higher levels of pollution, parasites, viruses, infections, acidification, and toxicities such as shellfish poisoning. Global food safety strategies should be developed to reduce greenhouse gas emissions and promote environmentally friendly technology, which indirectly affects seafood quality and microbiological safety, especially for Adriatic Sea, which is part of the Mediterranean Sea, characterized by the most polluted waters in the world.

Drug-induced movement disorders (DIMDs) are a group of neurological conditions caused by the use of certain medications. These disorders can significantly impact a person's quality of life and are essential to recognize and manage. This article provides an overview of the causes, symptoms, and treatment of DIMDs. DIMDs can manifest in various forms, including parkinsonism, tardive dyskinesia, dystonia, and akathisia. They are most commonly associated with medications such as neuroleptics, antidepressants, antipsychotics, antiemetics, and anticonvulsants. Risk factors for developing DIMDs include age, genetics, duration of medication use, and dose of medication. Symptoms of DIMDs can range from mild to severe and may include tremors, rigidity, bradykinesia, and involuntary movements. These symptoms can significantly impact a person's ability to perform daily activities and lead to social isolation and decreased quality of life. DIMD diagnoses are based on clinical evaluation, including a thorough medical history and physical examination. Imaging studies such as MRI or CT scans may also be used to rule out other possible causes of symptoms. Treatment of DIMDs involves the withdrawal of the offending medication if possible. Pharmacological treatments such as anticholinergic drugs, benzodiazepines, and dopamine agonists may also be used to manage symptoms. Non-pharmacological treatments such as physical, occupational, and speech therapy can also be beneficial. DIMDs are necessary neurological conditions that can significantly impact a person's quality of life. Early recognition and management of these disorders are essential for optimizing outcomes. Further research is needed to understand the underlying mechanisms of DIMDs better and to develop more effective treatments.

Inflation and exchange rates have great influence on consumer prices especially on imports and exports. Exchange rate fluctuations create inefficiency and distort world prices whereas changes in inflation rates have a direct impact on consumer goods prices which incidentally include exchange rates. There is a direct interdependence between inflation and exchange rates and this paper is aimed at investigating this relationship in dynamic context. It tries to find out how changes in inflation and exchange rates impact on another by adopting the econometric and copula approaches. Both inflation and exchange rates data are susceptible to volatility clustering, possess fat tails and are skewed coupled with conditional heteroskedasticity. Hence we model the univariate distributions by using ARMA$(p,q)$-GARCH$(x,y)$ so as to capture the most important stylized features of inflation and exchange rates. A bivariate model is then constructed by coupling the marginal distributions of inflation and exchange rates using the survival Clayton copula. Empirical results from monthly inflation and exchange rates data show positive correlation between the two based on Kendall $\tau$ test which confirms that a change in inflation results in change of exchange rates an vice versa hence there is co-movement. Furthermore, by the Granger causality test, exchange rates spikes cause changes in inflation rates. The results of the study have implications on economic policy design and hedging strategies for traders on imports and exports.

The planar cell polarity (PCP) of epithelial ciliated cells is essential for effective mucociliary clearance (MCC) in the sinonasal mucosa. We hypothesize that MCC coordination is impaired in nasal polyp (NP) mucosae due to suppressed expression of a series of CPLANE (ciliogenesis and planar cell polarity effector) complex proteins in chronic rhinosinusitis (CRS) patients. To inves-tigate this hypothesis, we subjected sinonasal mucosal samples to live video recording to measure mucociliary transport velocity (MCTV) and scanning electron microscopy to evaluate surface morphology. The expression and distribution of a panel of PCP proteins, e.g. WDPCP and FUZ, were investigated in relation to inflammatory cytokine levels and clinical features. The mean MCTV of NP mucosae was significantly lower than that of the inferior turbinate mucosae. The CRS group with NPs (CRSwNP group) (n=28) showed increased expression of IL-13 and CCL26 mRNA compared to CRS patients without NPs (n=25) and controls (n=30). WDPCP and FUZ mRNA levels were significantly decreased in NP mucosae compared to ethmoid sinus mucosae in CRSwNP patients. WDPCP protein distribution was reduced in the cytoplasmic region of ciliated cells in CRSwNP patients. We conclude that suppression of WDPCP in ciliated cells is responsible for the impaired MCC of nasal polyps with type-2 inflammation. This mechanism might explain the decreased clearance and the potential for worsening symptoms of CRSwNP.

Subnational governments play a key role responding to climate change risks in terms of policy strategies and instruments. This article analyzes how Brazilian municipal and state governments have developed and implemented public policies to mitigate and to adapt to climate change risks. We surveyed all cities’ and states’ climate policies within the country. The methodological approach includes five main points of analysis: 1. mitigation targets and intentions; 2. adaptation actions; 3. stakeholders’ participation; 4. policy implementation; 5. participation in networks related to climate change. Our results suggest that even though subnational climate policies in Brazil are isolated initiatives within the national context, they play an important role responding to climate change risks in different scales and levels. The strongest Brazilian policies with both mitigation and adaptation actions counted on previous mobilization for the climate issue involving different stakeholders from several segments of the society. These governments have also participated in transnational cooperation networks related to climate change.

The recent mountain pine beetle outbreaks have caused widespread mortality among lodgepole pine trees in western North America, resulting in a reduced population of surviving trees. While previous studies have focused on the cascading impacts of these outbreaks on the physiology and growth of the surviving trees, there remains a need for a comprehensive study into the interactions among various physiological traits and the growth in post-outbreak stands. Specifically, the relationship between chemical (primarily terpenes) and anatomical (mainly resin ducts) defences, as well as the allocation of non-structural carbohydrates (NSCs) to support these defence modalities, is poorly understood. To address these gaps, we conducted a field survey of surviving lodgepole pine trees in post-mountain pine beetle outbreak stands in western Canada. Our retrospective analysis targeted to determine correlations between the post-outbreak concentrations of monoterpenes, diterpenes, and NSCs in the phloem, and the historical resin duct characteristics and growth traits before and after the outbreak. We detected strong correlations between post-outbreak concentrations of monoterpenes and historical resin duct characteristics, suggesting a possible link between these two defence modalities. Additionally, we found a positive relationship between NSCs and the total concentrations of monoterpenes and diterpenes, suggesting that NSCs likely influence the production of these terpenes in lodgepole pine. Furthermore, historical tree growth patterns showed strong positive correlations with many individual monoterpenes and diterpenes. Interestingly, while surviving trees had enhanced anatomical defences after the outbreak, their growth patterns did not vary before and after the outbreak conditions. The complexity of these relationships emphasizes the dynamics of post-outbreak stand dynamics and resource allocation in lodgepole pine forests, highlighting the need for further research. These findings contribute to a broader understanding of conifer defenses and their coordinated responses to forest insect outbreaks, with implications for forest management and conservation strategies.

Museums are called to respond to contemporary challenges and contribute to the formation of more progressive societies. One of the major challenges of our time is climate change and museums could construct cocreated narratives around climate and implement targeted actions for the audiences through their sensorial and affective experiences. More specifically, Geology and Palaeontology museums are repositories of knowledge on geoheritage and geoconservation, recognized for their scientific, pedagogical, cultural and recreational values. The educational potential of geological and paleontological exhibits could be used in informal education activities regarding the climate emergency. Taking the above into consideration, this study focuses on both the creation and evaluation of an educational program for the Natural History Museum of Arsakeio Campus at Psychicko.

To evaluate the used and End-of-Life tyre management chains, both direct observation and interviews with approximately 200 used-tyre dealers were conducted. The study revealed that while the used tyre business is well-organized, End-of-Life tyre treatment is nearly non-existent, often involving dumping, open burning for metal recovery, or use in meat processing, causing environmental and health risks. To address these challenges, an 8 t/hr capacity tyre recycling plant is planned, based on estimated tyre availability and development opportunities for sustainable recycling in Togo.

This study explores the application of the Laban/Bartenieff Movement System (® LBMS), particularly its Effort component, to analyze the biomechanical dynamics of the golf swing. Focusing on the initiation of the downswing, this paper investigates how the instantaneous screw axis (ISA) with rotational and linear motions contributes to subsequent movements, such as the hip turn. We propose that the physical forces generated by the golf club, characterized by mass moment inertia, extend beyond the body's boundaries, such as through the hand grip. A skilled golfer’s ability to 'allow' these forces to influence body dynamics without opposing them is analyzed through the lens of LBMS's Free Flow Effort, suggesting an indulgent and expansive use of movement energy.

The enterprise software sector is experiencing a significant transformation driven by rapid technological progress and evolving business needs. An effective release management process is crucial for the solution providers and customers, as they incorporate the principles of Industry 4.0 and 5.0. With the growing dependence on software solutions and services, ensuring their quality, reliability, and security is highly necessary. The release management process incorporates strategic planning, regression testing, accurate deployment, and continuous monitoring of software updates. However, the rapid advancements in artificial intelligence (AI) and machine learning (ML) create a unique challenge to the release management process. The existing research needs to address the necessary adaptations for Industry 5.0, mainly in product-based software organizations, to the release management process without a change management system. After working with several software solution stakeholders, based on the responses from SaaS project stakeholders, we have presented a revised software release readiness workflow by incorporating a change management module. The preliminary result based on data over a limited period of time indicates that the revised workflow has the potential to improve the management of slippage, particularly by more effectively addressing NFR-related issues, thereby resulting in more predictable and reliable release cycles.

In this proposed work, five systems were developed to classify four motor functions—forward hand movement (FW), grasp (GP), release (RL), and reverse hand movement (RV)—from EEG signals. The dataset used is WAY-EEG-GAL, involving participants performing a sequence of hand movements. During preprocessing, bandpass filtering was applied to remove artifacts and focus on the mu and beta frequency bands. The first system, a preliminary study model, explored the overall framework of EEG signal processing and classification. It utilized time-domain features like variance and frequency-domain features like alpha and beta power, with classification performed using a KNN model. Insights from this system informed the development of a baseline system, which uses the same dataset but different feature extraction and classification paradigms. This baseline system combined the common spatial patterns (CSP) method with continuous wavelet transform (CWT) for feature extraction and employed a GoogLeNet classifier with transfer learning. Classification was performed on six unique pairs of events derived from the four motor functions, using both intrasubject and intersubject methods. The baseline system achieved the highest accuracy of 99.73% for the GP-RV pair and the lowest accuracy of 80.87% for the FW-GP pair in intersubject classification. Building on this, three additional systems were developed to perform 4-way classification. Among these, the final model, ML-CSP-OVR, achieved the highest intersubject classification accuracy of 78.08% using all combined data and 76.39% for leave-one-out intersubject classification. This proposed model, which features a novel combination of CSP-OVR, CWT, and GoogLeNet, demonstrates strong potential as a general system for motor imagery (MI) tasks without being subject-dependent.

In Africa, the urban population and informal settlements are increasing, resulting in additional public health and environmental risks and challenges related to the need of basic and sustainable infrastructures and services. In Maputo, the capital of Mozambique, at least 80% of the city is composed of informal settlements, and although some areas are regularized and have approved urbanization plans, the municipality has major deficiencies in meeting current demands in terms of basic infrastructures, such as water supply, sewerage, solid wastes, energy, roads and communications. Most of the peri-urban areas is occupied with small but overcrowding houses, mostly self-built, served by unpaved roads, and with access limitations. The water network is almost non-existent, and the same occurs for stormwater drainage, sanitation, waste collection and public illumination. Despite the improvements made in the last few years, some households still do not have safe sanitation, and in some neighborhoods, open defecation still prevails. In this study, the authors try to understand and explore the interdependences among the infrastructures of the different sectors and how they may jointly contribute for adequate services and a better life of the urban poor, and how to identify the combination of infrastructures to be implemented at short term in face of the limited budgets for investments.

Introduction: Subtalar Arthroereisis (STA) is a surgical intervention for pediatric flexible flatfoot (PFF), primarily targeting hindfoot alignment by limiting excessive subtalar eversion. However, its effects on forefoot parameters remain underexplored. This study aims to investigate radiological changes following STA in pediatric patients. Materials and Methods: A retrospective analysis was conducted on consecutive patients treated with STA for PFF. First ray-related angles, including Hallux Valgus Angle (HVA) and Inter-Metatarsal Angle (IMA), alongside hindfoot radiological parameters such as Meary, Calcaneal Pitch, and Costa Bartani angles, were assessed. Subgroup analysis by gender was performed, and correlations between demographic and pre-operative radiological parameters were examined. Results: Forty-one patients (81 feet) with a mean age of 11.6 years were included, with a mean follow-up duration of 6.4 months. No significant differences were observed in first ray-related an-gles pre- and post-operatively, with mean IMA changing from 7.97° to 7.18° and mean HV angles from 9.51° to 8.66°. Noteworthy improvements were seen in flat foot angles, including Meary, Calcaneal Pitch, and Costa Bartani angles, postoperatively. Age subgroup analysis revealed similar trends in IMA and HVA changes between Group A (operated before peak growth) and Group B (operated later). Higher preoperative angles tended to improve, while lower preoperative IMA and HVA tended to worsen postoperatively, all remaining within normal ranges. Conclusion: STA showed positive radiological outcomes for PFF treatment, while negligible changes in first ray-related angles were observed. Age subgroup analysis indicated similar trends regardless of operation timing. Higher preoperative angles tended to improve, while lower preoperative angles tended to worsen postoperatively, despite all falling within non-pathological ranges. Further re-search is warranted to confirm this correlation.

The importance of sleep for healthy brain function is widely acknowledged. However, it remains unclear how the internal generation of dreams might facilitate cognitive processes. In this perspective we review a computational approach inspired by artificial intelligence that proposes a framework for how dreams occurring during rapid-eye-movement (REM) sleep can contribute to learning and creativity. In this framework, REM dreams are characterized by an adversarial process that, against the dream reality, tell a discriminator network to classify the internally created sensory activity as real. Such an adversarial dreaming process is shown to facilitate the emergence of real-world semantic representations in higher cortical areas. We further discuss the potential contributions of adversarial dreaming beyond learning, such as balancing fantastic and realistic dream elements, and facilitating the occurrence of creative insights. We characterize non-REM (NREM) dreams, where a single hippocampal memory is replayed at a time, as serving a complementary role of improving the robustness of cortical representations to environmental perturbations. We finally explain how subjects can become aware of the adversarial REM dreams, but less of the NREM dreams, and how the awareness phenomenon of wake, dream and lucid dreaming may appear.

Movement disorders encompass a diverse group of neurological conditions characterized by abnormal voluntary or involuntary movements. These disorders can be classified broadly into hyperkinetic and hypokinetic disorders. Excessive, involuntary movements, including tremors, dystonia, chorea, and myoclonus characterize hyperkinetic disorders. Tremors are rhythmic, involuntary movements occurring at rest or during movement. Dystonia involves sustained muscle contractions, leading to twisting and repetitive movements or abnormal postures. Chorea manifests as brief, irregular, involuntary movements that flow from one body part to another. Myoclonus consists of sudden, brief muscle contractions, either spontaneous or in response to a stimulus. Hypokinetic disorders are characterized by a lack of movement or difficulty initiating movement, as seen in Parkinson's disease and Parkinsonism. Parkinson's disease is a progressive neurological disorder that primarily affects movement, causing tremors, stiffness, and difficulty with balance and coordination. Parkinsonism refers to a group of disorders with similar symptoms to Parkinson's disease but with different underlying causes. Diagnosing movement disorders involves a thorough clinical evaluation, including a detailed medical history and physical examination. Neuroimaging studies such as MRI, CT scans, and functional imaging techniques may be used to assess brain structure and function. Additionally, laboratory tests, including genetic testing and biochemical markers, can help diagnose certain movement disorders.

Smartwatches provide technology-based assessments in Parkinson’s disease (PD). We present results for sensor validation and disease classification via Machine Learning (ML). A comparison setup was designed with two different series of Apple smartwatches, one Nanometrics seismometer and a high-precision shaker to measure tremor-like amplitudes and frequencies. Clinical smartwatch measurements were acquired from a prospective study including 450 participants with PD, differential diagnoses (DD) and healthy participants. All participants wore two smartwatches and within a 15-min examination. Symptoms and medical history were captured on the paired smartphone. A broad range of different ML classifiers were cross-validated. Amplitude and frequency differences between smartwatches and the seismometer were under the level of clinical significance. The most advanced task of distinguishing PD vs DD was evaluated with 74,1% balanced accuracy, 86,5% precision and 90,5% recall by Multilayer Perceptrons. Deep Learning architectures significantly underperformed in all classification tasks. Smartwatches are capable of capturing subtle-tremor signs with low noise. This study provided the largest PD sample size of two-hand smartwatch measurements and our preliminary ML-evaluation shows that such a system provides powerful means for diagnosis classification and new digital biomarkers but it remains challenging for distinguishing similar disorders.

In this study the effects of three different main preparatory tillage operations [ploughing at 0.4 m (P40) and 0.20 m (P20) depth and minimum tillage at 0.20 m depth (MT) each of them carried out at two different soil water contents (WC) [low, 58% (LH) and high, 80% (HH) of field capacity] were investigated. The results obtained in this research show high values of soil strength in term of Penetration resistance (CI) and shear strength (SS) particularly in deeper soil layers at lower water content. Fossil-fuel energy requirements both for P40 LH and P20 LH were 25 and 35% higher with respect to the HH treatments and tractor slip were very high (P40 LH = 32.4%) with respect to the P40 HH treatment (16%). Therefore soil water content had significantly influenced tractor performance during soil ploughing, particularly at 0.40 m depth while MT was not influenced at all. A significant correlation between grain yield and soil penetration resistance was found highlighting how soil strength may be good indicator of its productivity. Obtained results during these field tests allowed considering MT and P20 treatments more suitable for this type of soil in climate change scenarios.

Secondary movement disorders (SMDs) represent a heterogeneous group of neurological conditions characterized by abnormal, involuntary movements resulting from various underlying causes. This comprehensive review aims to thoroughly understand SMDs, including their epidemiology, pathophysiology, clinical manifestations, diagnostic approach, and management strategies. SMDs encompass a spectrum of movement abnormalities, including dystonia, chorea, athetosis, myoclonus, tics, and tremors. They can arise from a multitude of etiologies, such as drug-induced effects, post-infectious processes, metabolic disturbances, and structural brain lesions. The epidemiology of SMDs varies depending on the underlying cause, with some conditions being more prevalent in specific populations or age groups. Understanding the pathophysiology of SMDs is crucial for accurate diagnosis and targeted management. Diagnosing SMDs requires a comprehensive approach, including a detailed history, physical examination, laboratory investigations, neuroimaging studies, and sometimes electrophysiological studies. Management of SMDs is multifaceted and may involve pharmacological, non-pharmacological, and surgical interventions. Individualized treatment plans are essential, considering the underlying cause, severity of symptoms, and patient preferences. Emerging concepts in the field of SMDs include advancements in genetic research, identification of biomarkers, and development of novel therapeutic approaches. There is a growing focus on patient-centered care and improving the quality of life for individuals with SMDs. In conclusion, SMDs pose diagnostic and therapeutic challenges, requiring a multidisciplinary approach for optimal management. Continued research and collaboration are essential for advancing our understanding and treatment of these complex disorders.

The genetic development of commercial broiler led to body misconfiguration and consequent walking disabilities, mainly at the slaughter age. The present study aimed to identify broiler locomotion ability using image analysis automatically. A total of 40 broiler 40 d-old were placed to walk on a specially built runway, and their locomotion was recorded. An image segmentation algorithm was developed, and the coordinates of the bird's center of mass were extracted from the segmented images for each frame analyzed, and the Unrest Index (UI) was applied. We calculated the center of mass's movement of the broiler walking's lateral images, therefore, capturing the bird's displacement speed in the onward direction. Results indicated that broiler speed on the runway tends to decrease with the increase of the gait score. The locomotion did not differ between males or females. The proposed algorithm was efficient if predicting the broiler gait score based on their displacement speed.

Classification of electromyographic signals has a wide range of applications, from clinical diagnosis of different muscular diseases to biomedical engineering, where their use as input control of prosthetic devices has become a hot topic of research. Challenge of classifying this signals relies on the accuracy of the proposed algorithm and the possibility of its implementation on hardware. This paper consider the problem of electromyography signal classification, solved with the proposed signal processing and feature extraction stages, with focus lying on the signal model and time domain characteristics for better classification accuracy. The proposal considers a simple preprocessing technique that produces signals suitable for feature extraction, and the Burg reflection coefficients to form learning and classification patterns. These coefficients yield a competitive classification rate compared to used time domain features. Sometimes, the feature extraction from electromyographic signals showed that procedure can omit less useful traits for machine learning models. Using feature selection algorithms provides a higher classification performance with as fewer traits as possible. Algorithms achieved a high classification rate up to 100% with low pattern dimensionality, with other kinds of uncorrelated attributes for hand movement identification.

As the global population ages, the prevalence of neurodegenerative diseases has become a major public health concern. The adoption of a less sedentary lifestyle has been shown to have a beneficial effect on cognitive decline, but the molecular mechanisms responsible are less clear. Here we provide a detailed analysis of the complex molecular, cellular, and systemic mechanisms underlying age-related cognitive decline and how lifestyle choices influence these processes. A review of the evidence from animal models, human studies, and postmortem analyses emphasizes the importance of integrating physical exercise with cognitive, multisensory, and motor stimulation as part of a multifaceted approach to mitigating cognitive decline. We highlight the potential of these non-pharmacological interventions to address key aging hallmarks—such as genomic instability, telomere attrition, and neuroinflammation—and underscore the need for comprehensive and personalized strategies to promote cognitive resilience and healthy aging.

This study explores the application of the Laban/Bartenieff Movement System (® LBMS), particularly its Effort component, to analyze the biomechanical dynamics of the golf swing. Focusing on the initiation of the downswing, this paper investigates how the instantaneous screw axis (ISA) with rotational and linear motions contributes to subsequent movements, such as the hip turn. We propose that the physical forces generated by the golf club, characterized by mass moment inertia, extend beyond the body's boundaries, such as through the hand grip. A skilled golfer’s ability to 'allow' these forces to influence body dynamics without opposing them is analyzed through the lens of LBMS's Free Flow Effort, suggesting an indulgent and expansive use of movement energy.

Nowadays, the growing concern about improving thermal comfort in textiles, asphalt pavements and buildings has stimulated research into phase change materials (PCMs). However, the incorporation of PCMs directly causes mechanical impacts. Therefore, this study herein reported focuses on designing coaxial phase change fibres using commercial cellulose acetate (CA) or recycled CA obtained from cotton fabrics (CAt) as a coating and polyethylene glycol (PEG) 2000 as a core. The phase change fibres (PCF) were produced by wet spinning, varying the parameters: (i) CA concentration, molecular weight and source (virgin versus recycled); and (ii) PEG concentration and ejection. For phase change recycled fibres (PCFt), PEG concentration and ejection were varied. The fibres were assessed for their optical, chemical, thermal and mechanical properties. Bright-field microscopy images and Scanning Electron Microscopy (SEM) micrographs proved the coaxial structure. Fourier Transform Infrared spectroscopy (FTIR) confirmed the presence of PEG in the core. Thermogravimetric Analysis (TGA) proved the ability of PCFs to tolerate high temperatures. Differential Scanning Calorimetry (DSC) attested to the presence of PEG2000 peaks, since their melting points were close to those of virgin PEG2000, with a slight change in the PCFs and PCFts caused by the protective sheath of CA and CAt.

Climate change has altered the frequency and severity of extreme weather, which can affect vegetation condition and habitat quality for wildlife. Declines in vegetation productivity during droughts and heatwaves can negatively impact animals that depend on vegetation for water and nutrition. The ability to detect such effects on habitat suitability can reveal refugia, which can be prioritised for protection to improve threatened species conservation. We used the normalised difference vegetation index (NDVI) to look at relationships between vegetation productivity and the presence of koalas (Phascolarctos cinereus) in potential habitat throughout much of their range. Using a large, long-term koala presence dataset, we tested the hypothesis that locations where koalas had been observed would exhibit higher NDVI values than a random, representative sample from the same vegetation group (i.e. woodlands, open forests or tall open forests). We also identified the minimum NDVI threshold at which koalas occurred across time for each vegetation group and compared these to the minimum NDVI values observed across potential koala habitat before and during the millennium drought; one of the worst recorded in Australia. Additionally, we investigated whether vegetation above the minimum NDVI thresholds was significantly closer to perennial water than unsuitable vegetation. We found that koalas tend to occur at locations exhibiting higher NDVI than average for all vegetation groups. We also found that 49% of all vegetation groups maintained a minimum NDVI above the koalas’ NDVI threshold before drought, equating to 190,227 km2, which declined to 166,746 km2 during drought (a 12% reduction). We also found that unsuitable vegetation tended to occur farther from perennial water than suitable vegetation for some vegetation groups. Areas that remained above the NDVI thresholds during the drought should be considered potential refugia for populations during an event of similar magnitude and could indicate future core habitat extent.

Currently, one of the main challenges is the mitigation of the effects of climate change on the agricultural sector. Conventional agriculture, with the intensive use of herbicides and pesticides to control weeds and pests, and the improper use of mineral fertilizers, contributes to climate change by causing increased greenhouse gases and groundwater pollution. Therefore, more innovative technologies must be used to overcome these problems. One possible solution is nanotechnology, which has the potential to revolutionize the conventional agricultural system. Active nanoparticles can be used both as a direct source of micronutrients and as a delivery platform for bioactive agrochemicals to improve crop growth, yield and quality. The use of nanoparticle formulations, including nanopesticides, nanoherbicides, nano-fertilizers and nano-emulsions, has been extensively studied to improve crop health and shelf life of agricultural products. Comprehensive knowledge of the interactions between plants and nanoparticles opens up new opportunities to improve cropping practices through the enhancement of properties such as disease resistance, crop yield, and nutrient use. The main objective of this review is to analyze the main effects of climate change on conventional agricultural practices, such as the use of pesticides, herbicides and fertilizers. It also focuses on how the introduction of nanoparticles into conventional practices can improve the efficiency of chemical pest control and crop nutrition. Finally, this review examines in depth the last 10 years (2014-2024) of scientific literature regarding the use of nanoparticles in agriculture to mitigate the effects of climate change.

During the last decade, Bangladesh has been experienced a significant climatic anomalies which lead to an increase in magnitude and frequency of various climate relate extreme events. Climate scientists substantiate that global temperature and precipitation pattern is expected to change, which may result in consequential impact on agriculture, livelihood, and ecosystem. Bangladesh is therefore likely to face substantial challenges in the coming decades. In order to adequately understand this complex, dynamic phenomena, Analyzing historical Climate change scenarios as well as projecting its future trends is a great concern for researcher. This study aims to analyzes/ historical climatic data from (1901-2020), and predict future temperature and precipitation patterns in Bangladesh using CMIP6 data. Data used in this study (Observed data is from CRU TS 4.05 and future data is from CMIP6) have been acquired from WorldClim v2.1. Various methods including correlation, regression, standard deviation, correlation matrix, percentiles, cell statistics, and IDW interpolation were performed to analyze the trends, variability and spatial patterns of temperature and rainfall. This study revealed that Over the historical study period (1901-2020) Bangladesh has been experienced a significant warming trend with an average increase in temperature 2°C and with annual decline of the total precipitation 607.26 mm along with a shift towards drier conditions despite weak correlation with hotter years. Projected climate models represents that Bangladesh minimum temperature is expected to increase from 1°C to 4.4°C as well as maximum temperatures from 1°C to 4.1°C by 2100. Moreover, projected precipitation is expected to increase by 480.38 mm, with the biggest rises during monsoon months. Regional variations in temperature and precipitation are again expected, with the Southeast (SE) likely experiencing the most significant warming and the Northeast (NE) seeing the most substantial increase in precipitation.

The study examines projected changes in dry- and wet-spell probabilities in West Africa using a Markov chain approach. Four simulations of regional climate models from the CORDEX-Africa program were used to analyze projected changes in intraseasonal variability. The results show an increase in the probability of having a dry day, a dry day preceding a wet day and a dry day preceding a dry day, and a decrease in the probability of wet days in the Sahel region under anthropogenic forcing scenarios RCP4.5 and RCP8.5. The decrease in wet days is stronger in the far future and under the RCP8.5 scenario (up to -30%). The study also finds that the probability of consecutive dry days (lasting at least 7 days and 10 days) is expected to increase in the Western Sahel, the Central Sahel, and the Sudanian Area under both scenarios, with stronger increases in the RCP8.5 scenario. In contrast, the decrease is expected over the Guinea Coast, with the changes more important under the RCP4.5. These changes in dry- and wet-spell probabilities are important for water management decisions and risk reduction in the energy and agricultural sectors. The study also highlights the need for decision-makers to implement mitigation and adaptation policies to minimize the adverse effects of climate change.

Abstract—Annually, approximately 500,000 Merger and Ac- quisition (M&A) transactions are disclosed globally, each trans- action inciting substantial perturbations to the associated com- panies’ equity prices. The probability of an M&A transaction’s closure, as perceived by the public, inherently influences the stock price of the target company leading up to the proposed date of the deal. Given the recent advancements in the realm of Natural Language Processing (NLP), we propose an empirical investigation into the correlation between digital dialogue sur- rounding M&A transactions and consequent movements in the stock prices of involved companies. Utilizing transformer-based encoder-only architectures, we fine tune a stance detection model on an extensive dataset, amassed from digital communication platforms, featuring public discourse related to five historical M&A transactions. Ultimately, we achieved 70% accuracy on deal-completion stance detection using the Roberta-base model. We subsequently employ the aggregated the public sentiment towards the completion or termination of a proposed M&A transaction to model stock price movement. Utilizing a multitude of time-series based approaches, we achieve a mean absolute error of 2.29 USD for next-day price prediction and 3.40 USD for next-week price prediction. Ultimately, we find an existing but tenuous relationship between online discourse and the price trajectory of target companies, ultimately highlighting the complex social and economic phenomena behind M&A deals.Index Terms—Mergers and Acquisitions, Stock prediction, su- pervised learning, neural networks, Recurrent Neural Network, LSTM, stance detection, transformers

The climate change constitutes nowadays an enormous global threat for human health and environmental sustainability. The expanding world population and the increased global needs for food production have an important negative impact upon environment. Diet can link human health with environmental sustainability. Food production systems are closely related to anthropogenic greenhouse gas emissions and the aggravation of climate change, and current western type, animal-based, dietary patterns may lead to adverse environmental footprints. In the present narrative review, we address the interconnection of the Mediterranean diet (MD) with climate change and sustainability. MD is a highly recommended dietary intervention for the prevention and management of various endocrine and cardiometabolic diseases. Beyond its evidence-based, health-promoting effects, it also has beneficial environmental impact, reducing greenhouse gas emissions and enhancing biodiversity, food security and sustainability. Based on the evidence reviewed herein, MD should be incorporated within the framework of a “One Health” model, which involves the improvement not only of human health but also of planetary health and food system sustainability. Our review aims to provide a stimulus for health pro-fessionals to strongly recommend the implementation of MD under the current pressure of climate change, despite all barriers, targeting both human health preservation and the planetary well-being.

The current study aimed to examine the relationship between sociodemographic variables (i.e., sex, age, marital status, educational level, socioeconomic status, and working mode) and physical activity levels declared by Chilean adults. The sample comprised 483 Chilean adults, 159 men (32.9%), and 324 women (67.1%) aged from 18 to 69 years old (36.5±12.0). The participants completed an ad-hoc sociodemographic online survey that included questions about characteristics of participants such as sex, age, educational level, household income, marital status, and working mode. Vigorous, moderate, and walking activities were measured using the International Physical Activity Questionnaire-Short Form (IPAQ-SF), a self-administered questionnaire. Results: Men declared significantly higher vigorous and moderated physical activity than women. People aged 18 to 25, single or unmarried, and with the lowest household income, showed significantly higher scores in vigorous physical activity than those aged 26 to 45, cohabiting with a partner or married, and middle household income, respectively. Regarding working mode, people working on their job site said walking more than people not working, working on hybrid, and online mode. Our findings suggest that promoting strategies that increase physical activity during the pandemic is necessary to avoid health problems.

This work attempts to answer in a clear way the following key questions regarding the optimal initialization of the Sysmon tool, towards the identification of Lateral Movement in the MS Windows ecosystem. First, from an expert’s standpoint and with reference to the relevant literature, what are the criteria of determining the possibly optimal initialization features of the Sysmon’s event monitoring tool, which are also applicable as custom rules within the config.xml configuration file? Second, based on the identified features, how can a functional configuration file, able to identify as many LM variants as possible, be generated? To answer these questions, we relied on the MITRE ATT&amp;CK knowledge base of adversary tactics and techniques, and focused on the execution of the nine commonest LM methods. The conducted experiments, performed on a properly configured testbed, suggested a great number of interrelated networking features, that were implemented as custom rules in the Sysmon’s config.xml file. Moreover, by capitalizing on the rich corpus of the 870K Sysmon logs collected, we create and evaluate in terms of TP and FP rates an extensible Python .evtx file analyzer, dubbed PeX, which can be used towards automatizing the parsing and scrutiny of such voluminous files. Both the .evtx logs dataset and the developed PeX tool are provided publicly for further propelling future research in this interesting and rapidly evolving field.

Urban beggars are social problems that are related to the poverty of citizen. In Denpasar City Bali Province, particularly in West Denpasar District, the beggars have specificity in activities of begging. Studies in this article demonstrate their specificity begging activity which can be evaluated from the spatial movement of beggars based on the place, time and the distance. Through the method of grounded research with qualitative analysis showed that: (1) the beggars have permanent objects to visit, which consist of shops, settlement and places of worship of the Muslim community, (2) begging activities performed every Friday for 6 hours from 08.00 to at 14.00, and (3) beggars not only walking, but also using public transportation to visiting the object that is relatively far from beggars lane. The findings of this study reinforces that begging has become a profession that is conducted in a structured and well-organized.

This article examines the impact of climate change on the hydrometeorological state of some lakes and reservoirs in the Akmola and North Kazakhstan regions. Time series with values of various climate parameters for the period 1986-2023 are used for the climate analysis; the reliability of the results was assessed using the Fisher criteria. Hydrometric indicators were studied using the ArcGIG program. Using GIS to spatially analyze water climate data, 8-channel satellite images from 1995 to 2023 were used. During the study, it was found that the area of the main lakes has undergone changes.

With the exponential growth of internet usage and mobile devices, the volume of user behavior data has surged, offering significant opportunities and challenges for businesses. This paper explores user behavior analysis in the context of big data, highlighting its pivotal role in driving innovation and strategic decision-making. We begin by discussing the importance of user behavior data and reviewing technological advancements such as machine learning, natural language processing, and data mining that enable deep insights into user behavior. Through a case study on linguistic analysis in livestreaming e-commerce, we demonstrate how text-mining techniques can correlate linguistic characteristics with sales performance, providing actionable marketing insights. We further explore the broader business applications, including personalized recommendations, user portraits, product design, and strategic decision-making. Technical and ethical challenges, such as data integration, privacy concerns, and algorithmic bias, are also addressed. The paper concludes with a discussion on future trends, such as AI and ML advancements, edge computing, IoT proliferation, and ethical AI frameworks, poised to shape user behavior analysis. Our findings underscore the transformative potential of user behavior data in enhancing business operations and user experiences, providing recommendations for future research focused on real-time analytics, privacy-preserving techniques, and ethical implications of data-driven decisions.

Human development encompasses the integration of neuromotor, psychological, social-emotional, and cognitive processes across time. However, a better understanding of the interconnectedness of motor and cognitive development throughout the lifespan is needed. The integrative and dynamic nature of short-term motor skill acquisition and long-term developmental processes may foster executive functions. Unfortunately, assessments of motor competence have traditionally focused on skillfulness from a movement perspective, using restrictive task protocols that decontextualize performance and limit cognitive involvement. Additionally, traditional motor-cognitive dual-task assessments centered on cognitive involvement during specific movement protocols, have minimized impacts of task complexity and motor competence on cognitive performance. To gain a more ecologically valid understanding of the relation between motor and cognitive development, a novel assessment paradigm using an integrative approach to motor-cognitive dual-tasking is needed. The purpose of the present paper is to: 1) provide a conceptual bridge, based on multidisciplinary evidence, to effectively link the concurrent development of motor competence and executive functions via learning-related and exercise-related neurotrophic mechanisms, and 2) use this conceptual bridge to inform the development of novel motor-cognitive dual-task assessments that account for the role of task complexity, current levels of motor competence, and the continuous decision-making inherent in “real world” performance environments.

This study investigates the impacts of climate change policies on businesses across various sectors, aiming to understand how these regulations affect operational, financial, and strategic aspects of business management. Utilizing a mixed-methods approach, data was collected from 500 businesses through surveys and interviews, encompassing a wide range of industries, sizes, and geographic locations. The findings reveal a complex landscape where 30% of businesses report positive impacts, primarily in the renewable energy and technology sectors, citing increased demand for green products and improvements in energy efficiency. Conversely, 45% of businesses, especially from manufacturing and agriculture, experience negative impacts, including increased operational costs and regulatory compliance challenges. Notwithstanding, a significant majority of businesses are committed to enhancing their sustainability practices, viewing climate change policies as an opportunity for innovation and long-term growth. The study highlights the nuanced effects of climate change policies, emphasizing the need for sector-specific support measures to alleviate financial and operational burdens on negatively impacted businesses. Moreover, it points to a broader shift towards sustainability within the business community, suggesting that climate policies, despite their varied impacts, are driving significant changes in business strategies towards environmental stewardship.

Understanding the interrelationships between land use, climate change, and regional water yield is critical for effective water resource management and ecosystem protection. However, comprehensive insights into how water yield evolves under different land use scenarios and climate change remain elusive. This study employs the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models, Patch-generating Land Use Simulation (PLUS) model, and Geodetector within a unified framework to evaluate the dynamics of land use, water yield, and their relationships with various factors (meteorological, social, economic, etc.). To forecast the Land Use/Cover Change (LUCC) pattern of the Yellow River Basin by 2030, three scenarios were considered: economic development priority (Scenario1), ecological development priority(Scenario2), and cropland development priority(Scenario3). Climate change scenarios were constructed using CMIP6 data, representing low stress (SSP119), medium stress (SSP245), and high stress (SSP585) conditions. The results show the following: (1) From 2000 to 2020, cropland was predominant in the Yellow River Basin, Henan Province, with significant land conversion to impervious land (construction land) and forest land; (2) Water yield changes during this period were primarily influenced by meteorological factors, with land use changes having negligible impact; (3) By 2030, the water yield of Scenario1 is highest among different land use scenarios, marginally surpassing ecological development priority by 0.5%; (4) Climate scenarios reveal significant disparities, with SSP126 yielding 67% higher water production than SSP245, driven predominantly by precipitation; (5) Geodetector analysis identifies precipitation as the most influential single factor, with significant interactions among meteorological and socio-economic factors. These findings offer valuable insights for policymakers and researchers in formulating land use and water resource management strategies.

(1) Background: The aim of the work was to characterize the climatic evolution and change based on the Multi Criteria Classification through the dynamics of bioclimatic indices in viticulture across Italy and its regional administrative boundaries, focusing on latitudes and elevations. (2) Methods: The impact of climate change on viticulture in Italy was analysed and spatialized with reference to historical data from 1991 to 2021 and to the Future Scenarios up to 2080 assumed by SSP2-4.5 and SSP5-8.5, taking into account 13 GCMs. (3) Results: The bioclimatic indices have all shown a significant trend in the historical period, with an increase in temperature and a decrease in precipitation, reflecting their effects on the entire Italian territory with respect to HI, up to 44°N for CI and up to 46°N for DI, regardless of altitude. The Future Scenarios highlighted a shift towards the warmer classes of the two temperature-based indices (HI and CI) for both SSPs, especially for altitudes up to 900 m a.s.l.. The DI-based classification based on DI remained relatively stable in Italy over time, although DI values will become increasingly negative in the near future. (4) Conclusions: The climate in Italy is warming, especially in the south and in the coastal regions. By 2080, more areas will be “Very Hot” with “Warm Nights.” Drought will also increase and have a negative impact on viticulture. The importance of higher latitudes and altitudes in mitigating the effects of climate change justifies the continuing trend towards the relocation of vineyards as a medium-term solution and as an alternative to targeted cultivation methods that must be adopted in the short-term to safeguard the suitability of an area to quality viticulture.

This research analyzes the phenomenon of the reduction of urban green spaces in the post-socialist city. Belgrade was selected as a post-socialist city of the former Yugoslavia. The article analyses the views of urban planners on the reasons for the reduction of urban green areas in the post-socialist city based on semi-structured interviews with representative samples for urban areas. This result research confirms the hypothesis that post-socialist city planning reduces urban green areas due to the lack of new mechanisms in documents for the planning of urban green space. The concept of sustainability should connect and balance the skills of urban planners and focus on how urban planners develop and apply standards and protect them in market-democratic systems. In other words, a new mechanism of post-socialist city planning implies a balance between the private and public sectors. In the planning document, urban planners should find a common denominator between the public interest, citizens, investors, and spheres determined by the sustainable principles of the development. City institutions should provide opportunities for the application of those standards. With the new approach, planning would imply work in the service of citizens in the concepts of a sustainable and green city.

Movement disorders can be associated with various drugs and systemic diseases, posing diagnostic challenges for clinicians. This review explores the spectrum of movement disorders associated with pharmacological agents and medical conditions. Drug-induced movement disorders encompass a broad range of conditions resulting from exposure to medications that affect several neurotransmitters. Neuroleptic medications can lead to tardive dyskinesia, characterized by involuntary, repetitive movements. Antipsychotics and antiemetics, including metoclopramide, may induce acute dystonic reactions. Other drugs, such as dopamine receptor-blocking agents, can contribute to drug-induced parkinsonism. Beyond medications, movement disorders can also arise secondary to systemic diseases. Metabolic disorders like Wilson's disease, characterized by copper accumulation, may manifest as chorea or dystonia. Inflammatory conditions such as rheumatoid arthritis and systemic lupus erythematosus can result in secondary movement disorders due to autoimmune-mediated processes affecting the central nervous system. Movement disorders linked to drugs or systemic diseases often necessitate a thorough clinical evaluation, including detailed medication histories and comprehensive systemic assessments. Neuroimaging, laboratory investigations, and, in some cases, cerebrospinal fluid analyses and electrodiagnostic studies help in establishing accurate diagnoses. Management involves addressing the underlying cause, modifying medications, and employing symptomatic treatments.

Ankle joint flexion and extension exercises play an important role in the rehabilitation training of patients who have been injured or bedridden for a long time before and after surgery. Accurately guiding patients to perform ankle flexion and extension exercises can significantly reduce deep vein thromboembolism. Currently, most ankle rehabilitation devices focus on assisting patients with ankle flexion and extension movements, and there is a lack of devices for effectively monitoring these movements. In this study, we designed an ankle joint flexion and extension movement monitoring device based on a pressure sensor. It is composed of an STM32 microcontroller, a pressure sensor, an HX711A/D conversion chip, and an ESP8266 WiFi communication module. The value of force and effective number of ankle joint flexion and extension movements were obtained. An experimental device was designed to verify the accuracy of the system. The results showed that the device can effectively monitor and control ankle flexion and extension movements remotely, ultimately ensuring that the patient can effectively monitor and grasp the active ankle pump movement.

The performance of choice-reaction tasks during athletic movement has been demonstrated to evoke unfavorable lower limb biomechanics. However, the mechanism of this observation is unknown. We conducted a systematic review examining the association between 1) the biomechanical and functional safety of unplanned sports-related movements (e.g. jumps/runs with spontaneously indicated landing leg/cutting direction) and 2) markers of perceptual-cognitive function (PGF). A literature search in three databases (Pubmed, ScienceDirect, Google Scholar) identified five relevant articles. Study quality, rated by means of a modified Downs & Black checklist, was moderate to high (average: 13.5/16 points). Four of five papers, in at least one parameter, found either an association of lower PGF and reduced task safety or significantly reduced task safety in low vs. high PGF performers. Yet, as a) the outcomes, populations and statistical methods of the included trials were highly heterogeneous and b) only two out of five studies had an adequate control condition (pre-planned movement task), evidence was classified as conflicting. In sum, PGF may represent a factor increasing injury risk during unplanned sports-related movements but future research strengthening the evidence of this association is warranted.

Exergy analysis evaluates the efficiency of system components by quantifying the rate of entropy generation. In general, the exergy destruction rate or irreversibility rate was directly obtained through the exergy-balance equation. However, this method cannot determine the origin of the component's entropy generation rate, which is a very important factor in system design and improvement. In this study, a thorough energy, exergy thermoeconomic analysis of a proton exchange membrane fuel cell (PEMFC) was performed, providing the heat transfer rate, entropy generation rate and cost loss rate of each component. The irreversibility rate of each component is obtained by the Gouy-Stodolar theorem. Detailed and extensive exergy and thermoeconomic analyses of PEMFC system have determined that water cooling units experience the greatest heat transfer among the components in the studied PEMFC system, resulting in the greatest irreversibility and thus the greatest monetary flow loss.

Artificial intelligence (AI) has emerged as a powerful tool for addressing the challenges posed by climate change and their impact on public health. By leveraging its capacity to analyze and predict climatic patterns, AI offers opportunities to enhance resource management and develop effective strategies for climate change mitigation. Moreover, AI can contribute to generating sustainable solutions that address the complex and interconnected nature of climate change. For example, AI can enable the optimization of energy consumption and facilitate the integration of renewable energy sources into existing systems. It can also support the development of climate models that provide timely and accurate predictions, enabling policymakers to implement proactive measures for disaster preparedness and response. Furthermore, AI-powered disease surveillance and mitigation techniques can improve public health outcomes by identifying patterns and trends in the spread of diseases in relation to climatic factors.However, the widespread adoption of AI-based solutions is not without challenges. Ethical concerns surrounding privacy and data ownership must be addressed, as the use of AI requires access to large datasets, raising potential privacy risks. Technical constraints, such as limited computational power and the need for sophisticated algorithms, also pose obstacles to the implementation of AI in climate change mitigation strategies. Furthermore, issues related to the accessibility and affordability of AI technologies must be resolved to ensure equitable distribution and maximize its potential impact on public health.To fully harness the power of AI in addressing climate change and improving public health outcomes, it is crucial to promote innovation, multidisciplinary collaboration, and open data science. Innovation can drive the development of new AI algorithms and technologies specifically tailored to address climate change challenges. Multidisciplinary approaches that bring together experts from diverse fields, including climate science, public health, and computer science, can foster a holistic understanding of complex systems and enable the design of comprehensive solutions. Finally, open data science practices, such as sharing data and algorithms, can facilitate collaboration and accelerate progress in mitigating climate change and its public health impacts.In conclusion, AI offers promising opportunities for effectively addressing climate change and its impact on public health. However, to fully realize its potential, it is essential to tackle ethical and privacy concerns, overcome technical constraints, and ensure accessibility and affordability. By promoting innovation, multidisciplinary collaboration, and open data science, we can unlock the transformative power of AI in mitigating climate change and improving public health outcomes.

The paper provides a methodological framework based on Multiple Criteria Decision Aid methods for determining relative regional vulnerabilities associated with forest fires that occurred during a given period. Different notions of ex-post vulnerability are defined based on the forest area burned and the frequency of forest fires, and their relation to the regions’ area and several socioeconomic characteristics. The methodology is applied to Greece and its administrative regions for the period 2000–2022. Linking the forest fire events with summer and spring temperatures and precipitation and using econometric count data analysis, the paper explores the climatic drivers of forest fire occurrence and provides projections of the expected change in the frequency of fires of specific size classes conditional on the evolution of mean seasonal regional temperature and precipitation according to IPCC scenarios. The results regarding relative regional vulnerabilities and expected forest fires could be useful in designing policies for preserving forests as natural capital and promoting sustainability.

The exponential growth of user-contributed data provides a comprehensive basis for assessing collective perceptions of landscape change. A variety of possible public data sources exist, such as geospatial data from social media or Volunteered Geographic Information (VGI). Key challenges with such ‘opportunistic’ data sampling are variability in platform popularity and bias due to changing user groups and contribution rules. In this study, we use five case studies to demonstrate how intra- and inter-dataset comparisons can help to assess the temporality of landscape scenic resources, such as identifying seasonal characteristics for a given area, or testing hypotheses about shifting popularity trends observed in the field. By focusing on the consistency and reproducibility of temporal patterns for selected scenic resources and comparisons across different dimensions of data, we aim to contribute to the development of systematic methods for disentangling the perceived impact of events and trends from other technological and social phenomena included in the data. The proposed techniques may help to draw attention to overlooked or underestimated patterns of landscape change, fill in missing data between periodic surveys, or corroborate and support field observations. Despite limitations, the results already provide a comprehensive basis for developing indicators with a high degree of timeliness for monitoring perceived landscape change over time.

The understanding of spatiotemporal variations in reference evapotranspiration (ETo) and its long-term trends is of paramount importance for water cycle studies, modeling, and water resource management, especially in the context of climate change. Therefore, the primary aim of this study is to critically evaluate the performance of various CMIP5 global climate models in simulating the Penman-Monteith reference evapotranspiration and its associated climate variables (maximum and minimum air temperature, incident solar radiation, relative humidity, and wind speed). This evaluation is based on data from nine climate models and 33 automatic meteorological stations (EMA) in the state of Mato Grosso, spanning the period 2007-2020. The statistical metrics used for evaluation include Bias, root mean square error, and Pearson and Spearman correlation coefficients. The projections of the most accurate model were then used to analyze the spatial and temporal changes and trends in ETo under the RCP 2.6, 4.5, and RCP 8.5 scenarios from 2007 to 2100. The HadGEM2-ES model projections indicate static averages similar to current conditions until the end of the century in the RCP 2.6 scenario. However, in the RCP 4.5 and 8.5 scenarios, there is a continuous increase in ETo, with the most significant increase occurring during the dry period (May to September). The areas of the Amazon biome in the north of Mato Grosso exhibit the largest increases in ETo when comparing the observed (2007-2020) and projected (2020-2100) averages. The trend analysis reveals significant changes in ETo and its variables across the state of Mato Grosso in the RCP 4.5 and 8.5 scenarios. In the RCP 2.6 scenario, significant trends in ETo are observed only in the northern Amazon areas. Despite not being observed in all AWSs, the trend analysis of the observed data demonstrates more intense changes in ETo and the existence of the evapotranspiration paradox with an increase in the Cerrado areas and reductions in the Pantanal and southern Amazon areas.

Oedaleus decorus asiaticus, Calliptamus abbreviatus, Angaracris rhodopa, and Myrmeleotettix palpalis are the main grasshoppers that harm the natural grassland in the Hexi Corridor. In this study, the MaxEnt model was employed to identify the key environmental factors affecting the distribution of the four grasshoppers habitats and to assess their distribution under current and future climate change conditions. The aim was to provide a basis for grasshopper monitoring, prediction, and precise control. In this study, 61 occurrences of O. decorus asiaticus, 68 occurrences of A. rhodopa, 58 occurrences of C. abbreviatus, and 92 occurrences of M. palpalis were recorded by GPS, and the distribution of suitable habitats for O. decorus asiaticus, C. abbreviatus, A. rhodopa, and M. palpalis were predicted under current and future climatic scenarios using a MaxEnt model. The average AUC and TSS values of the four grasshoppers were greater than 0.9, and the simulation results were excellent and highly reliable. The mean annual precipitation was the main factor limiting the current range of suitable areas for these four species. Under the current climate, O. asiaticus, C. abbreviatus, and A. rhodopa were mainly distributed in the central and eastern parts of the Hexi Corridor, and M. palpalis was distributed throughout the Hexi Corridor, with a potential distribution area of 1.44×104, 1.43×104, 1.29×104, and 2.12×104 km2, accounting for 15.3, 15.2, 13.7, and 22.5% of the total area of the grasslands in the Hexi Corridor, respectively. The highly suitable areas of O. asiaticus, C. abbreviatus, and A. rhodopa were mainly distributed in the east-central part of Zhangye City, the western part of Wuwei City, and the western and southern part of Jinchang City, with areas of 0.35×104, 0.29×104, and 0.20×104 km2, accounting for 3.7, 3, and 2.2% of the grassland area, respectively. The high habitat of M. palpalis was mainly distributed in the southeast of Jiuquan City, the west, middle, and east of Zhangye City, the west of Wuwei City, and the west and south of Jinchang City, with an area of 0.32×104 km2, accounting for 3.4% of the grassland area. In the 2030s, the range of O. asiaticus, C. abbreviatus, A. rhodopa, and M. palpalis was predicted to decrease.

This study analyzes future hydrological droughts in LCKW using the SWAT model and data from 2010-2021, evaluating the Streamflow Drought Index (SDI) for 5, 10, 25, and 50-year return periods (RP) for 2029 and 2039 under RCP4.5 and RCP8.5 scenarios. The model shows high accuracy (R² = 0.82, NSE = 0.78). Under RCP4.5, streamflow may increase by 34.74% and 18.74%, while RCP8.5 predicts significant decreases of 37.06% and 55.84%. Historical data reveal frequent short-term droughts during SDI-3, notably in 2014–2016 and 2020–2021, with SDI-6 indicating less frequent but severe droughts, especially in 2015 and 2020. Future projections under RCP8.5 suggest wors-ening drought conditions in 2029 and 2039, with critical drought periods from January to April and November. Wavelet analysis indicates a high risk of severe hydrological drought in LCKW due to low annual recurrence rates, with the highest drought severity over a 50-year RP. The study high-lights an increasing likelihood of frequent and severe droughts, particularly under high emission scenarios such as RCP8.5, which could result in significant water shortages and ecosystem disrup-tions. It emphasizes the significance of adaptive water resource management strategies in mitigating negative impacts on water security and ecosystem health.

CO2 flooding stands as a pivotal technique for significantly enhancing oil recovery in low-permeability reservoirs. The movement and sweeping rules at the front of CO2 flooding play a critical role in its oil recovery, yet a comprehensive quantitative analysis remains an area in need of refinement. In this study, we have developed 1D and 2D numerical simulation models to explore the sweeping behavior of miscible, immiscible, and partly-miscible CO2 flooding patterns. The front position and movement rules of the three CO2 flooding patterns are determined. A novel approach of the contour area calculation method is introduced to quantitatively characterize the sweep coefficients, and the sweeping rules are discussed regarding geological parameters, oil viscosity, and injection-production parameters. Furthermore, the Random Forest (RF) algorithm is employed to identify the controlling factor of the sweep coefficient, as determined by out-of-bag (OOB) data displacement analysis. The results show that the miscible front is located at the point of maximum CO2 content in the oil phase. The immiscible front occurs at the point of maximum interfacial tension near the production well. Remarkably, the immiscible front moves at a faster rate compared to the miscible front. Geological parameters, including porosity, permeability, and reservoir thickness, significantly impact the gravity segregation effect, thereby influencing the CO2 sweep coefficient. Immiscible flooding exhibits the highest degree of gravity segregation, with a maximum gravity segregation degree (GSD) reaching 78.1. The permeability ratio is a crucial factor, with a lower limit of approximately 5.0 for reservoirs suitable for CO2 flooding. Injection-production parameters also play a pivotal role in sweep coefficient. Decreased well spacing and increased gas injection rates are found to enhance sweep coefficients by suppressing gravity segregation. Additionally, higher gas injection rates can improve the miscibility degree of partly-miscible flooding from 0.69 to 1.0. Oil viscosity proves to be a significant factor influencing the sweep coefficients, with high seepage resistance due to increasing oil viscosity dominating the miscible and partly-miscible flooding patterns. Conversely, gravity segregation primarily governs the sweep coefficient in immiscible flooding. In terms of controlling factors, the permeability ratio emerges as a paramount influence, with a factor importance value (FI) reaching 1.04. these results provide a theoretical foundation for the application of CO2 flooding, enhancing the understanding of the critical factors governing its success.

The purpose of this study was to detect mind-wandering experienced by pre-service teachers while learning video lecture on physics. The lecture was videotaped and consisted of a live lecture in a classroom. The lecture was about Gauss's law on physics. We investigated whether oculomotor data and eye movements could be used as a marker to indicate the learner’s mind-wandering. Each data was collected in a study in which 24 pre-service teachers (16 females and 8 males) reported self-caught mind-wandering while learning physics video lecture during30 minutes. A Tobii Pro Spectrum (sampling rate: 300Hz) was used to capture their eye-gaze during learning Gauss's law course video. After watching video lecture, we interviewed pre-service teachers about their mind-wandering experience. We first used the self-caught method to capture the mind-wandering timing of pre-service teachers while learning from video lectures. We detected more accurate mind-wandering segments by comparing fixation duration and saccade count. We investigated two types of oculomotor data (blink count, pupil size) and nine eye movements (average peak velocity of saccades; maximum peak velocity of saccades; standard deviation of peak velocity of saccades; average amplitude of saccades; maximum amplitude of saccades; total amplitude of saccades; saccade count/s; fixation duration; fixation dispersion). The result was that the blink count could not be used as a marker for mind-wandering during learning video lectures among them (oculomotor data and eye movements), unlike previous literatures. Based on the results of this study, we identified elements that can be used as mind-wandering markers while learning from video lectures that are similar to real classes, among the oculomotor data and eye movement mentioned in previous literatures. Also, we found that most participants focused on past thoughts and felt unpleasant after experiencing mind-wandering through interview analysis.