This research uses the DPSIR framework to analyse and anticipate Taiwan's marine ecosystems' ecological security. The goal is to understand how human-induced pressures including pollution, overfishing, habitat loss, and climate change affect Taiwan's marine habitats. For Taiwanese maritime ecological security assessments, the DPSIR framework, case studies, and assessment models are used. The DPSIR model classifies human activities, environmental pressures, marine ecosystem states, effects, and reactions. Assessment models complement the DPSIR framework for systematic and quantitative evaluation, while case studies are practical. This systematic literature review follows PRISMA guidelines for thoroughness and organisation. The research shows the DPSIR framework's adaptability and efficacy in analysing Taiwan's complex marine biological processes. Human-induced stressors on marine states are revealed via a comprehensive examination of causes, pressures, states, consequences, and responses, contributing to ecological security discourse. The DPSIR model helps Taiwan identify environmental change sources, analyse pressures, and provide sustainable marine environmental management solutions. The research concludes that the DPSIR framework is crucial to Taiwan's maritime environmental preservation. Despite its strengths, the DPSIR framework has to be refined and customised to Taiwan's unique maritime environments. Taiwan's maritime protection policies are shaped by the study's evidence-based findings. The report also recommends combining the DPSIR framework with SWOT analysis to improve evaluation and decision-making in Taiwan's marine environmental protection setting.

This study demonstrates the efficacy of structured pruning and architectural fine-tuning on the YOLOv7-tiny model for eye state detection, emphasizing optimization for real-time applications. Structured pruning significantly reduced the model's complexity and storage size while maintaining high detection accuracy, as evidenced by stable precision, recall, and mAP@.5 metrics across iterations. Further fine-tuning adjusted the model's width and depth, optimizing efficiency and processing speed without compromising performance. These optimizations yielded YOLOv7-tiny variants that are both computationally efficient and accurate, suitable for resource-constrained environments. The findings highlight the critical role of model optimization in deploying effective neural networks for specific detection tasks in real-time scenarios.

Objective To observe the effect of roxadustat on blood pressure and micro-inflammatory response in patients with hemodialysis anemia, and to provide a viable technique for the treatment of hemodialysis anemia patients. Methods A total of 100 hemodialysis anemia patients admitted to the Nephrology Department of our hospital from July 2020 to July 2021 were enrolled and randomly divided into an observation group (roxadustat) and a control group (human recombinant erythropoietin (rhEPO). The clinical efficacy, blood lipid metabolism, inflammatory factor levels, iron metabolism-related indicators, blood biochemical indicators, anemia indicators, adverse reactions and blood pressure were recorded and compared. Results There was no significant difference in baseline data and serum indicators (P>0.05). The study group demonstrated superior performance to the control group in terms of clinical efficacy, blood lipid metabolism, inflammatory factor levels, iron metabolism-related indicators, blood biochemical indicators, anemia indicators, adverse reactions and blood pressure (all P<0.05). Conclusion Compared with rhEPO treatment, roxadustat exhibits a promising outcome in treating anemia and has slight impact on blood pressure of patients.

Amidst escalating environmental concerns, short natural fiber thermoplastic (SNFT) biocomposites have emerged as sustainable materials for the eco-friendly production of mechanical components. However, their limited durability has prompted research into the experimental evaluation of the deterioration of the mechanical characteristics of SNFT biocomposites, particularly under the influence of ultraviolet rays. However, conducting tests to evaluate the mechanical properties can be time-consuming and expensive. In this study, an artificial neural network (ANN) model was employed to predict the mechanical properties (tensile strength) and the impact performance (resistance and absorbed energy) of polypropylene reinforced with 30 wt.% short flax or wood pine fibers (referred to as PP30-F or PP30-P, respectively). Eight parameters were collected from experimental studies. The ANN input parameters comprised nondestructive test results, including mass, hardness, roughness, and natural frequencies, while the output parameters were the tensile strength, the maximum impact load and absorbed energy. The model was developed using the ANN toolbox in MATLAB. The linear coefficient of correlation and mean squared error were selected as the metrics for evaluating the performance function and accuracy of the ANN model. They calculate the relationship and the average squared difference between the predicted and actual values. The data analysis conducted by the models demonstrated exceptional predictive capability, achieving an accuracy rate exceeding 96%, which was deemed satisfactory. For both the PP30-F and PP30-P biocomposites, the ANN predictions deviated from the experimental data by 3, 5, and 6% about the impact load, absorbed energy, and tensile strength, respectively.

Due to the high solar irradiance or energy price, certain regions in the U.S. may reach 100% PV penetration and experience degradation of frequency response greater than the interconnection as a whole. Therefore, in this section, the 100% PV penetration region in each interconnection is simulated to study the local high PV penetration effects. The study was performed by quantifying RoCoF, frequency nadir, and settling frequency at different regional PV penetration levels. The impact of high regional PV penetration on the compliance of grid code on frequency response is also studied.

This paper investigates the impact of sediment deposition and inflow conditions on horizontal impact pressure and frequency analysis of bridge deck vibrations during flooding. Flooding-induced pressure and vibrations contribute to bridge collapse, and sediment deposition influences water flow and impact pressure. The study explores the relationship between sediment deposition height and impact pressure, revealing a significant increase as sediment approaches 50% of bridge deck clearance. Sediment amplifies impact pressure response to flow velocity changes. The dimensionless sediment deposition height has a greater influence on impact pressure compared to the inflow Froude number. Two distinct frequencies, dominant and secondary, are identified for impact pressure and water level fluctuations. Dominant frequencies positively correlate with sediment deposition height and Froude number, indicating an increasing trend. Secondary frequencies remain stable (0.31-0.58 Hz). These findings enhance understanding of flow dynamics and bridge-flow interaction in sediment-deposited channels, providing theoretical support for evaluating and managing disasters related to bridges in such environments. Overall, this research contributes to the field of bridge engineering and supports improved design and maintenance practices for bridges exposed to sediment-deposited channels.

Continuous rigid frame bridges across valleys are often at the risk of rockfalls caused by heavy rainfalls, earthquakes and debris flows in a mountainous country. Hollow thin-walled bridge piers (HTWBP) in valleys are exposed to the threat of the impact of accidental rockfalls. In the current research, ANSYS/LS-DYNA is used to establish a high-precision rockfall-HTWBP model. The rockfall-HTWBP model is verified against a scaled impact test of a previous research. A mesh independence test is also performed to obtained an appropriate mesh size. Based on the rockfall-HTWBP model, the impact force, damage and dynamic response characteristics of HTWBP under the rockfall impact are studied. In addition, a damage assessment criteria is proposed based on the response surface model combined with Central Composite Design method and Box-Behnken Design method. The main conclusions are as follows: 1）The impact force of rockfall has a substantial impulse characteristic, and the duration of the impulse load is approximately 0.01s. 2）The impacted surface of the pier is dominated by the final elliptic damage with the conical and strip damage areas as the symmetry axis. The cross-sectional damage mode is compression failure in the impact area and shear failure at the corner. 3）The maximum displacement occurs in the middle height of the pier. The maximum displacement increases with impact height, impact velocity and rockfall diameter and decreases with the uniaxial compressive strength of the concrete. 4) The initial impact velocity and diameter of the rockfall are the most significant parameters affecting the damage indices. In addition, a damage assessment method with a damage zoning diagram based on the response surface method is established for the fast assessment of the damage level of impacted HTWBP.

Study background and aims: Laparoscopic cholecystectomy is one of the most frequently performed interventions in departments of general surgery. One of the most important aims in achieving perioperative stability of these patients is diminishing the impact of general anesthesia on the hemodynamic stability and the optimization of anesthetic drug doses based on the individual clinical profile of each patient. The objective of this study is the evaluation of the impact monitoring the depth of anesthesia through Entropy (state entropy – SE and response entropy -RE) has on the hemodynamic stability and on the doses of volatile anesthetic. Material and Methods: This is a prospective, observational, randomized, monocentric study carried out between January 2019 and December 2019 in the Clinic of Anesthesia and Intensive Care from the “Pius Brînzeu” Emergency County Hospital in Timișoara, Romania. The patients included in the study were divided in two study groups; patients in Group A (target group) received multimodal monitoring that included monitoring of standard parameters and of Entropy (SE and RE), while patients in Group B (control group) only received standard monitoring. Anesthetic dose in group A were optimized to achieve a target entropy of 40-60. Results: 68 patients met the inclusion criteria and were allocated to one of the two study groups, Group A (N=43) and Group B (N=25). There were no statistically significant differences identified between the two groups for both demographical and clinical data (p>0.05). Statistically significant differences have been identified for the number of hypotensive episodes (p = 0.011, 95% CI 0.1851 to 0.7042) and for the number of episodes of bradycardia (p < 0.0001, 95% CI 0.3296 to 0.7923). Moreover, there was a significant difference in the Sevoflurane consumption between the two study groups (p = 0.0498, 95% CI -0.3942 to 0.9047). Conclusions: The implementation of the multimodal monitoring protocol that includes the standard parameters and the measurement of Entropy for determining the depth of anesthesia (SE and RE) lead to a considerable improvement in perioperative hemodynamic stability. Optimizing the doses of anesthetic drugs based on the individual clinical profile of each patient leads to a considerable decrease in drug consumption as well as to a lower incidence of hemodynamic side-effects.

This research assessed the level of peer influences among the students of Ebonyi State University, Abakaliki and the existing policy framework in the University to control its negative impact. Objectives: To assess the knowledge, attitude and practice of peer pressure influence control among the students of the institution. Methodology: We used a cross-sectional design, a structured questionnaire of a five-point Likert scale as a veritable instrument for collecting the data from 30 student respondents. The questionnaire was made up of four key sections comprising student’s demographic parameters, knowledge, attitude and practice of students on the subject matter. Data collected was analyzed in a table of descriptive statistics to determine the total, range, mean and median, which were used to ascertain students’ level of knowledge, attitude, practice and countermeasures to overcome negative peer influences emanating from their peers. Results: The mean value outcome of knowledge of students fall between 2.7 to 3.3, the mean value for attitude of student falls between 2.4 to 3.6, while the practice of students falls between mean value 2.7 and 3.2. Most of these outcomes represents poor or weak weight factor which requires several levels of interventions. Conclusion: This study highlights the overriding importance of peer pressure management among the students of Ebonyi State University, Abakaliki to create a safe academic environment and guarantee higher academic performances. This research recommended that the University management should commission research on peer pressure among students, the causes, manifestations and possible remedies to enable them to develop a comprehensive framework for the University.

All-solid-state lithium batteries (ASSLBs) using argyrodite electrolyte materials have shown promise for applications in electric vehicles (EVs). However, understanding the effects of pro-cessing parameters on the ionic conductivity of these electrolytes is crucial for optimizing battery performance and manufacturing methods. This study investigates the influence of electrolyte op-erating temperature, electrolyte operating pressure, electrolyte pelletization pressure, and electro-lyte pelletizing temperature on the ionic conductivity of Li6PS5Cl0.5Br0.5 argyrodite electrolyte (AmpceraTM, D50=10 µm). A specially designed test cell is employed for the experimental meas-urements, allowing for controlled pelletization and testing within the same tooling. The results demonstrate the significant impact of the four parameters on the ionic conductivity of the argy-rodite electrolyte. The electrolyte operating temperature has a more pronounced effect than oper-ating pressure, and pelletizing temperature exerts a greater influence than pelletizing pressure. This study provides graphs that aid in understanding the interplay between these parameters and achieving desired conductivity values. It also establishes a baseline for the maximum pelletizing temperature before undesirable degradation of electrolyte occurs. By manipulating the pelletizing pressure, operating pressure, and pelletizing temperature, battery engineers can achieve the desired conductivity for specific applications. The findings emphasize the need to consider operating conditions to ensure satisfactory low-temperature performance, particularly for EVs. Overall, this study provides valuable insights into processing and operating conditions for ASSLBs utilizing Li6PS5Cl0.5Br0.5 argyrodite electrolyte.

The Macroscopic Mechanical Equilibrium Condition can be shown to be the physical origin of the Equation of State of any material system, then can describe all thermodynamic quasi-equilibrium processes caused by the change of the external temperature and/or mechanical environment. If it cannot be satisfied, the system would be broken.

Background: Sex differences in blood pressure (BP) exist during all reproductive life between women and men whereas a sharper increase in BP occurs after menopause which is associated with increased prevalence of cardiovascular diseases. This study examined cardiovascular and biochemical parameters in perimenopausal women (PW) aiming to investigate the influence of sex on a) office BP and for 24 hours; b) cardiac autonomic modulation; c) redox state by measuring MDA, SOD, and catalase; d) NO_x^- concentration. In addition, aerobic exercise training (AET) was applied for detecting changes in cardiovascular responsiveness during the menopausal transition. Methods: Thirty-one participants were enrolled, healthy PW and age-matched men. Cardiovascular and biochemical biomarkers were evaluated at baseline and after AET (8 weeks of exercise on a treadmill, three sessions/week, duration of 30-40 minutes). Results: At rest, PW presented: a) a lower diastolic BP during daytime; b) a lower absolute and normalized LF component as well as a higher HF normalized component; d) no sex differences for redox biomarkers and NO_x^- concentration. After AET, only PW was responsive in lowering systolic BP that was accompanied by an increase in NO_x^- concentration and SOD activity. Regarding HRV, both groups were responsive to the AET. Conclusions: During the menopausal transition, systolic BP was similar to men whereas cardiac autonomic modulation remained unaltered showing the influence of sex steroids on BP. In Addition, AET was fundamental during the menopause transition by preventing an elevation in BP, minimizing the effects of aging associated with estrogen deficiency on women's cardiovascular health.

The change in the value of the breaking energy is discussed here for selected steel grades used in building structures after subjecting the samples made of them to episodes of heating in the steady-state heating regime and then cooling in a simulated fire conditions. These changes were recorded based on the instrumented Charpy impact tests, in relation to the material initial state. The S355J2+N, 1H18N9T steels and also X2CrNiMoN22-5-3 duplex steel were selected for detailed analysis. The fire conditions were modelled experimentally by heating the samples and then keeping them for a specified time at a constant temperature of: 600°C (first series) and 800°C (second series), respectively. Two alternative cooling variants were investigated in the experiment: slow cooling of the samples in the furnace, simulating the natural fire progress, without any external extinguishing action, and cooling them in water mist simulating an extinguishing action by a fire brigade. The temperature of the tested samples was set at the level -20oC and alternatively at the level + 20oC. The conducted analysis is aimed at assessing the risk of sudden, catastrophic fracture of load-bearing structure made of steel degraded as a result of a fire previously occurred with different development scenarios.

Background: Long COVID, characterized by a persistent symptom spectrum following SARS-CoV-2 infection, poses significant health, social, and economic challenges. This review aims to consolidate knowledge on its epidemiology, clinical features, and underlying mechanisms to guide global responses; Methods: We conducted a systematic literature review, analyzing peer-reviewed articles and reports to gather comprehensive data on long COVID’s epidemiology, symptomatology, and management approaches; Results: Our analysis revealed a wide array of long COVID symptoms and risk factors, with notable demographic variability. The current understanding of its pathophysiology suggests a multifactorial origin yet remains partially understood. Emerging diagnostic criteria and potential therapeutic strategies were identified, highlighting advancements in long COVID management.; Conclusion: This review highlights the multifaceted nature of long COVID, revealing a broad spectrum of symptoms, diverse risk factors, and the complex interplay of physiological mechanisms underpinning the condition. Long COVID symptoms and disorders will continue to weigh on healthcare systems in years to come. Ad-dressing long COVID requires a holistic management strategy that integrates clinical care, social support, and policy initiatives. The findings underscore the need for increased international cooperation in research and health planning to address the complex challenges of long COVID. There is a call for continued refinement of diagnostic and treatment modalities, emphasizing a multidisciplinary approach to manage the ongoing and evolving impacts of the condition.

Covid-19 has had a significant impact on the lives of populations across the world. Since the first reported case of the coronavirus in Wuhan, China, the world faced a situation of dealing with a novel virus. While the physical health effects of the coronavirus was the center of focus for much of the pandemic, Covid-19 was accompanied with significant social and psychological consequences on the world populations. In this review, we aim to assess how the coronavirus pandemic has affected the African continent at large, highlighting the socio-psychological consequences. Through citing some examples of a few countries in Sub-Saharan Africa, the review will detail the experiences of the populations within this region which remain plagued with economic and health vulnerabilities that were further exposed by the pandemic.

The earth pressure acting on soilbag reinforced retaining structures subjected to surcharge loads under non-limited states, is crucial for designing these structures. In this study, the earth pressures are investigated through model tests of the soilbag reinforced retaining wall. Findings from these tests reveal a non-linear distribution of lateral earth pressure on the wall when subjected to surcharge loads in non-limited states, with an observed escalation in pressure corresponding to increased surcharge loads. Compression tests on soilbags were conducted to analyze their lateral stress-strain behavior. Insights from these tests facilitated the development of a predictive method for estimating lateral pressure on soilbag reinforced retaining walls under similar conditions. This method, rooted in the principle of force equilibrium in differential elements, has its accuracy and reliability substantiated by the alignment of its predictions with the model test outcomes.

This study simulated the effects of direct predatory pressure, indirect predatory pressure, and conspecific injury signals on the sea cucumber (Apostichopus japonicus) to determine changes in the activity of immune defense enzymes (lysozyme, acid phosphatase, alkaline phosphatase) and antioxidant stress enzymes (catalase, superoxide dismutase, malondialdehyde). Samples of sea cucumber juveniles were collected at 3 hours, 12 hours, 72 hours, and 96 hours post-predatory stress, and six enzymes related to immune defense and antioxidant stress were selected for activity assays, namely lysozyme (LZM), acid phosphatase (ACP), alkaline phosphatase (AKP), superoxide dismutase (SOD), catalase (CAT), and malondialdehyde (MDA). The results indicated that under direct predatory pressure, the activity of catalase in sea cucumbers was significantly higher than that of the control group at 3 hours (P < 0.05), while the activities of acid phosphatase, alkaline phosphatase, and catalase were significantly lower at 72 hours (P < 0.05). Under indirect predatory pressure, the activity of malondialdehyde in sea cucumbers was significantly higher than that of the control group at 12 hours (P < 0.05), the activity of alkaline phosphatase was significantly higher at 72 and 96 hours (P < 0.05), catalase was significantly lower at 72 hours, and the activity of superoxide dismutase was significantly higher at 72 hours (P < 0.05). Under the influence of conspecific injury signals, the activity of malondialdehyde in sea cucumbers was significantly higher than that of the control group at 12 hours (P < 0.05), and the activity of superoxide dismutase was significantly higher at 96 hours (P < 0.05). The sea cucumber enhanced its antioxidant capacity 3 hours after facing the predator, while its immune defense mechanism was suppressed at 72 hours. When facing indirect predatory pressure, the sea cucumber may have made immune and antioxidant preparations for the arrival of unknown risks. The experimental results show that predatory pressure has a significant impact on the immune and antioxidant functions of sea cucumbers, which may be related to the physiological state and environmental adaptability of the sea cucumber. This study provides a new perspective for understanding how sea cucumbers cope with predatory pressure in the natural environment and offers theoretical support for the cultivation management of sea cucumbers.

Abstract: In the past years, lithium-ion solid-state batteries demonstrated significant advancements regarding such properties as safety, long-term endurance, and energy density. The properties of these depend on solid-state electrolytes and especially ionic transport interfacial transport with cathode or anode materials. Solid-state electrolytes based on lithium halides offer new opportunities due to their unique features such as broad electrochemical stability window, high lithium-ion conductivity, and elasticity at close to melting point temperatures that help to improve lithium-ion transport at interfaces. A comparative study of lithium indium halide (Li3InCl6) electrolytes syn-thesized by a mechano-thermal method using different optimization parameters revealed a signif-icant effect of ball-milling time, temperature, and pressure on lithium-ion transport. Based on the Electrochemical Impedance Spectroscopy (EIS) data in the temperature range of 25-100 °C, the optimized Li3InCl6 electrolyte phase demonstrates high ionic conductivity reaching 0.98 mS cm−1 at room temperature. However, at 70 °C, phase transformation was observed leading to significant changes in the activation energy for lithium-ion transport. In-situ X-ray diffraction and in-situ/operando X-ray photoelectron spectroscopy techniques confirmed the tempera-ture-dependent behavior of Li3InCl6 synthesized. These observations provide critical information for practical applications of solid-state electrolytes and nanocomposites based on Li3InCl6 within the broad temperature range for lithium-ion solid-state batteries with improved morphology, chemical interactions, and structural integrity.

Faced with difficulties stemming from the complex interactions between tight gas sand bodies and fractures when describing and identifying reservoirs, a composite reservoir model was established. By setting the supply boundary to characterize the superposition characteristics of sand bodies, a mathematical model of unstable seepage in fractured vertical wells in tight sandstone gas reservoirs was constructed considering the factors such as stress sensitivity, fracture density and fracture symmetry. The seepage law and pressure response characteristics of gas well in tight sandstone discontinuous reservoir with stress sensitivity, semi-permeable supply boundary and complex fracture topology were determined, and the reliability of the model was verified. The research results more accurately depict the pressure characteristic curve of the superposed sand body complex fracture vertical well, and provide a more comprehensive model for tight gas production dynamic analysis and well test data analysis, which can more accurately guide the dynamic inversion of reservoir and fracture parameters.

The purpose of this study is to examine the relationship between the institutional investors which can affect financial performance for corporate sustainability on the income smoothing. Therefore, this study focus on the connection between the nature of stock rights and income smoothing in China. For this study, hypotheses were established on the relationship each state-controlled companies, income smoothing, and information equilibrium of individual investors, and empirical analysis was conducted through related variables. The analysis results are summarized in three categories as follows. First, this research finds that state-controlled firms (CONTs) prefer income smoothing activities compared to non-state-controlled firms for the long-term sustainable development of firms using data from 2011 to 2019. Second, this study found out that Institutional investors support the behavior of CONTs to smooth their earnings because this behavior is seen as an attempt by CONTs to convey valuable private information to other investors. Third, we was able to discover that institutional investors' monitoring effect is predominantly driven by pressure-resistant institutional investors. This research complements the lack of empirical research on income smoothing and enable to give a guideline that the type of stock rights is a critical key determinant of participation in income smoothing activities for stable growth and sustainability in the future.

Anticipating future successional forest trends in the face of ongoing global change is an essential conservation target. Mountain forests are especially sensitive to environmental shifts, and their past responses to climatic and anthropogenic (external) drivers may provide a basis for improving predictions of future developments. This paper uses independent high-resolution palynological and paleoclimatic reconstructions to statistically analyze the long-term effects of external drivers on regional forest succession in the central Iberian Pyrenees during the last 500 years. The dominant taxa of these forests (Quercus, Betula, Pinus) showed significant relationships with summer temperature, summer drought and autumn precipitation. Immediate and delayed (by two or more decades) responses of these trees to climatic drivers were identified. Regional succession showed a closed path, starting at the end points around the attraction domain of pine-dominated forests. This trajectory was determined by a trend toward anthropogenic forest clearing (16th to 18th centuries) and a reverse trend of natural forest recovery (18th to 20th centuries). Forest clearing was due to burning, facilitated by drought, and was followed by the expansion of cropping and grazing lands. Forest recovery was fostered by reduced human pressure and rising temperatures. The statistical approach used in this work has unraveled ecological relationships that remained unnoticed in previous works and would be important for predicting future successional trends under changing climates. The reported response lags of individual taxa to climatic drivers may complicate the establishment of reliable ecological relationships and should be addressed in future studies.

A stable driver state is essential in the process of manually transition control, which inevitably occurs in Level 3 automated driving situations. To this end, this paper proposed a CNN algorithm-based driver state monitoring system that uses multi-sensor data such as driver's face image, biometric information, and vehicle behavior information as input. This system calculates the probability of drowsiness for each of the four time periods using a convolutional neural network (CNN) based on ToF camera-based eye blinking, ECG information (pulse rate) embedded in the steering wheel, and vehicle information (steering angle data). In order to build a reliable and high-quality training dataset (Ground Truth) for the CNN algorithm, a baseline was established by matching the driver's face image with the electrocardiogram (ECG) and electroencephalogram (EEG) changes in the drowsy and normal states. In a simulation test of the proposed CNN algorithm using more than 20,000 driver image data acquired using a driving simulator, the TNR was 94.8% and the accuracy was 94.2%. Our proposed method is expected to minimize human errors that may occur when switching control by monitoring inappropriate driver state (drowsiness) in real time.

This study addresses the causal links between external factors and the main hydro-climatic variables. There is a gap in the literature on the description of a complete chain in addressing the structures of direct causal links of solar activity on the terrestrial variables. This is why, the present study uses the extensive facilities of the application of information theory in view of recent advances in different fields. Also, by other methods (e.g. neural networks) first are tested the existence non-linear links of solar-terrestrial influences on hydro-climate system. The results are promising related to the solar impact on terrestrial phenomena which is discriminant in space-time domain. The implications prove robust for determining the causal measure of climate variables under direct solar impact which makes it easier to consider solar activity in climate models, by appropriate parametrizations. This study found that hydro-climatic variables are sensitive to solar impact only for certain frequencies (periods) and these have a coherence with the Solar-Flux only for some lags of the Solar-Flux (in advance).

Pancreatic cancer is one of the most aggressive and lethal forms of cancer, with a five-year survival rate of less than 10%. Despite advances in treatment modalities, the prognosis for pancreatic cancer patients remains poor, highlighting the urgent need for innovative approaches for early diagnosis and targeted therapies. In recent years, there has been significant progress in understanding the molecular mechanisms underlying pancreatic cancer development and progression. This paper reviews the current knowledge of molecular targets for the diagnosis and treatment of pancreatic cancer.

Current adaptive cruise control (ACC) systems adopt fixed desired time headway, which leads to an abrupt speed reduction after being cut-in by a lane changer in front or when changing lanes too close to the new leader. In contrast, human drivers behave differently and feature a variable spacing within 20 or 30 seconds right after a cut-in or lane change. Motivated by the smooth transition found in driver relaxation, the paper aims to incorporate relaxation into ACC systems. Based on the open-source ACC platform, Openpilot, Comma.ai, the paper proposes a feasible relaxation model compatible with current factory ACCs, which has also been tested using a market car with stock ACC hardware. The study further investigates the impact of relaxation ACC on traffic operation. Numerical simulation suggests that incorporating relaxation into ACC can help: i) reduce the magnitude of speed perturbations in both cut-in vehicles and followers; ii) stabilize the lane-changing traffic by reducing the speed variance and prevent the lateral propagation of congestion, and iii) increase the average vehicle speed and capacity in merging traffic.

Abstract: This study aims to analyze the physico-mechanical properties and dynamic models of tissue-simulating hydrogels, specifically the photoacoustic (PA) response signals, by varying the concentrations of polyvinyl alcohol (PVA) and molecular weight (MW). A state space model (SSM) is proposed to study the PVA hydrogels to retrieve the PA-related signal's damping ratio and nat-ural frequency. Nine box-shaped PVA hydrogels containing saline solution were used, with five concentrations of PVA (7, 9, 12, 15, 20%) for MW1 and four for MW2. The results indicated that the concentration of PVA and MW played an important role in the PA wave's amplitude, arrival time, and speed of sound over the hydrogels. The SSM parameters showed that increasing PVA and MW concentrations improved the hydrogels' ability to absorb and transfer energy under the PA effect. These parameters were also found to be correlated with density and modulus of elasticity. Addi-tionally, the concentrations of PVA and MW affected the absorption and optical scattering coeffi-cients. The physical-mechanical properties, including porosity, density, and modulus of elasticity, improved as the concentration of PVA and MW increased. The ultimate goal of this study is to develop hydrogels as phantoms that can be used for tissue simulation and imaging.

This article examines the complex interactions of the multiplier effect within the realm of tourism, with a specific emphasis on national parks. The main objective is to evaluate the multiplier effect within national parks, specifically focusing on Buiratau State National Nature Park in Kazakh-stan as a case study. The multiplier effect is a fundamental principle in the field of economic analysis. Economic multiplier effect is the term used to describe the occurrence when an initial infusion of spending in a certain industry leads to subsequent rounds of extra and sustainable economic activity. In the context of national parks, this phenomenon arises when visitor expendi-tures result in several favorable consequences, including increased employment, infrastructure advancement, and general economic expansion. The article seeks to measure the multiplier effect of tourism activities in Buiratau State National Nature Park through a thorough assessment. This entails examining several variables and datasets pertaining to visitor expenditure and its influ-ence. The study contributes to the existing literature by examining a recently constructed national park in a developing country. It compares the findings of this park with well-established national parks in other areas, emphasizing the distinct problems and opportunities it presents. Further-more, the research presents a methodological framework for evaluating the multiplier effect of national parks, which may be utilized in comparable contexts. This research ultimately enhances our comprehension of the economic implications of national parks and emphasizes their function as drivers for local and regional growth.

Laser Powder Bed Fusion (L-PBF)-based manufacturing is a growing area of research, with a particular focus on evaluating constraints in printed products. This research emphasises the importance of considering various factors—including mechanical properties and support structures—that influence the final product during the design phase. Specifically, the design of microchannel heat exchangers is highlighted, where all constraints are critical. This article will present a method for analysing channel pressure limitations and report findings about mechanical properties loss from examining tube porosity. This includes a summary of results and the establishment of an experimental device system.

In this paper, we found a new model for compact star with charged anisotropic matter distribution considering an extended version of the Chaplygin equation of state. We specify a particular form of the metric potential Z(x) that allows us to solve the Einstein-Maxwell field equations. The obtained model satisfies all physical properties expected in a realistic star such that the expressions for the radial pressure, energy density, metric coefficients, measure of anisotropy and the mass are fully well defined and are regular in the interior of star. The solution obtained in this work can have multiple applications in astrophysics and cosmology.

The Hertzian contact theory, as well as most of the other classical theories of normal and tangential contact, provides displacements and the distribution of normal and tangential stress components directly in the contact surface. However, other components of the full stress tensor in the material may essentially influence the material behaviour in contact. Of particular interest are principal stresses and the equivalent von Mises stress, as well as the gradient of the hydrostatic pressure. For many engineering and biomechanical problems, it would be important to find these stress characteristics at least in the contact plane. In the present paper, we show that the complete stress state in the contact plane can be easily found for axially symmetric contacts under very general assumptions. We provide simple explicit equations for all stress components and the normal component of the gradient of hydrostatic pressure in the form of one-dimensional integrals.

The optimization of the pile driver frame is very important to the overall performance of the pile driver. This paper takes the large body structure of a model of hydraulic static pile driver as the research object. ANSYS APDL finite element software is used to perform static analysis and sensitivity analysis on the large body structure of the pile driver. On the premise of meeting the design requirements, according to the most dangerous working conditions of the pile driver, the size optimization of the frame structure of the pile driver is carried out based on sensitivity analysis. The mathematical model is established with the plate thickness as the design variable, the strength and stiffness of the body structure as the constraints, and the minimum mass of the body structure as the objective function. The optimization results show that the optimization design model based on sensitivity analysis not only meets the strength and stiffness conditions of the large structure, but also reduces the structural quality by 22.1% and greatly saves the production cost.

The dynamic response of the shed-tunnel structure under rockfall impact attracts much attention in recent years. However, the research on the dynamic response of the shed-tunnel structure under rockfall impact mostly focuses on the rockfall single impact, while in practical engineering, the shed-tunnel structure often encounters the rockfall repeated impacts during its service life. Therefore, this research focuses on exploring the dynamic response characteristics of the shed-tunnel structure under the rockfall repeated impacts. First of all, based on the model test of the shed-tunnel under rockfall impact as a reference, the FEM (Finite Element Method)-SPH (Smoothed Particle Hydrodynamics) coupling numerical calculation model is established based on ANSYS/LS-DYNA finite element code. The numerical simulation of the dynamic response of the shed-tunnel structure under rockfall impact is realized, and the rationality of the model is verified. Then, with this model and the full restart technology of LS-DYNA code, the effects of four factors, e.g. rockfall mass, rockfall impact velocity, rockfall impact angle and rockfall shape, on the impact force and impact depth of the buffer layer, the maximum plastic strain and axial force of the rebar, the shed roof vertical displacement and the shed-tunnel plastic strain are studied. These results show that the cumulative deformation and damage of the shed-tunnel structure caused by the rockfall repeated impacts play an important role in the destruction of the shed-tunnel structure, and the special attention should be paid to this issue.

Abstract: Coal bed methane (CBM) reservoirs are complex systems whose properties differ from those of conventional reservoirs. Coal seams are dual-porosity systems that comprise the porosities of the matrix and cleat system. Gas in the coal seams can be stored as free gas in the cleat system and as adsorbed gas in the porous medium. The flow mechanisms of the natural gas through the formation include desorption, diffusion, and Darcy’s flow regimes. The permeability of CBM reservoirs is more sensitive to pressure variations than conventional gas reservoirs. To study the flow behavior of CBM reservoirs it is mandatory to use a model that considers their unique characteristics. The objective of this study was to propose a physical and mathematical model of production performance for horizontal wells in CBM reservoirs whose permeability is dependent on pressure. A solution for the model was obtained by applying Pedrosa´s transformation, perturbation theory, Laplace transformation, the point source method, and Sthefest´s algorithm. The solution to this problem was validated with previous work thoroughly. The type curves of the model were built and the pressure transient behavior of the model was analyzed and discussed. The effects of several parameters on pressure behavior were also discussed.

In cosmology, the cosmic curvature $K$ and the cosmological constant $\Lambda$ are two most important parameters, whose values have strong influence on the behavior of the universe. By analyzing the energy-momentum tensor and equations of state of ideal gas, scalar, spinor and vector potential in detail, we find that the total mass density of all matter is always positive, and the initial total pressure is negative. Under these conditions, by qualitatively analyzing the global behavior of the dynamical equation of cosmological model, we get the following results: (i) $K= 1$, namely, the global spatial structure of the universe should be a 3-dimensional sphere $S^3$. (ii) $0\le\Lambda < 10 ^ {-24} {\rm ly} ^ {-2}$, the cosmological constant should be zero or an infinitesimal. (iii) $a(t)>0$, the initial singularity of the universe is unreachable, and the evolution of universe should be cyclic in time. This means that the initial Big Bang is impossible at all. Since the matter components considered are quite complete and the proof is very elementary and strict, these logical conclusions should be quite reliable. Obviously, these conclusions will be much helpful to correct some popular misconceptions and bring great convenience to further research other problems in cosmology such as property of dark matter and dark energy.

The clinical relationship between diabetes and inflammation is well-established. Various branches of science independently have confirmed that disrupting oxidant-antioxidant equilibrium and elevated lipid peroxidation could be a potential mechanism for chronic kidney disease associated with Type 2 diabetes mellitus (T2DM). Under diabetic condition, hyperglycemia, especially inflammation, and increased reactive oxygen species generation are bidirectionally associated. Inflammation, oxidative stress and tissue damage are believed to have a role in the development of diabetes. Although the exact mechanism underlying the oxidative stress and its impact on diabetes progression remains uncertain, the hyperglycemia-inflammation-oxidative stress interaction clearly plays a significant role in onset and progression of vascular disease, kidney disease, hepatic injury, pancreas damage and, therefore holds promise as a therapeutic target. Evidence strongly indicates that the use of multiple antidiabetic medications therapy fails to achieve the normal range for glycated hemoglobin target, signifying treatment resistant diabetes. Antioxidants with polyphenols are considered useful as adjuvant therapy for their potential anti-inflammatory effect and antioxidant activity. We aimed to analyze the current major points reported in preclinical in vivo and clinical studies of antioxidants in the prevention or treatment of inflammation in T2DM. Then, we will share our speculative vision of the future diabetes clinical trials.

Outdoor air pollution is a leading cause of death and premature death globally. Motorcycle-taxi drivers were most at risk associated with occupational exposure to ambient air pollution in urban areas. Therefore, a cross-sectional study was conducted to determine the influencing factors and prediction of lung function impairment in 308 motorcycle-taxi drivers living in Bangkok and adjacent provinces between February and June 2022. The study design included: data collection using questionnaires applied from the Thai version of ATS-DLD-78A: American Thoracic Society Division of Lung Diseases and Department of Disease Control, Ministry of Public Health, Thailand; a collection of respirable dust, and ambient air pollution parameters measured by per-sonal air sampling pump and real-time air quality index (AQI) station, and lung function determined by the spirometer. The results showed that 14 factors were significantly associated with lung function impairment (p<0.05). Apparently, seven influencing factors showing the most association were included: gender, the height of the subjects, history of allergies, exposure to respirable dust, mask types, helmet types, and family history of lung disease. The lung function impairment of motorcycle-taxi drivers was significantly predicted in 28.1% by regression analysis of these seven variables (R2=0.281). Therefore, this is the first report on influencing factors and prediction of lung function impairment among motorcycle-taxi drivers. These findings would be very useful for preventing and controlling measure ambient air pollution, setting policies and strategies to mitigate the risks for motorcycle-taxi drivers and the other ex-posed population.

Synthetic chalcomenite-type cupric selenite CuSeO₃∙2H₂O has been studied at room temperature under compression up to pressures of 8 GPa by means of single-crystal X-ray diffraction, Raman spectroscopy, and density-functional theory. According to X-ray diffraction, the orthorhombic phase undergoes an isostructural phase transition at 4.0(5) GPa with the thermodynamic character being first-order. This conclusion is supported by Raman spectroscopy studies which have detected the phase transition at 4.5(2) GPa and by the first-principles computing simulations. The structure solution at different pressures has provided information on the change with pressure of unit-cell parameters as well as on the bond and polyhedral compressibility. A Birch-Murnaghan equation of state has been fitted to the unit-cell volume data. We found that chalcomenite is highly compressible with a bulk modulus of 42 – 49 GPa. The possible mechanism driving changes in the crystal structure is discussed, being the behavior of CuSeO₃∙2H₂O mainly dominated by the large compressibility of the coordination polyhedron of Cu. On top of that, an assignation of Raman modes is proposed based upon density-functional theory and the pressure dependence of Raman modes discussed. Finally, the pressure dependence of phonon frequencies is also reported.

Climate change causes weather extremes to rise in frequency and severity, which could have detrimental effects on human life, property and livelihood activity. There is significant uncertainty about the influences of anthropogenic climate change on the occurrence and severity of small-scale, sudden onset weather phenomena such as hailstorms and subsequent loss and damage. Yet, several studies indicate that there is an apparent stable connection between hailstorm activity and hailstorm damage. Severe hailstorm events are observed in Bangladesh in recent years, which are, in fact, rapid-onset disasters but low exposure in terms of giving government response and media consideration. Hence this study examines potential impacts and management strategies for loss and damage resulting from hailstorm events among smallholder farmers in Kurigram District's Phulbari Upazila of Bangladesh. Firstly, the direct and long term economic and non-economic loss and damage caused by the hailstorm on human well-beings and livelihoods were assessed. Then, the study evaluated the current adaptation, coping, management and response strategies at the institutional and community level in the context of such extreme events. Finally, a regulatory framework and implementation approaches had suggested achieving the country's resilience against disaster and climate change-induced loss and damage. Participatory Vulnerability Analysis, Key Informant Interviews and Sample Surveys accumulated the primary data for the study. In addition, secondary data were collected through analysis of literature, published and unpublished scientific articles and media reports, etc. This research outcome will help countries develop a guideline to address climate change and disaster-related loss and damage.

Among the sensors necessary to equip vehicles with an autonomous driving system, there is a tacit agreement that cameras and some type of radar would be essential. The ability of radar to spatially locate objects (pedestrians, other vehicles, street furniture and traffic signs) makes it the most economical complement to the cameras in the visible spectrum, in order to give the correct depth to scenes. From the echoes obtained by the radar, some data fusion algorithm will try to locate each object in its correct place within the space surrounding the vehicle. In any case, the usefulness of the radar will be determined by several performance parameters, such as its aver-age error in distance, the maximum errors and the number of echoes per second it can provide. In this work we have tested experimentally the AWR1843 MIMO radar from Texas Instruments to measure those parameters.

Partially automated driving functions (SAE Level 2) can control a vehicle's longitudinal and lateral movements. However, taking over the driving task involves automation risks that the driver must manage. In severe accidents, the driver's ability to avoid a collision must be assessed, considering their expected reaction behavior. The primary goal of this study is to generate essential data on driver reaction behavior in case of malfunctions in partially automated driving functions for use in legal affairs. A simulator study with two scenarios involving 32 subjects was conducted for this purpose. The first scenario investigated driver reactions to system limitations during cornering. The second scenario examined driver responses to phantom braking caused by the AEBS. As a result, the first scenario shows that none of the subjects could control the situation safely. Due to partial automation, we could also identify a new part of the reaction time, the hands-on time, which leads to increased steering reaction times of 1.18 to 1.74 seconds. In the second scenario, we found that 25 of the 32 subjects could not override the phantom braking by pressing the accelerator pedal, although 16 subjects were informed about the system analog to the actual vehicle manuals. Overall, the study suggests that the current legal perspective on vehicle control and the expected driver reaction behavior for accident avoidance should be reconsidered.

To solve the problem of smooth switching between car-following model and lane-changing model, the Intelligent Driver Model (IDM) for a single lane was used to study the driver's behavior switching mechanism of normally following, generating intentions to change lanes, creating space and speed gains, and performing lane change. In the case of sufficient lane-changing space and speed gains, the ego vehicle's intention to change lane was considered to solve the switching boundary between car-following behavior and lane-changing behavior, which is also the IDM failure point. In the event that there is no lane-changing gains, the IDM was optimized by incorporating the constraint components of the target lane vehicles in conjunction with the actual motion state of the ego vehicle, and the Stepless Switching Intelligent Driver Model (SSIDM) was constructed. Drivers' natural driving information was collected and scenario mining was performed on structured roads. On the basis of the collected data, an elliptic equation was used to fit the behavior switching boundary, and the two component balance coefficients of the front and rear vehicles on the target lane were identified. According to the test set verification results, the Mean Square Error (MSE) of the SSIDM is 2.172, which is 57.98% less than that of the conventional single-lane IDM. The SSIDM can accomplish stepless switching comparable to driver's behavior between the car-following behavior and the lane-changing behavior, with greater precision than IDM.

The vehicular technology has integrated many features in the system, which enhances the safety and comfort of the user. Among these features, heating, ventilation, and air conditioning (HVAC) is the only feature that maintains the set cabin air temperature (CAT). The user’s command drives the set CAT, and the thermostat provides feedback to the HVAC to maintain the set CAT. The CAT is increased by extracting the heat from the engine surface produced by the fuel combustion, whereas the CAT is reduced by the known processes of the air conditioning system (ACS). Therefore, the CAT driven by the user’s command may not be optimal, and estimating the optimal CAT is still unsolved. In this work, the user was allowed to input a range for CAT instead of a single value. Optimal HVAC criteria were defined, and the CAT was estimated by performing iterative analysis in the user-selected range satisfying the criteria. The HVAC criteria were defined based on two measurable parameters: air conditioning refrigerant fluid pressure (ACRFP) and engine surface temperature (EST) empirically defined as the vector CATOP. In this article, a NARX DL model by mapping the vehicle-level vectors (VLV) to predict the CATOP in real-time using field data obtained from a 2020 Cadillac CT5 test vehicle. Utilising the DL model, CATOP for future time steps were predicted by varying the CAT in the definite range and applying HVAC criteria. Thus, an optimal set CAT was estimated, corresponding to the optimal CATOP defined by the HVAC criteria. We performed the validation of the DL model for multiple datasets using traditional statistical techniques, namely, signal-to-noise ratio (SNR) values, first-order derivatives (FOD), and root-mean-square error (RMSE).

Abstract: Traffic collisions cause a huge problem of public health in low and middle income countries.. The safe system approach is generally considered as the leading concept on the way to road safety. Based on the fundamental premise that humans make mistakes, the overall traffic system should be ‘forgiving’. Sustainable safe road design is one of the key elements of the safe system approach. However, the road design principles behind the safe system approach are certainly not leading in today’s infrastructure developments in most LMICs. Cities are getting larger and road networks are expanding. In many cases, existing through-roads in local communities are up-graded, resulting in heavy traffic loads and high speeds on places, that are absolutely not suited for this kind of through-traffic. Furthermore a safe system would require that functional design properties of cars and roads would be conceptually integrated, which is not the case at all. Although advanced driver assistance systems are on their way of development for quite a long period, their potential role in the safe system concept is mostly unclear and at least strongly underexposed. The vision on future cars is dominated by the concept of automation. This paper argues that the way to self-driving cars, should take a route via the concept of guidance, i.e. vehicles that guide drivers, both on self-explaining roads and on more or less unsafe roads. Such an in-vehicle support system may help drivers to choose transport mode, route and speed, based on criteria related to safety and sustainability. It is suggested to develop a driver assistance system using relatively simple and cheap technologies, particularly for the purpose of use in LMICs. Such a GUIDE (Generic User Interface for Driving Evolution) may make roads self-explaining - not only by their physical design characteristics - but also by providing in-car guidance for drivers. In future the functional characteristics of both cars and roads should be conceptualized into one integrated safe system, in which the user plays the central role. As such GUIDE may serve as the conceptual bridge between vehicle and roadway characteristics. It is argued that GUIDE is necessary to bring a breakthrough in road safety developments in LMICs and also give an acceleration towards zero fatalities in HICs.

In the context of the COVID-19 epidemic, and on the basis of the Theory of Dynamical Systems, we propose a simple model for the expansion of contagious diseases, with a particular focus on viral respiratory tracts. The infection develops through contacts between contagious and exposed people, with a rate proportional to contact duration and turnover, inversely proportional to the efficiency of protection measures, and balanced by the average immunological response. The obvious initial exponential increase is readily hindered by the size reduction of the exposed population. The system converges towards a stable attractor whose value is expressed in terms of the ratio C/D of contamination vs decay factors. Decreasing this ratio below a critical value leads to a tipping point beyond which the epidemic is over. By contrast, significant values of C/D may bring the system through a bifurcating hierarchy of stable cycles up to a chaotic behaviour.

A qualitative analysis of pressure acting within the human eye is presented. The situation emerging within the human eye in rest and human eye of accelerated/training person should be distinguished. When the person is in rest, the hydrostatic pressure is much larger than the Laplace pressure. The dynamic (Bernoulli pressure) emerging from intraocular flows in this case is negligible. The situation is rather different for accelerated or decelerated person. In this case, the dynamical pressure and the water hammer pressure become dominant. Under certain circumstances, the water hammer pressure may be larger than the ultimate tensile strength of retina, choroid and the Bruch membrane‐choroid complex, which may possibly affect the retina. As a recommendation: physical training, which is not accompanied with ultimate acceleration/acceleration of the body, may be performed after posterior vitreous detachment; however, potentially traumatic activities such as boxing or competitive diving should be avoided.

This paper proposes a Case-Based Reasoning (CBR) system to contribute to reinforce the sustainable performance of an environmental management system. The CBR system aims to support the decision-making process to select environmental management actions aimed at reducing risky trends of the environmental state of a region. The CBR system takes advantage of a set of situation-solution pairs called cases, which are stored in a memory and then retrieved as candidates to solve new problems. Situations in this work are represented by a set of risky trends of the following key environmental variables: CO2 emissions, Air-Quality, Loss of Vegetation Cover, Water Availability, and Solid Waste, whose combination damage the environmental state quality of a region. Meanwhile, solutions are represented by a set of environmental management actions. Similar situations to a given current situation are retrieved from the memory of cases and then their solutions are combined, through an adaptation mechanism, until the solution of the current problem is obtained. We used risky trends derived from real data related to the environmental states of a Mexican region to test the proposed CBR system. The results obtained provided insights into the potential of CBR systems to support the decision-making process to select environmental management actions aimed at reducing risky trends of current environmental states.

From experimental studies of protein folding, it is now clear that there are two types of folding behavior, i.e., two-state folding and non-two-state folding, and understanding the relationships between these apparently different folding behaviors is essential for fully elucidating the molecular mechanisms of protein folding. This article describes how the presence of the two types of folding behavior has been confirmed experimentally, and discusses the relationships between the two-state and the non-two-state folding reactions, on the basis of available data on the correlations of the folding rate constant with various structure-based properties, which are determined primarily by the backbone topology of proteins. Finally, a two-stage hierarchical model is proposed as a general mechanism of protein folding. In this model, protein folding occurs in a hierarchical manner, reflecting the hierarchy of the native three-dimensional structure, as embodied in the case of non-two-state folding with an accumulation of the molten globule state as a folding intermediate. The two-state folding is thus merely a simplified version of the hierarchical folding caused either by an alteration in the rate-limiting step of folding or by destabilization of the intermediate.

The Thermodynamic Formalism provides a rigorous mathematical framework to study quantitative and qualitative aspects of dynamical systems. At its core there is a variational principle and corresponding, in its simplest form, to the Maximum Entropy principle, used as a statistical inference procedure to represent, by specific probability measures (Gibbs measures), the collective behaviour of complex systems. This framework has found applications in different domains of scienThe Thermodynamic Formalism provides a rigorous mathematical framework to study quantitative and qualitative aspects of dynamical systems. At its core there is a variational principle and corresponding, in its simplest form, to the Maximum Entropy principle, used as a statistical inference procedure to represent, by specific probability measures (Gibbs measures), the collective behaviour of complex systems. This framework has found applications in different domains of science, in particular, has been fruitful and influential in neurosciences. In this article, we review how the Thermodynamic Formalism can be exploited in the field of theoretical neuroscience, as a conceptual and operational tool, to link the dynamics of interacting neurons and the statistics of action potentials from either experimental data or mathematical models. We comment on perspectives and open problems in theoretical neuroscience that could be addressed within this formalism.ce, in particular, has been fruitful and influential in neurosciences. In this article, we review how the Thermodynamic Formalism can be exploited in the field of theoretical neuroscience, as a conceptual and operational tool, to link the dynamics of interacting neurons and the statistics of action potentials from either experimental data or mathematical models. We comment on perspectives and open problems in theoretical neuroscience that could be addressed within this formalism.

Globally, road traffic collisions cause over a million deaths annually, with pedestrians accounting for nearly one-quarter (23%) of these fatalities. This casualty proportion highlights the critical importance of adhering to traffic regulations. This study analyzes the factors influencing driver yielding behavior at midblock crosswalk improvements, comparing (1) a typical zebra crossing (C1) and (2) an intelligent signalized crosswalk (C2). The study used video-based observational data to investigate driver behaviors and factors influencing driver behaviors. The study applied multinomial logistic regression to formulate yielding behavior models. The results indicate that the number of traffic lanes, width of the traffic lanes, width and length of the crosswalk, vulnerable group, the number of pedestrian crossings, pedestrian crossing time, the number of vehicles approaching a crosswalk, speed of vehicle, headway, the post-encroachment time (PET) between vehicles and pedestrian, and roadside parking are the significant factors influence yielding behavior. These findings provide a better understanding of the factors influencing driver yielding behavior and propose measures to set proper physical improvements (e.g., curb extensions, raised pedestrian platforms, and pedestrian fencing), enforcement (e.g., parking restriction, speed violation detection), public awareness campaigns, and education initiatives.

Advanced paternal age increases the risk of transmitting de novo germline mutations, particularly missense mutations activating the receptor tyrosine kinase (RTK) signaling pathway, exemplified by the FGFR3 mutation linked to achondroplasia (ACH). This risk is attributed to the expansion of spermatogonial stem cells carrying the mutation, forming sub-clonal clusters in the ageing testis, thereby increasing the frequency of mutant sperm and the number of affected offspring from older fathers. While prior studies proposed a correlation between sub-clonal cluster expansion in the testis and elevated mutant sperm production in older donors, limited data exist on the universality of this phenomenon. Our study addresses this gap by examining the testis expansion patterns, as well as increases of mutations in sperm for two FGFR3 variants: c.1138G>A (p.G380R) and c.1948A>G (p.K650E)- associated with ACH or thanatophoric dysplasia (TDII), respectively. Unlike the ACH mutation, which showed sub-clonal expansion events in an aged testis and a significant increase of mutant sperm with the donor’s age, the TDII mutation formed sub-clonal clusters, but exhibited reduced transmission into sperm and no significant age-related increase. The mechanism behind this divergence remains unclear, suggesting potential pleiotropic effects of aberrant RTK signaling in the male germline, possibly hindering differentiation requiring meiosis. This study provides further insights into transmission risks of micro-mosaics associated with advanced paternal age in the male germline.

We present a design of electrostatic comb driver to improve and investigate its actuation performance. The proposed electrostatic comb actuator (ECA) is composed of two set of interdigitated comb microstructures, the inner combs are fixed to form the fish-bone microstructures and the outer combs are movable and connected to crab-leg flexure beams microstructures. The ECA is investigated to optimize the actuation performance by changing the comb shape and the intersection angle of crab-leg flexure beams. The comb shapes are compared between the traditional rectangle shape and the trapezoid shape, while the intersection angles of crab-leg flexure beams are compared between 45°, 60°, and 90° on the influences of ECA displacement and stability characteristics. These parameters are investigated for their impacts on the dynamic comb displacement and driving voltage. Under the condition of a driving DC bias voltage of 100 volts, the ECA displacement is firstly increased and then gradually decreased by increasing the comb finger length. The maximum displacement of ECA with trapezoid comb is 47.2 μm while that of ECA with rectangle comb is 22.4 μm. By using trapezoid comb shape to replace the rectangle comb under the same conditions, the ECA displacement is improved 2-fold. To enhance the stability of ECA system, the intersection angle of 90˚ of crab-leg flexure beams shows highest stability that is great better than the intersection angle of 45° and 60° of crab-leg flexure beams by increasing the driving different DC bias voltage to 100 volts on ECA. The stability of the ECA with the intersection angle of 90° of crab-leg flexure beams is enhanced 1.1-fold and 1.4-fold compared to that of 45° and 60° of crab-leg flexure beams, respectively. This design provides an optimized approach to the electrostatic comb actuator that can be used expansively in the gyroscope, motion sensor, position sensor, imaging sensor, optical sensor, and so on.

Online transportation services, initially presented as an innovative employment approach by categorizing workers as 'independent contractors', have come to be recognized for their exploitative nature. The notion of 'flexibility' suggests that workers have the autonomy to tailor their hours and location according to their income goals. However, this disguises the true situation for informal workers who lack rights and protections. This study delves into these issues from a psychological standpoint to uncover the mental and emotional interplay between the motivations and exploitation experienced by online drivers affiliated with multiple platforms. The study adopts a qualitative methodology with a phenomenological lens. Data was gathered through thorough interviews, observations, and document analysis, with Interpretative Phenomenological Analysis (IPA) employed as the data analysis technique. The study's participants were five male multi-platform online drivers from the Special Region of Yogyakarta, ranging in age from 18 to 64, and had been associated with at least two platforms for more than a year. The findings highlight two primary themes: firstly, the decision to join multiple platforms is chiefly driven by economic reasons, including a decline in orders, daily earnings, bonus incomes, and the conclusion of the initial profitable phase. Secondly, the exploitative conditions are linked to the platforms' algorithms, which exert control and influence the psychological state of the drivers. Nonetheless, the participants have developed effective strategies to manage fatigue, anxiety, and stress.

The devastating COVID-19 pandemic forced academia to go virtual. Educational institutions around the world have stressed online learning programs in the aftermath of the pandemic. However, because of insufficient access to ICT, a substantial number of students failed to harness the opportunity of online learning. This study explores the latent digital divide exhibited during the COVID-19 pandemic while online learning activities are emphasized among Bangladeshi students. It also explores the digital divide exposure and the significant underlying drivers of the divide. A cross-sectional survey was employed to collect quantitative data mixed with open-ended questions to collect qualitative information from the student community. The findings revealed that despite the majority of students have physical access to ICT but only 32.5% of students could attend online classes seamlessly, 34.1% of the students reported the data prices as the critical barrier, and 39.8% of students identified the poor network infrastructure is the significant barrier for them to participate in online learning activities. This paper aimed to explore the underlying issues of the digital divide among Bangladeshi students to assist relevant stakeholders (e.g., the Bangladesh government, Educational Institutions, Researchers) in providing the necessary insights to arrange for students to undertake online learning activities successfully.

Community co-creation is increasingly crucial to the building of sustainable societies. Communities must proactively and independently create value chains in the face of many wicked problems. However, practical frameworks and tools for facilitating community co-creation require further development. As such, for this paper, we propose a theoretical framework for analyzing community co-creation value chain mechanisms based on a narrative review of literature on Collective Impact, social impact assessment, and Community Capital from the perspective of collective impact, a framework with a fair amount of previous research. We argue for the importance of applying knowledge of social impact assessment, particularly for the collective impact conditions of common agenda and shared measurement system. We discuss its relationship with the Theory of Change and the use of systems thinking to mitigate the subjectivity and arbitrariness of design thinking. Furthermore, we emphasize the value of employing the community capital concept as a framework for analyzing interrelationships among elements. By integrating multiple concepts, we enhance the collective impact framework and outline potential avenues for future research on analyzing and effectively implementing co-creation value chain mechanism in a community-based approach.

Background: High blood pressure (BP) has been implicated as a major risk factor for cardiovascular diseases in several global populations, including in individuals of African ancestry. Despite the elevated burden of high BP-induced cardiovascular diseases in Africa and other global populations with African ancestry, limited genetic studies have been carried out to explore the genetic machinery driving this phenomenon. Methods: We performed univariate and multivariate analyses using Genome-wide association studies (GWAS) and summary statistics data of 77,850 individuals of African ancestry for systolic (SBP) and diastolic blood pressure (DBP) traits. The six independent cohorts used included individuals derived from the African Partnership for Chronic Disease Research (APCDR), the UK Biobank, and the Million Veteran Program (MVP). Subsequently, we annotated, prioritized, visualized, and interpreted our meta-analyses results using FUMA, to gain further insight into the molecular mechanism(s) that contribute to the genetics of BP traits. Finally, loci attaining genome-wide significance, GWS (p<5x10-8) were also followed up with Bayesian fine-mapping to identify potential causal variants. Results: Our meta-analyses altogether identified 350 GWAS SNPs for SBP (166 SNPs) and DBP (184 SNPs, including two novel loci) whilst our multivariate GWAS method identified 166 SNPs (including three novel loci). Interestingly, in FUMA there was significant tissue enrichment of up-regulated differentially expressed genes (DEGs) in the sigmoid and transverse colon for SBP, as well as 10 significant gene sets from MAGMA gene set analyses, However, for DBP, no significant DEGs nor gene sets in MAGMA were found; instead, in DBP for gene property analysis for tissue specificity nine candidates were found to be significant and all nine were in different brain regions. Finally, Bayesian fine-mapping revealed that only 11 variants from the lead SNPs had >50% posterior probability (PP) of being causal and they included novel variant rs562545 (MOBP, PP = 77%) and 10 other previously published variants. Conclusion: Our results demonstrate the importance of performing GWAS in large sample sizes of global populations of African ancestry, including continental Africans; which yield novel insights, from novel loci to novel pathways/tissue expression candidates. Large-scale genomic datasets are required to enhance further discovery and fine-mapping of high-risk loci/variants in highly susceptible groups for cardiovascular disease and other related traits. Our study highlights the need for diversity in genetic research and the importance of expanding large GWASs to include ancestrally diverse populations.

The many-body problem in quantum physics originates from the difficulty of describing the non-trivial correlations encoded in the exponential complexity of the many-body wave function. Motivated by the Giuseppe Carleo's work titled solving the quantum many-body problem with artificial neural networks [Science, 2017, 355: 602], we focus on finding the NNQS approximation of the unknown ground state of a given Hamiltonian $H$ in terms of the best relative error and explore the influences of sum, tensor product, local unitary of Hamiltonians on the best relative error. Besides, we illustrate our method with some examples.

The influence of linear and nonlinear modes of ADC driver on the operational amplifier (Op-Amp), which has different values of maximum output voltage slew rate, on the effective number of bits of ADC is considered. It is shown that the effective number of bits of ADC when op-amps on bipolar transistors with input signal amplitudes exceeding 50-100 mV is determined by the nonlinear modes of its input differential stage.

SHANK3 encodes scaffold protein involved in postsynaptic receptor density in glutamatergic synapses, including those in the parvalbumin (PV)+inhibitory neurons – the key players in generation of sensory gamma oscillations, such as 40-Hz auditory steady-state response(ASSR). Here we describe a clinical and neurophysiological phenotype of a 15-years old girl (SH01) with microduplication of 16389 bp in 22q13.33, affecting the SHANK3 gene in comparison to typically developing children (n=32). EEG were recorded during the binaurally presentation of 40-Hz clicks’ trains lasting for 500 ms with inter-trial intervals 500-800 ms. SH01 was diagnosed with mild mental retardation and learning disabilities(F70.88) and had problems with reading and writing, as well as smaller vocabulary than TD peers. Her clinical phenotype generally resembled the phenotype of previously described patients with 22q13.33 microduplication. SH01 had mild autistic symptoms but below the threshold for ASD diagnosis. No seizures or MRI abnormalities were reported. While SH01 had relatively preserved auditory event-related potential(ERP) with slightly attenuated P1, her 40-Hz ASSR was totally absent significantly deviating from TD’s ASSR. Absence of 40-Hz ASSR in patient with microduplication, affected SHANK3 gene, indicates deficient temporal resolution of the auditory system, that might underlie language problems, and represent neurophysiological biomarker of SHANK3 abnormalities.

A numerical method has been presented to simulate hypervelocity impacts into metal targets. The target is a rectangular prism and positioned at various inclined angles relative to the impact direc-tion, while four different projectile such as square prism, triangular prism, truncated cone and ogival shape are chosen. With this numerical model we aim to evaluate the risk of orbital debris impacting space structures in the design of shield systems for protection against hypervelocity impacts in space. To explore the geometric influences on hypervelocity impact, various projec-tile/target configurations are simulated using the Material Point Method. The Johnson–Cook plas-ticity model with a failure criterion is employed alongside Mie-Grüneisen's equation of state. Our analysis results reveal that the structure of debris cloud formations, scattering behavior of the ejected particle from both front and rear faces and penetration depth measures are significantly influenced by the projectile shape and impact angles.

A structure based analysis of the pion’s decay path reveals that neutrinos can show up in three eigenstates. It requires a proper understanding of the nature of charged leptons, such as why the loss of binding energy stops the lepton generation at the tauon level. The analysis quantifies this binding energy in terms of the weak interaction strength as embodied by the weak interaction boson and the strength of the energetic background field as embodied by the Higgs boson. Next to this it is shown that a reconstruction of Fermi’s neutrino theory allows a quantitative assessment of the Fermi constant straightforwardly from the weak interaction strength. The article ends with the conclusion that neutrino oscillation is not a physical phenomenon, but, instead, a measurement interpretation induced from projecting the statistical behaviour of a multi-particle ensemble onto a single particle.

We study the changes in quantum Fisher information (QFI) values for one quantum system consisting of a superposition of W and GHZ states. In a recent work [6], QFI values of this mentioned system studied. In this work, we extend this problem for the changes of QFI values in some noisy channels. We show the change in QFI depending on noise parameters. We report interesting results for different type of decoherence channels.

The increasing growth in road users who are unfamiliar with traffic rules and regulations provides a serious safety problem for Pakistani traffic conditions. This study has two main objectives. First, it seeks to validate the reliability and applicability of the Dula Dangerous Driving Index (DDDI) in Pakistan. Second, it intends to investigate the effects of DDDI, sociodemographic characteristics, seat belt use, and driving training on the occurrence of traffic accidents. A total of 623 Pakistani individuals completed a questionnaire as part of this study. The questionnaire consists of items related to dangerous driving behaviors, sociodemographic characteristics, seat belt use, driving instruction, and accident involvement. The DDDI's accuracy was evaluated by comparing it to self-reported traffic incidents and seat belt compliance. To discover predictors within the DDDI dimensions, generalized linear models were used. A binary logistic regression analysis was also performed to evaluate the factors that influence traffic accidents. DDDI dimensions, demographic characteristics, seat belt usage, and driving training were all considered in this study. The use of seat belts while driving reduced the likelihood of an accident by 25%. On the other hand, aggressive driving and risky driving increased the chances of getting involved in traffic accidents by 36%% and 20%. Furthermore, the chances of being involved in a traffic accident decreased by 21% as the drivers age increased. The results also illustrate that Pakistani drivers are more aggressive and risk taker compared to Chinese drivers who are more disciplined. This study suggests that lack of comprehensive and standardized driving training and education programs, in consistent enforcement of traffic laws, the quality of road infrastructure and lack of public awareness campaigns can be attributed to adverse road safety situations in country.

Background: The efficacy of local therapies for lung cancer patients with postoperative oligo-recurrence has been reported. However, whether local therapies should be chosen over molecular targeted therapies for oligo-recurrence patients with driver mutations remains controversial. We hence aimed to investigate the optimal initial treatment strategy for oligo-recurrence in lung cancer patients with driver mutations. Methods: Among 2,152 patients with lung adenocarcinoma who underwent surgical resection at our institute between 2008 and 2020, 66 patients with driver mutations who experienced cancer oligo-recurrence after surgery, and were treated with local or molecularly targeted therapy as an initial therapy after recurrence were evaluated. Oligo-recurrence was characterized by the presence of 1 to 3 recurrent lesions. These patients were investigated focusing on their post-recurrence therapies and prognoses. Results: The median follow-up period was 71 months. Local and molecular targeted therapies were administered to 41 and 25 patients, respectively. The number of recurrence lesions tended to be lower in the initial local therapy group than in the molecular targeted therapy group. In the initial local therapy group, 23 patients (56%) subsequently received molecular targeted therapies. The time from recurrence to the initiation of molecular targeted therapy was significantly longer in the local therapy group than in the molecular targeted therapy group (p &lt; 0.001). There was no significant difference in post-recurrence overall survival (hazard ratio, 1.429; 95% confidence interval, 0.701–2.912; log-rank, p = 0.324), and post-recurrence progression-free survival (hazard ratio, 0.799; 95% confidence interval, 0.459–1.390; log-rank, p = 0.426) in the initial local ablative therapy group compared with the initial molecular targeted therapy group. Conclusions: Local therapies as a first-line treatment did not show statistically significant differences in post-recurrence survival or progression-free survival compared with molecular targeted therapies. However, local therapies as an initial treatment should be considered preferably, as it can cure the recurrence and can delay the start of administration of molecular-targeted therapies.

Drowsiness detection is an important task in road safety and other areas that require sustained attention. In this article, an approach to detect drowsiness in drivers is presented, focusing on the eye region, since eye fatigue is one of the first symptoms of drowsiness. The method used for the extraction of the eye region is Mediapipe, chosen for its high accuracy and robustness. Three neural networks were analyzed based on: InceptionV3, VGG16 and ResNet50V2 that implement deep learning. The database used is NITYMED, which contains videos of drivers with different levels of drowsiness. The three networks were evaluated in terms of accuracy, precision and recall in detecting drowsiness in the eye region. The results of the study show that all three convolutional neural networks have high accuracy in detecting drowsiness in the eye region. In particular, the Resnet50V2 network achieved the highest accuracy, with a rate of 99.71% on average. For better visualization of the data, the Grad-CAM technique is used, with which we get a better understanding of the performance of the algorithms in the classification process.

The ACC feature when activated augments the engine performance in real-time. This article presents a novel methodology to predict the optimal adaptive cruise control set speed profile (ACCSSP) by considering all the effecting parameters. This paper investigates engine operating conditions (EOC) criteria to develop a predictive model of ACCSSP in real-time. We developed a deep learning (DL) model using the NARX method to predict engine operating point (EOP) mapping the vehicle-level vectors (VLV). We used real-world field data obtained from Cadillac test vehicles driven by activating the ACC feature for developing the DL model. We used a realistic set of assumptions to estimate the VLV for the future time steps for the range of allowable speed values and applied them at the input of the developed DL model to generate multiple sets of EOP’s. We imposed the defined EOC criteria on these EOPs, and the top three modes of speeds satisfying all the requirements are derived for each second. Thus three eligible speed values are estimated for each second, and an additional criterion is defined to generate a unique ACCSSP for future time steps. Performance comparison between predicted and constant ACCSSPs indicates that the predictive model outperforms constant ACCSSP.

Growing evidence has revealed the implication of germline variation in cancer predisposition and prognostication. Here, we describe an analysis of putatively disruptive rare variants across the genomes of 726 patients with B-cell lymphoid neoplasms. We discovered a significant enrichment of 26 genes in germline protein truncating variants (PTVs), affecting cell signaling (MET, JAK2, ANGPT2), energy metabolism (ACO1) and nucleic acid metabolism and repair pathways (NT5E, DCK). Interestingly, some of these variants were restricted to either chronic lymphocytic leukemia (CLL) (i.e., ANGPT2 and AKR1C3) or B-cell lymphoma cases (PNMT, TPT1 and IGHMBP2). Additionally, we detected 1,675 likely disrupting variants in genes associated with cancer, of which 44.75% were novel events and 7.88% were PTVs. Among these, the most frequently affected genes were ATM, BIRC6, CLTCL1A and TSC2. Homozygous or compound heterozygous variants were detected in 28 cases; and coexisting somatic events were observed in 17 patients, some of which affected key lymphoma drivers such as ATM, KMT2D and MYC. Finally, we observed that variants in the helicase gene WRN were independently associated with shorter survival in CLL. Our study results support an important role for rare germline variation in the pathogenesis, clinical presentation and disease outcome of B-cell lymphoid neoplasms.

The betel nut chewing habit of taxi drivers has shown that can promote companionship, relaxation, and emotional stability at work. 19.3% of betel nut behaviors are instigated by an invitation among drivers to engage in the habit. The objective of this study was to explore the impact of social learning, subjective norm, and self-efficacy on betel nut chewing in taxi drivers in Taiwan. We conducted a cross-sectional study on taxis’ driver of betel nut behaviour and measured their evaluations of its consequences using a self-report questionnaire. Other variables include socio-demographic characteristics and chewing-related experience. The overall variance is 44.5% in socio-demographic variable, social learning, self-efficacy, and subjective norm. Results show that the variables of affected betel nut chewing behavior, driving years has the strongest influence, followed by learning about betel nut from the media, relatives, and friends, and education level, which positively affect betel nut chewing behavior. Findings indicated that education related to quitting betel nut chewing, significant others, and rules of the taxi fleet are adopted to design a plan for quitting betel chewing to reduce the positive expectations of taxi drivers for betel nut chewing and decrease their betel nut chewing behavior.

The objective of this study was to investigate the impact of athletes' respiratory muscle strength, as assessed through maximal inspiratory (MIP) and expiratory pressure (MEP), on aerobic endurance, as indicated by maximal oxygen consump-tion (Max VO2) kinetics. Respiratory muscle strength was assessed using a digital spirometer (Pony FX Cosmed, Italy), while maximal oxygen utilization capacity was measured using a breath-by-breath automatic portable gas analysis system (Cosmed K5, Italy). Statistical analysis was conducted utilizing SPSS 22.0. Based on the standardized regression coefficients (β), it was found that MEP (mean ± SD: 130.95 ± 42.82) and inspiratory diaphragmatic circumference values significantly influenced ventilatory equivalent (VE), oxygen consumption (VO2), and carbon dioxide pro-duction (VCO2). Conversely, the remaining predictor variables did not exhibit a sig-nificant effect on VE (mean ± SD: 134.80 ± 36.69), VO2 (mean ± SD: 3877.52 ± 868.47 ml), and VCO2 (mean ± SD: 4301.27 ± 1001.07 ml). In contrast, measurements of chest circumference (mean ± SD: 91.40 ± 10.72 cm), MEP, and diaphragmatic cir-cumference during inspiration (mean ± SD: 95.20 ± 10.21 cm) were found to signifi-cantly impact Max VO2 (mean ± SD: 58.52 ± 10.74 ml/kg/min), while the other pre-dictor variables did not demonstrate a significant effect on Max VO2. Conclusively, the study revealed that measured values of diaphragmatic circumference during inspiration and MEP exerted a notable influence on Max VO2, VE, VO2, and VCO2. Our findings underscore the importance of considering respiratory muscle strength in assessing and enhancing athletes' aerobic performance. These insights contribute to a deeper understanding of the interplay between respiratory function and exercise capacity, offering potential avenues for optimizing training regimens and perfor-mance outcomes in athletic contexts.

1) Introduction: Negative pressure wound therapy (NPWT) is a frequently applied open abdomen (OA) treatment. There are only a few experimental data supporting this method and describing the optimal settings and pressure distribution in the abdominal cavity during this procedure. The aim of our study was to evaluate pressure values at different points of the abdominal cavity during NPWT in experimental abdominal compartment syndrome (ACS) animal model. 2) Methods: In this study (permission Nr. 13/2014/UDCAR) 27 Hungahib pigs (15.4- 20.2 kg) were operated. ACS was generated by implanting a plastic bag in the abdomen through mini-laparotomy and filled with 2100- 3300 ml saline solution (37 C°) to an intraabdominal pressure (IAP) of 30 mmHg. After 3 hours, NPWT (Vivano Med ® Abdominal Kit, Paul Hartmann AG, Germany) or Bogota bag was applied. NPWT group was divided into -50, -100 and 150 mmHg suction group. Pressure distribution to the abdominal cavity was monitored at 6 different points of the abdomen via a multichannel pressure monitoring system. 3) Results: The absolute pressure levels were significantly higher above than below the layer. The values of the pressure were similar in the midline than laterally. Amongst the bowels, the pressure values changed periodically between 0 and -12 mmHg which might be caused by the peristaltic movements. 4) Conclusions: The porcine model of the present study seems to be well applicable for investigating ACS and NPWT. It was possible to provide valuable for clinicians. The pressure was well distributed by the protective layer to the lateral parts of the abdomen and this phenomenon did not change considerably during the therapy.

One of the earliest hallmarks of plant immune response is production of reactive oxygen spe-cies (ROS) in different subcellular compartments, which regulate plant immunity. A suitable equilibrium, which is crucial to prevent ROS over-accumulation leading to oxidative stress, is maintained by salicylic acid (SA), a chief regulator of ROS. However, ROS are not only acting downstream of SA signaling, but were also proposed to be a central component of a self-amplifying loop that regulates SA signaling as well as the interaction balance between dif-ferent phytohormones. The exact role of this crosstalk, the position where SA interferes with ROS signaling and ROS interferes with SA signaling and the outcome of this regulation depend on the origin of ROS but also on the pathosystem. The precise spatiotemporal regulation of or-ganelle specific ROS and SA levels determine the effectiveness of pathogen arrest and is there-fore crucial for a successful immune response. However, the regulatory interplay behind still remain poorly understood, as up till now, the role of organelle specific ROS and SA in HR-conferred resistance has mostly been studied by altering the level of a single component. In order to address these aspects, a sophisticated combination of research methods for monitoring the spatiotemporal dynamics of key players and transcriptional activity in plants is needed, and will most probably consist of biosensors and precision transcriptomics.

To understand lung damage caused by COVID-19, we deduced two-phase lung damage mechanisms. After the lungs are infected with SARS-CoV-2 virus, the affected lung tissue swells and surface properties of pulmonary capillaries change, resulting in an increased flow resistance of affected capillaries. If a sufficient number of capillaries are affected by the infection, the swelling and increased cell wall adhesion collectively raise pulmonary vascular resistance. The increased vascular resistance further increases the dwell times of WBCs in affected capillaries and nearly capillaries. When pulmonary pressure is sufficiently higher, WBCs are forced to squeeze into interstitial spaces or alveolar spaces when local pressures are higher than what the capillaries can withstand. When more and more WBCs are dynamically retained, the flow resistance of more capillaries rises, pulmonary vascular resistance rises, and pulmonary pressure rises. The rise in the pulmonary pressure in turn results in elevated capillary pressures. When capillary pressures around the alveoli are sufficiently high, they cause interstitial pressures to change from normally negative values to positive values. The positive pressures cause fluid leakage to the alveolar space and thus degrade lung function. Tissue swelling, and occupation of WBCs in interstitial spaces and alveolar spaces further reduce compressible volume, and thus cause further rise in the pulmonary vascular resistance and pulmonary pressure. When the pulmonary pressure has reached a critical point as in the second phase, the blood breaks capillary walls and squeezes through interstitial spaces to reach alveolar spaces, resulting in irreversible lung damages. The available free volume in the thorax cage, organ usable capacities, temperature and humid are expected to have great impacts on degree of lung damages. The free volume in the thorax cage, lung usable surplus capacity, and other organ usable capacities determine the arrival time of last-phase irreversible damage. The mechanisms imply that the top priority for protecting lungs is maintaining pulmonary micro-circulation and preserving organ functions in the entire disease course while controlling viral reproduction should be stressed in the earliest time possible. The mechanisms also explain leukecytes are recruited and migrated into inflamed tissues by increasing their dwell times caused by increased local flow resistance.

Mammalian species possess sophisticated innate immune mechanisms that collectively combat a wide array of viral pathogens. Among these, the well-characterized interferon (IFN) response has been extensively researched; however, the role of antiviral RNA interference (RNAi) in mammals is emerging as an area of significant interest. Previous research has noted that Dicer, an enzyme crucial for processing double-stranded RNA (dsRNA), exhibits reduced activity in vitro, and that the IFN response may overshadow or inhibit the antiviral functions of RNAi in mammalian cells. Consequently, the functional relevance of RNAi in antiviral defense within mammalian somatic cells remains an open question. The evolution of antiviral systems in human populations reflects their substantial advantages, paralleling the evolutionary pressure on genomes encoding such defense mechanisms. While the well-studied protein-guided immune responses in mammals are essential for survival in viral environments, small RNA-mediated antiviral systems, which utilize complementary base pairing to silence non self-genetic material, also play a crucial role. In mammals, evidence suggests that microRNAs (miRNAs) regulate genes integral to antiviral responses, and emerging data indicate that small interfering RNAs (siRNAs), PIWI-interacting RNAs (piRNAs), and transfer RNAs (tRNAs) can directly target virus-derived nucleic acids. This review aims to highlight some of the recent progress in understanding mammalian antiviral RNAi mechanisms.

We propose a novel protocol to build a maximally entangled state based on controlled-not (CNOT) gates. In particular, we give detailed steps to construct maximally entangled state for 4-, 5-, and 6-qubit systems. The advantage of our method is the simple algebraic structure which can be realized via current experimental technology.

Purpose: Nycthemeral (24-hour) glaucoma inpatient intraocular pressure (IOP) monitoring has been used in Europe for more than 100 years to detect peaks missed during regular office hours. Data supporting this practice is lacking, partially because it is difficult to correlate manually drawn IOP curves to objective glaucoma progression. To address this, we deployed automated IOP data extraction tools and tested for a correlation to a progressive retinal nerve fiber layer loss on spectral-domain optical coherence tomography (SDOCT). Methods: We created and deployed a machine-learning image analysis software to extract IOP data from hand-drawn, nycthemeral IOP curves of 225 retrospectively identified glaucoma patients. The relationship between demographic parameters, IOP and mean ocular perfusion pressure (MOPP) data to SDOCT data was analyzed. Sensitivities and specificities for the historical cut-off values of 15 mmHg and 22 mmHg in detecting glaucoma progression were calculated. Results: IOP data could be extracted efficiently. The IOP average was 15.2±4.0 mmHg, nycthemeral IOP variation was 6.9±4.2 mmHg, and MOPP was 59.1±8.9 mmHg. Peak IOP occurred at 10 AM and trough at 9 PM. Disease progression occurred mainly in the temporal-superior and -inferior SDOCT sectors. No correlation could be established between demographic, IOP, or MOPP parameters and SDOCT disease progression. The sensitivity and specificity of both cut-off points (15 and 22 mmHg) were insufficient to be clinically useful. Outpatient IOPs were non-inferior to nycthemeral IOPs. Conclusion: IOP data obtained during a single visit make for a poor diagnostic tool, no matter whether obtained using nycthemeral measurements or during outpatient hours.

Background: Pressure ulcers (PU) affect millions of people worldwide and always occur over bony areas of the body where pressure and tissue distortion is greatest. The national pooled prevalence of pressure ulcer remains unknown. Hence, the aim of this meta-analysis was to determine the effect of position change on pressure ulcer among hospitalized clients in Ethiopia. Methods: Studies were retrieved through search engines in PubMed, Scopus, WHO afro library, Google Scholar, Africa journal online, PsycINFO and web-science following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P). Analysis was done using STATA version 14 software. We checked the between-study heterogeneity using the I² and examined a potential publication bias by visual inspection of the funnel plot and Egger’s regression test statistic. The random-effect model was fitted to estimate the summary effects, odds ratios (ORs), and 95% confidence interval (CIs) across studies. Results: Out of the reviewing 401 studies, 7 studies fulfilled the inclusion criteria and were included in the meta-analysis. The estimated pooled prevalence of pressure ulcer in Ethiopia was 11.7% (95% CI (7.28, 16.13%)). Based on the subgroup analysis, the estimated magnitude of pressure ulcer was 15.89% (95% CI: 35.34, 54.04) among studies their sample size were greater than or equals to 250. Those clients who have position change during hospitalization were 85% less likely to develop pressure ulcer [(OR 0.15, 95%CI (0.06, 0.4)] than their counter part. Conclusion: The overall prevalence of pressure ulcer in Ethiopia was relatively high. Position change of the client during hospitalization had paramount benefit to reduce the burden of pressure ulcer. Therefore, policymakers could give special attention to minimize the magnitude of pressure ulcer in order to improve the overall quality of healthcare service. Further meta-analysis study is need to identify individual and health care service related factors to the occurrence of pressure ulcer.

Wilms tumor (WT), the most prevalent type of renal cancer in children, exhibits overall survival rates exceeding 90%. However, chemotherapy resistance, which occurs in approximately 10% of WT cases, is a major challenge for the treatment of WT, particularly for advanced-stage patients. In this study, we aimed to discover potential mutation markers and drug targets associated with chemotherapy resistance in advanced stage WT. We performed exome sequencing to detect somatic mutations and molecular targets in 43 WT samples, comprising 26 advanced stage WTs, of which 7 cases are chemotherapy-resistant. Our analysis revealed four genes (ALPK2, C16orf96, PRKDC, and SVIL) that correlated with chemotherapy resistance and reduced disease-free survival in ad-vanced-stage WT. Additionally, we identified driver mutations in 55 genes within the chemo-therapy-resistant group, including 14 druggable cancer driver genes. Based on the mutation profile of the resistant WT samples, we propose potential therapeutic strategies involving platinum-based agents, PARP inhibitors, and antibiotic/antineoplastic agents. Our findings provide insights into the genetic landscape of WT and offer potential avenues for targeted treatment, particularly for patients with chemotherapy resistance.

Vision impairment may delay responses to hazards when driving. In a proof-of-concept driving simulator study, we evaluated a hazard warning device designed for vision impaired drivers. Three groups participated: 11 persons with central vision loss (CVL; median age 60 years), 12 with homonymous field loss (HFL; 52 years) and 11 with normal vision (NV; 60 years). CVL is characterised by impaired visual acuity and contrast sensitivity while HFL is a loss of vision in the same half of the visual field (blind side) in both eyes. Participants completed drives with and without the device which gave a directional vibro-tactile warning for an approaching pedestrian hazard when collision risk exceeded a pre-defined threshold. Warnings significantly (p< 0.001) reduced brake response times for CVL (∆= 0.54s) and HFL (∆= 0.30s), but not NV participants. For HFL participants, the reduction was greater (p = 0.02) for hazards on the blind (∆= 0.57s) than seeing side (∆= 0.10s). The warnings significantly reduced collision rates for CVL participants from 11 to 0% (all hazards) and for HFL participants from 30 to 1.7% (blind side hazards). Thus, hazard warnings may be beneficial in improving safety of vision impaired drivers; further research is warranted.

Driver drowsiness is one of the leading causes of traffic accidents. This paper proposes a new method for classifying driver drowsiness using deep convolution neural networks trained by wavelet scalogram images of electrocardiogram (ECG) signals. Three different classes were de-fined for drowsiness based on video observation of driving tests performed in a simulator for manual and automated modes. The Bayesian optimization method is employed to optimize the hyperparameters of the designed neural networks, such as the learning rate and the number of neurons in every layer. To assess the results of the deep network method, Heart Rate Variability (HRV) data is derived from the ECG signals, some features are extracted from this data, and finally, random forest and k-nearest neighbors (KNN) classifiers are used as two traditional methods to classify the drowsiness levels. Results show that the trained deep network achieves balanced accuracies of about 77% and 79% in the manual and automated modes, respectively. However, the best obtained balanced accuracies using traditional methods are about 62% and 64%. We conclude that designed deep networks working with wavelet scalogram images of ECG signals significantly outperform KNN and random forest classifiers which are trained on HRV-based features.

In order to understand the evolution of multicellularity, we must understand how and why selection favors the first steps in this process: the evolution of simple multicellular groups. Multicellularity has evolved many times in independent lineages with fundamentally different ecologies, yet no work has yet systematically examined these diverse selective drivers. Here we review recent developments in systematics, comparative biology, paleontology, synthetic biology, theory, and experimental evolution, highlighting ten selective drivers of simple multicellularity. Our survey highlights the many ecological opportunities available for simple multicellularity, and stresses the need for additional work examining how these first steps impact the subsequent evolution of complex multicellularity.

This paper examines the Business Model (BM) from a socioeconomic system perspective to discern key factors, and understand its interactions resulting in the Scaling of Social Impact (SSI) in Social Entrepreneurship (SE). Previously, studies have explained the importance of BM in relation to SE. However, there is a lack of empirical studies on how BM’s transitions through participation of various actors result in SSI. This research applies qualitative analysis on a single case study of a Japanese social startup, “mymizu”, the first water refill application platform in Japan. The findings show that collaboration amongst different stakeholders on the initial phase of the BM could increase awareness of responsible consumption, convert into actual users for sustainability, and change their behavior. Secondly, members of the society could take on dual roles, both as users and collaborators in the BM, which results in an exponential scaling effect of the social impact. This paper contributes towards adding a participatory stakeholder (PS) to the ecosystem of SSI and building a “regenerative” BM that is relevant in SE towards sustainability.

Concurrent waves of Coronavirus disease, Ebola virus disease, avian influenza A and black fungus are jeopardizing the lives in some parts of Africa and Asia. From this point of view, this review aims to summarize both socio-economic and public health implications of these parallel outbreaks along with their best possible management approaches. Various online databases were used to collect the necessary information regarding these outbreaks. Based on the reports published and analyses done so far, the long-lasting damages caused by these simultaneous outbreaks on global socio-economical and public health status can be conceived from the past experiences of outbreaks, especially the COVID-19 pandemic. Moreover, prolonged restrictions by the local government may lead to food insecurity, global recession, and an enormous impact on the mental health of people of all ages, specifically in developing countries. Such overwhelming effects already have been reported to be declining national growth of the economy as well as increasing political insecurity and shortage of basic needs. Although various actions have already been taken including vaccination, clinical management, and further research, social distancing, and lockdown, etc. to improve the situation, the emerging variants and associated genetic mutations may make the containment difficult worsening the situation again. Considering the current mutational dynamics of the pathogens and the past experiences, perpetual preparedness along with updated clinical management backed by epidemiological studies and innovating scientific effort are inevitable to combat the simultaneous waves of multiple infectious diseases.

.With the increasing use of carbon fiber reinforced plastics in various area, carbon fiber composites based on prepregs have attracted attention in industries and academia research. However, prepreg manufacturing processes are costly, and the strength of structures varies depending on the orientation and defects (pores and delamination). For non-contact evaluation of internal defects, we proposed lock-in infrared thermography to investigate orientation angles after a compression test. We also conducted a drop-weight impact test to study the behaviour of the composites after impact according the fibers orientation for composite fabricated using unidirectional carbon fiber prepregs. Using CAI tests, we determined the residual compressive strength and confirmed the damage modes using a thermal camera. The results of the drop weight impact tests show that the specimen laminated at 0° suffered the largest damage because of susceptibility of the resin to impact. In contrast, the specimens oriented in of 0°/90° and +45°/–45° directions transferred more than 90% of the impact energy back to the impactor because of the lamination of fibers in the orthogonal directions. Furthermore, the specimens that underwent complete damage in the impact tests were subjected to the lock-in method and showed internal delamination and cut fibers. With the finite elements analysis, the damage of each ply could be observed. Moreover, the temperature differences in the residual compression tests were not significant.

Social surveys are conducted to determine how annoyed people are in a certain noise situation. The results are typically presented as exposure-response curves showing the percentage of the area population that are highly annoyed as a function of the noise exposure level. It is a well-known fact that the survey results are not only dependent on the accumulated noise exposure, DNL, DENL, or similar, but also on various other factors such as maximum levels, exposure patterns, noise spectra, etc. A re-analysis of previously reported surveys shows that the results are also to a large extent dependent on survey-specific factors like wording of the annoyance questions, how the questionnaires are presented, response scales, methods of scoring highly annoyed, etc. This paper discusses and quantifies the influence of such factors and suggests ways of comparing results from surveys that have been conducted according to different protocols and different analysis methods.

In this paper, Hybrid Automata, which is a formal model for hybrid systems, has been introduced. A summary of its theory is presented and some of its special and important classes are listed and some properties that can be studied and checked for it are mentioned. Finally, the purposes of use, the most widely used areas, and the tools that provide H.A. Support are addressed.

Quantum Fisher Information (QFI) is a very useful concept for analyzing situations that require phase sensitivity. It become a popular topic especially in Quantum Metrology domain. In this work, we study the changes in quantum Fisher information (QFI) values for one relative arbitrary phased quantum system consisting of a superposition of N Qubits W and GHZ states. In a recent work [7], QFI values of this mentioned system for N qubits were studied. In this work, we extend this problem for the changes of QFI values in some noisy channels for the studied system. We show the changes in QFI depending on noise parameters. We report interesting results for different type of decoherence channels. We show the general case results for this problem.

This study investigates the effect of oil viscosity on pollutant emissions and fuel consumption of an internal combustion engine (ICE) in high-altitude using Response Surface Methodology (RSM). A Chevrolet Corsa Evolution 1.5 SOHC gasoline engine was used in Cuenca, Ecuador (2560 meters above sea level), testing three lubricating oils with kinematic viscosities of 9.66, 14.08, and 18.5 cSt under various engine speeds and loads. Key findings include: hydrocarbon (HC) emissions were minimized to 7.25 ppm with low viscosity and load; carbon dioxide (CO2) emissions peaked at 15.2% vol with high viscosity and load; carbon monoxide (CO) ranged from 0.04% to 3.74% depending on viscosity and load; nitrogen oxides (NOx) were significantly influenced by viscosity, RPM, and load, indicating a need for model refinement; and fuel consumption was significantly affected by load and viscosity. RSM-based optimization identified optimal operational conditions with a viscosity of 13 sCt, 1473 rpm, and a load of 78%, resulting in 52.35 ppm of HC, 13.97% vol of CO2, 1.2% vol of CO, 0 ppm of NOx, and a fuel consumption of 6.66 l/h. These conditions demonstrate the ability to adjust operational variables to maximize fuel efficiency and minimize emissions. This study underscores the critical role of optimizing lubricant viscosity and operational conditions to mitigate environmental impact and enhance engine performance in high-altitude environments.

The problem of normal impact of a rigid sphere onto a Maxwell viscoelastic solid half-space is considered. The first-order asymptotic solution is constructed in the framework of Hunter’s model of viscoelastic impact [Hunter, S. C., 1957. Energy absorbed by elastic waves during impact. Journal of the Mechanics and Physics of Solids, 5(3), 162–171.]. In particular, simple analytical approximations have been derived for the maximum contact force and the time to achieve it. A linear regression method is suggested for evaluating the instantaneous elastic modulus and the mean relaxation time from a set of experimental data collected for different impactors and impact velocities.

Floor mats are commonly used to improve the impact sound performance of existing homes, but the actual reduction does not consistently appear depending on the test-bed conditions used to determine it. Therefore, this study evaluated the effects of the environmental conditions of the test-bed on the impact sound reduction performance of different floor mats. The Korean Industrial Standard, KS F 2865, specifies the measurement method in the test room and sets the thickness range of the available target floor structure from bare slab 120 mm to 210 mm. The evaluation method is ∆?, which is the difference in standardized impact sound levels before and after the installation of the floor finishing material. In this study, a total of eight types of floor mats were tested in four different test-beds according to KS F 2865. The impact sources used were tapping, bang machines and a rubber ball to consider both light-weight and heavy-weight impact sounds. The results were derived as impact sound reduction performance for each frequency band and a single number quantity. The results showed that light impact sound had a similar minimum reduction characteristic of at least 38 dB, regardless of the floor structure on which the mat was installed. However, the heavy-weight impact sound showed different tendencies depending on the floor mat and the characteristics of the floor structure of the test-bed when a bang machine and a rubber ball were used. In particular, the reduction by the bang machine showed less than half the tendency of the reduction by the rubber ball, and the tendency of the heavy-weight impact sound to be reduced depending on the floor mat was maintained, but the reduction differed depending on the test bed. The reduction was larger in the box-type test room than in the real-life type test room, and among the box-type test rooms, the one with a thicker bare slab showed a relatively larger reduction. In addition, the reliability of the measurement results was discussed through the correlation analysis between the single number quantities depending on the thickness of the bare slab of the test-beds.

This research delves into the water hammer occurrences, in the transmission pipeline of the SMD (Manda Daba) Multi Village Water Supply Schemes in Afar, Ethiopia. It utilizes simulation software, Bentley HAMMER version 8i to assess transient flow issues and the effectiveness of protective measures. The study pinpoints high risk areas in Scenario 1 marked by pressure spikes, negative pressures and frequent cavitation highlighting the importance of efforts. Prior to safeguards significant pressures reaching 288.27 m H₂O and minimum pressures dropping as low as 9.98 m H₂O are observed. In Scenario 2 where protective measures are implemented notable enhancements are seen with pressures ranging from 121.38 m H₂O to 150.49 m H₂O improved safety levels and substantial reductions in minimum pressures at pump stations. Moreover the study delves into Scenario 3 which explores pipe materials and diameters to provide insights, for pipeline design standards. It emphasizes how protective measures effectively mitigate water hammer effects while also highlighting cost saving potential by incorporating 2000 liter hydro tanks at pump stations. This integration leads to decreased pipeline collapses and maintenance expenses underscoring the significance of addressing challenges pinpointing failure causes and offering solutions to enhance system performance and strengthen reliability within the SMD water supply system

The diffusion coefficient (D) is a key parameter characterizing gas transport in coal seams. Usually, the D is calculated from the desorption curve of particle coal, which cannot accurately reflect the diffusion characteristics under the stress constraint conditions of in-situ coal seams. In this paper, based on Fick's law of counter diffusion, different metamorphic deformed coals of medium and high coal rank are taken as the research object. The change laws of D under different confining pressure, gas pressure, and temperature conditions are tested and analyzed, and the influencing mechanisms on the D are discussed. The results show that the D of different metamorphic deformed coals decreases exponentially with the increase of confining pressure, and increases exponentially with the increase of gas pressure and temperature. There is a limit diffusion coefficient. The influence of confining pressure on the D is essentially determined by the change of effective stress, and the D has a negative effect of effective stress similar to permeability. The effect of gas pressure on the D involves two mechanisms, namely, mechanical and adsorption effects, which are jointly restricted by effective stress and coal particle shrinkage and expansion deformation. The effect of temperature on the D is mainly achieved by changing the root mean square speed and average free path of gas molecules. Under the same temperature and pressure conditions, the D increases first and then decreases with the increase of deformation degree, and the D of fragmented coal is the largest. Under similar deformation conditions, the D of high-rank anthracite is greater than that of medium-rank fat coal. It is considered that porosity is the key factor affecting the change of D in different metamorphic deformed coals.

The cornerstone of molecular magnetism is a detailed understanding of the relationship between structure and magnetic behaviour, i.e. the development of magneto-structural correlations. Traditionally, the synthetic chemist approaches this challenge by making multiple compounds that share a similar magnetic core but differ in peripheral ligation. Changes in the ligand framework induce changes in the bond angles and distances around the metal ions which are manifested in changes to magnetic susceptibility and magnetisation data. This approach requires the synthesis of series of different ligands and assumes that the chemical/electronic nature of the ligands and their coordination to the metal, the nature and number of counter ions and how they are positioned in the crystal lattice, and the molecular and crystallographic symmetry have no effect on the measured magnetic properties. In short, the assumption is that everything outwith the magnetic core is innocent, which is a huge oversimplification. The ideal scenario would be to have the same complex available in multiple structural conformations, and this is something that can be achieved through the application of external hydrostatic pressure, correlating structural changes observed through high pressure single crystal X-ray crystallography with changes observed in high pressure magnetometry, in tandem with high pressure inelastic neutron scattering (INS), high pressure electron paramagnetic resonance (EPR) spectroscopy and high pressure absorption/emission/Raman spectroscopy. In this review, which summarises our work in this area over the last 15 years, we show that the application of pressure to molecule-based magnets can (reversibly): (1) lead to changes in bond angles, distances and Jahn-Teller orientations; (2) break and form bonds; (3) induce polymerisation/depolymerisation; (4) enforce multiple phase transitions; (5) instigate piezochromism; (6) change the magnitude and sign of pairwise exchange interactions and magnetic anisotropy and (7) lead to significant increases in magnetic ordering temperatures.

Considering that a fair coin has two sides and a cylindrical edge, the probability that it would fall on its edge is calculated, yielding the probability of heads or tails less than 50%. Theoretical models for a static case and for five dynamic cases, without and with rebounds, show that there is a small probability that the coin does not fall on its head or tail, depending on initial toss conditions, the coin geometry and conditions of the coin and landing surfaces. For the dynamic model with rebounds, it is found that the probability that a 50 Eurocent coin thrown from a normal height with common initial velocity conditions and appropriate surface conditions will end up on its edge is in the order of one against several thousand.

We have modelled the energy consumption of prototype and real buildings under present and future climatic conditions with the EnergyPlus model to develop a better understanding of the relationship between changing climate conditions and energy demand. We have produced detailed meteorological information with 50 meters of spatial resolution through dynamical downscaling process combining regional, urban and computational fluid dynamics models which include the effects of the buildings on urban wind patterns. The city of Madrid has been chosen for our experiment. The impact on energy demand and their respective economic cost are calculated for year 2100 versus 2011 based on two IPCC climate scenarios, RCP 4.5 (stabilization of emissions) and RCP 8.5 (not reduction of emissions). Findings show that climate change will have a significant impact on the energy demand for buildings. Space heating demand will be increased by the RCP 4.5 and cooling demand will be increased for the RCP 8.5 in the analysed buildings.

The advent of remote work has ushered in a new era of economic transformation, redefining the dynamics of local economies, and unleashing the multiplier effect on a national scale. This abstract explores the profound implications of remote work on local economies, dissecting how the multiplier effect operates within a nation's economic landscape. The multiplier effect is a fundamental economic concept that highlights how changes in spending and investment can create a ripple effect, leading to a magnified impact on an economy. This concept gains new significance in the context of remote work, as it triggers a chain reaction of economic activities that radiate from remote workers to their local communities. The increased flexibility and reduced geographical constraints of remote work have reshaped the allocation of resources. The continued reliance on remote work may lead to a reduction in demand for commercial real estate in urban centers, necessitating adaptive urban planning strategies. In conclusion, the rise of remote work has initiated a transformative era for local economies, driven by the multiplier effect. By amplifying the impacts of spending and investment, remote work fosters job diversification, innovation, and infrastructure development within communities. As remote work continues to reshape the landscape of work and life, understanding and harnessing its multiplier effect remains paramount for policymakers, businesses, and local communities alike. The multiplier effect is a concept in economics that illustrates how changes in spending can lead to larger impacts on a nation's economy through a chain reaction of economic activities. It demonstrates that an initial injection of spending, whether from government expenditure, investment, or consumption, doesn't just have a one-time impact. Instead, it sets off a series of interconnected spending and income-generation processes that result in a larger overall increase in economic activity. t's important to note that the multiplier effect can work in reverse as well. If there's a decrease in spending, it can lead to a decrease in economic activity and income through the same chain reaction process. This concept highlights the interconnected nature of economic activities and emphasizes the significance of changes in spending patterns on a nation's overall economic health. The magnitude of the multiplier effect is influenced by factors such as the marginal propensity to consume (the proportion of additional income that households spend), leakages (savings and taxes that reduce the multiplier effect), and the extent to which additional spending creates additional production capacity within the economy. Understanding the multiplier effect is essential for policymakers, as it helps them gauge the potential impacts of changes in fiscal and monetary policies on the economy.

Climate change represents a major threat to lotic freshwater ecosystems and their ability to support the provision of ecosystem services. England’s chalk streams are in a poor state of health, with significant concerns regarding their resilience, the ability to adapt, under a changing climate. This paper aims to quantify the effect of climate change on hydroecological response, the health of the river, for the River Nar, a SSSI in the south-east of England. To this end, we apply a coupled hydrological and hydroecological modelling framework, with the UKCP09 probabilistic climate projections serving as input (A1B high emissions scenario). Results show that, from 2021 to the end of the century, hydroecological response becomes more heterogeneous. Despite the limited range of the functional feeding groups on the baseline, the River Nar has been able to adapt to extreme events due to inter-annual variation. In the future, this variation is greatly reduced, raising real concerns over the resilience of the river ecosystem under climate change. These new insights into the health of the River Nar, and chalk streams more generally, highlights the necessity of further study and the real need to for changed river management practices.

A high performance Driver State Monitoring (DSM) application for the detection of driver drowsiness is presented in this paper. It relies on the usage of an Ensemble of Regression Trees (ERTs) machine learning method that aligns 68 facial landmarks. Special focus is given on the acceleration of the frame processing using reconfigurable hardware. Reducing the frame processing latency saves time that can be used to apply frame-to-frame facial shape coherency rules. False face detection and false shape estimations can be ignored for higher robustness and accuracy in the operation of the DSM application without reducing the frame processing rate that can reach 65 frames per second. The sensitivity and precision in yawning recognition can reach 93% and 97%, respectively. The implementation of the employed DSM algorithm in reconfigurable hardware is challenging since the kernel arguments require large data transfers and the degree of data reuse in the computational kernel is low. Due to this, unconventional hardware acceleration techniques have been employed that can also be useful for the acceleration of several other applications.

Seemingly normal tissues progressively become populated by mutant clones over time. Most of these clones bear mutations in well-known cancer genes but only rarely do they transform into cancer. This poses questions on what triggers cancer initiation and what implications somatic variation has for cancer early detection. We analysed recent mutational screens of healthy and cancer-free diseased tissues to compare somatic drivers and the causes of somatic variation across tissues. We then reviewed the mechanisms of clonal expansion and their relationships with age and diseases other than cancer. We finally discussed the relevance of somatic variation for cancer initiation and how it can help or hinder cancer detection and prevention. The extent of somatic variation is highly variable across tissues and depends on intrinsic features, such as tissue architecture and turnover, as well as the exposure to endogenous and exogenous insults. Most somatic mutations driving clone expansion are tissue-specific and inactivate tumour suppressor genes involved in chromatin modification and cell growth signalling. Some of these genes are more frequently mutated in normal tissues than cancer, indicating a context-dependent cancer promoting or protective role. Mutant clones can persist over a long time or disappear rapidly, suggesting that their fitness depends on the dynamic equilibrium with the environment. The disruption of this equilibrium is likely responsible for their transformation into malignant clones and knowing what triggers this process is key for cancer prevention and early detection. Somatic variation should be considered in liquid biopsy, where it may contribute cancer-independent mutations, and in the identification of cancer drivers, since not all mutated genes favouring clonal expansion also drive tumourigenesis. Somatic variation and the factors governing homeostasis of normal tissues should be taken into account when devising strategies for cancer prevention and early detection.

The intricate interplay between driver cognitive dysfunction, mental workload (MWL), and heart rate variability (HRV) provides a captivating avenue for investigation within the domain of transportation safety studies. This article presents a comprehensive review and examines cognitive hindrance stemming from mental workload and heart rate variability. It scrutinizes the mental workload experienced by drivers by leveraging data gleaned from prior studies that employed heart rate monitoring systems and eye tracking technology, thereby illuminating the correlation between cognitive impairment, mental workload, and physiological indicators such as heart rate and ocular movements. The investigation is grounded in the premise that the mental workload of drivers can be assessed through physiological cues, such as heart rate and eye movements. The study discovered that heart rate variability (HRV) and infrared (IR) measurements played a crucial role in evaluating fatigue and workload for skilled drivers. However, the study overlooked potential factors contributing to cognitive impairment in drivers and could benefit from incorporating alternative indicators of cognitive workload for deeper insights. Furthermore, investigated driving simulators demonstrated that an eco-safe driving Human-Machine Interface (HMI) significantly promoted safe driving behaviors without imposing excessive mental and visual workload on drivers. Recommendations were made for future studies to consider additional indicators of cognitive workload, such as subjective assessments or task performance metrics, for a more comprehensive understanding.

Hemifacial spasm (HFS) is a rare disorder characterized by involuntary facial muscle contractions. The primary cause is mechanical compression of the facial nerve by nearby structures. Lateral spread response (LSR) is an abnormal muscle response observed during electromyogram (EMG) testing and is associated with HFS. Intraoperative monitoring of LSR is crucial during surgery to confirm successful decompression. Proper anesthesia and electrode positioning are important for accurate LSR monitoring. Stimulation parameters should be carefully adjusted to avoid artifacts. The disappearance of LSR during surgery is associated with short-term outcomes, but its persistence does not necessarily indicate poor long-term outcomes. LSR monitoring has both positive and negative prognostic value, and its predictive ability varies across studies. Early disappearance of LSR can occur before decompression and may indicate better clinical outcomes. Further research is needed to fully understand the implications of LSR monitoring in HFS surgery.

Controlling injection parameters is paramount when it comes to producing high-quality green parts using powder injection molding. This work combines experimental and numerical approaches to study the impact of injection parameters on mold in-cavity pressure and on the overall quality of green parts produced by low-pressure powder injection molding. The properties of two low-viscosity feedstocks (formulated from a water-atomized stainless-steel powder and wax-based binder system) were measured and implemented in an Autodesk Moldflow numerical model to quantify the molding pressures, which were finally validated using experimental real-scale injections. The results confirmed that an increase in mold temperature, an increase in feedstock temperature, and a decrease in solid loading decrease the mold in-cavity pressure, which was correlated with the feedstock viscosity. As a key result, real-scale injections confirmed that a minimum flow rate was required to avoid atypical high in-cavity pressure leading in several visual defects such as weld lines, flow marks, cracks, sinks, and incomplete filling. Due to differences in its thermal transfer properties, this flow rate threshold value decreases as the feedstock solid loading increases. For injection speeds higher than this value, the injection pressure measured experimentally was linearly correlated with the injection flow rate.