This paper proposes a contact force controller for a constrained flexible manipulator in three-dimensional motion. This controller used the conversion formula obtained empirically and experimental results showed the effectiveness of the proposed contact force controller. First, the manipulator was operated with the tip of the second link restrained, then, time response of the root strain, joint angles and contact force were used to derive the relational between the three quantities. The effectiveness of the relational expression was verified by conducting a target contact force tracking experiment by inputting the angle from the relational expression. The contact force control using the strain feedback method was proposed with the strain amount estimated from the target contact force as the target value, and its effectiveness was verified by experiments. From the results obtained, controller using the strain feedback method was designed for the purpose of controlling the contact force at the tip of a flexible manipulator with two links and three degrees of freedom that performs three-dimensional spatial motion, and its effectiveness was shown by comparison with the contact force feedback method.

This research explores the feasibility of a data-driven optimization algorithm for placing sparse arrays of artificial hair-cell airflow velocity sensors to enable agile and robust flight-by-feel control of unmanned aircraft. The Sparse Sensor Placement Optimization for Prediction (SSPOP) algorithm exploits the information-rich features of large flow datasets to find a near-optimal set of locations for flow sensors on a wing. The flow information from these sensors can be used to predict flight state parameters such as the angle of attack, mimicking the fly-by-feel control systems observed in nature. We evaluate the effectiveness of this approach for a blunt-edged 45∘ swept delta wing. Exploiting the information in the complex airflow patterns over this wing, the SSPOP algorithm selects a sensor location design point (DP) which reliably ranks within the top 1% of all possible DPs by root mean square error in angle of attack prediction. This performance was consistent across models of various artificial hair lengths, and one model with variable hair lengths. This bioinspired dimension-reducing method for sensor placement optimization exhibits reliability and flexibility benefits when compared with a conventional greedy search algorithm and gradient-based optimization using auto-differentiation. The successful application of SSPOP in complex 3D flows paves the way for experimental evaluation of data-driven sparse sensor placement optimization for artificial hair-cell airflow sensors and is a major step toward biomimetic flight-by-feel.

Classical laws of friction suggest that friction force is proportional to the normal load and independent of the nominal contact area. As a great improvement in this subject, it is now widely accepted that friction force is proportional to the real area in contact, and much work has been conducted based on this hypothesis. In present study, this hypothesis will be carefully revisited by measuring the friction force and real contact area in-site and real-time at both normal loading and unloading stages. Our experiments reveal that the linear relation always holds between friction force and normal load. However, for the relation between friction force and real contact area, the linearity holds only at the loading stage while fails at the unloading stage. This study may improve our understanding of the origin of friction.

In recent years, research on adversarial attack techniques for remote sensing object detection (RSOD) has made great progress. Still, most of the research nowadays is on end-to-end attacks, which mainly design adversarial perturbations based on the prediction information of the object detectors (ODs) to achieve the attack. These methods do not discover the common vulnerabilities of the ODs and thus the transferability is weak. Based on this, this paper proposes a foreground feature approximation (FFA) method to generate adversarial examples (AEs) that discover the common vulnerabilities of the ODs by changing the feature information carried by the image itself to implement the attack. Specifically, firstly, the high-quality predictions are filtered as attacked objects using the detector, after which a hybrid image without any target is made, and the hybrid foreground is created based on the attacked targets. The images' shallow features are extracted using the backbone network, and the features of the input foreground are approximated towards the hybrid foreground to implement the attack. In contrast, the model predictions are used to assist in realizing the attack. In addition, we have found the effectiveness of FFA for targeted attacks, and replacing the hybrid foreground with the targeted foreground can realize targeted attacks. Extensive experiments with seven rotating ODs on the RSOD datasets DOTA and UCAS-AOD show that FFA achieves both targetless and targeted attacks with a high success rate and transferability.

This paper represents the first investigation into the consensus problem of linear time-varying multi-agent systems utilizing an event-triggered communication scheme. First, a general event-triggered consensus control scheme is proposed for a general category of linear time-varying multi-agent systems. Under some suitable assumptions, it is demonstrated that all agents’ states will converge exponentially, with Zeno behaviour being ruled out. Second, the consensus problem in a network of linear time-varying multi-agent systems with a spanning tree is investigated using the proposed control strategy. It demonstrates that the consensus issue for the specified system can be reformulated as a stabilization problem for an error system through a time-varying linear transformation. Then, the event-triggered consensus problem is just a special instance of the general event-triggered consensus problem mentioned above. Finally, to illustrate the efficacy of the event-triggered method proposed in this study, simulation results are shown.

Coupling faults that occur simultaneously widely exist in the operation of mechanical equipment, and coupling fault features are formed by nonlinear coupling of multiple base fault features. In this paper, hypergraph neural network is used to obtain the characteristics of coupling faults, and two coupling fault diagnosis frameworks based on hypergraph are provided. 1. Coupling fault diagnosis framework based on feature generation: The hypergraph neural network is used as a generator to provide negative samples for discriminator training. The generator outputs hyperedge vectors as fake samples, and each hyperedge connects a base fault containing a fault type. 2. Coupling fault diagnosis framework based on feature extraction: Each node is regarded as a fault type, and the fault characteristics of each type of fault are extracted through the aggregation operation of hypergraph. The attention mechanism is introduced to realize the dynamic adjustment of the hyperedge, and the dynamic vertex is used to classify the unknown faults. The results show that the diagnostic accuracy of coupling faults under the two frameworks reaches 88.6% and 86.76%, respectively.

Human-robot collaboration is a new trend in modern manufacture. The safety or human protection is of great significance due to the share of the same workshop between humans and robots. To achieve effective protection, in this paper, a contact force sensor based on the 8-shaped wound polymer optical fiber is proposed. The 8-shaped wound structure can convert the normal contact force to the shrinkage of the 8-shaped optical fiber ring. The macro-bending loss of the optical fiber is used to detect the contact force. Compared with conventional sensors, the proposed scheme has the advantage of high flexibility, low cost, fast response, high repeatability, which shows the great promise on actively alarming collision and passively reducing the hurt.

Mechanical equipment is composed of several parts, the interaction between the parts exists throughout whole life cycle leads to the widespread phenomenon of fault coupling and the diagnosis of independent faults cannot meet the requirements of the health management of mechanical equipment under actual working conditions. In this paper, the topological structure of graph neural network is used to describe the correlation of coupling faults and multiple fault types are regarded as network nodes respectively. The fault features are fused and extracted by graph convolution to achieve the classification of coupling faults. In this paper, dynamic vertexes are defined in data topology and the parameters of DIGNN classification model are optimized by changing the fault type of dynamic vertexes during training stage. The data is loaded into dynamic vertexes for classification and analysis during testing stage. The one-dimensional vibration data is converted into two-dimensional time-frequency domain data by wavelet transform making the input features of the model interpretable to reduce the uncertainty of model training. The data topology is then fed into DIGNN for fault classification, and GCN's node aggregation gives interpretability to each layer of network data processing. The method proposed in this paper can realize accurate diagnosis of independent faults on the data set, and can effectively judge the coupling mode of coupling faults, which is suitable for coupling fault analysis of mechanical equipment.

The SARS-CoV-2 pandemic has resulted in the generation of evolutionary-related variants. The S-protein of the B.1.1.7 variant (deletion N-terminal domain (NTD) His69Val70Tyr144) may contribute to altered infectivity. These mutations may have been presaged by animal mutations in minks housed in mink farms that according to the present analysis by modelling of protein ligand docking altered a high affinity binding site in the S-protein NTD. These mutants likely occurred only sporadically in humans. Tissue-adaptations and the size of the mink relative to the infected human population size back then may have comparatively increased the relative mutation rate. Simple, multi-threaded automated docking that is widely available, assigns increased binding of the blood type II A antigen to the SARS-Cov-2 S-protein NTD of B.1.1.7 with an overall increased docking interaction of blood group A harbouring glycolipids relative to group B or H (H, p=0.04). The top scoring glycan is identified as a DSGG (also classified as sialosyl-MSGG or disialosyl-Gb5) that may compete with heparin, which is similar to heparan sulfate linked to proteinaceous receptors on the tissue surface. Other glycolipids are found to interact with lower affinity, except long ligands that have suitable ligand binding poses to match the curved binding pocket.

This paper studies the maximum reliability of multi-hop relay UAV, in which UAV provides wireless services for remote users without direct communication link on the ground as a coded cooperative relay. In this paper, the analytical expressions of total power loss and total bit error rate are derived as reliability measures. Firstly, based on the environmental statistical parameters, a LOS probability model is proposed. Then the problem of minimizing the bit error rate of static and mobile UAVs is studied. The goal is to minimize the total bit error rate by jointly optimizing the height, elevation, power and path loss, and subject to the maximum allowable path loss con-straints, transmission power allocation constraints and UAV height and elevation constraints. At the same time the total path loss is minimized to achieve maximum ground communication cov-erage. However, the formulated joint optimization problem is non-convex and generally difficult to solve. Therefore, we decomposed the problem into two subproblems and proposed an effective joint optimization iteration algorithm. Finally, the simulation results are given, and the analysis shows that the optimal height of different reliability measures is slightly different, and using the mobility of UAVs can improve the reliability of communication performance.

Predation is a driving force of organismal ecology and evolution. Predator-prey interactions, constrained by other environmental factors and historical contingency, shape physical and behavioral phenotypes of organisms on both sides of the interaction arrow. Yet despite the universality of trophic interactions in biology, study of the ecology and evolution of anti-predator defense is challenging because these interactions tend to be brief and unpredictable, and thus gathering direct evidence requires patience and serendipity. The evolution of prey defenses can be studied by DNA sequencing followed by phylogenetic analysis, and the ecology can be studied by field observation and bringing tractable systems into the lab. However, animal models generally do not allow genetic manipulation, strict control of environmental variables, or detailed observation of evolution in real time, all of which are important for demonstrating evolutionary causes and consequences. Developing complementary microbial predator-prey systems can help overcome this hurdle. There is an extensive body of work on microbial experimental evolution, and many microbes come with well-characterized genomes and established methods for genetic manipulation. As understanding of microbial ecology and the mechanisms of their trophic interactions grows apace, these systems are poised to make valuable contributions to our understanding of how predator behaviors evolve, why certain anti-predator defenses evolve and not others, and how multiple defenses function together in a single defense portfolio. These systems will enable us to both test hypotheses formulated from the study of larger organisms and to propose new ones that can be tested in larger organisms with existing methods.

In the paper, a study of the performance of unmanned ground vehicle (UGV), establishes numerical simulation model of the chassis system by three-dimensional software and finite element analysis software. Based on the numerical modelling and analysis, the work focuses on study of the strength and stiffness of the vehicle's chassis and researched the distribution of stress and deformation under the extremal condition. The paper also presents an autopilot design with new cascade control system for an autonomous motion of an unmanned ground vehicle based on Proportional-Integral-Derivative (PID) and Feed-Forward (FF) control. The PID-FF controller is a part of dedicated for presented UGV used in a hybrid control system for precise control and stabilization, necessary to increase the vehicle motion stability and maneuvers precision. The hybrid PID-FF control system proposed for the ground vehicle model gives a satisfactory quality of control, while maintaining the simplicity of the control system. Presented tests performed in area of mechanical design and control analysis gives good results and proves usefulness of designed unmanned device.

Green Infrastructures (GI) are considered key to reconcile ecological and social benefits by providing multiple functions. The concept is increasingly promoted and guidelines for its implementation have been developed in many countries and regions of the Western Hemisphere. However, for other parts of the world, especially for countries with less developed infrastructures, promotion, guidance for decision-making and manuals for GI are often lacking. But the state of infrastructure development and often unplanned character of settlements in the Global South differ and result in specific constraints as well as demands to GI that need to be addressed explicitly. This study presents a methodological approach to explicitly address the specific conditions and physical limitations to GI development in urban areas of the Global South. A four step methodology was developed to assess the implementation potential for retrofitted and multifunctional urban green infrastructure in public areas. An initial site analysis (1) and the definition of design criteria as well as general strategies (2) to achieve the different dimensions of multi-functionality are the basis to derive spatial typologies (3) for GI elements and finally the spatial suitability assessment for potential placements (4). An application of the methodology to a study area in the metropolitan region of San José, Costa Rica, shows exemplarily that the potential to improve the hydrological conditions (up to 34% of surface runoff reduction), ecological conditions (increase of green space by 2,2 %, creation of 1500 m length of roadside greenery and two new habitat types), and social conditions (2.200 m of road type upgrading) of multi-functionality of the site through Green Infrastructures. These assessment results of different multi-functionality dimension can serve as a guidance for GI promotion and implementation in urban areas of the Global South.

The unprecedented progress in Artificial Intelligence (AI), particularly in deep learning algorithms with ubiquitous internet connected smart devices, has created a high demand for AI computing on the edge devices. This review studied commercially available edge processors, and the processors that are still in industrial research stages. We categorized state-of-the-art edge processors based on the underlying architecture, such as dataflow, neuromorphic, and Processing in-Memory (PIM) architecture. The processors are analyzed based on their performance, chip area, energy efficiency, and application domains. The supported programming frameworks, model compression, data precision, and the CMOS fabrication process technology are discussed. Currently, most of the commercial edge processors utilize dataflow architectures. However, emerging non-von Neumann computing architectures have attracted the industry in recent years. Neuromorphic processors are highly efficient for performing computation with fewer synaptic operations, and several neuromorphic processors offer online training for secured and personalized AI applications. This review found that the PIM processors show significant energy efficiency and consume less power compared to dataflow and neuromorphic processors. The future direction of the industry would be to implement state-of-the-art deep learning algorithms in emerging non-Von Neumann computing paradigms for low power computing on the edge devices.

Emphasizing the importance of acoustic attenuation in maintaining compliance with stringent noise regulations and enhancing workplace safety, the analysis covers the theoretical and practical aspects of sound attenuation in a turboengine testing stand. This paper presents a preliminary analysis and also an evaluation of a procedure for projecting a noise attenuator for industrial application and especially for turboengine test stands. While primarily focusing on the static acoustic behavior of the attenuator, considerations were also made regarding flow dynamics, Mach number-dependent attenuation, pressure drop, and self-generated noise aspects to provide a comprehensive perspective in selecting the optimal design configuration. The study investigates different calculation methods for assessment of the noise reduction for linear and staggered baffles, applied on a scaled reduced model of attenuator. Thus, the critical parameters and projecting requirements necessary for effective noise reduction in high-performance turboengine testing environments will be evaluated in a down-scaled model. Key factors examined include the selection of design parameters and configurations from various options. Advanced computational methods, like analytic and finite element analysis (FEM) are utilized to predict the acoustic performance and identify potential design optimizations. Experimental validation is performed to corroborate the simulation results, ensuring the reliability and efficiency of the attenuator. The findings indicate that a well-designed sound attenuator module can significantly reduce noise levels without compromising the operational performance of the turboengine inside a test cell.

Natural rivers in urban areas bear significant potential to provide ecosystem services for the surrounding inhabitants. However, surface sealing by houses and street networks, urban drainage, disposal of waste and wastewater resulting from advancing urbanization usually lead to the deterioration of urban rivers and their riparian areas. This ultimately damages their ability to provide ecosystem services. This paper presents an innovative methodology for a rapid and low-cost assessment of the ecological status of urban rivers and riparian areas in developing countries under data scarce conditions. The methodology uses a combination of field data and freely available high-resolution satellite images to assess three ecological status categories: river hydromorphology, water quality, and riparian land cover. The focus here is on the assessment of proxies for biophysical structures and processes representing ecological functioning that enable urban rivers and riparian areas to provide ecosystem services. These proxies represent a combination of remote sensing land cover- and field-based indicators. Finally, the three ecological status categories are combined to quantify the potential of different river sections to provide regulating ecosystem services. The development and application of the methodology is demonstrated and visualized for each 100 m section of the Pochote River in the City of León, Nicaragua. This spatially distributed information of the ecosystem service potential of individual sections of the urban river and riparian areas can serve as important information for decision making regarding the protection, future use, and city development of these areas, as well as the targeted and tailor-made development of nature-based solutions such as green infrastructure.

Graph visualization has evolved significantly over time, offering various methods to effectively represent complex data structures. This study introduces a novel force-directed algorithm for 3D data visualization, specifically tailored for commonly used datasets in linked data visualization. Leveraging the power of graph theory and methods, the algorithm aims to address the challenge of creating visually appealing and easily interpretable visualizations, which often necessitate advanced user interaction. By utilizing 3D space and the Unity Engine, the research successfully visualizes data and develops interactive visualizations, overcoming limitations of basic force-directed implementations. The main contribution of presented research is in the force-directed algorithm with springs and controlled placement as a visualization technique that combines the use of springs and attractive forces to stabilize a graph in a 3D environment. The combination of these two techniques also helps prevent the formation of a single large cluster within the graph, enhancing the overall visualization quality.

In the present work, an innovative range of foams, based on flax gum-filled epoxy resin was developed, reinforced or not by flax fibers. Foams and composites with different gum and epoxy resin contents were produced and characterized for mechanical and thermal performances. To enhance the organic flax gum filler's cross-linking, we exploited the oxidized components' reactivity with the amine hardener (isophorone diamine). We compared the materials obtained with those derived from the native components. Flax gum and fibers were primarily characterized by chemical analysis, NMR, and FTIR to evaluate the mild oxidation of native materials. The formation of chemical bonds between oxidized polymer chains, epoxy resin, and hardener has been evidenced by FTIR, and the materials were then studied by SEM, X-ray computed micro-tomography (CT), and submitted to mechanical and thermal tests. The relevance of oxidation treatment was highlighted, through a significant increase in density and mechanical performances (+36% and +81%, respectively for the 100% flax gum material). The positive effect of flax fibers on homogeneity evidenced through micro-CT analysis was also clearly addressed. This set of promising results paves the way for future development of fully flax-based insulation composite materials.

Understanding the structural intricacies of RNA molecules is essential for deciphering numerous biological processes. Traditionally, scientists have relied on experimental methods to gain insights and draw conclusions. However, the recent advent of advanced computational techniques has significantly accelerated and refined the accuracy of research results in several areas. A particularly challenging aspect of RNA analysis is the prediction of its secondary structure, which is crucial for elucidating its functional role in biological systems. This paper deals with the prediction of pseudoknots in RNA, focusing on two types of pseudoknots: K-type and M-type pseudoknots. Pseudoknots are complex RNA formations in which nucleotides in a loop form base pairs with nucleotides outside the loop and thus contribute to essential biological functions. Accurate prediction of these structures is crucial for understanding RNA dynamics and interactions. Building on our previous work in which we developed a framework for the recognition of H- and L-type pseudoknots, an extended grammar-based framework tailored to the prediction of K- and M-type pseudoknots is proposed. This approach uses syntactic pattern recognition techniques and provides a systematic method to identify and characterize these complex RNA structures. Our framework uses context-free grammars (CFGs) to model RNA sequences and predict the occurrence of pseudoknots. By formulating specific grammatical rules for type K and type M pseudoknots, we enable efficient parsing of RNA sequences to recognize potential pseudoknot configurations. This method ensures an exhaustive exploration of possible pseudoknot structures within a reasonable time frame. In addition, the proposed method incorporates essential concepts of biology, such as base pairing optimization and free energy reduction, to improve the accuracy of pseudoknot prediction. These principles are crucial to ensure that the predicted structures are biologically plausible. By embedding these principles into our grammar-based framework, we aim to predict RNA conformations that are both theoretically sound and biologically relevant.

Twelve overnight fasted, healthy, male volunteers received on separate days a test breakfast consisting of (A) 100 g fresh white bread (providing 50 g starch) and 250 mL drinking water, (B) the same bread with a supplement of 10 g alpha-cyclodextrin dissolved in the drinking water (250 mL), and (C) 250 mL drinking water containing 25 g alpha-cyclodextrin. Capillary and venous blood samples were collected before breakfast and at regular intervals for a period of 3 hours thereafter. Plasma glucose was determined in capillary blood and plasma insulin in venous blood samples. Breakfast (A) let to the expected rise in blood glucose and insulin concentrations. Breakfast (C) did not produce a significant glycemic and insulinemic response, demonstrating that alpha-cyclodextrin is not hydrolyzed to glucose in the human digestive tract. Mild intestinal symptoms after the ingestion of alpha-cyclodextrin were reported by 4 subjects. The postprandial rises of plasma glucose and insulin were significantly smaller after breakfast (B) than (A). Under the conditions of this study, alpha-cyclodextrin reduced the glycemic and insulinemic index of white bread by 57 and 55 %, respectively. The postprandial time profile of plasma glucose and insulin suggests that, in an initial phase, the digestion of starch is inhibited by alpha-cyclodextrin almost completely. Yet, despite the delayed and reduced digestion of starch, the intake of breakfast (B) was not associated with flatulence or any other gastrointestinal symptoms.

Treatment of neurological disease is hampered by the lack of validated specific and sensitive biomarkers, resulting in delayed diagnosis and nonspecific disease modifying therapies. For example, in ALS the lack of a sensitive and specific biomarker impedes the ability to administer a treatment prior to or at the onset of motor neuron dysfunction. Although viral or other infectious etiologies have been proposed as a contributing factor to neurodegeneration, it can be argued that these are casual and not causal associations. In the case of ALS, evidence for direct causality would require in vivo validation of specific nucleotide sequences of microbial origin which are known to be neuroinvasive with tropism for motor neurons, such as polio and non-polio. Several viral enteropathogens recapitulate the pathological events in sporadic ALS, including the ability to cleave TDP-43 resulting in accumulation of misfolded proteins in the cytoplasm. This review provides supporting evidence that motor neuron disease is causally related to specific enteroviruses and argues that prospective validation is imperative for effective prevention and treatment.

(1) Background: A wide literature based on loading and unloading bending tests has been carried out over the half past century for assessing the force released by superelastic wires. The aim of this investigation is not only to characterize a broadly described superelastic NiTi and a novel CuNiTi archwire, but also to provide novel insights into the load vs deflection profiles. A harmonic scenario for superelastic wires will be shown as temperature is kept constant at 37°C. However, a completely different picture will be highlighted as a temporary heating step up to 50°C is introduced within the force vs deflection profiles. (2) Methods: A variety of NiTi and a novel CuNiTi round and rectangular cross-section archwires have been investigated. Static 3-point bending tests up to a deflection level of 3.0 mm have been carried out for detecting the unloading force plateau levels occurring at 37°C. A hold deflection step of 5 min at deflection levels occurring along the unloading plateau extension is introduced. The effect of a temporary heating up to 50°C on the force plateau level released by the investigated wires is analyzed. (3) Results: Mechanical profiles suggest that the plateau force levels detected at 37°C are consistent with those broadly reported in the literature, but they only represent a single block puzzle of the force scenario that a superelastic wire releases during the orthodontic treatment. (4) Conclusions: Once a superelastic wire is bent and clinically applied, the effect of a temporary heating up to 50°C (e.g. hot food or drink ingestion) produces a significant plateau force increase whose magnitude depends on the deflection level. The highest force increase of about 50% and 40% have been detected at deflection levels located at the beginning of the unloading plateau extension for NiTi and CuNiTi wires, respectively.

Predicting the outcome of a future game between two National Basketball Association (NBA) teams poses a challenging problem of interest to statistical scientists as well as the general public. In this article, we formalize the problem of predicting the game results as a classification problem and apply the principle of maximum entropy to construct NBA maximum entropy (NBAME) model that fits to discrete statistics for NBA games, and then predict the outcomes of NBA playoffs by the NBAME model. The best NBAME model is able to correctly predict the winning team 74.4 percent of the time as compared to some other machine learning algorithms which is correct 69.3 percent of the time.

Metaverse represents a multifaceted digital universe integrating diverse technologies to create immersive, interconnected virtual environments. Key components foundational to its structure include the infrastructure layer for hardware and network support, the human interface layer utilizing virtual reality (VR) and augmented reality (AR) devices, and a decentralized layer leveraging blockchain for secure digital asset management. Further components encompass spatial computing for realistic 3D environments, the creator economy for content generation and monetization, and discovery mechanisms for navigation within Metaverse. VR, AR, blockchain, AI, the fifth-generation (5G) networks, and the Internet of Things (IoT) are central to Metaverse functionality, enabling real-time interactions and data integration. Real-Time Metaverse aims to replicate instantaneous real-world interactions, requiring advanced technological infrastructure for seamless data exchange. Critical challenges include ensuring low latency, high bandwidth, scalability, and robust security measures. Metaverse’s potential spans various domains, promising to revolutionize social interactions, entertainment, workplaces, and education through dynamic, immersive experiences. Ongoing advancements in high-performance computing, cloud services, and AI-driven technologies are essential for addressing existing barriers and achieving a cohesive, secure, and inclusive Metaverse ecosystem. Future research must focus on enhancing user experience, accessibility, and standardized interoperability to fully realize the transformative capabilities of a Metaverse.

Wind energy is a kind of renewable energy with great potential for development. This study mainly investigated the application of shock waves generated by high-pressure gases (wind energy) for generating energy. In this study, we designed a new supersonic shock wave generator that can be reused without disassembling and assembling bolts and developed a supersonic shock wave monitoring system. This system monitored the velocity of the generated shock waves, which was Mach 3-5, and the output pressure was more than 100 times higher than the input pressure of the shock wave generator tank.Then, we developed a power generation system driven by supersonic shock waves based on the characteristics of the new shock wave generator, which can generate high-pressure and high-speed blast waves and can be reused. The shock wave generator can repeatedly generate high-pressure waves to drive the Tesla turbine and then the magnetic energy generator for power generation. We established a complete control process for power generation driven by shock waves by controlling the valve stem. The system can detect the tank pressure, output pressure, gas flow, rotation speed, voltage, and current during the control process for the performance analysis of power generation.

Green Infrastructure promotes the use of natural functions and processes as potential solutions to reduce negative effects derived from anthropocentric interventions such as urbanization. In cities of Latin America, for example, the need for more nature-sound infrastructure is evident due to its degree of urbanization and degradation of ecosystems, as well as the alteration of the local water cycle. In this study, an experimental approach for implementation of a prototype is presented. The experiment took place in a highly urbanized watershed located in the Metropolitan Area of Costa Rica. Initially, understanding the characteristics of the study area at different scales was achieved by applying the Urban Water System Transition Framework to identify the existing level of development of the urban water infrastructure, and potential future stages. Subsequently, preferences related to spatial locations and technologies were identified from different local decision-makers. Those insights were adopted to identify a potential area for implementation of the prototype. The experiment consisted on an adaptation of the local sewer to act as a temporal reservoir to reduce the effects derived from rapid generation of stormwater runoff. Unexpected events, not considered initially in the design, are reported in this study as a means to identify necessary adaptations of the methodology. Our study shows from an experimental learning-experience that the relation between different actors advocating for such technologies influences the implementation and operation of non-conventional technologies. Furthermore, the perception of security associated to green spaces was found as a key driver to increase the willingness of residents to modify their urban environments. In consequence, those aspects should be carefully considered as factors of designs of engineering elements when they are related to complex socio-ecological urban systems.

The paper presents a method to assess the effect of electrolyte additives on the energy capacity of Pb-acid batteries. The method applies to any chemically unreactive additive, including suspensions and gels. The approach is thermodynamically based and it leads to the definition of a region of admissible concentrations –the battery’s admissible range– where the battery can undergo an indefinite number of charge/discharge cycles without suffering permanent damage. An experimental procedure to determine this range is presented. The obtained results provide a way to assess the potential of electrolyte additives to improve the energy capacity of Pb-acid batteries. The same results also provide a means to determine the additive concentration that produces the maximum energy capacity increase of the battery. The paper closes with an example of application of the proposed approach to a practical case.

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

Purpose of research was to determine changes in optical quality for monthly disposable soft contact lenses (SCL) wearers with new and monthly worn SCL. Retinal straylight was assessed in SCL wearers using a C-Quant straylight meter. The study included 33 participants (age 22 ± 1.4 years) who wore monthly disposable silicone hydrogel contact lenses. Measurements were taken with month-old SCL that had been worn for no more than 4 hours. Participants then replaced the old lenses with new ones. After a 15-minute adaptation period, straylight measurements were taken with the new SCL. A questionnaire was administered to all participants, inquiring about vision complaints and the type of contact lens material used. The decimal logarithm of the stray-light parameter, log(s), was notably higher with month-old SCL (log(s) = 0.97±0.17) than with brand-new SCL (log(s) = 0.86±0.15), p < 0.001. The average increase in retinal straylight after a month of SCL use was log(s) = 0.11 ± 0.08. The questionnaire revealed that 35% of participants observed a reduction in visual quality after wearing the contact lenses for a month. Results showed that monthly disposable soft contact lenses could reduce visual quality when scheduled replacement time has been reached.

Contact inhibition (CI) represents a crucial tumor-suppressive mechanism responsible for controlling the unbridled growth of cells, thus preventing the formation of cancerous tissues. CI can be further categorized into two distinct yet interrelated components: CI of locomotion (CIL) and CI of proliferation (CIP). These two components of CI have historically been viewed as separate processes, but emerging research indicates that they share both distinctive and common pathways. Moreover, they exhibit intriguing intersections with mechanotransduction, a process that involves cells sensing and responding to mechanical forces. This review article describes the intricate interplay between mechanical forces and CI, shedding light on how these forces regulate CIL and CIP. Emphasis is placed on filamin A (FLNA)-mediated mechanotransduction, elucidating how FLNA senses mechanical forces and translates them into crucial biochemical signals that regulate cell locomotion and proliferation. In addition to FLNA, trans-acting factors (TAFs) emerge as sensitive players in both CI and the mechanotransduction process. This article presents methods for identifying these TAFs and profiling the associated changes in chromatin structure, offering valuable insights into CI and mechanotransduction regulation. Finally, it addresses unanswered research questions in these fields and delineates their possible future directions.

Our decisions today are part of an economic thinking which aims to fix problems and increase the efficiency of capital markets. Our economy is still largely approached as a system which is unre-lated to our environment or social returns like community well-being, social cohesion, equitable distribution of resources, etc. To fully incorporate sustainability into cost-benefit analysis, busi-nesses need to change their financial approach, showcasing how long-term thinking impacts prof-its. Money's value is not static and evolves with time and technology. We propose to introduce a variation of cost/benefit and present value calculations. Precise calculations reveal the benefits of long-term strategies over short-term profit focus. As financial systems evolve and technology advances, the accurate calculation of money's time value will continue to play a crucial role in shaping economic landscapes and guiding financial choices. In this article, we demonstrate that updated calculations could be a key enabler to visualize the benefits of long-term thinking or “patient finance” as compared to a short-term focus on profit. We introduce the concept and calculation of a Present Future Value (PFV).

To analyze the combined response of ocular cyclotorsion and head tilt during body tilt and to interpret the physiologic role of those movements, each of the three subjects completed six different experiments of body tilt not fixating their head movements using a flight simulator, which consisted of combinations of three tilt angles (30, 45, and 60) and two visual conditions. Head tilt and ocular cyclotorsion of the right eye before, during, and after the tilt maneuver were recorded and analyzed by time sequence. In the active tilting phase, the right eye showed a stepladder pattern of multiple repeats of fast and slow cyclotorsion along with head tilt to obtain maximum visual information. During the stationary tilting phase, there occurred a small amount (mean, 2.3) of ocular cyclotorsion which was reciprocal to that of head tilt. The visual cue of body tilt through the central visual field induced a larger amount of head tilt but affected little ocular cyclotorsion. The maximum degree of ocular cyclotorsion during each experiment was 10.2 on average. In conclusion, the combined response of ocular cyclotorsion and head tilt develops during body tilt and it compromises the conflicting needs between binocular vision and gravitational orientation.

Tackling the intricacies of network dismantling in complex systems poses significant challenges. This task has relevance across various practical domains, yet traditional approaches focus primarily on singular metrics, such as the number of nodes in the Giant Connected Component (GCC) or average pairwise connectivity. In contrast, we propose a unique metric that concurrently targets nodes with the highest degree and reduces the GCC size. Given the NP-hard nature of optimizing this metric, we introduce MaxShot, an innovative end-to-end solution that leverages graph representation learning and reinforcement learning. Through comprehensive evaluations on both synthetic and real-world datasets, our method consistently outperforms leading benchmarks in accuracy and efficiency. These results highlight MaxShot’s potential as a superior approach to address the network dismantling problem effectively.

In this paper, we study the global existence and exponential decay for a dynamic contact problem between a Timoshenko beam with second sound and two rigid obstacles, of which the heat flux is given by Cattaneo's law instead of the usual Fourier's law. The main difficulties arise from the irregular boundary terms, from the low regularity of the weak solution and from the weaker dissipative effects of heat conduction induced by Cattaneo's law. By considering related penalized problems, proving some a priori estimates and passing to the limit, we prove the global existence of the solutions. By considering the approximate framework, constructing some new functionals and applying the perturbed energy method, we obtain the exponential decay result for the approximate solution, and then prove the exponential decay rate to the original problem by utilizing the weak lower semicontinuity arguments.

Electrical contacts are important circuit components with diverse industrial applications, and their failure can lead to multiple unwanted effects. Hence, the behavior of electrical contacts is a widely studied topic in scientific literature based on various approaches, tools, and techniques. The present study proposes a numerical modeling and simulation approach based on the Holm contact theory to study the dependence between the electric potential and the temperature within an electrical contact. Structured in 5 sections, the research was conducted using COMSOL Multiphysics software and its solid-state mechanics, electric current, and heat transfer modules in order to highlight contact behavior from mechanical, electrical and thermal points of view: the von Mises stress, contact force, the electric field amplitude, the variation of the electrical potential along the current path, the temperature gradient, and dependence of temperature along the contact elements edges were obtained by simulation and graphically represented. The results are in line with the expectations and with past research that was studied in the literature review.

An outbreak caused by coronavirus disease 2019 (COVID-19) occurred in Wuhan City, Hubei Province, China, in December 2019. Up to March 2, 2020, at least 80180 cases have been reported. Most of the patients had a history of visiting Hubei Province or contacting with people who had ever stayed in or passed by Hubei Province, or exposed to symptoms. Some patients got infected only from asymptomatic contacts. This study aimed to report the epidemic features and lab identification of a patient confirmed with COVID-19 infection only from asymptomatic contact.

A typhoon-induced storm surge is considered one of the most severe coastal disasters in Taiwan. However, the combination of the storm surge and the astronomical tide called the storm tide can actually cause extreme flooding in coastal areas. This study implemented a two-dimensional hydrodynamic model to account for the interaction between tides and storm surges on the coast of Taiwan. The model was validated with observed water levels at Sauo Fish Port, Hualien Port, and Chenggong Fish Port under different historical typhoon events. The model results are in reasonable agreement with the measured data. The validated model was then used to evaluate the effects of the typhoon's intensity, bathymetric change, and the combination of the typhoon’s intensity and bathymetric change on the maximum storm tide and its distribution along the east coast of Taiwan. The results indicated that the maximum storm tide rises to 1.92 m under a typhoon with an intensity of a 100-year return period. The maximum storm tide increased from a baseline of 1.26 m to 2.63 m for a 90% bathymetric rise at Sauo Fish Port under the conditions of Typhoon Jangmi (2008). The combination of the intensity of a typhoon with a 100-year return period and a 90% bathymetric rise will result in a maximum storm tide exceeding 4 m, 2 m, and 3 m at Sauo Fish Port, Hualien Port, and Chenggong Fish Port, respectively. We also found that the distribution of the maximum storm tide on the east coast of Taiwan can expand significantly subject to the bathymetric rise.

Monitoring is an important component of pest management, to prevent or mitigate outbreaks of native pests, and to check for quarantine organisms. Surveys often rely on trapping, especially when the target species respond to semiochemicals. Many traps are available for this purpose, but they are bulky in most cases, which raises transportation and deployment issues, and they are expensive, which limits the size and accuracy of any network. To overpass these difficulties, entomologists have used recycled material, such as modified plastic bottles, producing cheap and reliable traps but at the cost of recurrent handywork, not necessarily possible for all end-users (e.g., for national plant protection organizations). These bottle-traps have allowed very large surveys which would have been impossible with standard commercial traps, and we illustrate this approach with a few examples. Here we present, under a Creative Commons BY-SA License, the blueprint of a fan-trap, a foldable model, laser-cut from a sheet of polypropylene, that can rapidly be produced in large numbers, and could be transported and deployed in the field with very little efforts. Our first field comparisons show that fan-traps are as efficient as bottle-traps, and we describe two cases where they are being used for monitoring.

Currently, there is a high interest in smart sensors and integrated composite materials in various industries such as construction, aviation, automobile, medical, information technology, communication, and manufacturing. Here, a new conceptual design for a force and temperature sensor system is developed by integrating fiber optic Bragg grating sensors embedded within composite materials, and a mathematical model is proposed that allows one to estimate strain and temperature based on signals obtained from optical Bragg gratings. This is important for understanding the behaviors of sensors under different conditions and for creating effective monitoring systems. Describing the strain gradient distribution, especially considering different materials with different values of Young's modulus, provides insight into how different materials respond to applied forces and temperature changes. The shape of the strain gradient distribution was obtained, which is a quadratic function with a maximum value of 1500 µ, with a maximum value at the center of the lattice and a symmetrically decreasing strain value with distance from the central part of the fiber Bragg grating. With axial strain at the installation site of the Bragg grating sensor under applied force values ranging from 10 to 11 N, the change in strain was linear. As a result of theoretical research, it was found that the developed system with fiber-optic sensors based on Bragg gratings embedded in composite materials is resistant to external influences and temperature changes.

A reliable and efficient rail track defect detection system is essential for maintaining rail track integrity and avoiding safety hazards and financial losses. Eddy current (EC) testing is a non-destructive technique that can be employed for this purpose. The trade-off between spatial resolution and lift-off should be carefully considered in practical applications to distinguish closely spaced cracks such as those caused by rolling contact fatigue (RCF). A multi-channel eddy current sensor array has been developed to detect defects on rails. Based on the sensor scanning data, defect reconstruction along the rails is achieved using an inverse algorithm that includes both direct and iterative approaches. In experimental evaluations, the EC system with the developed sensor is used to measure defects on a standard test piece of rail with a probe lift-off of 4-6 mm. The reconstruction results clearly reveal cracks at various depths and spacings on the test piece.

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

Background: Upper respiratory tract infections (URTIs) are a major public health concern due to their high incidence and potential for complications. Pharmacists often serve as the first point of contact for patients with URTIs. This study aims to develop and evaluate the RESP-8 tool to assist pharmacists in determining the need for medical evaluation. Methods: This prospective interventional cohort study was conducted over six months (October 2023 to March 2024) in community pharmacies. Participants included adults aged 18 years and older presenting with URTI symptoms. Pharmacists used the RESP-8 tool, which comprises eight criteria to assess the need for medical referral. Data on medical history, symptom duration, and progression were recorded. The primary outcome was the feasibility of implementing the RESP-8 tool. Secondary outcomes included the accuracy of the tool, the percentage of patients recommended for medical evaluation, and compliance with these recommendations. Results: A total of 64 participants were included, with an average age of 55.7 years. Pharmacists recommended medical evaluation for 75% (48/64) of patients using the RESP-8 tool. Among these, 70.83% (34/48) complied with the recommendation. The tool demonstrated high accuracy in identifying patients needing further medical evaluation, with only two noted errors. All compliant patients received appropriate treatment without complications. The tool was easy to implement, taking less than 5 minutes per patient. Discussion: The RESP-8 tool effectively guided pharmacists in recommending medical evaluations for URTI patients. The high compliance rate indicates patient trust in pharmacists' guidance. While the study's small sample size limits generalizability, the results are promising. Future studies with larger populations are necessary to validate these findings and further refine the tool. Conclusion: The RESP-8 tool shows potential in enhancing pharmacists' ability to make informed decisions about medical referrals for URTIs, ultimately improving patient outcomes and optimizing healthcare resource management.

Dynamic time history analysis is a powerful and effective method to study the seismic response of tunnels, the dynamic time history to analyze the seismic response of the tunnel in the typical subway in this paper. The analysis results show that the overall levelling of the tunnel will not affect the tunnel too much, and the seismic response of the tunnel is mainly related to the relative displacement of the ground around the tunnel. The analysis results show that the internal force of the tunnel and the tunnel inclination have a good linear relationship, and the tunnel inclination can be used to measure the magnitude of the seismic response of the tunnel.

The paper presents the prediction of hydrodynamic characteristics of different rudder -plane configurations behind a submarine in deep water through the Reynolds-Averaged Navier-Stokes method in Ansys Fluent Solver. The hydrodynamic force and moment acting on the Cross-plane, X-plane, and Y-plane rudder configurations are analyzed for estimating hydrodynamic coefficientsfor predicting the advantages of each configuration to control the ship. The obtained results show that X-force of the X-plane rudder configuration is larger than the force acting on the Cross-plane rudder and Y-plane rudder configurations. However, Y-force, and Z-force of the X-plane rudder configuration are significantly greater than the Y-force of the left configurations. The same tendency can be seen in the moment of the X-plane rudder about the y-axis and z-axis. The roll moment induced by the Y-plane and Cross-plane rudder configurations is significantly larger than the case of the X-plane rudder configuration.

Analytics have become increasingly popular among sports in recent years, providing valuable information regarding physical and mental health. Many athletes have found that analytics during training can help to improve their performance, reduce the risk of injury, and enhance their overall well-being. This paper aims to improve the results of handball players by applying a method for measuring the influence of different trials on aggregate performance calculated per each athlete in order to qualify for the Olympic Games. By separating the isolated action of each trial, the result is an additional influence caused by the interaction of factors or the simultaneous action. That might explain why the neuromuscular feedback loop is utterly necessary to perform handball motor actions. Further on, the ML analysis can help identify areas for improvement, optimize training programs, and enhance overall team performance.

Background/Objectives: Dental implants have become a cornerstone of restorative dentistry, providing a long-lasting method for tooth replacement. The level of osseointegration has a big impact on the biomechanical stability at the bone-implant contact (BIC), which determines how long these implants will work. However, the exact consequences of changing osseointegration levels on different implant designs, especially in bones with variable densities, are not well known. Three short dental implants were tested in this study: BioMet 3iT3, Straumann® Standard Plus Short Regular Neck (SPS-RN), and Straumann® Standard Plus Short-Wide Neck (SPS-WN). 3D finite element analysis (FEA) was used to look at how well they worked biomechanically. This paper tests the implants at four stages of osseointegration: 25%, 50%, 75%, and 100% in both high-density (Bone Type III) and low-density (Bone Type IV) cancellous bone. It also created and examined realistic CAD models under static occlusal loading conditions to assess stress distribution and major strains at the bone-implant contact.; Results: The study discovered that as osteointegration increases, von Mises stress and principal strains go down significantly for all implant types. The SPS-WN implant had the lowest strain values, especially for bone with low density. These reductions demonstrate increased mechanical stability as the bone-implant inter-face becomes more capable of dispersing mechanical stresses, minimizing the potential for localized deformation and bone resorption.; Conclusions: The results highlight the importance of achieving optimum osseointegration to reduce mechanical stress and increase the lifespan of dental implants. The SPS-WN type implant performed better in biomechanical tests than the others, especially when bone conditions were not ideal. This makes it a great choice for clinical applications that need long-term implant success.

The mortality of birds resulting from collisions and electrocutions with overhead lines, such as power lines, and phone line among others, has been implicated in the decline of various avian species globally. Specifically, overhead line collisions pose a significant threat to the conserva-tion of the Canarian houbara bustard (Chlamydotis undulata fuertaventurae), an endangered sub-species endemic to the Canary Islands. This study centres on the postmortem findings of Canarian houbara bustards that have collided with overhead lines, providing insights into the post-collision outcomes for these birds. A com-plete standardized necropsy of nine Canarian houbara bustards revealed that polytrauma was the cause of death in all cases. The most notable gross lesions associated with trauma included bone fractures, soft tissue lacerations, haemorrhages, luxations, and hemocoelom, with certain body regions being more frequently affected. Histopathology, immunohistochemistry, and en-tomology analysis confirmed that numerous birds survived the initial trauma, exhibiting varia-ble survival intervals before succumbing to their injuries. We concluded that when a houbara bustard collide with an overhead line it frequently survives the initial trauma. The histopathology, immunohistochemistry, or entomologic analysis may be helpful to approximate the timing interval between trauma and death.

The interaction forces and mechanical properties of the interaction between melittin (Mel) and lipopolysaccharide (LPS) are considered a crucial driving force for Mel in killing Gram−negative bacteria (GNB). However, how their interaction forces are performed at the single−molecule level and the dissociation kinetic characteristics of the Mel/LPS complex remain poorly understood. In this study, the single−molecule level interaction forces between Mel and LPSs from E. coil K−12, O55:B5, O111:B4, and O128:B12 were explored using atomic force microscopy (AFM) based single−molecule force spectroscopy (SMFS). Further, the AFM−based dynamic force spectroscopy (DFS) and advanced analytical model were employed to investigate the kinetic characteristics of the Mel/LPSs complex dissociation. The results indicated that Mel could interact with both rough (R)−form LPS (E. coli K−12) and smooth (S)−form LPSs (E. coli O55:B5, O111:B4, O128:B12), and the S−form LPSs showed a more robust interaction with Mel than R−form LPS, and a slight difference existed in the interaction forces between Mel and diverse S−form LPSs. The Mel interacts with S−form LPSs showed greater specific and non−specific interaction forces than R−form LPS (p &lt; 0.05), as determined by AFM−based SMFS. However, there was no significant difference in the specific and non−specific interaction forces among the three S−form LPSs (p &gt; 0.05), indicating the variability of O−antigen could not affect the interaction between Mel and LPSs. The DFS result showed that the Mel/S−form LPSs complexes had a lower dissociation rate constant (koff), a shorter energy barrier width (xβ), a longer bond lifetime (τoff), and a higher height of the energy barrier (∆G), demonstrating that Mel could interact with S−form LPSs to form more stable complexes. In conclusion, this study promotes our knowledge of the interaction micromechanics and kinetics characteristics between Mel and LPS at the single−molecule level. Moreover, it can help us design and evaluate new anti−GNB drugs.

Predictive numerical models in the study of ground-borne vibrations generated by railway sys-tems have traditionally relied on the segmented approach of subsystems. In this approach, loads are individually applied, and the cumulative effect of rolling stock is obtained through superposi-tion. While this method serves to mitigate computational costs, it may not fully capture the com-plex interactions involved in ground-borne vibrations. Recent advancements in computational and software tools have enabled the development of more sophisticated vibrational pollution models. These advanced models encompass the entire dynamic system, from the rolling stock to the terrain, allowing for continuous simulations with a defined time step. Furthermore, the incorporation of computational contact tools between various ele-ments not only ensures temporal accuracy but also extends the analysis to the frequency domain. This paper explores the evolution of predictive numerical models in the context of ground-borne vibrations generated by trains on ballasted tracks. It highlights the shift from segmented models to continuous simulations, demonstrating the progressive advancement towards more comprehen-sive and accurate representations of railway-induced and generated vibrations in the track sur-roundings as an additional way of evaluate sustainability of infrastructures. In particular, this development of a numerical model from its inception aimed to expand upon ex-isting emission - prediction models by enriching the data with frequency-domain information. This approach has been driven by the aspiration to bridge the gap between numerical predictions and measured signals, striving for a higher level of accuracy in our obtained results. This model can predict the impact of a high-speed rail (HSR) vehicle passing on its own track. It possesses sufficient information in both the time and frequency domains to precisely characterize vibrations. This initiative marks a pivotal advancement, enabling us to more effectively capture the intricacies of ground-borne vibrations and their impact on the surrounding environment due to a deeper comprehension of the occurrences in the frequency domain, there's a heightened ca-pability to accurately characterize vibrations.

The electric field is enormously more powerful than the gravitational field. However, in our normal experience there is no electric field, the electric force is missing. How is it that when you get to larger and larger scales the gravitational field is extremely important whereas the electric field becomes less and less important [1]? This paper proposes a model to explain why gravitation dominates at a larger scale.

The pursuit of materials that offer both wear comfort and protection for functional and protective clothing has led to the exploration of weft-knitted spacer structures. Traditional cushioning materials such as spacer fabrics and laminated foam often suffer from deformation under compression stresses, thus compromising their protective properties. This study investigates the enhancement of the force absorption, stress-strain and thermal properties of weft-knitted spacer fabrics with inlays. Surface yarns with optimal stretchability and thermal properties are used and combined with elastic yarns in various patterns to fabricate nine different inlay samples. The mechanical and thermal properties of these samples are systematically analyzed, including their compression, stretchability, thermal comfort and surface properties. The results show that the inlay spacer fabric exhibits superior compression properties and thermal conductivity compared to traditional laminated foam and spacer fabrics, while maintaining stretchability, thus providing a better performance than traditional fabrics for protective clothing and wearable cushioning products. This study further confirms that the type of inlay yarn and inlay structure are crucial factors that significantly influence the thermal, tensile and compressive properties of fabric. This research provides valuable insights into the design and development of advanced textile structures to improve wear comfort and protection in functional garment applications.

The objective of the analysis carried out in this paper is to quantify the impact of subsidies on the activity of two vegetable farms, of different sizes in terms of agricultural area under cultivation, 600 ha and 3000 ha, which can constitute a model at macroeconomic level, indicating the ways in which these farms can ensure their income. For the analysis carried out, indicators were taken into account concerning production, net profit and subsidies received over a period of three years for the agricultural crops grown on these farms, identifying their contribution and effects on profitability. Descriptive statistics, visual inspections and basic comparison methods were also used, thus determining the patterns of the impact of subsidies and their variation for each of the existing crops in the vegetable farms studied. The data on which the statistical models are based are extracted from the financial statements of the farms analysed, giving the possibility of a predictive extension of the evolution of income and, very importantly, of their profitability. The conclusions revealed, for the 600 ha vegetable farm, that this farm maintained its area constant during the analysis period, benefiting from annual subsidies, and that the practice of crop diversification (rape, barley, winter wheat, oats, soybean, maize, lucerne), appropriate rotation, conservation farming and crop irrigation on 85.34% of the area, ensured average yields/ha that exceeded those recorded at national and regional level, except for 2020. The economic performance of this farm is oscillating in the period 2018-2021, with the ability to consistently generate profit, but in 2020 it is close to break-even, a year in which subsidy income tipped the balance towards positive but modest financial results. For this farm, the statistical model carried out was inconclusive because the farm optimises its cropping plan every year, depending on agrometeorological predictions, subsidy levels and market trends, changing crops, thus not being able to estimate the extent to which each crop contributes to maintaining the financial balance of the farm. Thus, although subsidies have impacted the level of net income, the extent to which they have done so is unclear. For the 3000 ha farm, the findings revealed that this farm also has a roughly constant area in use over the analysis period and for which it receives subsidies. This farm practices crop diversification (rape, barley, winter wheat, sunflower, soybean, grain maize, late potatoes, sweet potato, carrot and flowers) and adequate crop rotation. The data highlight that subsidies played a significant and sometimes overwhelming role in determining the gross output of each crop to achieve a positive value of this indicator. Modern conservation farming technologies and crop irrigation on 74.14% of the area justify the average yields/ha achieved, which again exceeded those recorded at national, regional and county level, with the exception of 2020. Maize and soybean crops consistently contributed to the farm's income, with a high gross product and net income, despite changes in the average yield per hectare achieved each year. Good and rising economic performance for this farm during the period under review, which justifies the profitability of the business from an economic, financial and commercial point of view. Although there have been fluctuations in the value of yields realized on different crops, net revenues continued to be high and even up significantly in 2021. Thus, the study highlighted and identified trends and patterns in agriculture, patterns that can serve as a source of information for relevant policy decisions, playing a key role in guiding future research and allocating resources efficiently in the agricultural sector.

A global existential and interlocking environmental, climate and cooperation/equity polycrisis is being faced, which increasingly impacts and is impacted by water and land systems. As a result, transformations in response are gaining increasing traction. Advances in approaches to visualising and communicating how innovations and changes in landscape features enable shifts, transformations and transitions are more crucial than ever before. Visions help focus actions, collaboration and alignment of multiple actors in working towards a common purpose, whilst also entering people’s consciousness at the deep level of values, transforming beliefs and consequently, thinking and action. They give direction on effort and pull on transformational innovation. The evidence-based ‘Water Visions Visualisation Platform’ presents an innovative and accessible way to illustrate, communicate and support future water visioning and strategizing at the landscape scale based on composite paradigms, scenarios, horizons and concepts. Plausible visions of the future are envisioned, illustrated, narratively described and qualitatively assessed, as well as connected with real-world examples and resources through the interactive Platform. This paper outlines the co-creation methodology, the architecture and the co-development of the Platform, as well as a preliminary evaluation through literature-based criteria and the sharing of the Platform with a number of audiences.

Contact tracing has become a vital tool for public health officials to effectively combat the spread of new diseases, such asthe novel coronavirus disease COVID-19. Contact tracing is not new to epidemiologist rather, it used manual or semi-manualapproaches that are incredibly time-consuming, costly and inefficient. It mostly relies on human memory while scalabilityis a significant challenge in tackling pandemics. The unprecedented health and socio-economic impacts led researchersand practitioners around the world to search for technology-based approaches for providing scalable and timely answers.Smartphones and associated digital technologies have the potential to provide a better approach due to their high level ofpenetration, coupled with mobility. While data-driven solutions are extremely powerful, the fear among citizens is thatinformation like location or proximity associated with other personal data and can be weaponised by the states to enforcesurveillance. Low adoption rate of such apps due to the lack of trust questioned the efficacy and demanded researchers tofind innovative solution for building digital-trust, and appropriately balancing privacy and accuracy of data. In this paper,we have critically reviewed such protocols and apps to identify the strength and weakness of each approach. Finally, wehave penned down our recommendations to make the future contact tracing mechanisms more universally inter-operable andprivacy-preserving.

In cross-country skiing the time difference between a race winner and the person coming second is typically very small. Since much of the energy is spent on overcoming resistive forces, a relatively small reduction of these can have a significant impact on the results. The resistive forces come partly from the friction in the tribological interface, between the ski and the snow, and as with many tribological applications the characterisation of its origin, plays an important role in determining the frictional properties. Also in cross-country ski friction, there are several scales impacting the frictional performance, with the major contributors being the ski-camber profile and ski-base structure. Macro-scale measurements of the ski's camber profile under load, are often used to determine how adequate the ski is for a specific condition. The characteristic properties usually obtained are, the force required to collapse the ski to a certain camber height, the topography of the kick-wax zone, and by simple means a determined lengths of the frictional interface, i.e., the apparent contact length. To this date, there are some mathematical models, but there is no robust way of determining the macro-scale contact properties between a cross-country ski and a counter surface using simulations. In the present paper an Artificial neural networks (ANN) is trained to predict the ski-camber profile for various loads placed at different positions, and a well established deterministic approach is used to simulate the contact between the ANN-predicted ski-camber profile and a linearly elastic body with a flat surface, representing the snow. The results suggest that this method is feasible for the determination of the apparent contact characteristics of different skis. Moreover, we show that the apparent contact area does not linearly depend on the load, and that the elastic properties of the counter surface also has a large impact on the apparent contact area and the average apparent contact pressure.

Proteins have the ability to adsorb on the surface of materials, such as soft contact lenses (SCLs), and can affect the hydrophobicity, roughness and surface properties of the contact lenses (CLs), which, in turn, can influence the friction between the lenses and the ocular surface. Excessive friction between contact lenses and the ocular surface can lead to discomfort for the wearer and may cause irritation or inflammation of the cornea, better known as corneal ulcers (keratitis). Bovine serum albumin (BSA) is often used as a standard protein in biocompatibility testing of materials, including contact lenses. One standard commercial contact lenses was tested under lubricated conditions to access the coefficient of friction (CoF), being the contact lubricated with a tear like fluid (TLF) solution containing six different concentrations of BSA. In all cases, a good linearity of the results of the friction force was verified, so the first friction law can be applied to determine the value of the coefficient of friction. It was found that friction increases with increasing protein concentration.

Digital gait monitoring is increasingly used to assess locomotion and fall risk. The aim of this work is analyzing the changes in the foot-floor contact sequences of Parkinson’s Disease (PD) patients in the year following the implant for deep brain stimulation (DBS). During their best-ON condition, 30 PD patients underwent gait analysis at baseline (T0), at 3 months (T1), and 12 months (T2) after the DBS neurosurgery for bilateral high-frequency subthalamic nucleus stimulation. Thirty age-matched controls underwent gait analysis once. Each subject was equipped with bilateral foot-switches and a 5-minute walk was recorded, including both straight-line and turnings. The walking speed, turning time, stride time variability, percentage of atypical gait cycles, stance, swing, and double support duration were estimated. Overall, the gait performance of PD patients improved after DBS, as also confirmed by the decrease in the UPDRS-III score from 19.4±1.8 to 10.2±1.0 points (T0 vs. T2) (p < 0.001). In particular, the percentage change of atypical gait cycles of PD more affected side decreased at T1 (Straigh-line: -72%; Turnings: -43%) and at T2 (Straigh-line: -54%; Turnings: -20%). The percentage of atypical gait cycles proved an informative digital biomarker for quantifying PD gait changes after DBS, both in straight-line paths and turnings.

Hypersonic aircraft focuses more on the integration of aircraft and engine than ordinary aircraft owing to high performance requirements, and the nozzle design is reflected in the required large area ratio of nozzle inlet and outlet and the compactness of the overall size of the aircraft. In this study, the height constraint is directly introduced into the maximum thrust nozzle design method. A new method for designing nozzles under the height constraints that consults the maximum thrust theory is proposed. Initially, the condition that the nozzle reaches the maximum thrust under the height constraint is deduced mathematically. Then, a nozzle design method satisfying the height constraint is computed using the method of characteristics (MOC). Subsequently, the influence of the design parameters on the design method is studied parametrically. Results show that Mach number scale and asymmetrical factors can affect ramp length and flap length of the nozzle, respectively. These factors great influence the axial thrust performance and lift under a specific height constraint. Compared with the traditional truncation design method, the thrust coefficient and lift increased by 11.93% and 138.45% respectively.

Maximum entropy production principle (MEPP) has been formulated in the mid-twentieth century, and today it has acquired the status of an important principle of science, which is extremely effective in considering various non-equilibrium problems. In this study, for the first time, definition of life is based on an easily measurable physical quantity that is entropy production. Life and evolution are discussed from the point of view of MEPP and the Universe, but not a human

The effectiveness of combining strength-specific training with endurance training to enhance the performance of endurance runners remains uncertain. This study aimed to analyze effect of practising maximum-strength (MAX), explosive strength (EXP) or both combined (COMB) on seven runners’ performance-indicators: vertical jump (VJ), one-repetition-maximum-squat (1RM), peak-velocity/peak-running-speed (PV), lactate-threshold (over incremental-test-protocols, LT), middle-distance-time-trial (TT), maximum-oxygen-consumption (VO2max), running-economy (RE). Systematic-review (Scopus, Wed of Science, Sports Discuss, PubMed) with meta-analysis was conducted following PRISMA standards. Inclusion-criteria (PICOS) were: recreational or well-trained athletes aged 18-45 performing concurrent-training ≥five-week. Used search-terms were related to different types of strength/endurance, participants’ age, sport-modality. 20 manuscripts were selected, quality-assessed with PEDro. MAX training is more effective than EXP, COMB in improving VJ, 1RM, PV, while COMB is more effective than MAX, EXP to enhance TT. MAX is more effective than EXP in improving LT. Concurrent-workouts do not provide additional benefits to VO2max. It is unknown which strength-modality (MAX, EXP or COMB) is more effective in improving RE. Concurrent-training is more effective than single-mode-endurance-training for enhancing specific performance-variables in adult-endurance-runners. Middle-, long-distance-runners may consider incorporating MAX-training to target specific goals, e.g., improving VJ, 1RM, LT, PV while utilizing COMB-training to enhance TT. Certain variables may benefit from EXP. New randomized-controlled-trials are required to confirm these findings.

Abstract: Understanding the reliability and sensitivity of jump testing is essential to determine the neuromuscular progress of athletes and make informed decisions. This study aimed to assess the reliability and sensitivity of countermovement jump (CMJ) and drop jump (DJ) tests metrics in female volleyball players. Sixteen semi-professional female volleyball players participated in the study. Intrasession and intersession reliability of CMJ and DJ metrics were evaluated using a randomized cross-over design. Dual force platform was used to collect data, and several dependent variables were calculated using forward dynamics. Intraclass correlation coefficients (ICC), coefficients of variation (CV) and minimum difference (MD) were calculated. The third attempt presented the highest values for both test, and changes in jump strategy in DJ. CMJ is consistent across sessions, while DJ also shows intersession differences (p<0.05) in 11 out of 15 variables. Most CMJ variables exhibit excellent reliability while DJ variables have lower reliability and higher variability. Concentric and eccentric impulses for DJ showed excellent reliability. Most CMJ variables showed excellent reliability and variability, DJ had lower reliability, higher variability, and lower sensitivity. These findings provide valuable information when assessing athletes' performance and highlight the reliability, sensitivity, and variability in jump performance for CMJ and DJ tests.

The need for continuous research to refine the models used in accident reconstruction appears with the development of new car models that satisfy consumer complaints. The paper analyzed a sub-sequence of car and pedestrian accidents, from the perspective of the distance traveled by them in the contact phase, with the aim of improving the information regarding the reconstruction of road accidents. The research included the analysis of some accidents with pedestrian dummies, as well as the simulation of the impact between different classes of vehicles and pedestrians in two different walking positions. Specialized software was used with complex multibody models of pedestrians, modifying the speed and deceleration parameters at the time of the collision. The research results highlight the differences between bilinear models used in accident reconstruction and the proposed study. They can also be used to determine the distance traveled by the vehicle in the first phase of the collision with pedestrians.

Should our planet be visited by an extraterrestrial civilization, the prevailing assumption would undoubtedly be that the extraterrestrial civilization is Type I i.e. its capacity for interstellar travel results from its technological development. This assumption is dangerous for it unnecessarily leads to the Extraterrestrial Tandem Hypothesis (ETH): the belief than an extraterrestrial civilization technologically capable of interstellar travel must also be technologically compatible with the inexorably rapid annihilation of life on Earth. Such a state of things would compromise the planet’s capacity to stage a confident defense should the extraterrestrials prove belligerent. The presumption of Type I extraterrestrials (on the premise of the capacity for interstellar travel alone) is unfounded as extraterrestrials may be Type II i.e. capable of interstellar travel by virtue of natural intrinsic or extrinsic factors. This paper advances, most importantly, that the fundamental policy of first contact should be the employment of various strategies toward the evaluation of the technological capacity of visiting extraterrestrials. This evaluation must be particularly devoted to the detection of Type II extraterrestrials masquerading as Type I (using concealment and Wizard of Oz strategies). Integral to this detection are the concepts of the precedence relation and The Extraterrestrial Exclusion Principle (EEP). A precedence relation is a qualitative relation expressing the relative difficulty of producing a technological action. The Extraterrestrial Exclusion Principle states that a Type I extraterrestrial life form is excluded from certain actions. Such actions are lower in precedence than interstellar travel and may be described as in violation of the EEP or EEP forbidden. EEP actions reveal extraterrestrials to be Type II. As an example, the value of the Hawking Warning is subjected to EEP analysis. Furthermore, a hypothetical conundrum in linguistics termed the Kryptonian Linguistic Paradox (KLP) is discussed as a case of an EEP forbidden act. Finally, the paper explores the limitations of the stated fundamental policy of first contact.

Contact tracing is one of the oldest social network health interventions used to reduce the diffusion of various infectious diseases. However, some infectious diseases like COVID-19 amass at such a great scope that traditional methods of conducting contact tracing (e.g., face-to-face interviews) remain difficult to implement, pointing the need to develop reliable and valid survey approaches. The purpose of this research is to test the effectiveness of three different egocentric survey methods for extracting contact tracing data: (1) a baseline approach, (2) a retrieval cue approach, and (3) a context-based approach. A sample of 397 college students were randomized into one of each condition and were prompted to anonymously provide contacts and populated places visited from the past four days. After controlling for various demographic, social identity, psychological, and physiological variables, participants in the context-based condition were significantly more likely recall more contacts (medium effect size) and places (large effect size) than the other two conditions. Theoretically, the research supports suggestions by field theory that assume network recall can be significantly improved by activating relevant activity foci. Practically, the research contributes to developing innovative social network data collection methods for contract tracing survey instruments.

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

Background: The risk to physicians who worked with patients without confirmed COVID-19 testing during the pandemic has been little studied. However, they were at high risk. Methods: A total of 1285 Romanian physicians completed an online survey. We performed Mann-Whitney comparisons between physicians who reported that they knowingly had direct contact with COVID patients and those who didn't regarding their willingness to work. Results: Compared with their colleagues, physicians who reported not knowingly having direct contact with COVID patients reported less access to protective equipment, less overall willingness to respond when asked to work with infected patients, more likely to work out of fear of losing their jobs, and fear of legal repercussions. They received less training in the use of protective equipment. Conclusions: Physicians who worked with patients not yet diagnosed with COVID-19 were significantly less willing to work. The perception of invisible risk may explain the observed differences.

(1) Background: Little research has been done on professionals' perceptions of institutions and governments during epidemics. We aim to create a profile of physicians who feel they can raise public health issues with relevant institutions during a pandemic. (2) Methods: A total of 1285 Romanian physicians completed an online survey as part of a larger study. We used binary logistic regression to profile physicians who felt able to raise public health issues with relevant institutions; (3) Results: Five predictors could differentiate between respondents who tended to agree with the trust statement and those who tended to disagree: feeling safe at work during the pandemic, considering the financial incentive worth the risk, receiving training on the use of protective equipment, having the same values as colleagues, and enjoying work as much as before the pandemic; (4) Conclusions: Physicians who trust the system to raise public health issues with the appropriate institutions feel they share the same values as their colleagues, say they were trained in the use of protective equipment used during the pandemic, felt they were safe at work during the pandemic, enjoyed their work as much as before the pandemic, and felt the financial bonus justified the risk.

(1) Background: To further investigate the link between inadvertent tooth movements (ITMs) and mechanical properties of different retainers, the response upon vertical loading was compared in three different retainers (two stainless steel and one nickel-titanium). The influence of different reference teeth was also considered. (2) Methods: Three retainers (R1, R2, R3) were tested in a newly developed biomechanical analysis system (FRANS). They were bonded to 3D-printed models of the lower anterior jaw and vertically displaced up to 0.3mm. Developing forces and moments were recorded at the center of force. (3) Results: The vertical displacement caused vertical forces (Fz) and labiolingual moments (My) to arise. These were highest in the lateral incisors (up to 2.35±0.59N and 9.27±5.86Nmm for R1; 1.69±1.06N and 7.42±2.65Nmm for R2; 3.28±1.73N and 15.91±9.71Nmm for R3) for all analyzed retainers, and with the R3 retainer for all analyzed reference teeth, while the lowest Fz and My values were recorded with the R1 retainer. (4) Conclusions: Displacements of 0.2mm and larger provided forces and moments which could be sufficient to cause unwanted torque movements, such as ITMs in all analyzed retainers. Clinicians must be mindful of these risks and perform posttreatment checkups on patients with retainers of all materials.

The manual muscle test (MMT) is a flexible diagnostic tool, which is used in many disciplines, applied in several ways. The main problem is the subjectivity of the test. The MMT in the version of a “break test” depends on the tester’s force rise and the patient’s ability to resist the applied force. As a first step, the investigation of the reproducibility of the testers’ force profiles is required for valid application. The study examined the force profiles of n=29 testers (n=9 experiences (Exp), n=8 little experienced (LitExp), n =12 beginners (Beg)). The testers performed 10 MMTs according to the test of hip flexors, but against a fixed leg to exclude the patient’s reaction. A handheld device recorded the temporal course of the applied force. The results show significant differences between Exp and Beg concerning the starting force (padj=0.029), the ratio of starting to maximum force (padj=0.005) and the normalized mean Euclidean distances between the 10 trials (padj=0.015). The slope is significantly higher in Exp vs. LitExp (p=0.006) and Beg (p=0.005). The results also indicate that experienced testers show inter-tester differences and partly even a low intra-tester reproducibility. That highlights the necessity of an objective MMT-assessment. Furthermore, an agreement on a standardized force profile is required – a suggestion is given.

This work (in two parts) will review the recently developed predictive modeling methodology called “4th-BERRU-PM” and its applicability to energy systems as exemplified by an illustrative application to the Polyethylene-Reflected Plutonium (acronym: PERP) OECD/NEA reactor physics benchmark. The acronym 4th-BERRU-PM designates the “Fourth-Order Best-Estimate Results with Reduced Uncertainties Predictive Modeling” methodology, which yields best-estimate results with reduced uncertainties for the first fourth-order moments (mean values, covariance, skewness, and kurtosis) of the optimally predicted posterior distribution of model results and calibrated model parameters. The 4th-BERRU-PM uses the Maximum Entropy (MaxEnt) principle to incorporate fourth-order experimental and computational information, including fourth (and higher) order sensitivities of computed model responses to model parameters, thus incorporating, as particular cases, the results previously predicted by the second-order predictive modeling methodology 2nd-BERRU-PM, and vastly generalizing the results produced by extant data assimilation and data adjustment procedures. The 4th-BERRU-PM methodology encompasses the scopes of high-order sensitivity analysis (SA), uncertainty quantification (UQ), data assimilation (DA) and model calibration (MC). The application of the 4th-BERRU-PM methodology to energy systems is illustrated by means of the above-mentioned OECD/NEA reactor physics benchmark, which is modeled using the neutron transport Boltzmann equation involving 21976 imprecisely known parameters, the solution of which is representative of “large-scale computations.” The model result (“response”) of interest is the leakage of neutrons through the outer surface of this spherical benchmark, which can be computed numerically and measured experimentally. Part 1 of this work illustrates the impact of high-order sensitivities, in conjunction with parameter standard deviations of various magnitudes, on the determination of the expected value and variance of the computed response in terms of the first four moments of the distribution of the uncertain model parameters. Part 2 of this work will illustrate the capabilities of the 4th-BERRU-PM methodology for combining computational and experimental information, up to and including forth-order sensitivities and distributional moments, for producing best-estimate values for the predicted responses and model parameters while reducing their accompanying uncertainties.

Africa's health landscape is rapidly changing, requiring new solutions such as a focus on health literacy. However, there is currently a limited overview of the development and application of health literacy in African countries and societies. To inform progress, a scoping review was conducted, including a systematic literature search of research approaches, historical developments, geographic origins, target populations and settings, and topical interests. 336 articles were retrieved from six databases following PRISMA guidelines. Sources identified included reports, policy briefs, book chapters, and research publications. The analysis provided the most comprehensive overview of the current scope and scale of health literacy in Africa to date. The publications represented 38 of the 54 African Union countries and dated back to 2001, although most were published in the last decade. The content analysis identified 13 broad themes, including mental health, communicable diseases, non-communicable diseases, maternal health, digital health, information and communication, health care, prevention and health promotion, conceptual perspectives, cultural perspectives, outcomes and measurement. The stakeholder analysis revealed a wide range of actors involved in different settings, mostly in health care or community settings. These comprehensive and novel findings can be used to prioritize future actions for public and professional capacity building, policy development and improved practice to improve health literacy for all in Africa.

The aim of this study was to quantify methane (CH4) emissions from dairy cows during milking by maximum amplitude of eructation peaks and compare estimates with other metrics for CH4 emissions. Spot measurements of CH4 and carbon dioxide (CO2) emissions were recorded for at least 7 days of continuous sampling using an infrared gas analyser in a robotic milking station whilst cows were milked. Concentrations of CH4 and CO2 were measured at 1 second intervals. A total of 105,701 CH4 spot measurements were obtained from 2,206 dairy cows on 18 farms. Methane emissions per individual cow were quantified by maximum amplitude of eructation peaks, average area under eructation peaks (integral of eructation), average concentration during milking and ratio of CH4 to CO2 concentration. There was a high correlation (r = 0.71) between CH4 emissions quantified by maximum amplitude and integral of eructation peaks. The correlation between maximum amplitude and average CH4 concentration was low, and there was no correlation between maximum amplitude and ratio of CH4 to CO2. As both approaches identify and extract eructation peaks to quantify enteric CH4 emissions, the substantial association between maximum amplitude and eructation integral was expected.

In recent decades, there have been numerous endeavors to develop a novel category of survival distributions possessing enhanced flexibility through the extension of existing distributions. This article constructs and validates the statistical properties of a novel survival distribution in order to obtain an alternative distribution that is suitable for analyzing survival data by presenting the novel mixture of the Fréchet distribution along with statistical properties such as the probability density function (PDF), cumulative distribution function (CDF), rth ordinary moment, skewness, kurtosis, moment-generating function, mean, variance, mode, survival function, hazard function, and asymptotic behavior, as well as constructing the estimators of the unknown parameter by employing the expectation-maximization (EM) algorithm, and simulated annealing. Additionally, the performance of the proposed estimators was compared with bias, mean squared errors (MSE), and simulated variances, and given an illustrative example of the proposed distribution to the survival data set in order to show that the proposed distribution is appropriate for the right-skewed data. This will be extremely advantageous in survival analysis.

The proliferation of Unmanned Aerial Vehicle (UAV) networks is increasing, driven by their capacity to deliver automated services tailored to the varied demands of numerous smart city applications. Trust, security, and privacy remain paramount in the public domain. Traditional centralized network designs fall short of ensuring device authentication, data integrity, and privacy within UAV networks’ highly dynamic and adaptable environments. Decentralized reputation systems emerge as a promising solution to enhance the reliability and trustworthiness of data and communications within these networks while safeguarding UAV security. This paper presents an exhaustive survey of trust and reputation systems, exploring existing frameworks and proposed innovations alongside their inherent challenges. It highlights the crucial role of reputation systems in strengthening trust, security, and privacy throughout these networks and discusses various strategies to mitigate existing vulnerabilities. As a useful resource for researchers and practitioners seeking to advance the state of the art in UAV network security, we hope this survey will spark further community discussion and stimulate innovative ideas in this burgeoning field.

The Principle of Indifference (“PI”: the simplest non-informative prior in Bayesian probability) has been shown to lead to paradoxes since Bertrand (1889). Von Mises (1928) introduced the “Wine/Water Paradox” as a resonant example of a “Bertrand paradox”, and which has been presented as demonstrating that the PI must be rejected. We now resolve these paradoxes by a Maximum Entropy (MaxEnt) treatment of the PI that also includes information provided by Benford’s “Law of Anomalous Numbers” (1938). We show that the PI should be understood to represent a family of informationally-identical MaxEnt solutions; each solution being identified with its own explicitly justified boundary condition. In particular, our solution of the Wine/Water Paradox exploits Benford’s Law to construct a non-uniform distribution representing the universal constraint of scale invariance, which is a physical consequence of the Second Law of Thermodynamics.

The recent glaciation of the southern part of the Altai is estimated (1256 glaciers with the total area of 559.15±31.13 km2), the area of the glaciers of the whole Altai mountains is evaluated by 1096.55 km2. In the southern part of Altai 2276 glaciers with the total area of 1348.43±56.16 km2 were reconstructed, the first estimate of the LIA glacial area for the whole Altai mountain system is given (2288.04 km2). Since the LIA the glaciers decrease by 59% in the southern part of Altai and by 47.9% for the whole Altai. The ELA in the southern part of Altai increased averagely by 106 m. The higher changes of ELA in relatively humid areas is probably caused by decrease of precipitation. Glaciers of Tavan Bogd glacial center degraded with higher rates after 1968 relative to the interval between 1850-1968. One of the intervals of the fastest shrinkage of the glaciers in 2000-2010 was caused by unfavorable for the glaciers dry and warm interval 1989-2004. However, the fast decrease of the glaciers in 2000-2010 was mainly caused by the shrinkage or disappearance of the smaller glaciers, large valley glaciers started fast retreat after 2010.

This paper reviews the low-resilience problem in many cities, poor designs of cities to cope with disasters, and the need for tolerance of urban constructions. It explores answers concerning the question of how shall we build cities resiliently? The method of this applied research is a multiphase process that considers all physical and socioeconomic elements of a city. It introduces six indicator groups of urban management (M), economy (E), built environments (U), Infrastructures (I), natural environments (N), and health protection (H). The groups include 55 indicators as variables in the mathematical calculations in this paper. This paper builds a mathematical model to maximize the profitability of resilient buildings by optimizing investments in the required projects. The projects will upgrade the firmness and tolerance of cities against nature-based and human-made dangers and risks. There is a linear programming in 55 variables to select optimal solutions from fifty-five factorial alternatives. Then, the programming will develop into non-linear programming. The unique innovation of this paper is its linear programming interpretation by non-linear to give optimal solutions for the problem. Applying the Lagrange function in the Kuhn-Tucker conditions proves the accuracy of the hypothesis that post-COVID urbanization requires maximum resilience. Only in this way, the urban economies will be free of risks. Outcomes in this paper will assist in the pre-planning, design, and building of built environments everywhere resilient and sustainable.

In this paper we re-investigated the relationship between the symmetry of inertial systems and the Lorentz transformation. We found that when we just follow the following three principles: (1)we can define the time in the whole space with a prescribed clock synchronization, (2)the time-space is uniform and the space is isotropic and (3)all the inertial systems are equivalent, then we can totally construct a general coordinate transformation to meet the symmetry of inertial systems, and with a special assumption on the speed of light, we can construct a non-Lorentz transformation between inertial systems to make the particle’s energy have a limited value, which is similar to the rainbow model. Similar to the usual Lorentz violating models, the non-Lorentz transformation in this paper lead to a new modified disperse relation. We applied the obtained disperse relation to analyze the photon’s arrival time lag effect in astronomy and found that the "maximum energy" derived in our model is somewhat related to the "maximum energy" assumed in the rainbow model.

Common prosperity is the core goal of rural revitalization, and sustainable growth of farmers' income is an inevitable requirement. This study uses CLDS2016-2020 village and family level questionnaire data to reveal how the degree of village organization affects the sustainable growth of farmers' income, thus providing reference and decision-making for the local government to promote the increase of farmers' income and narrow the gap from the village level. The results show that the degree of village organization can significantly affect farmers' income, and the analysis results of the degree of formal organization are consistent with them. Specifically, for every 1% increase in the degree of village organization, the per capita household income will increase by 32.4%, among which the wage income will increase by 22.6%, the operational income will increase by 5%, the property income will increase by 0.8%, and the transfer income will increase by 4.2%. The estimation results through instrumental variables are consistent, and the results are robust. At the same time, improving the degree of village organization can also significantly increase the proportion of farmers' non-agricultural income and narrow the income gap among farmers. On the impact of heterogeneity, it is found that the geographical distance between villages and county and township governments, as well as the political identity and education level of farmers will affect the role of the degree of organization. The results of mechanism analysis show that improving the degree of village organization is mainly through promoting the circulation of agricultural land, socialized service of agricultural machinery and industrial and commercial capital to the countryside to increase farmers' income. The research revealed that the modernization of rural governance should be accelerated, and the degree of village organization should be improved, especially the degree of formal organization, so as to build a benign trust and cooperation relationship between the two village committees and the villagers, and implement policies and measures to improve the income of farmers according to local conditions. At the same time, strengthen the publicity and education in party member to improve the proportion of rural party member and the education level of farmers.

Malignant lymphoma is an unusual form of gallbladder neoplasm. Almost all of these tumors are diffuse large B-cell lymphomas or mucosa-associated lymphoid tissue-type lymphomas. Herein, we report a rare case of a gallbladder Burkitt’s lymphoma (BL) in a child living with HIV. As far as we are concerned, this is the secondfirst report in the pediatric population and the first one in an individual living with HIV. The patient (a five-year-old black female child) attended the Federal Hospital of Lagoa, Rio de Janeiro, Brazil, underwent cholecystectomy and the postoperative pathological analysis of the gallbladder revealed a diagnosis of BL (EBV-positive). Also, HIV serology was performed and returned positive. She was transferred to the Martagão Gesteira Institute of Pediatrics and Childcare for oncological treatment, dying from sepsis and disease progression about 18 months later. Patient did not undergo ART/cART. Previous cases of gallbladder BL were herein described and analyzed to characterize the clinicopathological features and possible similarities. BL can occur in the gallbladder both in the context of HIV infection and in the pediatric population. Biopsy is mandatory in cases with suggestive findings of lymphoma, and an early diagnosis can change the course of the disease. Furthermore, the case highlights the importance of an early initiation of ART/cART in people living with HIV (PLWH).

In diabetic foot injury prevention, no studies relate physical activity with the inflammatory response of the plantar tissues, evaluated by thermography and pressure distribution. These measurements are easy to be implemented in diabetic foot follow-up. The objective of this study was to analyze whether the plantar skin response, evaluated with thermography, after physical activity in healthy or diabetic patients, is a foot ulcer prognostic tool and to asses if there is a correlation between exercise intensity, plantar pressure and plantar thermographic response. A systematic review was carried out following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) format in the PubMed, Scopus and Web of Science databases, with no year limit during the second quarter of 2024. A total of 14 studies have been included in this review. The use of infrared thermography for early inflammatory tissue detection, plantar pressures and the monitoring of controlled physical activity, make possible to monitor changes that allow the identification of patients at risk of developing foot ulcers.

In this study, a computational method is proposed that employs Recurrent Convolutional 1 Neural Networks, utilizing meteorological radar images to forecast storm movement and intensity up 2 to 3 hours ahead, a process known as nowcasting. For this purpose, images from a radar situated in 3 southern Brazil were used. These data are publicly accessible on the website of the National Institute 4 for Space Research (INPE) in Brazil. The approach involves evaluating a spatiotemporal learning 5 recurrent convolutional neural network called PredRNN++. The results were validated through 6 case studies of storms within the radar’s coverage area. To evaluate the performance of the neural 7 network, both visual assessments and metrics such as RMSE and SSIM were employed. The findings 8 indicate that PredRNN++ was effective in simulating the shape and location of the meteorological 9 system.

The aim of the study was to determine the maximum safe concentration of calcium and phosphate in neonatal parenteral nutrition (PN) solutions when various combinations of inorganic and organic salts are applied. Twelve PN solutions for neonatal use were aseptically prepared. Increasing concentration of inorganic and organic calcium and phosphate were added to the standard formulas. Each admixture was separately tested according to following conditions; after mixing, 37°C for 24 h, and maximum safe combination of calcium and phosphate were stored at 4°C for 30 days and followed by 24 h at 37°C. Visual inspections against a black and white contrast background, microscopic observation of undiluted PN solutions as well as the membrane filter after filtration of the PN solution, pH evaluation, and spectrophotometry at 600 nm were examined in triplicate. Safe maximum concentration of organic and inorganic calcium and phosphate was proposed individually for each composition of parenteral nutrition solutions. Surprisingly organic calcium with organic phosphate showed precipitation but over the therapeutic range. The protective effect of amino acid was observed and higher concentrations of calcium and phosphate were free of precipitation.

The Universe is treated as an unbound thermodynamic system in which two forces of Nature compete: Attractive gravity loss and repulsive entropic gain. Entropic gain, although not presently considered a force of Nature, is otherwise well known and can be expressed with the gas laws. The Universe at the time of last scattering was all gas. Its instant gain is expressed as gas pressure. When the Gibbs equation is properly applied to this unbound gas, the resulting atomic Hubble parameter is found to be exclusively dependent on baryon density, giving a constant and perpetual two-to-one gain/loss ratio. Instant loss to gravity cannot offset gas pressure in this “thermal equation”. By contrast, the Friedmann equation, a ΛCDM foundation, treats baryon mass as accreted, having little if any entropic gain. These two equations are actually equivalent. Expanding accreted matter at its comoving critical density is herein shown to behave exactly like a freely expanding gas. However, neither equation includes all of today’s Universal kinetic energy, and cannot by themselves fully account for observed stellar movement. The present paper proposes the plausible existence of highly energetic or “suprathermal” free electrons which comprise about half of the intergalactic medium’s kinetic total. It is this suprathermal energy which Λ expresses. The fluid equation, another ΛCDM foundation, eliminates entropic gain from the Gibbs equation. Additionally, rest mass’s Einstein energy E=Mc² is treated as a thermal variable. These two assumptions, isoentropy and energy conflation, led astronomers to populate Λ as they followed the prior art.

This article deals primarily with the problem of determining the cutting force when machining hardened steels. Secondary issues are focused on the evaluation of surface quality on machined samples and the recommendation of cutting conditions. A wide variety of components are used in engineering, the final heat treatment of which is hardening. These components are usually critical in a particular product. The quality of these components determines the correct functioning of the entire technical equipment and ultimately its service life. In our case, these are the core parts of thrust bearings, specifically the rolling elements. The subject of the experiment is machining these components in the hardened state with cubic boron nitride tools and continuous measurement of the cutting force using a dynamometer. The following evaluation assesses the surface quality by both touch and non-touch methods. A structural equation with appropriate constant and exponents was then constructed from the data obtained using the dynamometer.

This paper provides a new management method (MM) to optimally operate standalone direct current (DC) photovoltaic water pumping system (PVWPS) and synchronize its hydraulic performance to variable daily irradiance. The proposed approach well considers the issues from PV generator and a positive displacement pump mismatching to deserve a hydraulic network. Accordingly, Management Method uses small pumps mounted in parallel scheme to displace the hydraulic power point (HPP) in order to satisfy the mal adequacy between supply and load. Based on experimental Study; this approach showed a yielded standalone system, possibility of running pumping system using only photovoltaic supply (Without use of capacitance), and possibility to design more economical PV systems as the maximum peak power demand for each month can be satisfied using small power pumps in parallel and adjusting their switch with accordance to varying daily irradiance. Moreover, an analytical model was developed with reference to the obtained experimental results. This model based on a daily occurring irradiance as inputs in order to predict optimal performance outputs. It can be considered as a decision tool to track power point resulting from optimal electrical and hydraulic performances of the pumping system according to changes of the daily irradiance.

(1) Background: The aim of this investigation is to determine the effect of archwires’ deflection on the temperature transitions driving the austenite to martensite transformation (and vice versa) and the force released by NiTi and CuNiTi orthodontic wires. (2) Methods: Round cross-section archwires have been investigated. The calorimetric approach has been used for measuring transition temperatures occurring in the unstressed (e.g. undeflected) state of the wires. Static Thermo-mechanical analysis in a temperature controlled wet environment has been performed in the range of temperature between 5°C and 55°C for measuring temperature transitions occurring in highly deflected archwires in conjunction with the force released by these wires. (3) Results: Plateau forces investigated in Part I and those reported in the literature describes the wire’s behaviour only at deflection levels close to the end point of the force plateau extension detected at 37°C. Upon heating or cooling, the austenite finish (Af) transition temperature and the martensite start (Ms) temperature largely depends on the deflection level for both NiTi and CuNiTi. (4) Conclusions: The plateau force levels at 37°C, broadly reported in the literature, only represent the lower boundary force that a superelastic wire releases at 37°C above its elastic limit. For both NiTi and CuNiTi, plateau force levels at 37°C can be predicted by the static TMA profile matching the end point of the force plateau extension. Transition temperatures in largely deflected wires are significantly higher than those determined through the calorimetric approach.

The basis of the work of electroencephalography (EEG) is the registration of electrical impulses from the brain or some of its individual areas using a special sensor/electrode. This method is used for the treatment and diagnosis of various diseases. The use of wet electrodes in this case does not seem viable, for several well-known reasons. As a result of this, a detailed analysis of modern EEG sensors developed over the past few years is carried out, which will allow researchers to choose this type of sensor more carefully and, as a result, conduct their research more competently. Due to the absence of any standards in the production and testing of dry EEG sensors, the main moment of this manuscript is a detailed description of the necessary steps for testing a dry electrode, which will allow researchers to maximize the potential of the sensor in the various type of research.

COVID-19 is frequently associated with a coagulopathy with severe consequences. The mechanisms leading to a pro-coagulant state in these patients is multifactorial, including tissue destruction and inflammatory mechanisms. Based on the analysis of publicly available interactomes, we propose that SARS-CoV-2 infection causes a deficiency in C1 esterase inhibitor (C1-INH), a pathogen-specific mechanism that may help explain the pro-coagulant state in COVID-19 patients.

Togo is one of the countries characterized by the highest deforestation rate in the world, caused mainly by the overexploitation of domestic biomass energy. Uapaca togoensis being one of the species appreciated for its strong calorific power, is increasingly overexploited, and its rarefaction in the Togolese forest landscapes becomes worrying hence the need to conduct this study to evaluate the possibilities of its vegetative reproduction. This study contributes to the sustainable development of natural resources by determining the optimal conditions for assisted regeneration of Uapaca togoensis. The approach consisted in conducting a series of nursery trials to determine the impact of the substrate, size of cuttings, sunlight, and apical tip coverage of the plastic film on its germination and budburst capacity. The lower calorific value is determined from samples in dry wood slices of 350g to 500g in five diameter classes. After 33 days, only one unscarred seed germinated in the compost. Substrate type, diameter of cuttings, sunlight, and plastic film significantly influenced the budburst rate and delay. More than 70% of the medium-diameter segments budded compared to 60% and 50% for small and large-diameter segments. More than 80% of the segments exposed to sunlight budded compared to 60% for the shaded segments. The average lower calorific value of dry wood of Uapaca togoensis varies between 7.35 Mj/Kg and 12.12 Mj/Kg depending on the humidity rate and the diameter.

We consider the problem of finding the largest clique of a graph. This is an NP-hard problem and no exact algorithm to solve it exactly in polynomial time is known to exist. Several heuristic approaches have been proposed to find approximate solutions, Markov Chain Monte Carlo being one of those. In the context of Markov Chain Monte Carlo, we present a class of ``parallel dynamics'', known as Probabilistic Cellular Automata, which can be used in place of the more standard choice of sequential ``single spin flip'' to sample from a probability distribution concentrated on the largest cliques of the graph. We perform a numerical comparison between the two classes of chains both in terms of the quality of the solution and in terms of computational time. We show that the parallel dynamics are considerably faster than the sequential one while providing solutions of comparable quality.

The algorithm now known as Kadane’s algorithm for the maximum subarray problem uses many of the ideas that Kadane proposed, but it is not the algorithm that Kadane intended. This paper compares the two algorithms in question. They are both linear in time, employ just a few words of memory, and use a dynamic programming structure. The upshot is two light-weight algorithms for the maximum subarray problem.

The maximization of entropy S within a closed system is accepted as an inevitability (as the second law of thermodynamics) by statistical inference alone. The Maximum Entropy Production Principle (MEPP) states that not only S maximizes, but $\dot{S}$ as well: a system will dissipate as fast as possible. There is still no consensus on the general validity of this MEPP, even though it shows remarkable explanatory power (both qualitatively and quantitatively), and has been empirically demonstrated for many domains. In this theoretical paper I provide a generalization of entropy gradients, to show that the MEPP actually follows from the same statistical inference, as that of the 2nd law of thermodynamics. For this generalization I only use the concepts of super-statespaces and microstate-density. These concepts also allow for the abstraction of 'Self Organizing Criticality' to a bifurcating local difference in this density, and allow for a generalization of the fundamentally unresolved concepts of 'chaos' and 'order'.

The modeling of tilting-pad journal and thrust bearings presents a level of complexity beyond that of bearings of fixed-arc geometry, particularly with regard to dynamic influences. With tilting-pad bearings, the theory surrounding the fluid film must be complemented with representative modeling of the pad dynamics. What has been recognized in recent decades has been the significance of the pad support, in particular the flexibility of the pivot region of the pad. The typical model for including the stiffness of the pivot has been based on Hertzian contact theory. Some researchers have been noting that the Hertzian theory does not permit sufficient flexibility in the pivot region. It is suggested that the contact mechanics at the pivot would be better represented as a pairing of rough surfaces. The modeling used here is based on a statistical asperity micro-contact theory for rough-surface line contact that has been extended to include contact stiffness. This model has been applied to the determination of the effective dynamic properties of tilting-pad bearings. The results show that pivot stiffness can be as low as one-third the stiffness determined by Hertzian theory. Comparison to published experimental results confirms the significance of the rough-surface modeling, particularly for the line contacts associated with rocker-back tilting pads.

Concrete condition assessing penetrometers need to be able to distinguish between making contact with a hard (concrete) surface as opposed to a semi-solid (corroded concrete) surface. If a hard surface is mistaken for a soft surface, concrete corrosion may be over-estimated, with the potential for triggering unnecessary remediation works. Unfortunately, the variably-angled surface of a concrete pipe can cause the tip of a force-sensing tactile penetrometer to slip and thus to make this mistake. We investigated whether different shaped tips of a cylindrical penetrometer were better than others at maintaining contact with concrete and not slipping. We designed a range of simple symmetric tip shapes, controlled by a single superellipse parameter. We performed a finite element analysis of these parametric models in SolidWorks before machining in stainless steel. We tested our penetrometer tips on a concrete paver cut to four angles at 20∘ increments. The results indicate that penetrometers with a squircle-shaped steel tip (a=b=1,n=4) have the least slip, in the context of concrete condition assessment.

The accurate calculation of real contact area between rough surfaces is a key issue in tribology. In this paper, based on the geometrical information of total contact area and the number of contact spots with respect to surface separation, a new method is proposed to determine the relation between real contact area and normal load. The contact of rough surfaces is treated as an accumulation of incremental multi-plateaus indentations with varying average contact radius. Comparisons with direct finite element calculations and some other theoretical predictions demonstrate the efficiency of this approach.

Total hip arthroplasty is a complex procedure. The achievements of implantology enabled the development of a faithful representation of hip joint physiology as well as the production of materials that can successfully replace damaged natural tissues. A very important issue is the correct selection of the geometry of the endoprosthesis adequate to the load of the joint. Materials used for endoprosthesis are a metal head and a polymer cup (e.g. PE-UHMW). The main interactions in the endoprosthesis are friction and surface pressure, which must be limited, exceeding them causes the destruction of the biomechanical system - plastic deformation of the polymer and the formation of too large and unacceptable radial clearances. Based on the author's developed calculation method of hip joint endoprosthesis contact parameters, the impact on maximum contact pressure and the angle of contact of the joint load was estimated depending on the diameter of the endoprosthesis and radial clearance. The correctness of changing the values of maximum contact pressure from the mentioned parameters was determined. Correspondingly: an increase in joint load causes a linear increase in the maximum contact pressure; increasing the diameter of the endoprosthesis head - their non-linear decrease, and increasing radial clearance - their increase

In this paper we analyse spatial variation in Japanese dialectal lexicon by assembling a set of methodologies using theories in variationist linguistics and GIScience, and tools used in historical GIS. Based on historical dialect atlas data, we calculate a linguistic distance matrix across survey localities. The linguistic variation expressed through this distance is contrasted with several measurements, based on spatial distance, utilised to estimate language contact potential across Japan, historically and at present. Further, administrative boundaries are tested for their separation effect. Measuring aggregate association within linguistic variation can contrast previous notions of dialect area formation by detecting continua. Depending on local geographies in spatial subsets, great circle distance, travel distance and travel times explain a similar proportion of the variance in linguistic distance despite the limitations of the latter two. While they explain the majority, two further measurements estimating contact have lower explanatory power: least cost paths modelling contact before the industrial revolution, based on DEM and seafaring, and a linguistic influence index based on settlement hierarchy. Historical domain boundaries and present day prefecture boundaries are found to have a statistically significant effect on dialectal variation. However, the interplay of boundaries and distance is yet to be identified. We claim that a similar methodology can address spatial variation in other digital humanities, given a similar spatial and attribute granularity.

Drones have experienced rapid technological advancements, leading to the proliferation of small, low-cost, remotely controlled, and autonomous aerial vehicles with diverse applications, from package delivery to personal transportation. However, integrating these drones into the existing air traffic management (ATM) system poses significant challenges. The current ATM infrastructure, designed primarily for traditional manned aircraft, requires enhanced capacity, workforce, and cost-effectiveness to coordinate the large numbers of drones expected to operate at low altitudes in complex urban environments. To address this critical issue, this study aims to develop an intelligent, highly automated drone management system for integration into smart city transportation networks. The key objectives include: i) Developing a conceptual framework for an intelligent total transportation management system tailored for future smart cities, focusing on incorporating drone operations; ii) Designing an advanced air traffic management and flight control system capable of managing individual drones and drone swarms in complex urban environments; iii) Improving drone management methods by leveraging drone-following models and emerging technologies such as the Internet of Things (IoT) and the Internet of Drones (IoD); and iv) Investigating the landing processes and protocols for unmanned aerial vehicles (UAVs) to enable safe and efficient operations.

In the case of solid slabs made of reinforced concrete that are usually subjected to bending, large areas of the structure are stressed well below their load-bearing capacity. Contrary to this are shell structures, which can bridge large spans with little material if designed according to the force flow. To improve the efficiency of ceiling slabs, we want to utilize the shell load-bearing behavior on a smaller scale by resolving the solid interior accordingly. In order to be able to study a wide range of such constructions virtually, a parametric multiobjective simulation environment is being developed in an ongoing research project. The basic analysis approaches which were implemented are presented in this paper. The basic workflow, the used programs and material models and their calibration on the tests on textile-reinforced concrete (TRC) samples are described.