The aim of this study was to introduce a new activity-based balance index by using accelerometer data. Twenty-seven junior soccer players from the Iranian premier league were selected. Four functional tests, consisting of one leg stance, dynamic Y balance, running and dribbling tests, were conducted to assess the players’ balance, activity and skill. During these four tests, besides their relative scores, the acceleration of their body center was also recorded. Activity-based balance index (ABI) was calculated using these acceleration data. The results showed positive correlations between ABI and both static and dynamic balance scores. Additionally, negative correlations were found between ABI and dribbling scores, which demonstrate the agility required for this skill. It seems that this new index achieves the evaluation of both the balance and the skill level of soccer players. Perhaps this is a new way of talent identification and also a re-development of balance tests from traditional to modern.

In the software development process, the decision-maker (DM) has a range of problems inherent to its function. Wrong choices during software planning can bring great risk to the project. Therefore, the planning of software releases to be delivered to the customer should be well done. This is not an easy task because releases are made up of many requirements that contain complex variables that must be considered, such as precedence, cost, requirement stability, among other features that make the requirements-selection process challenging. To make this process less exhaustive, DM can use tools that facilitate this work. In software engineering, we can find fields of research specialists in this context, such as Search-Based Software Engineering (SBSE). The SBSE makes use of advanced metaheuristics to search for optimal solutions or the closest to it. In this work, we try to use another field of research to solve this same problem type, the Verbal Decision Analysis (VDA). To do this, we elaborate a workflow that will use the same source data, execute two solutions using the two search fields (SBSE and VDA) and compare the results. In the end, we evaluated and commented on the results.

Fragment-based drug discovery (FBDD) has become a major strategy to derive novel lead candidates for various therapeutic targets, as it promises efficient exploration of chemical space by employing fragment-sized (MW < 300) compounds. One of the first challenges in implementing a FBDD approach is the design of a fragment library, and more specifically, the choice of its size and individual members. A diverse set of fragments is required to maximise the chances of discovering novel hit compounds. However, the exact diversity of a certain collection of fragments remains underdefined, which hinders direct comparisons among different selections of fragments. Based on structural fingerprints, we herein introduced quantitative metrics for the structural diversity of fragment libraries. Structures of commercially available fragments were retrieved from the ZINC database, from which libraries with sizes ranging from 100 to 100,000 compounds were selected. The selected libraries were evaluated and compared quantitatively, resulting in interesting size-diversity relationships. Our results demonstrated that while library size does matter for its diversity, there exists an optimal size for structural diversity. It is also suggested that such quantitative measures can guide the design of diverse fragment libraries under different circumstances.

The objective to fast-track the mapping and registration of large numbers of unrecorded land rights globally, leads to the experimental application of Artificial Intelligence (AI) in the domain of land administration, and specifically the application of automated visual cognition techniques for cadastral mapping tasks. In this research, we applied and compared the ability of rule-based systems within Object Based Image Analysis (OBIA), as opposed to human analysis, to extract visible cadastral boundaries from Very high resolution (VHR) World View-2 image, in both rural and urban settings. From our experiments, machine-based techniques were able to automatically delineate a good proportion of rural parcels with explicit polygons where the correctness of the automatically extracted boundaries was 47.4% against 74.24% for humans and the completeness of 45% for machine, as against 70.4% for humans. On the contrary, in the urban area, automatic results were counterintuitive: even though urban plots and buildings are clearly marked with visible features such as fences, roads and tacitly perceptible to eyes, automation resulted in geometrically and topologically poorly structured data, that could neither be geometrically compared with human digitised, nor actual cadastral data from the field. These results provide an updated snapshot with regards to the performance of contemporary machine-drive feature extraction techniques compared to conventional manual digitising.

Over half of adult Americans now have diabetes or prediabetes and worse, this epidemic is now world-wide and shows no signs of slowing, with rates of both diabetes and diabetes-related health complications still rising. When advising patients with diabetes on food choices, many providers rely on nutrition guidelines provided by the American Diabetes Association (ADA), and these guidelines influence other recommendations across the globe. Given the alarming trends in diabetes, it is paramount to review the treatment guidelines to ensure they are based on rigorous and accepted scientific methods. Our review included the evidence cited by the ADA in support of its claims and recommendations for eating patterns to combat diabetes (see Description of Eating Patterns, Supplemental Appendix), as presented in the most current edition of the annual ADA’s Standards of Medical Care in Diabetes (2018 Standards). Our review also includes sources cited in the latest edition of the ADA’s Nutrition Therapy Recommendations for Adults with Diabetes (2014 Recommendations), which also informed the 2018 Standards. In October 2018 low carbohydrate was named as a recommended eating pattern by the ADA and European Association for the Study of Diabetes (EASD)⁵but only citations from the 2014 and early 2018 ADA documents were reviewed.

Background: The aim of this study was to investigate the risk of obstructive sleep apnea (OSA) among ankylosing spondylitis (AS) patients in a nationwide population. Methods: We conducted a nationwide cohort study between 2003 and 2013 using the Taiwan National Health Insurance Research Database. The AS cohort included 2210 patients who were newly diagnosed between 2003 and 2013. Randomly selected non-AS controls were matched at a 1:4 ratio based on age, sex and index date. The endpoint of OSA was occurrence or the end of 2013. Cumulative incidences, hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated after adjusting for age, gender, comorbidities and co-medications. Multivariate analyses were performed using Cox proportional hazards model. Due to violation of the proportionality assumption, landmark analysis was conducted to explore the risk of OSA during specific follow-up periods. Results: The adjusted HR (aHR) of OSA for the AS group was 2.826 (95% C.I. = 1.727–4.625) compared to the control group. On landmark analysis, aHR was 7.919 (95% C.I. = 3.169–19.792) for AS group 0–24 months from index date, and decreased to 1.816 (95% C.I. = 0.944–3.494) at ≥ 24 months from index date. On subgroup analyses increased risks of OSA in AS group compared to the control group were found for both males and females (aHRs were 4.533 (95% C.I. = 1.441–14.262) and 2.672 (95% C.I. = 1.522–4.692) for females and males, respectively). On age stratified analysis, there was significant risk only for the 40–59 age group with aHR of 3.913 (95% C.I. = 1.890–8.102). Conclusions: A higher risk of developing OSA was found among newly diagnosed AS cohort during the 12-year follow-up period, especially within 2 years after AS index date and in the 40–59 age group.

The current focus on afforestation in climate policy runs the risk of compromising both longterm carbon storage and human adaptation. It also works against efforts to stem the tide of biodiversity loss. We outline why an emphasis on diverse, intact natural ecosystems—as opposed to tree plantations with fast-growing exotic species—will help nations deliver the goals of the Paris Agreement and much more.

With the development of IoT technology, various information resources, such as social resources and physical resources, are deeply integrated for different comprehensive applications. Social networking, car networking, medical services, video surveillance and other forms of IoT information Service model gradually change people's daily life. Facing the vast amounts of IoT information data, IoT search technology is used to quickly find accurate information to meet real-time search needs of users. However, IoT search requires to use a large number of user privacy Information, such as personal health information, location information, social relations information, to provide personalized services. User privacy information will meet security problems if an effective access control mechanism is missing during the IoT search process. Access control mechanism can effectively monitor the access activities of resources, and ensure authorized users to access information resources under legitimate conditions. This survey examines the growing literature on access control for IoT search. Problems and challenges of access control mechanism are analyzed to facilitate the adoption of access control solutions in real-life settings. This paper aims to provides theoretical, methodological and technical guidance for IoT search access control mechanism in large-scale dynamic heterogeneous environment. Based on the literature study, we also analyzed future development direction of access control in the age of IoT.

In this work, the decennial experience of Policumbent student team at Politecnico di Torino is summarized by focusing on the acquired knowledge in design of Human Powered Vehicles (HPVs) and on soft skills developed by both students and staff. Policumbent was funded by the authors at the end of 2008 in order to gather engineering students interested in design and construction of HPVs. In the last decade, the team has grown from 10 up to 50 students enrolled per year, exploring a range of HPV design for sports and mobility. Even when focusing on sport vehicles and extreme HPVs for speed record, such kind of projects allows students to familiarize with important concepts related to sustainable mobility: the amount of resistive forces and dissipated power, the role of vehicle weight and the impact of acceleration on the overall energetic balance as far as fundamental concepts about energy consumption, efficiency and emissions of the ``human engine'' in comparison with other kind of engines. By touching with hands such topics in the framework of a ``human-centred'' design project, the students have opportunity to develop awareness about the impact of design choices on sustainability of any kind of vehicle for transportation. Also, the paper retraces the team evolution path by focusing on a thorough analysis of what factors contributed to the success of this project.

Hot rolling tests of a low-alloy steel were conducted at a rolling temperature of 850 ℃ under different lubrication conditions, including benchmarks (dry condition and water) and water-based nanolubricants containing different concentrations of nano-TiO₂ from 1.0 to 8.0 wt%. The effects of nanolubricants on rolling force, surface roughness, thickness of oxide scale and microstructure were systematically investigated through varying nano-TiO₂ concentrations. The results show that the application of nanolubricants can decrease the rolling force, surface roughness and oxide scale thickness of rolled steels, and refine ferrite grains. In particular, the nanolubricant containing an optimal concentration (4.0 wt%) of nano-TiO₂ demonstrates the best lubrication performance, owing to the synergistic effect of lubricating film, rolling, polishing and mending generated by nano-TiO₂.

Neisseria meningitidis causes most cases of bacterial meningitis. Meningococcal meningitis is a public health burden to both developed and developing countries throughout the world. There are a number of vaccines (polysaccharide-based, glycoconjugate, protein-based and combined conjugate vaccines) that are approved to target five of the six disease-causing serogroups of the pathogen. Immunization strategies have been effective at helping to decrease the global incidence of meningococcal meningitis. Researchers continue to enhance these efforts through discovery of new antigen targets that may lead to a broadly protective vaccine and development of new methods of homogenous vaccine production. This review describes current meningococcal vaccines and discusses some recent research discoveries that may transform vaccine development against N. meningitidis in the future.

This paper presents a novel 3-degrees-of-freedom (3-DOF) haptic master with rubber bands for self-resetting. The mechanical design avoids coupling between three directions mechanically by using three perpendicular axis intersecting at one point. Bevel gear transmission is adopted to increase the compactness of the overall structure. VR-based interactive system is designed and built by incorporating the proposed haptic master. The proposed haptic device can generate force feedback along 3-degree-of-freedom motion using motors and provide command signals to the avatar in the virtual environment. In order to analyze the performance of the developed device in terms of haptic feedback operation, ergonomics assessments are designed and experimentally implemented. Preliminary studies on the influencing factor including the guidance force, the reset force, the speed of the avatar and the arm the length have been conducted. The results of this paper are of great significance for the design of the haptic master and interactive system.

Smoothed particle hydrodynamics (SPH) is regarded as a pure Lagrangian approach, which can solve fluid dynamics problems without the creation of mesh. In this paper, a paralleled SPH solver is developed to solve particle-based computational acoustics (PCA). The aim of this paper is to study the feasibility of using SPH to solve acoustic problems and to improve the efficiency of solving processes by paralleling some procedures on GPU during calculating. A stand SPH code running serially in a CPU is proposed to solve wave equation. This is a wave propagating in a two-dimensional domain. After finishing the computation, the results are compared with the theoretical solutions and they agree well. So its feasibility is verified. There are two main methods for searching neighbor particles: all-pair search method and linked-list search method. Both methods are used in different codes to simulate an identical problem and their runtimes are compared to investigate their searching efficiencies. The runtime results show that linked-list search method has a higher efficiency, which can save a lot of searching time when simulating problems with huge amounts of particles. Furthermore, the percentages of different procedures’ runtimes in a simulation are also discussed to find the most consuming one. Then, some codes are modified to run in different GPUs and their runtimes are compared with those of serial ones on a CPU. Runtime results show that the paralleled algorithm can be more than 80 times faster than the serial one. The result shows that GPU paralleled SPH computing can achieve desirable accuracy and speed in solving acoustic problems.

The purpose of the article is to determine the peculiarities of using of teaching elements of research-based training at the Institute of Human Sciences of Borys Grinchenko Kyiv University. Based on the focus group methodology, the authors identify the key methodological characteristics of research-based training, which have been put into basis of analysis of educational programs for the purpose of determining the application of tasks that contribute to the development of research skills of students. The study used a method of focus group. Its purpose was to obtain the necessary information from the participants to describe the methodological basis and justification of methods, forms, indicators, etc. of research-based training system among people who are competent, have experience in this field. After that, the method of "theoretical sampling" was used, which enabled to formulate generalized characteristics according to the results of focus groups. The practical value of the study is determination of the methodological characteristics of research-based training which is the basis for the application of tasks by university teachers that promote the development of research competence of students. The research is one of the first attempts to determine the methodological characteristics of research-based training in Ukraine.

This paper shows a method for pipeline leak detection using a transient-based method with MATLAB® functions. The simulation of a pipeline systems in the time domain are very complex. In the case of the dissipative model, transfer functions are hyperbolic Bessel functions. Simulating a pipeline system in the frequency domain using a dissipative model we could find an approximate transfer function with equal frequency domain response to in order get the pipeline system's time domain response. The method described in this paper can be used to detect, by comparison, to detect a leak in a pipeline system model.

The comprehensibility of good predictive models learned from high-dimensional gene expression data is attractive because it can lead to biomarker discovery. Several good classifiers provide comparable predictive performance but differ in their abilities to summarize the observed data. We extend a Bayesian Rule Learning (BRL-GSS) algorithm, previously shown to be a significantly better predictor than other classical approaches in this domain. It searches a space of Bayesian networks using a decision tree representation of its parameters with global constraints, and infers a set of IF-THEN rules. The number of parameters and therefore the number of rules are combinatorial to the number of predictor variables in the model. We relax these global constraints to a more generalizable local structure (BRL-LSS). BRL-LSS entails more parsimonious set of rules because it does not have to generate all combinatorial rules. The search space of local structures is much richer than the space of global structures. We design the BRL-LSS with the same worst-case time-complexity as BRL-GSS while exploring a richer and more complex model space. We measure predictive performance using Area Under the ROC curve (AUC) and Accuracy. We measure model parsimony performance by noting the average number of rules and variables needed to describe the observed data. We evaluate the predictive and parsimony performance of BRL-GSS, BRL-LSS and the state-of-the-art C4.5 decision tree algorithm, across 10-fold cross-validation using ten microarray gene-expression diagnostic datasets. In these experiments, we observe that BRL-LSS is similar to BRL-GSS in terms of predictive performance, while generating a much more parsimonious set of rules to explain the same observed data. BRL-LSS also needs fewer variables than C4.5 to explain the data with similar predictive performance. We also conduct a feasibility study to demonstrate the general applicability of our BRL methods on the newer RNA sequencing gene-expression data.

Diseases in articular cartilages have affected millions of people globally. Although the biochemical and cellular composition of articular cartilages is relatively simple, there is the limitation in self-repair ability of cartilage. Therefore, developing the strategies for cartilage repair is very important. Here, we reported a new manufacturing process of water-based polyurethane based photosensitive materials with hyaluronic acid and applied the materials for 3D printed customized cartilage scaffolds. The scaffold has high cytocompatibility and is one that closely mimics the mechanical properties of articular cartilages. It is suitable for culturing human Wharton's jelly mesenchymal stem cells (hWJMSCs) and the cells showed an excellent chondrogenic differentiation capacity. We consider that the 3D printing hybrid scaffolds may have potential in customized tissue engineering and facilitate the development of cartilage tissue engineering.

Satellite-based rainfall estimation products provide a vital alternative source of rainfall data in areas where conventional precipitation measurement is not readily available. In order to facilitate the use of these products there is the need to evaluate their accuracies. This study evaluated the accuracy of three satellite rainfall products; TMPA 3B42RT, TMPA 3B42 and CMORPH in the Pra basin (23,330 km²) of Ghana. The evaluation was through the point-to-pixel method by comparing 0.25°x 0.25° satellite grids to gauged rainfall based on gauge locations and analyzed statistically using correlation coefficient (r), bias and percent bias (pBias) as the performance verification methods. Seven (7) gauge stations with no missing data for the period of 2003-2008 was used in the evaluation. The analysis was based on daily, monthly, annual and seasonal timescales. Our results showed a good correlation between the TMPA products and the gauged data on all timescales considered. The CMORPH on the other hand showed huge overestimation at all gauge locations. The TMPA 3B42 was seen to be the best amongst the three products. The overall rainfall in the basin was well depicted by the TMPA 3B42 and 3B42RT. Although there wasn’t a perfect match between the 3B42RT and 3B42 products and the gauged rainfall, these products can be used to supplement gauged rainfall measurements in the basin and in estimation of rainfall in ungauged basins with similar characteristics.

The prototype misfit layer compound (SnS)1.17NbS2 consists of alternatively a metallic triatomic NbS2 layer in which Nb atoms are sandwiched by S atoms and an insulating SnS double-layer of NaCl-type structure. Here we investigate the effect of lattice misfit on the stability and chemical bonding in the misfit layer compound using a first-principles density-functional theory approach. The calculations show that for the (SnS)1+xNbS2 approximants, the most stable one has x = 0.167, close to the experimental observations. Charge analysis finds a moderate charge transfer from the SnS to NbS2. Sn or S vacancies in the SnS part affect the electronic properties and interlayer interactions. The obtained information here helps understand the mechanism of formation and stability of the misfit layer compounds and ferecrystals, and further to design of novel multilayer compounds and emerging van der Waals heterostructures.

We present first-principles DFT+U investigation of the bulk properties including structural, energetic and mechanical properties for uranium-americium mixed oxides (U, Am)O₂. The various Am aggregation contents have been investigated to better understand the impact of Am in the nuclear fuel UO₂. The supercell defect models at different scales were used to describe the solid solution (U, Am)O₂. The obtained results show that different contents of Am has a significant impact on the volume and energy of the mixed oxides systems. The results on the electronic structure calculations exhibit a narrow band gap owing to the mixing of UO₂ and AmO₂. The mixing enthalpy of the Am aggregation systems are used to describe the phase stability for the solid solution. In particular, mixing enthalpy of the (U, Am)O₂ significantly reduced as the Am content increases. The elastic properties of the (U, Am)O₂ mixed oxides have also been compared as a function of Am content. Moreover, the impacts of the whole Pu aggregation content range on the bulk properties for the (U, Pu)O₂ mixed oxides is also discussed.

An H-bond involves the sharing of a hydrogen atom between an electronegative atom to which it is covalently bound (the donor) and another electronegative atom serving as an electron acceptor. Such bonds represent a critically important geometrical force in biological macromolecules and, as such, have been characterized extensively. H-bond formation invariably leads to a weakening within the acceptor moiety due to the pulling exerted by the donor hydrogen. This phenomenon can be compared to a spring connecting two masses; pulling one mass stretches the spring, similarly affecting the bond between the two masses. Herein, we describe the opposite phenomenon when investigating the energetics of the C-H...O=C bond. This bond underpins the most prevalent protein transmembrane dimerization motif (GxxxG) in which a glycine C-H on one helix forms a hydrogen bond with a carbonyl in a nearby helix. We use isotope-edited FT-IR spectroscopy and corroborating computational approaches to demonstrate a surprising strengthening of the acceptor C=O bond upon binding with the glycine C-H. We show that electronic factors associated with the C-H bond strengthen the C=O oscillator by increasing the s-character of the -bond, lowering the hyperconjugative disruption of the -bond. In addition, a reduction of the acceptor C=O bond’s polarity is observed upon the formation of the C-H...O=C bond. Our findings challenge the conventional understanding of H-bond dynamics and provide new insights into the structural stability of inter-helical protein interactions.

Recently, due to the decrease in labor force, increase in labor costs, and the desire for improved quality of life, research on robots has been actively conducted to address these issues. However, it is currently difficult to find robots that physically interact with humans. The reason is that the actuators of robots do not have high torque density on their own. To solve this problem, high torque density motors, such as proprioceptive actuators, are being researched. However, the torque density is still insufficient for physical interaction with humans, so we have developed a motor with higher torque density. However, high torque density motors have the disadvantage of lower speed characteristics due to increased Back-EMF. Therefore, to address the deterioration of speed characteristics in the developed motor, we applied the Independent 3-Phase winding structure to improve the speed characteristics. Consequently, through comparison with Y-Connection and Delta-Connection, we propose the most suitable winding structure for high torque density motors intended for physical interaction with humans.

Background: Diabetes mellitus (DM) and osteoporosis are two of the most widespread metabolic disease in the world. The aim of this study is to investigate the prevalence of DM among patients affected by osteoporosis and fragility fractures, and to search differences in clinical features. Methods: 713 patients belonging to CTO Bone Unit because of osteoporosis and fragility fractures were divided into two groups, according to the diagnosis of DM. The clinical and bone characteristics of patients were compared. Results: Prevalence of DM was 10.8%. When compared to patients without DM, the median age at the time of first fracture was similar (72 years ± 14 IQR vs 71 years ± 12 IQR); prevalence of combination of vertebral and hip fractures was higher (p=0.039), as well as prevalence of males, although not significantly (p=0.051). Bone mineral density (BMD) at all sites was higher in DM group; Trabecular Bone Score (TBS), instead, was significantly lower (p&lt;0.001). Conclusions: Patients with fragility fractures and DM more frequently show combination of major fractures with higher BMD levels. In these patients, TBS could be a better indicator of bone health than BMD and therefore should be used as a diagnostic tool in clinical practice.

The current investigation presents porous ceramic materials prepared of cenospheres prepared by spark plasma sintering. The impact of sintering temperature, mould diameter (20 and 30 mm diameter) and cenosphere size on the properties of the sintered material was investigated. Shrinkage of the samples during sintering started at 900 °C. Sample shrinkage during sintering increases with increasing temperature and decreases with increasing mould size; increasing sample sintering temperature increases the apparent density of all sample series CS 63-150 µm in 20 mm mould from 0.97 to 2.3 g·cm-3 at 1050 - 1300 °C, in 30 mm mould 0.81 - 1.87 g·cm-3 at 1050 - 1200 °C, in 50 mm mould 0.54 - 0.75 g·cm-3 at 1050 - 1150 °C, while CS 150-250 µm in 20 mm mould 0.93 - 1.96 g·cm-3 at 1050 - 1200 °C. Total porosity decreases from 61.5% to 3.9% with increasing sintering temperature from 1050 to 1250 °C, while open porosity reduces at lower temperatures, with closed porosity being highest in samples sintered at 1150 °C. When the sintering temperature increases from 1050 to 1300 °C, the compressive strength of the CS 63-150 samples produced in a 20 mm mould increases from 11 MPa to 312 MPa. These results correlate with the Rice model, which describes an exponential dependence of compressive strength on material porosity and fully dense material compressive strength.

NiO-based nanomaterials have attracted a great deal of interest in view of various applications, that have stimulated the implementation of various synthetic approaches to control their chemico-physical properties as a function of the desired end-use. In this regard, their bottom-up preparation starting from suitable precursors plays an important role, but a molecular level in-sight into their reactivity remains an open challenge. In this study, we focus on the fragmentation of Ni(II) diketonate-diamine adducts, of interest as precursors for Ni(II) oxide systems, by com-bined electrospray ionization mass spectrometry (ESI-MS) with multiple collisional experiments (ESI-MSn) and theoretical calculations. The joint analyses revealed common features in the frag-mentation pattern of the target compounds: i) in the first-fragmentation, all three complexes form analogous base-peak cations by losing a negatively charged diketonate; in these cations, Ni-O and Ni-N interactions are stronger and the Ni positive charge is lower than in the neutral complexes; ii) the tendency of ligand electronic charge to migrate towards Ni further increases in the subsequent fragmentation processes, leading to the formation – in all three cases – of a tetracoordinated Ni environment involving an interesting cation-π intramolecular interaction.

Support effect is an important issue in heterogeneous catalysis while the explicit role of a catalytic support is often unclear for catalytic reactions. A systematic density functional theory computational study is reported in this paper to elucidate the effect of a model boron nitride (BN) support on the first N-H bond activation step of NH3 on Run (n =1, 2, 3) metal clusters. Geometry optimizations and energy calculations were carried out using density functional theory (DFT) calculation for intermediates and transition state from the starting materials undergoing the N-H activation process. The primary findings are summarized as follows. The involvement of the model BN support does not significantly alter the equilibrium structure of intermediates and transition state in the most favorable pathway (MFP). Moreover, the involvement of BN support decreases the free energy of activation, ΔG≠, thus improving the reaction rate constant. This improvement is more obvious at high temperatures like 673 K than low temperatures like 298 K. The BN support effect leading to the ΔG≠ decrease is most significant for the single Ru atom case among all three cases studied. Finally, the involvement of model BN may change the spin transition behavior of the reaction system during the N-H bond activation process. All these findings provide a deeper insight into the support effect on the N-H bond activation of NH3 for supported Ru catalyst in particular and for supported transition metal catalysts in general.

We discuss the neutron skins of 48Ca and 208Pb. We review and critically examine modern predictions and empirical constraints, with special attention to the dierent interpretations of the ndings from the PREX-II experiment and the recently reported value of the neutron skin in 48Ca extracted from the CREX experiment. We argue that, in the spirit of the ab initio philosophy, the path to understanding the behavior of dense neutron-rich matter must not circumvent fundamental nuclear forces. Based only on that argument, a thick neutron skin in 208Pb is highly unlikely.

The redox properties of quinones underlie their unique characteristics as organic battery components that outperform the conventional inorganic ones. Furthermore, the redox properties could be precisely shaped by using different substituent groups. Machine learning and statistics, onthe other hand, have proven to be very powerful approaches for efficient in silico design of novel materials. Herein, we demonstrated the machine learning approach for the prediction of the redox activity of quinones that potentially can serve as organic battery components. For the needs of the present study, a database of small quinone-derived molecules was created. A large number of quantum chemical and chemometrics descriptors was generated for each molecule and subsequently different statistical approaches were applied to select the descriptors that most prominently characterize the relationship between structure and redox-potential. Various machine-learning methods for screening of prospective organic battery electrode materials were deployed to select the most trustworthy strategy for machine learning aided design of organic redox materials. It was found that ridge regression models perform better than regression decision tree and decision tree based ensemble algorithms.

Based on the Generalized bracket, or Beris-Edwards, formalism of non-equilibrium thermodynamics, we have recently proposed [Stephanou et al. Materials, 13, 2867 (2020)] a new differential constitutive model for the rheology of entangled polymer melts and solutions. It has amended the shortcomings of a previous model that was too strict in the values of the convective constraint release parameter for the model not to violate the second law of thermodynamics and has been shown capable of predicting a transient stress undershoot (following the overshoot) at high shear rates. In this work, we wish to further examine this model’s capability of predicting the rheological response of industrial polymer systems by extending it to its multiple-mode version. The comparison against industrial rheological data (High-Density Polyethylene resins), as compared against available experimental data in (a) Small Amplitude Oscillatory shear, (b) start-up shear, and (c) start-up uniaxial elongation, is noted to be good.

Although many policosanols from different sources, such as sugar cane, rice bran, and insects, have been marketed worldwide, there has been no comparative study of the in vivo efficacy using a hyperlipidemic animal model. This study compared the efficacy of treating dyslipidemia with four different policosanols, including one sugar cane wax alcohol from Cuba (Raydel®) and three policosanols from China (Xi’an Natural sugar cane, Xi’an Realin sugar cane, and Shaanxi rice bran) in hyperlipidemic zebrafish. After 12 weeks of consumption of each policosanol (final 0.1% in diet, wt/wt) and high cholesterol diet (HCD, final 4%, wt/wt) in a tetrabit, the Raydel policosanol group and Xi’an Natural policosanol group showed the highest survivability of approximately 81%, whereas the Xi’an Realin policosanol group and Shaanxi policosanol group showed 57% and 67% survivability, respectively. Among five HCD groups, the Raydel policosanol group showed the lowest serum total cholesterol (TC, p<0.001 versus HCD control) and triglyceride (TG, p<0.001 versus HCD control) with the highest percentage of high-density lipoproteins (HDL)-C in TC. The Raydel policosanol group also showed the lowest serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels with the least infiltration of inflammatory cells and interleukin-6 production in hepatocytes. In the ovary, the Raydel policosanol group also showed the highest contents of mature vitellogenic oocytes with the lowest production of reactive oxygen species and cellular apoptosis in ovarian cells. In the testis, the Raydel policosanol group also showed the healthiest morphology for spermatogenesis with the least interstitial area and reactive oxygen species (ROS) production in testicular cells. In conclusion, 12 weeks of Raydel policosanol consumption resulted in remarkable improvement of the blood lipid profile, amelioration of inflammation in the liver, and enhancement of the cell morphology in the ovary and testis with the highest survivability under the HCD.

In swarm-robotics foraging, the purpose of task allocation is to adjust the number of active foraging robots dynamically based on the task demands and changing environment. It is a difficult challenge to generate self-organized foraging behavior in which each robot can adapt to environmental changes. To complete the foraging task efficiently, this paper presents a novel self-organized task allocation strategy known as the dynamic response threshold model (DRTM). To adjust the behavior of the active foraging robots, the proposed DRTM newly introduces the traffic flow density, which can be used to evaluate the robot density. First, the traffic flow density and the amount of obstacle avoidance are used to adjust the threshold which determines the tendency of a robot to respond to a stimulus in the environment. Then, each individual robot uses the threshold and external stimulus to calculate the foraging probability that determines whether or not to go foraging. Simulation and physical experiments are carried out to evaluate the performance of the proposed method. The experimental results show that the DRTM is superior to and more efficient than the adaptive response threshold model (ARTM) in swarm foraging.

new subsonic blower wind tunnel design has been studied both numerically and experimentally, it is also referred to as “blower” wind tunnel. This paper, is initially aimed to address each sequential stage of the wind tunnel design process. Rather than applying the standard method of modelling solely the flow in the test section, a large-scale CFD model of the whole wind tunnel was employed. The loss of every constituent element was calculated and then all the losses are added up to determine the power needed for the wind tunnel operation which is used as “intake fan” boundary conditions in the CFD model. Then, flow uniformity and turbulent intensity measurements in an empty test section using a Pitot-static tube and hot wire anemometer (HWA) were introduced to validate the CFD results. The results showed that flow quality was significantly affected by boundary layer controllers (honeycomb and mesh screens) in the settling chamber and wide-angle diffuser. Investigations were also conducted to evaluate the flow deficit in the wake area behind a convex hump model using HWA. This was additional experimental tests carried out to validate the suitability of the wind tunnel flow aerodynamic research.

We construct a novel family of summation-integral type hybrid operators in terms of shape parameter $\alpha\in \lbrack 0,1]$ in this paper. Basic estimates, rate of convergence, and order of approximation are also studied using the Korovkin theorem and the modulus of smoothness. We investigate the local approximation findings for these sequences of positive linear operators utilising Peetre's K-functional, Lipschitz class, and second-order modulus of smoothness.

Recent expansion in data sharing has created unprecedented opportunities to explore structure-function linkages in ecosystems across spatial and temporal scales. However, characteristics of the same data product, such as resolution, can change over time or spatial locations, as protocols are adapted to new technology or conditions, which may impact the data’s potential utility and accuracy for addressing end user scientific questions. The National Ecological Observatory Network (NEON) provides data products for users from 81 sites and over a planned 30-year time frame, including discrete return Light Detection and Range (LiDAR) from an airborne observatory platform. LiDAR is a well-established and increasingly available remote sensing technology for measuring three-dimensional (3D) characteristics of ecosystem and landscape structure, including forest structural diversity. The LiDAR product that NEON provides can vary in point density from 2 – 25+ points/m² depending on instrument and acquisition date. We used NEON LiDAR from five forested sites to (1) identify the minimum point density at which structural diversity metrics can be robustly estimated across forested sites from different ecoclimatic zones in the USA and (2) to test the effects of variable point density on the estimation of a suite of structural diversity metrics and multivariate structural complexity types within and across forested sites. Twelve out of sixteen structural diversity metrics were sensitive to LiDAR point density in at least one of the five NEON forested sites. The minimum point density to reliably estimate the metrics ranged from 2.0 to 7.5 pt/m^2, but our results indicate that point densities above 7-8 pt/m² should provide robust measurements of structural diversity in forests for temporal or spatial comparisons. The delineation of multivariate structural complexity types from a suite of 16 structural diversity metrics was robust within sites and across forest types for a LiDAR point density of 4 pt/m² and above. This study shows that different metrics of structural diversity can vary in their sensitivity to the resolution of LiDAR data and users of these open-source data products should consider the point density of their data and use caution in metric selection when making spatial or temporal comparisons from these datasets.

One of the intriguing recent results in the field of high-entropy alloys is the discovery of single-phase equiatomic multi-component Laves intermetallics. However, there is no clear understanding that a combination of chemical elements will form such high-entropy compounds. Here we contribute to understanding this issue by modifying the composition of duodenary TiZrHfNbVCrMoMnFeCoNiAl (12x) alloy in which we recently reported the fabrication of hexagonal C14 Laves phase. We consider three alloys based on 12x: 7x=12x-VCrMoMnFe, 12x+Sc, 12x+Be and observe that all of them crystalize with the formation of C14 Laves phase as a dominant structure. We report that 12x+Be alloy reveals single-phase C14 structure with very high concentration of structural defects and ultra-fine dendritic microstructure with almost homogenous distribution of the constituted elements over the alloy matrix. The 7x and 12x+Sc alloys contain C14 as a main phase and unknown impurity phases. To characterize the materials, we examine their heat capacity, electrical conductivity and magnetic properties. The measurements reveal that the Laves phases are Curie-Weiss paramagnets, which demonstrate metallic conduction; 7x and 12x alloys also reveal a pronounced Kondo-like anomaly. Analysis of experimental data as well as ab initio calculations suggests that chemical complexity and compositional disorder cause strong s-d band scattering and thus the rather high density of d-states in the conduction band. Analysis of the results suggests that the mechanism of Laves phase formation in multicomponent multi-principal element metallic alloys is may be the same as in polydisperse hardspheres mixtures. Another important conclusion is that the configurational entropy is a negligible factor in the stabilization of multi-element Laves phases.

Recently, the demand for electric vehicle is increasing worldwide due to eco-friendly policies and stricter emission regulations. As a traction motor for electric vehicle, interior permanent magnet synchronous motors are mainly used. For the design of the interior permanent magnet synchronous motor, the magnetic equivalent circuit method, which is a method of lumped constant circuit, and the finite element method, which is a method of distributed constant circuit, mainly are used. Magnetic equivalent circuit method is useful for simple design through fast and intuitive parameters, but it cannot derive the distribution of magnetic field. The finite element method can derive an accurate magnetic field distribution, but it takes a long time to analyze and it is difficult to analyze intuitive design parameters. In this paper, magnetic equivalent circuit method and Carter coefficient are mixed for rotor structure design. This design method will be called the hybrid magnetic equivalent circuit method. Intuitive design parameters are derived through this hybrid magnetic equivalent circuit method. We will derive the Air gap flux density distribution according to rotor shape, no-load induced voltage, and cogging torque, and compare and verify it with the finite element method.

Enhancing the degree of functional multiplexing while assuring operational reliability and manufacturability at competitive costs are crucial ingredients for enabling comprehensive sample-to-answer automation, e.g., for use in common, decentralized “Point-of-Care” or “Point-of-Use” scenarios. This paper demonstrates a model-based ‘digital twin’ approach which efficiently supports the algorithmic design optimization of exemplary centrifugo-pneumatic (CP) dissolvable-film (DF) siphon valves towards larger-scale integration (LSI) of well-established “Lab-on-a-Disc” (LoaD) systems. Obviously, the spatial footprint of the valves and their upstream laboratory unit operations (LUOs) have to fit, at a given radial position prescribed by its occurrence in the assay protocol, into the locally accessible disc space. At the same time, the retention rate of a rotationally actuated CP-DF siphon valve and, most challenging, its band width related to unavoidable tolerances of experimental input parameters, need to slot into a defined interval of the practically allowed frequency envelope. To accomplish particular design goals, a set of parametrized metrics is defined, which are to be met within their practical boundaries while (numerically) minimizing the band width in the frequency domain. While each LSI scenario needs to be addressed individually on the basis of the digital twin, a suite of qualitative design rules and instructive showcases structures are presented.

Traditional discrimination techniques for Euler deconvolution use only the color spectrums of structural indexes, without considering the spatial distribution characteristics and inherent relationships among the Euler solutions to separate adjacent causative sources. In the present study, a new approach was developed for discriminating uncorrelated Euler solutions from coherent solutions based on the focusing levels indicated by the probability density distributions generated using multivariate kernel density estimations (KDE). A novel multiple coverage technique was proposed by using a series of different sized moving windows over gridded gravity data, which formed tight clusters of Euler solutions for different sized causative sources. The results of the probability density distributions were obtained using a 3-D KDE method for the Euler solution subsets {x, y, z} of synthetical models, and real data from a survey conducted in British Columbia (Canada) which had successfully established more credible and meaningful geological models when compared with three other subsets.

As in any other plant, in the grapevine roots play a vital role in terms of anchorage, uptake of water and nutrients, as well as storage and production of chemicals. Their behaviour and development depend on various factors, namely rootstock genetics, soil physical and chemical features, field agronomic practices. Canopy management, involving techniques such as defoliation and pruning, could greatly influence root growth. To date, most of the studies on grapevine winter pruning have focused on the effects on yield and quality of grapes, achievable by using different pruning systems and techniques, while the knowledge of root distribution, development, and growth in relation to winter pruning is still not well understood. In this contest, the purpose of this study was to investigate the effect of winter pruning on the root system of field-grown Vitis vinifera cv. Pinot Gris grafted onto rootstock SO4. We compared two pruning treatments (pruning-P and no pruning-NP) and analysed the effect on root distribution and density, root index and on the root sugar reserves. Root data were analysed in relation to canopy growth and yield, to elucidate the effect of winter pruning on the root/yield ratio. Our data indicated that winter pruning stimulated the root growth and distribution without compromising canopy development, while no-pruning treatment produced less growth of roots but a larger canopy. Information regarding root growth and root canopy ratio is important as it gives us an understanding of the relationship between the aerial and subterranean parts of the plant, how they compete, and finally, offers us the possibility to ponder on cultural practices.

For traffic management under sudden disaster in high-density areas, the first and foremost step is to prevent traffic congestion in the disaster-affected area by traffic flow control, as to provide enough and flexible traffic capacity for emergency evacuation and emergency rescue. Catastrophe border identification is the foundation and the key to traffic congestion prediction under sudden disaster. This paper uses a mathematical model to study the regional traffic flow in the high-density area under sudden fire disaster based on the Cusp Catastrophe Theory (CCT). The catastrophe border is identified by fitting the CCT-based regional traffic flow model to explore the stable traffic flow changing to the instable state, as to provide a theoretical basis for traffic flow manage and control in disaster-affected areas, and to prevent the traffic flow being caught into disorder and congestion. Based on VISSIM simulator data by building simulation scenarios with and without sudden fire disaster in a Sudoku traffic network, the catastrophe border is identified as 439pcu/lane/h, 529pcu/lane/h, 377pcu/lane/h at 5s, 10s, 15s data collection interval respectively. The corresponding relative precision, which compares to the method of Capacity Assessment Approach (CAA), is 89.1%, 92.7% and 76.5% respectively. It means that 10s data collection interval would be the suitable data collection interval in catastrophe border identification and regional traffic flow control in high-density area under sudden fire disaster.

The work is devoted to the investigation of virus quasispecies evolution and diversification due to mutations, competition for host cells, and cross-reactive immune responses. The model consists of a nonlocal reaction-diffusion equation for the virus density depending on the genotype considered as a continuous variable and on time. This equation contains two integral terms corresponding to the nonlocal effects of virus interaction with host cells and with immune cells. In the model, a virus strain is represented by a localized solution concentrated around some given genotype. Emergence of new strains corresponds to a periodic wave propagating in the space of genotypes. The conditions of appearance of such waves and their dynamics are described.

In thermal friction drilling (TFD) operations, the geometrical dimensions of bushing shape, height and wall thickness are the most vital consequences, due to increasing the connecting length and strength. In this paper, AA7075-T651 aluminum alloys with 2, 4, 6, 8, and 10 mm in thicknesses were drilled with TFD process in order to investigate the density, the volume ratio, and height and wall thickness of the bushings. The experiments were conducted at constant spindle speed and feed rate conditions by using HSS conical tools of 5, 10, 15, and 20 mm in diameters. It was experimentally found that the bushing height and the wall thickness were tendency of increase linearly with increasing both material thickness and tool diameter. The effect of tool diameter was found to have much of influence on the measured values than the thickness of the drilled material. The density of the bushing was changed inconsiderably. Approximately 70-75 % percentages of the evacuated material composed the bushing shape, in TFD operations.

Satellite-based remote sensing technologies are utilized extensively to investigate urban thermal environments under rapid urban expansion. Current MODIS data is, however, unable to adequately represent the spatially detailed information because of its relatively coarser spatial resolution, while Landsat data can’t explore temporally the refined analysis due to the low temporal resolution. In order to resolve this situation, we used MODIS and Landsat data to generate “Landsat-like” data by using the flexible spatiotemporal data fusion method (FSDAF), and then studied spatiotemporal variation of land surface temperature (LST) and its driving factors. The results showed that 1) The estimated “Landsat-like” data have high precision; 2) By comparing 2013 and 2016 datasets, LST increases ranging from 1.8°C to 4°C were measurable in areas where the impervious surface area (ISA) increased, while LST decreases ranging from -3.52°C to -0.70°C were detected in areas where ISA decreased; 3) LST has a strongly negative relationship with the Normalized Difference Vegetation Index (NDVI), and a strongly positive relationship with Normalized Difference Built Index (NDBI) in summer; and 4) LST is well correlated with Building density (BD), in a complex conic mode, and LST may increase by 0.460°C to 0.786°C when BD increases by 0.1. Our findings can provide information useful for mitigating undesirable thermal conditions and for long-term urban thermal environmental management.

Prebiotic organic synthesis reactions catalyzed by Earth-abundant metal sulfides are key processes for understanding the evolution of biochemistry from inorganic molecules, yet the catalytic functions of sulfides have remained poorly explored in the context of the origins of life. Past studies on prebiotic chemistry have mostly focused on a few types of metal sulfide catalysts, such as FeS or NiS, which form limited types of products with inferior activity and selectivity. To explore the potential of metal sulfides on catalyzing prebiotic chemical reactions, here, the chemical diversity (variations in chemical composition and phase structure) of 304 natural metal sulfide minerals in a mineralogy database was surveyed and approaches to rationally predict the catalytic functions of metal sulfides are discussed based on advanced theories and analytical tools of electrocatalysis such as proton-coupled electron transfer, structural comparisons between enzymes and minerals, and in-situ spectroscopy. To this end, we introduce a model of geo-electrochemistry driven prebiotic synthesis for chemical evolution, as it helps us to predict kinetics and selectivity of targeted prebiotic chemistry under “chemically messy conditions”. We expect that combining the data-mining of mineral databases with experimental methods and theories developed in the field of electrocatalysis will facilitate the prediction and verification of catalytic performance under a wide range of pH and Eh conditions, and aid in the rational screening of mineral catalysts involved in the origins of life.

The properties of the charged dark matters are discussed in terms of the new three-dimensional quantized space model. Because of the graviton evaporations, the very small Coulomb’s constant (k(dd)) of 10 ⁻⁴⁸ k and large gravitation constant (G_N(dd)) of 10⁶ G_N for the charged dark matters at the present time are expected. The tentative values of G and k are used for the explanation purpose. Therefore, F_c(mm) > F_g(dd) > F_g(mm) > F_g(dm) > F_c(dd) > F_c(dm) = F_c(lq) = 0 for the proton-like particle. Also, the gravitation constant has been changed with increasing of the time because of the graviton evaporation. In the present work, the B1, B2 and B3 bastons with the condition of k(mm) = k >> k(dd) > k(dm) = 0 are explained as the good candidates of the dark matters. Also, the particle creation, dark matters and dark energy could be deeply associated with the changing gravitation constants (G). It is expected that the changing process of the gravitation constant between the matters from G_N(mm) ≈ 10³⁶ G_N to G_N(mm) = G_N happened mostly near the inflation period. Therefore, during most of the universe evolution the gravitation constant could be taken as G_N(mm) = G_N. And the effective charges and effective rest masses of the particles are defined in terms of the fixed Coulomb’s constant (k) and fixed gravitation constant (G_N). Then, the effective charge of the B1 dark matter with EC = −2/3 e is (EC)_eff = −2/3·10⁻²⁴ e. It is concluded that the photons, gravitons and dark matters are the first particles created since the big bang. The particles can be created from the decay of the matter universe and the pair production of the particle and anti-particle with decreasing of the gravitation constant (G_N(mm)). Also, the weak force, strong force and dark matter force bosons are created from the interactions of the elementary particles with the T fluctuations of the vacuum energy.

A novel plasma source of pulsed electrolyte cathode atmospheric pressure discharge (pulsed-ECAD) driven by an alternating current (AC) power supply coupled with a high voltage diode was generated, and the discharge was generated in the open-to-air atmosphere between a metal electrode and a small-sized flowing liquid cathode. The spatial distribution of plasma temperatures (excitation, vibrational and rotational) of the pulsed-ECAD were investigated. The electron excitation temperature of H T_exc(H), vibrational temperature of N₂ T_vib(N₂), and rotational temperature of OH T_rot(OH) were measured as 4900±36-6800±108 K, 4600±86-5800±100 K and 1050±20-1140±10 K, respectively. Meanwhile, the temperature characteristics of dc solution cathode glow discharge (dc-SCGD) were also studied for comparison with pulsed-ECAD. The effects of operating parameters, including discharge voltage and discharge frequency, on the plasma temperatures were investigated. The electron number density determined in the discharge system and dc-SCGD were within the range (3.8–18.9) ×10¹⁴ cm^-3 and 2.6×10¹⁴-17.2×10¹⁴ cm^-3, respectively.

There is an increased interest in the district-scale energy transition within interdisciplinary research community. Agent-based modelling presents a suitable approach to address variety of questions related to policies, technologies, processes, and the different stakeholder roles that can foster such transition. This state-of-the-art review focuses on the application of agent-based modelling for exploring policy interventions that facilitate the decarbonisation (i.e., energy transition) of districts and neighbourhoods while considering stakeholders’ social characteristics and interactions. We systematically select and analyse peer-reviewed literature and discuss the key modelling aspects, such as model purpose, agents and decision-making logic, spatial and temporal aspects, and empirical grounding. The analysis reveals that the most established agent-based models’ focus on innovation diffusion (e.g., adoption of solar panels) and dissemination of energy-saving behaviour among a group of buildings in urban areas. We see a considerable gap in exploring the decisions and interactions of agents other than residential households, such as commercial and even industrial energy consumers (and prosumers). Moreover, measures such as building retrofits and conversion to district energy systems involve many stakeholders and complex interactions between them that up to now have hardly been represented in the agent-based modelling environment.

How much is religion quantitatively involved in global climate politics? After assessing the role of the Conference of Parties to the United Nations Framework Convention on Climate Change from a normative perspective, this descriptive, transdisciplinary and unconventional study offers the first comprehensive quantitative examination of religious nongovernmental organizations that formally participate in its annual meetings, the largest attempts to solve the climate crisis through global governance. This study finds that although their numbers are growing, only about 3 percent of registered nongovernmental organizations accredited to participate in the conference are overtly religious in nature — and that more than 80 percent of those faith-based groups are Christian. Additionally, this study finds that religious nongovernmental organizations that participate in the conference are mostly from the Global North. The results call for greater participation of religious institutions in the international climate negotiations in order for society to address the planetary emergency of climate change.

The modern textbook analysis of the thermal state of photons inside a three-dimensional reflective cavity is based on the three quantum numbers that characterize photon’s energy eigenvalues coming out when the boundary conditions are imposed. The crucial passage from the quantum numbers to the continuous frequency is operated by introducing a three dimensional continuous version of the three discrete quantum numbers, that leads to the energy spectral density and to the entropy spectral density. This standard analysis obscures the role of the multiplicity of energy eigenvalues associated to the same eigenfrequency. In this paper we review the past derivations of Bose’s entropy spectral density and present a new analysis of energy spectral density and entropy spectral density based on the multiplicity of energy eigenvalues. Our analysis explicitly defines the eigenfrequency distribution of energy and entropy and uses it as a starting point for the passage from the discrete eigenfrequencies to the continuous frequency.

The catastrophic failure of two dams in Libya in the night of 10th and 11th September 2023, resulted in a significant amount of water and debris destroying a large part of the city of Derna, which is located downstream of the two dams. The flood caused more than 6000 fatalities and the dis-placement of thousands of people from the city. The dams failed due to heavy rainfall caused by the Medicane Daniel, resulting in intense precipitation and the dams overspilling after reaching full capacity. This paper analyses the consequences of the dam breach by modelling the flow discharge and the flooding of the city of Derna. The analysis compares the computed quantities with the findings of the post-event satellite image analysis from UNOSAT and Copernicus, the field reports, and information gathered from the social media through AI detection. The results allows to better understand the dynamics of the dam breach, its initial parameters and an assessment of the accu-racy of the results.

Motivated by the PEACOC project on metal recovery from solid wastes, an innovative magnetic density separation (MDS) process has been developed for granular material sorting. It has intrinsic advantages over the existing industrialized MDS by eliminating fluid turbulence and particle jamming problems. The new MDS applies an inclined planar magnet and a horizontal basin containing a static magnetic fluid as the separation medium. A particle sliding phenomenon is identified as a feature of the process which could help the separation. The MDS successfully sorted shredded PCBAs to concentrate valuable metals and sorted shredded wires to reduce metallic contaminants in the plastic fractions. A pilot scale facility is introduced to show the design to achieve continuous production and to reduce the consumption of ferrofluid.

Silica fly ash, Certyd aggregate, and an alkaline solution were used to produce lightweight geo-polymer concretes. The compressive strength, water absorption, bulk density and SEM photos showing the structure of the obtained composite were carried out. Tests conducted on the specifi-cation of lightweight geopolymer concretes have revealed significant chemical interactions between the ash aggregate and the geopolymer mortar, particularly when the coarse aggregate surface has been pre-treated with an alkaline solution. Statistical analysis of the experimental data, which in-vestigated the influence of three key variables on compressive strength, water absorption, and bulk density of Lightweight Geopolymer Concrete (LBG), identified the following factors as having the most substantial impact: the quantity of alkali used, the curing temperature, and the concentration of alkali in the mixture. The optimal test series exhibited a commendable compressive strength of 20.14 megapascals (MPa), accompanied by a water absorption rate of 14.72% and a bulk density of 1486.6 kilograms per cubic meter (kg/m³). These findings underscore the importance of alkali con-tent, curing temperature, and alkali concentration in tailoring the properties of lightweight geo-polymer concrete to meet specific performance requirements.

Estrogens play a protective role during early life stages. However, endogenous 17β-estradiol (E2) can accelerate atherosclerosis progression in low-grade inflammatory conditions like established atherosclerosis. Our single-center cohort study assessed sex-specific associations of gonadal hormones with oxidative stress, inflammation, and myocardial injury markers in 111 patients (37% women) diagnosed with acute myocardial infarction (MI) between July 2011 and December 2013. Blood samples were collected within 48 hours of symptom onset, and we measured sex steroids (E2, total testosterone [T]), oxidized low-density lipoproteins, high-sensitive C-reactive protein (CRP), white blood cell counts (WBC), and cardiac enzymes (creatine kinase [CK], the CK Muscle-Brain fraction [CK-MB], and high-sensitive troponin T [hsTnT]). The SYNTAX score gauged coronary disease severity from coronary angiography results. In men with acute MI, peak cardiac enzyme levels were predicted by post-percutaneous coronary intervention (PCI) E2 plasma levels (OR 1.011, p=0.047 - CK; OR 1.018, p=0.013 - CK- MB; OR 1.019, p=0.005 - TnT), peak WBC count (OR 1.487, p=0.015 - CK ; OR 1,709, p=0,005 - CK- MB; OR 1.391, p=0.012 - TnT), and peak CRP plasma levels (OR 1.040, p=0.033 - CK; OR 1.024, p=0.029 - CK-MB; OR 1.063, p=0.006 - TnT). T levels and E2/T ratio were associated with post-PCI CRP in these men (OR 0.980, p = 0.024 - T, OR 1.010, p = 0.076 - CRP). For women, peak WBC was a marker of highest testosterone (OR 1.348, p = 0.062), and only WBC was a significant indicator of myocardial injury extent (OR 1.426, p=0.039 - CK; OR 1.384, p=0.036 - CK-MB; OR 1.299, p=0.048 - TnT). During acute MI, elevated endogenous estradiol levels correlate with myocardial necrosis severity in men, while in women, increased leukocyte levels indicate acute myocardial damage. Elevated plasma T is associated with increased WBC in women. In men, post-PCI plasma CRP specifically indicates endogenous T levels and E2/T ratio during the acute phase.

Optimum design and accurate control of the internal structure of the laser target materials remain an important goal for various laser physics experiments, especially for generating high flux photon and neutron beams. The low-density material is considered to be one of the most difficult for X-ray study due to its high transparency and imperceptible contrast. To produce clear visualization of foam containing sparse structures we used a high-quality monochromatic X-ray beam of synchrotron radiation source PETRA-III at DESY. The X-ray beam parameters allow tomographic scanning with application of phase contrast retrieval algorithms. A series of 3D images of foam-suspended glass microsphere inside the plastic cylinder were obtained with the quality high enough to observe the internal structure and to visualize uniformity, displacement and surface roughness on both sides of the microsphere. The main object under investigation was a CH-plastic capillary including 10 mg/cc CHO-foam with the centered glass microsphere. The results of this work demonstrate that tomographic visualization based on a high quality X-ray radiation and phase contrast analysis is an effective and useful technique for development of new laser targets containing structured low density materials.

In the present study, we studied the effect of apolipoprotein A-1 (APOA1) on the spatial and molecular characteristics of bone marrow adipocytes, using well-characterized ApoA1 knockout mice. APOA1 is a central regulator of high-density lipoprotein cholesterol (HDL-C) metabolism, and thus HDL; our recent work showed that deficiency of APOA1 increases bone marrow adiposity in mice. We found that ApoA1 deficient mice have greatly elevated adipocytes within their bone marrow compared to wild type counterparts. Morphologically, the increased adipocytes were similar to white adipocytes, and displayed proximal tibial-end localization. Marrow adipocytes from wild type mice were significantly fewer and did not display bone-end distribution pattern. The mRNA levels of the brown/beige adipocyte-specific markers Ucp1, Dio2, Pat2, Pgc1a, and the expression of leptin were greatly reduced in the ApoA1 knock-out in comparison to the wild-type mice. In the knock-out mice adiponectin was remarkably elevated. In keeping with the close ties of hematopoietic stem cells and marrow adipocytes, we found that the elevated adiposity in the ApoA1 knock out mice is associated with a significant reduction of the hematopoietic stem cells and common myeloid, but not common lymphoid, progenitors. Moreover, the “beiging”-related marker osteopontin and the angiogenic factor VEGF were also reduced in the ApoA1 knock-out mice, further supporting the notion that APOA1, and most probably HDL-C, regulate bone marrow microenvironment, favouring beige/brown adipocyte characteristics.

The aim of this paper was to evaluate the changes in the mean bone density values of the midpalatal suture in 392 young patients treated with the Rapid Palatal Expander appliance according to sex, gender, vertical and sagittal skeletal patterns. Materials and Methods. The evaluations were performed using the low-dose protocol cone-beam computed tomography scans at t0 (preoperatively) and t1 (1 year after the beginning of the therapy). The region of interest was used to calculate bone density in Hounsfield units (HU) in the area between the maxillary incisors. Results. CBCT scan data of 196 females and 196 males (mean age of 11,7 years) showed homogeneous and similar density values of the MPS at T0 (547.59 HU - 565.85 HU) and T1 (542.31 - 554.20 HU). Class III skeletal individuals showed a significant higher BD than the II class group at T0, but not at T1. Females showed significantly higher BD than males at t0 and t1. No significant differences were found between the other groups and between two-time points in terms of bone density values of the MPS. Conclusions. Females and III class groups showed significantly higher bone density values than males and II class, respectively. No statistically significant differences were found from T0 to T1 in any groups, suggesting that a similar rate of suture reorganization occurs after the use of the RPE, following reorganization and bone deposition along with the MPS.

Phenol is added to acetophenone (methyl phenyl ketone) and to six of its halogenated derivatives in a supersonic jet expansion to determine the hydrogen bonding preference of the cold and isolated 1:1 complexes by linear infrared spectroscopy. Halogenation is found to have a pronounced effect on the docking site in this intermolecular ketone balance experiment. The spectra unambiguously decide between competing variants of phenyl group stacking due to their differences in hydrogen bond strength. Structures where the phenyl group interaction strongly distorts the hydrogen bond are more difficult to quantify in the experiment. For unsubstituted acetophenone, phenol clearly prefers the methyl side despite a predicted sub-kJ/mol advantage which is nearly independent of zero point vibrational energy, turning this complex into a challenging benchmark system for electronic structure methods which include long range dispersion interactions in some way.

The 32CA reactions of a series of pairs of bent three-atom-components (B-TACs) and linear TACs (L-TACs) towards electrophilic dicyanoethylene (DCE) have been studied within the Molecular Electron Density Theory in order to understand their different reactivity. ELF analysis indicates that while pseudodiradical B-TACs change their electronic structure to pseudoradical or carbenoid L-TACs upon dehydrogenation, zwitterionic B-TACs experience no remarkable change. Analysis of the CDFT indices indicates that five of the nine studied TACs have a strong nucleophilic character, thus participating in polar reactions towards electrophilic ethylenes. The activation energies of the 32CA reactions of the nine TACs towards electrophilic DCE range from 0.6 to 22.0 kcal·mol-1, which are by between 2.0 and 10.1 kcal·mol-1 lower than those involved in the non-polar 32CA reactions with ethylene. In general, B-TACs are more reactive than their L-TAC counterparts. A change of the regioselectivity is found in these polar 32CA reactions; in general, while B-TACs are meta regioselective, L-TACs are ortho regioselective. Analysis of the geometrical parameters indicates that at all TSs, the formation of the single bond involving the most electrophilic C4 carbon of DCE is more advanced than that involving the C5 one. A change of the asynchronicity in the reactions involving B-TACs and L-TACs is also found.

This paper presents sufficient conditions for almost global stability of nonlinear switched systems consisting of both stable and unstable subsystems. Techniques from the stability analysis of switched systems have been combined with the multiple Lyapunov density approach - recently proposed by the authors for the almost global stability of nonlinear switched systems composed of stable subsystems. By using slow switching for stable subsystems and fast switching for unstable subsystems lower and upper bounds for mode-dependent average dwell times are obtained. In addition to that, by allowing each subsystem to perform slow switching and using some restrictions on total operation time of unstable subsystems and stable subsystems, we have obtained a lower bound for an average dwell time.

The design of more efficient photosensitizers is a matter of great importance in the field of cancer treatment by means of photodynamic therapy. One of the main processes involved in the activation of apoptosis in cancer cells is the oxidative stress on DNA once a photosensitizer is excited by light. As a consequence, it is a matter of great relevance to investigate in detail the binding modes of the chromophore with DNA, and the nature of the electronically excited states that participate in the induction of DNA damage, for example, charge-transfer states. In this work, we investigate the electronic structure of the anthraquinone photosensitizer intercalated into a double-stranded poly(dG-dC) decamer model of DNA. First, the different geometric configurations are analyzed by means of classical molecular dynamics simulations. Then, the excited states for the most relevant poses of anthraquinone inside the binding pocket are computed by an electrostatic-embedding quantum mechanics/molecular mechanics approach, where anthraquinone and one of the nearby guanine residues are described quantum mechanically to take into account intermolecular charge-transfer states. The excited states are characterized as monomer, exciton, excimer and charge-transfer states based on the analysis of the transition density matrix, and each of these contributions to the total density of states and absorption spectrum is discussed in terms of the stacking interactions. These results are relevant as they represent the footing for future studies on the reactivity of anthraquinone derivatives with DNA and give insights on possible geometrical configurations that potentially favor the oxidative stress of DNA.

Southern highbush blueberry plantations have been expanded into worldwide non-traditional growing areas with elite cultivars and improved horticultural practices. This article presents a comprehensive review of current production systems – alternatives to traditional open field production – such as production in protected environments, high-density plantings, evergreen production, and container-based production. We discuss the advantages and disadvantages of each system and compare their differences to the open field production. In addition, potential solutions have been provided for some of the disadvantages. We also highlight some of the gaps existing between academic studies and production in industry, providing a guide for future academic research. All these alternative systems have shown the potential to produce high yields with high quality berries. Alternative systems, compared to the field production, require higher establishment investments and thus create an entry barrier for new producers. Nevertheless, with their advantages, alternative productions have potential to be profitable.

With reference to Planck scale, increasing support for large scale cosmic anisotropy and preferred directions and by considering an increasing ratio of Hubble parameter to angular velocity, right from the beginning of Planck scale, we make an attempt to estimate ordinary matter density ratio, dark matter density ratio, mass, radius, temperature, age and expansion velocity (from and about the baby universe in all directions). We would like suggest that, from the beginning of Planck scale, 1) Dark matter can be considered as a kind of cosmic foam responsible for formation of galaxies. 2) Cosmic angular velocity decreases with square of the decreasing cosmic temperature. 3) Increasing ratio of Hubble parameter to angular velocity plays a crucial role in estimating increasing cosmic expansion velocity and decreasing density ratios of dark matter and ordinary matter. 4) There is no need to consider dark energy for understanding cosmic acceleration.

The regulation of hepatic very-low-density lipoprotein (VLDL) secretion plays an important role in the pathogenesis of dyslipidemia and fatty liver diseases. VLDL is controlled by hepatic microsomal triglyceride transfer protein (MTTP). Mttp is regulated by carbohydrate response element binding protein (ChREBP) and small heterodimer partner (SHP). However, it is unclear whether both coordinately regulate Mttp expression and VLDL secretion. Here, adenoviral overexpression of ChREBP and SHP in rat primary hepatocytes induced and suppressed Mttp mRNA, respectively. However, Mttp induction by ChREBP was much more potent than suppression by SHP. Promoter assays of Mttp and the liver type pyruvate kinase gene revealed that SHP and ChREBP did not affect the transactivity of each other. Mttp mRNA and protein levels of Shp^/– mice were similar to those of wild-type; however, those of Chrebp^–/–Shp^–/– and Chrebp^–/– mice were much lower. Consistent with this, the VLDL particle number and VLDL secretion rates in Shp^–/–- mice were similar to wild-type, but were much lower in Chrebp^–/– and Chrebp^–/–Shp^–/–- mice. These findings suggested that ChREBP rather than SHP regulates VLDL secretion and that ChREBP and SHP do not affect the transactivities of each other.

Cropland area per capita and pressure index on cropland is the important parameters measuring the social vulnerability and sustainability in the perspective of food security in a certain region in China during the historical periods. This study reconstructs the spatial distribution change of cropland area per labor/household and pressure index on cropland during the 17th-20th century by the methods of historical documents, regression analysis, pressure index model and GIS. Then it analyzed the impacting process of climate change and sustainability of cropland use during the different periods. It draws conclusions: (i) the spatial difference of labor/household density was obvious which had the same pattern as cropland distribution during the same periods, which is higher density in three agricultural areas. (ii) Cropland area per capita was relatively higher during the 17th-18th century, which were above 0.4 ha/person in majority counties and distributed homogenously. Till the 19th century and the beginning of 20th century, cropland area per capita in large amount of regions decreased below 0.2 ha/person embodying the increase of social vulnerability and unsustainability at that time. (iii) Pressure index on cropland also showed the similar spatial pattern as cropland area per capita which presented lower threshold than nowadays. During the 17th-18th century there was no pressure on cropland. While, in the 19th century and at the beginning of 20th century, two high value centers of pressure index on cropland appeared in Middle Shandong and the Jiaodong region, pressure on sustainable cropland use increased obviously and a food crisis is probably created. (iv) Higher sustainable extent of cropland use corresponds to cold period, and lower sustainable extent of cropland use corresponds to warm period in Shandong over the past 300 years. The turning point of 1680s from dry to wet attributes to the decrease of sustainable extent of cropland use in Shandong not very distinctively. More and more pressure on sustainability of cropland use finally since the beginning of 20th century would intensify the social conflict and increase the probability of social revolts.

Ti-Al based alloys, particularly TiAl and Ti3Al two-phase alloys, have garnered significant attention as potential replacements for various high-temperature structural materials due to their exceptional properties, including low density, oxidation resistance, and high strength at elevated temperatures. Despite these advantages, experimental studies on the microstructure evolution of Ti-Al based alloys under complex conditions remain challenging to observe and characterize. This review article examines the current research on molecular dynamics (MD) simulations of Ti-Al based alloys, focusing on two-phase Ti-Al alloys, Ti-Al amorphous alloys, Ti-Al composite materials, and the welding and multi-layer/film applications of Ti-Al alloys. The review highlights the unique capabilities of MD simulations in predicting the behavior of Ti-Al based alloys and addresses existing scientific challenges. Furthermore, the article discusses future research directions and development prospects in this field.

Metal-reinforced polymethyl-methacrylate (PMMA) is considered the gold standard material for immediate loading on dental implants. However, mechanical problems under loading cycles can occur, such as fractures. To overcome these drawbacks, a novel polymer-based material has been proposed. The aim of the present in vitro comparative research is to validate a novel composite polymer developed to replace metal-reinforced PMMA interim restoration due to its advantages of good mechanical proprieties, easier manufacturing, and handling. Ten interim restorations were CAD/CAM designed and fabricated (five in the composite "ONLY" group, and five in the metal-reinforced PMMA group). All the samples were screwed into the prototype models, simulating a complete edentulous mandible rehabilitated with six straight implants. Outcome measures were breakpoint (load, N) and displacement (mm) thought a static, compression test and material behavior under dynamic cyclic test method (fatigue test). A total of twenty samples were tested. Ten samples were used for each test (10 for static and 10 for dynamic), five samples were used in each group (test and control). All the specimens completed the mechanical tests, as planned. There was no statistically significant difference between groups for all, breakpoint, displacement and fatigue tests. Breakpoint in the test group was 1953.19 ± 543.73 N, while, it was 2031.10 ± 716.68 N in the control group, with no statistically significant difference (P=0.775). The displacement was 1.89 ± 0.34 mm in the test group and 1.98 ± 0.75 mm in the control group, again, with no statistically significant difference (P=0.763). Under dynamic cyclic test method, in the control group the mean load was 2504.6 ± 972.15 N, while, in the test group the mean load was 3382 ± 578.5 N. The difference between group was 877.4 ± 579.3 N (p value=0.121). With the limitation of this in vitro study, the novel composite polymer can be used to immediately load dental implants. Further clinical researches are needed to confirm this preliminary results.

Fractional cointegration in time series data has been explored by several authors, but panel data applications have been largely neglected. A previous study of ours discovered that the Chen and Hurvich fractional cointegration test for time series was fairly robust to a moderate degree of heterogeneity across sections, out of the six tests considered. Therefore, this paper advances a customized version of the Chen and Hurvich methodology to detect cointegrating connections in panels with unobserved fixed effects. Specifically, we develop a test statistic that accommodates variation in the long-term cointegrating vectors and fractional cointegration parameters across observational units. The behaviour of our proposed test is examined through extensive Monte Carlo experiments under various data generating processes and circumstances. The findings reveal that our modified test performs quite well comparatively and can successfully identify fractional cointegrating relationships in panels even in the presence of idiosyncratic disturbances unique to each cross-sectional unit. Furthermore, the proposed modified test procedure established the presence of long-run equilibrium between the exchange rate and labour wage of 36 countries agricultural markets.

Graphene-based materials (GBMs) are a prospective material of choice for rechargeable battery electrodes because of their unique set of qualities, which include tunable interlayer channels, high specific surface area, and strong electrical conductivity characteristics. The market for commercial rechargeable batteries is now dominated by lithium-ion batteries (LIBs), however issues with organic electrolyte safety, high lithium pricing, and limited lithium resources have hindered LIB development. Zinc-based rechargeable batteries have emerged as a viable substitute for rechargeable batteries due to their affordability, safety, and improved performance. This review article explores recent developments in the synthesis and advancement of GBMs for rechargeable zinc‐air batteries (ZABs), and common graphene-based electrocatalyst types. An outlook on the difficulties and probable future paths of this extremely promising field of study is provided at the end.

Session-based recommendations which aim to predict subsequent user-item interaction based on historical user behavior during anonymous sessions can be challenging tasks. Two main challenges need to be addressed and improved: (1) How to analyze these sessions to accurately and completely capture users’ preferences, and (2) how to identify and eliminate any interference caused by noisy behavior. Existing methods have not adequately addressed these issues since they either neglected the valuable insight that can be gained from analyzing consecutive groups of items or failed to take these noisy data in sessions seriously and handled them properly, which can jointly impede recommendation systems from capturing users’ real intentions. To address these two problems, we designed a multi-order semantic denoising (MSD) model for session-based recommendations. Specifically, we grouped items of different lengths as varying multi-order semantic units to mine the user’s primary intention from multiple dimensions. Meanwhile, a novel denoising network was designed to alleviate the interference of noisy behavior and provide a more precise session representation. The result of extensive experiments on three real-world datasets demonstrated that the proposed MSD model exhibited improved performance compared with existing state-of-the-art methods in session-based recommendation.

Cardiovascular diseases, which are the leading cause of death in Croatia, are linked to the high prevalence of hypertension. Both are associated with high salt intake which was determined almost two decades ago when Croatian Action on Salt and Health (CRASH) was launched. The main objective of the present study was to evaluate salt, potassium, and iodine intake using 24-hour urine samples in a random sample of adult Croatian population, and to analyse trends in salt consumption after the CRASH has intensively started. Methods: In this national population-based EH-UH 2 study performed in 2018-2021 (participation rate 72 %) in which we analysed a single 24-hour urine sample, 1067 adult participants (mean age 57.12 (SD 13.9), men 35%) were included. Results: Mean salt and potassium intakes were 8.6 g/day (IQR 6.2-11.2) and 2.8 g/day (IQR 2.1-3.5), respectively, with sodium-to-potassium ratio of 2.6 (IQR 1.8-3.3). We detected a decrease of 17.6% (2 g/day less) in salt consumption compared to our previous salt-mapping study. However, only 13.7%, and 8.9 % met the WHO salt and potassium recommended target of 5 g/day, and 3.5 g/day, respectively. Salt intake was higher, and potassium ingestion was lower in rural vs. urban regions, and in continental vs. Mediterranean parts of Croatia. Moderate to severe iodine insufficiency was determined in only 3% adult participants. Conclusion: In the last fifteen years, salt consumption has been significantly reduced in Croatian adult population because of intensive and broad CRASH program led by the Croatian Society of Hypertension and the Croatian Hypertension League. However, salt intake is still too high, and potassium ingestion is too low. With expected more active engagement and help of the government, obtained results could be significantly improved. Salt reduction programs are most cost-effective methods of cardiovascular disease prevention and should be considered more seriously by the government and health policy makers.

The majority of local IPv6 networks continue to remain insecure and vulnerable to neighbor spoofing attacks. The Secure Neighbor Discovery (SEND) standard and its concomitant Cryptographically Generated Addressing (CGA) scheme were accepted by large standards bodies to codify practical mitigations. SEND and CGA have never seen widespread adoption due to their complexities, obscurity, costs, compatibility issues, and continued lack of mature implementations. In light of their poor adoption, research since their standardization has continued to find new perspectives and proffer new ideas. The orthodox solutions for securing Neighbor Discovery have historically struggled to successfully harmonize three core ideals: simplicity, flexibility, and privacy preservation. This research introduces Voucher-Based Addressing, a low-configuration, low-cost, and high-impact alternative to IPv6 address generation methods. It secures the Neighbor Discovery address resolution process while remaining simple, highly adaptable, indistinguishable, and privacy-focused. Applying a unique concoction of cryptographic key derivation functions, link-layer address binding, and neighbor consensus on the parameters of address generation, resolved address bindings are verifiable without the need for complex techniques that have hindered the adoption of canonical specifications.

In this work, zinc oxide (ZnO)/ granular activated carbon (GAC) composites at different ZnO concentration (0.25M-ZnO@GAC, 0.5M-ZnO@GAC, and 0.75M-ZnO@GAC) were prepared by an in-situ hydrothermal method and demonstrated synergistic photocatalytic degradation and ad-sorption of Rhodamine B (RhB). The thermal stability, morphological structure, elemental com-position, crystallographic structure, and textural properties of developed catalysts were charac-terized by thermal gravimetric analysis (TGA/DTG), scanning electron microscopy equipped with energy dispersive-x-ray (SEM-EDS), x-ray diffraction (XRD), and Brunauer–Emmett–Teller (BET) analysis. Successful loading of ZnO onto GAC was confirmed by SEM-EDS and XRD analysis. The BET surface areas of GAC, 0.25M-ZnO@GAC, 0.5M-ZnO@GAC, and 0.75M-ZnO@GAC were 474 m2/g, 450 m2/g, 453 m2/g, and 421 m2/g, respectively. The decrease in GAC could be attributed to the successful loading of ZnO on the GAC surface. Notably, 0.5M-ZnO@GAC exhibited the best photocatalytic degradation efficiency of 82% and 97% under UV-A and UV-C light over 120 min, attributed to improved crystallinity and visible light absorption. The photocatalytic degradation parameters revealed that lowering the RhB concentration, raising the catalyst dosage and pH be-yond the point of zero charge (PZC) would favor the RhB degradation. Photocatalytic reusability was demonstrated over 5 cycles. Scavenger tests revealed that the hydroxyl radicals (•OH), su-peroxide radicals (O2−•), and photoinduced hole (h+) radicals play a major role during the RhB degradation process. Based on the TOC results, the RhB mineralization efficiency of 79.1% was achieved by 0.5M-ZnO@GAC. Additionally, GAC exhibited a strong adsorptive performance towards RhB with adsorption capacity and RhB removal of 487.1 mg/g and 99.5% achieved within 90 min equilibrium time. The adsorption characteristics were best described by pseu-do-second-order kinetics, suggesting chemical adsorption. This research offers a new strategy for the development of effective photocatalyst materials with potential for wider wastewater treat-ment applications.

EphB2 is a member of the Eph family tyrosine kinase receptors. EphB2 binds to ephrin-B1, ephrin-B2, and ephrin-B3, which are critical regulators of vascular and nervous development through controlling cell migration and axon guidance. EphB2 is overexpressed in tumors, including glioma, breast cancer, hepatocellular carcinoma, and malignant mesothelioma, and it functions as a tumor promoter. Therefore, the development of monoclonal antibodies (mAbs) against EphB2 is essential for tumor diagnosis and therapy for EphB2-positive tumors. In this study, we developed novel mAbs for human EphB2 using the Cell-Based Immunization and Screening (CBIS) method. One of the established anti-EphB2 mAbs, Eb2Mab-3 (mouse IgG1, kappa), reacted with EphB2-overexpressed Chinese hamster ovary-K1 (CHO/EphB2) and an endogenously EphB2-expressing cancer cell line (LS174T) by flow cytometry. Using flow cytometry, the dissociation constant (KD) values of Eb2Mab-3 for CHO/EphB2 and LS174T were determined as 1.1 × 10−9 M and 3.6 × 10−10 M, respectively. These results indicated that Eb2Mab-3 possesses a high affinity for detecting EphB2 and could apply to tumor therapy.

Demand for environmentally friendly types of energy is growing all over the world, which naturally increases the intensity of work on the production of hydrogen-containing fuel mixtures. Steam reforming of methanol is one of the most effective areas of research, as it is a process with low energy consumption. The results of steam reforming of methanol on the catalysts prepared by solution combustion synthesis (SCS) and impregnation by moisture capacity are presented. Investigation of the activity of Cu-Ce-Al catalysts of different composition was carried out for production of hydrogen and comparison of SCS with traditional impregnation method. Methanol conversion reaches 99%, while the selectivity of H2 was 88%, at 500 °C. It was found that CuAl2O4 spinel formation is due to substitution of Al3+ with Cu2+ Ce3+ cations. A consequence CuAl2O4 and CeAlO3 lattice parameters increase because of difference in ionic radius of Al3+ (0.53 Å) and Cu2+ (0.73 Å), Ce3+ (1.07 Å). Advantages of SCS catalysts in steam reforming of methanol were shown. The aim of this research is to develop a new catalyst for conversion of methanol into hydrogen containing fuel mixtures, which will further promote the organization of a new era of environmentally friendly energy-saving production methods.

This study investigates the application of frequency augmentation techniques to improve condition-based maintenance (CBM+) systems for airborne weapon systems, focusing on the predictive accuracy of velocity and acceleration parameters. Utilizing MIL-STD-1553B MUX data from 138 sorties of fixed-wing aircraft, we explored six augmentation methods, including traditional interpolations (linear, quadratic, cubic spline) and advanced machine learning models (K-Nearest Neighbor, LSTM, and Bi-LSTM). Our findings indicate that while traditional methods like linear interpolation are more effective for velocity parameters, advanced ML techniques, particularly Bi-LSTM, provide better results for acceleration parameters, which exhibit more complex and rapid variability. The study underscores the necessity of tailoring augmentation approaches to specific parameter characteristics and highlights the potential of ML models in capturing intricate patterns within time-series data. These insights are critical for advancing CBM+ systems in military avionics, enhancing reliability and operational efficiency through improved data processing strategies. Future work should explore more performant augmentation techniques, such as by integrating multi-dimensional datasets, and explore ways to develop automated tools for a more powerful predictive maintenance framework.

Lysine plays a crucial role in promoting development, enhancing immune function, and improving the function of central nervous system tissues. The two configurational isomers of amino acids have significantly different effects. Currently, methods for chiral recognition of lysine all have drawbacks such as expensive equipment and complicated detection processes, whereas fluorescence analysis boasts high sensitivity, strong selectivity, and simple operation. In this study, we synthesized four novel Binaphthyl-Amine (BINAM)-based fluorescent probes capable of specifically identifying the L-configuration of lysine among the twenty amino acids constituting human proteins. The enantiomeric fluorescence enhancement ratio (ef or ΔIL/ΔID) reached up to 15.29, demonstrating high enantioselectivity. We also evaluated the probe's recognition ability under different pH, reaction times, and metal ion conditions, as well as the Limit of Detection of the probe. Our findings indicate that this probe is a highly stable tool for detecting chiral lysine.

In Pakistan, 2018 National Nutrition Survey reported 40% of under five children were stunted. This study assesses the effectiveness of nutritional supplementation in reducing stunting among under-five children in two rural districts in Sindh, Pakistan. This was a mixed-method quasi-experimental study with intervention and control population. 3397 and 3277 under-five children participated in the baseline and end-line surveys. Both study areas were matched for demographic and economic circumstances. The participants received nutrient supplements underpinned by nutrition behaviour change communication for appropriate complementary feeding practices and hand hygiene targeted at primary caregivers during the first 1000 days of an infant's life. The impact was assessed using the difference in difference analysis with kernel propensity score matching to adjust the differences among control and intervention populations.

The sustainable development of resource-based cities has long been a focal point for both governmental policies and academic research. A wealth of academic literature identifies the 'resource curse' as a critical barrier to sustainable development in these urban areas. Despite extensive studies, a consensus on effective strategies to circumvent or resolve this challenge remains elusive. Recent empirical data reveals a noticeable pattern of economic growth differentiation in China's resource-based cities. Why do some resource-based cities experience economic decline while others achieve sustainable economic growth? Therefore, this paper analyzes the reasons for the divergence of economic growth in resource cities from the perspective of heterogeneity. The results of the study show that the phenomenon of the resource curse is conditional, and the heterogeneity of demo-graphic changes, geographic location and institutional environment has a significant impact on the economic growth of resource cities. These factors are investigated to elucidate the observed diversification and heterogeneity in the economic growth of resource-based cities. Building upon this analysis, the paper proposes a framework for differentiated sustainable development pathways tailored to the unique contexts of these cities. This approach not only contributes to the current understanding of the 'resource curse' but also offers novel insights for future research aiming to adopt a more nuanced and context-specific perspective in examining sustainable urban development.

Among the different steps in software development software testing is one of the inevitable steps. Manual testing is considered to be more expensive and time-consuming, and this led to the formation of automated testing tools. Automated software testing tools offer a comprehensive system testing solution that minimizes the risk of any errors that could result in financial losses. One such tool is selenium. Selenium testing is an advantageous method employed by developers and testers to assess their code. Selenium is compatible with numerous widelyused programming languages like C#, Java, Python, and more. This paper focuses on understanding the in and outs of software testing using selenium

Recently, interest in STEM education has grown among researchers and educators, also considering the skills required to address the challenges of the 21st century. Supporting learning in STEM subjects is an open challenge, especially during secondary education, which is reflected in the implementation of innovative pedagogical practices, including approaches focused on Game-Based Learning (GBL). This study analyzed the main issues addressed by research on game-based educational approaches applied to STEM teaching and learning in secondary school and their evolving trends. A text analysis of abstracts published in the past decade was conducted using T-lab software. The “Word Analysis” function was used for preliminary visual mapping; then the “Specificity Analysis” and “Thematic Analysis of Elementary Contexts” functions were applied to explore changes in research directions and to map the themes covered by the most recent studies. The results showed that the implementation of games in STEM disciplines is a promising area of inquiry. A shift in research directions also emerged, currently more focused on studying how GBL can foster engagement and the emotional component of learning. Adapting to rapidly changing technology and integrating essential skills such as coding and computational thinking are additional challenges that the research community is facing.

This review highlights the potential and limitations of mRNA vaccines with a particular focus on mucosal delivery as an alternative to parenteral administration. The strengths of mRNA vaccines are: a) Versatility: they can be adapted to target a wide range of pathogens; b) Faster development: designed and produced more quickly than traditional vaccines; c) High efficacy: effective in preventing severe disease, as demonstrated during the COVID-19 pandemic. Current challenges: a) Delivery: current methods (mainly intramuscular injection) may not be optimal for inducing mucosal immunity; b) Stability: mRNA is fragile and needs to be protected from degradation; c) Safety: potential side effects, including myocarditis, blood clotting, allergic reactions need further investigation. Mucosal delivery could be more effective in preventing the transmission of pathogens and is generally better accepted by the population. Pros: offers the potential to induce local immunity at the site of pathogen entry, potentially providing broader protection; Cons: developing effective delivery systems and adjuvants for mucosal delivery is difficult. Extracellular vesicles as a mucosal delivery system are promising and offer a potentially safe, scalable, and needle-free approach. Future directions: a) Optimizing mRNA constructs: strategies like codon optimization and self-amplifying RNA can improve stability and translation efficiency; b) Rigorous pre-clinical studies are essential before human trials.

Most recent university campuses follow the North American model, built on city limits or countryside, with large separate buildings in open green spaces. Studies suggest that prevalence and severity of mental health issues among university students are increasing over the past decade in most countries. University services were created to face this growing problem, however individual based interventions have limited effects on mental health and well-being of a large population. Our aim was to verify if and how the natural environment in Campuses is focused on programs to cope with the issue of mental health and well-being among students. Systematic review of literature was undertaken with search in Scopus and LILACS with the keywords “green areas” AND “well-being” AND “Campus”, following PRISMA guidelines. As a result, 32 articles were selected. Research on the topic is recent, mostly in the USA, Bulgaria, and China. Most studies used objective information on campuses’ greenness and/or university students’ perception. Mental health was usually measured by validated scores. Findings of all the studies indicated positive association between campus greenery and well-being of students. We conclude that there is a large potential for use of university campuses in programs and sites for students´ restoration and stress relief.

OBJECTIVE: Cervical cancer is a major cause of cancer-related mortality, necessitating effective screening and diagnostic methods. This study aimed to assess the performance of cervicovaginal smear (CVS) and Human papilloma virus (HPV)-DNA cotest. STUDY DESIGN: The pathology results of 225 female patients who underwent HPV-DNA testing with CVS between 2014 and 2022 and were subsequently diagnosed by colposcopic cervical biopsy or second CVS were retrospectively analyzed. RESULTS: CVS samples showed Atypical Squamous Cells of Undetermined Significance (ASCUS), Low-grade squamous intraepithelial lesion (LSIL), High-grade squamous intraepithelial lesion (HSIL) and cervical cancer. Concordance between the first and second diagnoses demonstrated moderate agreement for LSIL. ASCUS cases exhibited a significant correlation with HPV-DNA positivity and higher-grade cervical lesions. In biopsy, sensitivity and specificity for CIN 2 were 67.8% and 67.9%, respectively, while for CIN 3, they were 81.8% and 58.5%. HPV testing showed significant correlation with histopathologic results. In women over 40 years, more intraepithelial lesions were diagnosed compared to younger women (p<0.005). The conventional smear technique proved reliable in detecting high-grade lesions. CONCLUSION: Despite the limitations of our study, our results emphasize the value of HPV-DNA testing to avoid unnecessary interventions and to establish appropriate follow-up strategies.

Flooding during the rainy season poses a significant threat to the city of Hargeisa, impacting the well-being of both its residents and the local ecosystems. This research focuses on urban flood control, with a specific emphasis on finding sustainable solutions for managing large stream in Hargeisa. The study identifies five key dimensions, including infrastructure, transportation, environmental soil, life, and property, as critical factors in addressing the issue. By employing a comparative method and collecting data through closed-ended questions, the research aims to analyze and weigh eleven potential solutions, seeking to identify the most effective approaches. The findings of the study indicate that constructing a dam emerges as a promising and sustainable solution, with a weightage of 70 percent. This highlights the potential of a dam in mitigating the impact of floods in the region. Additionally, considering the government's economic capacity, the implementation of check dams is identified as another viable option, with a weightage of 95 percent for reducing the flood power of the stream. These solutions offer practical and effective measures to address the recurring problem of flooding in Hargeisa. To support future decision-making and planning, the research underscores the need for establishing a comprehensive rainfall data database. This database would store relevant information on rainfall patterns, enabling better understanding and prediction of flood events. The study emphasizes the importance of collaboration between local government authorities, environmental organizations, and stakeholders to develop and implement effective flood control strategies. This research provides a systematic approach that can inform and benefit regional and global researchers, policymakers, and municipal governments in their efforts to address urban flood control challenges, not only in Hargeisa but also in similar contexts worldwide.

Carbon offsetting is currently a major tool in managing carbon emissions and the drive to Net-Zero. This study aims to identify the offsetting potential of existing conservation schemes, and whether carbon offsetting credits could potentially finance the continued management of the conservation activities. The results from Dorset, in the UK indicate that many existing conservation schemes in woodland, heathland and grasslands can not only enhance biodiversity but also capture significant amounts of carbon. We show that the cost per additional tonne of carbon sequestered as a result of conservation activities varies considerably between different conservation projects. On average, the cost of this offsetting is £80 per tonne CO2e sequestered and ranging between £120 and £0 depending on the project and whether existing biodiversity grants would be available. However, this figure was based on adapting and refining existing conservation projects, and did not involve expensive factors such as purchase of land, which make the prices potentially unrealistic. While the costs identified are higher than many offsetting schemes at present, it could present a useful option for those wishing to localise their offsetting, and could be combined with biodiversity credits or other credit schemes to make the higher costs more attractive.

Hepatic carboxylesterase 1(CES1) metabolizes many prodrugs into active ingredients or direct-acting drugs into inactive metabolites. We aim to develop a semi-physiologically based pharmacokinetic model(Semi-PBPK model) to simultaneously predict pharmacokinetics of CES1 substrates and their active metabolites in liver cirrhosis(LC) patients. Six prodrugs(enalapril, benazepril, cilazapril, temocapril, perindopril and oseltamivir) and three direct-acting drugs (flumazenil, pethidine and remimazolam) were selected. The parameters including organ blood flows, plasma binding protein concentrations, functional liver volume, hepatic enzymatic activity, glomerular filtration rate(GFR) and gastrointestinal transit rate were introduced into the simulation. Pharmacokinetic profiles of these drugs and their active metabolites were simulated in 100 virtual subjects. The developed semi-PBPK model, following validation in healthy subjects, was extrapolated to LC patients. Most of the observations are within the 5% and 95% quantile of simulations from 100 virtual patients. The estimated AUC and Cmax are within 0.5-2-fold of observation. The sensitivity analysis showed that the decreased plasma exposure of active metabolite due to the decreased CES1 was partly attenuated by the decreased GFR. Conclusion: The developed PBPK model has successfully predicted pharmacokinetics of CES1 substrates and their metabolites in healthy subjects and LC patients, which assists in tailoring dosages of CES1 substrates in LC patients.

Stroke remains one of the leading causes of death and disability worldwide. Current reperfusion treatments for ischaemic stroke are limited due to their narrow therapeutic window in rescuing ischaemic penumbra. Stem cell therapy offers a promising alternative. As a regenerative medicine, stem cells offer a wider range of treatment strategies, including long-term intervention for chronic patients, through the reparation and replacement of injured cells via mechanisms of differentiation and proliferation. The purpose of this review is to evaluate the therapeutic role of stem cells for ischaemic stroke. The paper discusses the pathology during acute, subacute, and chronic phases of cerebral ischaemic injury, highlights the mechanisms involved in mesenchymal, endothelial, haematopoietic, and neural stem cell-mediated cerebrovascular regeneration and evaluates the pre-clinical and clinical data concerning the safety and efficacy of stem cell-based treatments. Treatment of stroke patients with different type of stem cells appears to be safe and efficacious even at relatively higher concentrations irrespective of the route and timing of administration. Priming or preconditioning of cells prior to administration appears to help augment their therapeutic impact. However, larger patient cohorts and later phase trials are required to consolidate these findings.

The role of land surface temperature (LST) is of utmost importance in multiple academic disciplines such as climatology, hydrology, ecology, and meteorology. Until to now, many methods have been proposed to estimate LST from satellite thermal infrared data. The Thermal Infrared Sensor (IRS) on the Chinese ZY1-02E satellite is a pivotal instrument employed for gathering thermal infrared (TIR) data of land surfaces. The objective of this research is to evaluate the feasibility of a single-channel approach based on water vapor scaling (WVS) for deriving LST from ZY1-02E IRS data because of its wide spectrum range, i.e., 7~12μm, affected strongly by both atmospheric water vapor and ozone. Three study areas, namely Baotou, Heihe River Basin, and Yantai-sea sites, were selected as validation sites to evaluate the LST inversion accuracy. This evaluation was also conducted by cross-comparison between the retrieved LST and MODIS LST product. The results revealed that the WVS-based method exhibited an average bias of 0.63K and an RMSE of 1.62K compared to the in-situ LSTs. The WVS-based method demonstrated reasonable accuracy through cross-validation with the MODIS LST product, with an average bias of 0.77K and RMSE of 2.0K. These findings provide that the WVS-based method is effective to estimate LST from ZY1-02E IRS data.

This study measured secondary students’ digital literacy using a digital game-based assessment system that was designed and developed based on the Evidence-Centered Game Design (ECGD) approach. A total of 188 secondary students constituted the valid samples in this study. Fine-grained behavioral data generated from students’ gameplay processes were collected and recorded with the assessment system. The Delphi method was used to extract feature variables related to digital literacy from the process data, and the Analytic Hierarchy Process (AHP) method was used to construct the measurement model. The assessment results of the ECGD-based assessment had a high correlation with standardized test scores, which have been shown to be reliable and valid in prior large-scale assessment studies.

This article focuses on the variation of how the U.S. Circuit Court of Appeals uses the language of trauma in gender-based asylum claims. Gender-based asylum claims include female genital mu-tilation (FGM), domestic violence, forced marriage, coercive population control (CPC) in the form of forced abortions and forced sterilizations, and rape. The Circuit Courts have reviewed appeals from petitioners with asylum claims since 1946, yet the language of trauma did not appear in the Court’s decisions until 1983. From 1983-2023 only 385, 3.85% or less, of the over 10,000 asylum cases before the Circuit Courts used the language of trauma in its legal interpretation of persecution. I have identified 101 gender-based asylum cases that were reviewed by one of the eleven U.S. Circuit Court of Appeals that apply the language of trauma in its legal interpretation of persecution for this analysis. This study found that U.S. Circuit Courts use the language of trauma in four ways: precedent cases, psychological trauma, physical trauma, and policies and reports when reviewing gender-based asylum claims.

Modelling and presenting mathematical relationships for human behaviour is one of the most complex issues that researchers have always dealt with. In this article, a bottom-up framework for calculating agricultural needs is presented using the socioeconomic characteristics of farmers (such as education level, age, and dependence on income on agriculture) and how their lands are located concerning each other (interactions between neighbours). The objective function of this framework is to maximize the profit of individual farmers based on the amount of water received. Two scenarios, ABM1 (not considering neighbourhood effects) and ABM2 (all cases of farmers' placement and feeling neighbourhood effects), were investigated. In the first scenario (ABM1), there was a noteworthy reduction in water deficit volumes by approximately 35%, accompanied by a 20% increment in farmers' profits. Interestingly, higher risk-taking tendencies correlated with reduced profit margins. The second scenario (ABM2) underscored the significant role of neighborhood dynamics in cultivating diverse behavioral patterns among farmers, subsequently affecting their profitability. A granular examination revealed that farmers with a higher propensity for risk-taking generally accrued lower profits. Additionally, the study facilitated the calculation of total annual profits and average water consumption for each farmer, offering valuable insights for optimizing water resource management and allocation strategies. These findings are instrumental for planners and water resource managers aiming to promote sustainable agricultural practices and efficient water use.

The combined efect of shape and electrostatic complementarities (Sc, EC) at the interface of the interacting protein partners (PPI) serves as the physical basis for such associations and is a strong detterminant of their binding energetics. EnCPdock (https://www.scinetmol.in/EnCPdock/) presents a comprehensive web-platform for the direct conjoint comparative analyses of complementarity and binding energetics in PPIs. It elegantly interlinks the dual nature of local (Sc) and non-local complementarity (EC) in PPIs using the Complementarity Plot. It further derives an AI-based ∆G_binding with a prediction accuracy comparable to the state-of-the-art. This book-chapter presents a practical manual to conceptualize and implement EnCPdock with its various features and functionalities, collectively having the potential to serve as a valuable protein engineering tool in the design of novel protein interfaces.

Developmental hazard evaluation is an important part of assessing chemical risks during pregnancy. Toxicological outcomes from prenatal testing in pregnant animals result from complex chemical-biological interactions, and while New Approach Methods (NAMs) based on in vitro bioactivity profiles of human cells offer promising alternatives to animal testing, most of these assays lack cellular positional information, physical constraints, and regional organization of the intact embryo. Here, we engineered a fully computable model of the embryonic disc in the compucell3d.org modeling environment to simulate epithelial-mesenchymal transition of epiblast cells and self-organization of mesodermal domains (chordamesoderm, paraxial, lateral plate, posterior/extraembryonic). Cell fate in the model is determined by an autonomous homeobox (HOX) clock driven by morphogenetic signals (e.g., FGF, WNT, ATRA, CDX). Executing the model renders a quantitative cell-level computation of mesodermal subpopulations and consequences of perturbation based on known embryogeny. For example, synthetic perturbation of the control network rendered altered phenotypes (cybermorphs) mirroring experimental mouse embryology, with 50% reductions in FGF4, FGF8 and BMP4 signaling resulting in 86%, 98% and 59% reductions, respectively in the posterior mesodermal population, while ATRA exposure also resulted in a 78% decrease in this population. This model enables integration of in vitro chemical bioactivity data for specific molecular targets with known embryology to test mechanistic veracity and quantitative prediction of altered development.

In recent years the study of the teacher-student relationship in the teaching-learning processes in physical education has had great emphasis. Previous studies have shown that the use of the Spectrum of teaching Styles can enhance intrinsic motivation, enjoyment, adherence to physical activity and physical activity levels in children and adolescents. The present study aims to assess if a physical education (PE) intervention based on the variations in teaching styles, with reference to production ones, can also have positive effects on physical fitness. The sample involved 4 primary school classes (n = 124 children, mean age = 8-10 years) recruited from the SBAM (Health, Wellness, Food Education and Movement at School) Project in Apulia, Southern Italy. Classes were randomly assigned to Experimental Group (EG) and Control Group (CG). EG followed a 5months experimental intervention based on the variation of teaching styles, while CG performed regular PE lessons. Physical fitness test was assessed with Standing Long Jump (SLJ), Medicine Ball Throw 1kg (MBT), and 20m sprint (20m), while two validated questionnaires were used to evaluate physical self-perception (PSP) and enjoyment. A 2x2 (intervention group x time) ANOVA was carried out to assess significant difference and interaction effect pre (t0) and post (t1) intervention protocol. Data analysis showed a significant improvement of physical fitness in both EG and CG, while PSP and enjoyment increased only in EG. Moreover, significant interaction (p&lt;. 05) effects were found for 20m sprint, PSP and Enjoyment with low effect size (η2 ~. 20). The results of the present study highlight the effectiveness of a PE intervention based on the variation of teaching styles in improving physical fitness, self-perception, and enjoyment. Moreover, the use of production teaching styles significantly impacts self-perception and enjoyment, that are important mediating factors for guarantee better adherence to physical activity.

Recently, e-commerce companies have been adopting and continuously enhancing personalized product recommendation systems, and there is active research in this field within academia. However, personalized product recommendations in offline retail stores have not yielded significant outcomes thus far. Especially for small-format offline retail businesses like convenience stores, where customer information might be limited, providing personalized product recommendations poses even greater challenges. To address this issue, this study aimed to find a solution by shifting the perspective on recommendation methods and altering the target of recommendations in existing personalized recommendation models. In this study, recommending products that customers need in an offline store was defined as suggesting products that should be introduced and displayed within the store. In other words, the recommendation focus shifted from individuals to the stores themselves. This recommendation system proposes products that individual stores have not yet introduced but are anticipated to be purchased by customers among the products managed by the headquarters. Building upon this, we devised a store-based product recommendation system. The widely used user-based collaborative filtering model, a common technique in existing recommendation systems, was adapted into a store-based collaborative filtering model. Furthermore, various rules and logic pertinent to store operations and business considerations for convenience stores were integrated to implement this store product recommendation system. The accuracy and effectiveness of the system were demonstrated through its application in actual convenience stores. Results from the pilot implementation of the system showed that 88% of the newly recommended products in individual stores were sold based on one week of sales data, and the sales revenue was 1.75 times higher than the average sales revenue of those products across the entire company. Survey results on business owners' satisfaction yielded a score of 4.2 out of 5, indicating a high level of contentment. Additional observed effects included the expansion of product range and reduction in order lead times. However, 12% of the total recommended SKUs did not sell within one week, and 34% of the SKUs did not meet the overall average sales quantity. This research holds significance in extending the scope of personalized recommendation studies from primarily online platforms to offline retail businesses like convenience stores. It provides tangible methodologies and outcomes that can be implemented in real-world settings through the construction and validation of an actual system. The study also suggests avenues for future research to address some of the identified limitations.

Diabetes mellitus, a metabolic disorder that is persistent in nature, is identified by an elevated concentration of glucose in the bloodstream. The disease has become a major public health problem, affecting millions of people globally, and is associated with significant morbidity and mortality. The increasing prevalence of diabetes and the lack of effective therapeutic interventions have led to the exploration of alternative and complementary forms of therapy, including ethnomedicine. Ethnomedicine is the study of traditional medical systems and the medicinal plants used by Indigenous communities. In other words, Ethnomedicine refers to the traditional medical practices and beliefs of a particular cultural or ethnic group. The most popular example of traditional medicine is the use of Aloe vera for the treatment of various diseases such as sunburn, cuts, burns, hypertension, diabetes, and jaundice for thousands of years [1]. In recent years, there has been increasing interest in the potential role of ethnomedicine in the management of diabetes, given its widespread use in many communities and its potential to offer cost-effective and culturally acceptable treatment options. It encompasses a range of traditional healing practices, including herbalism, acupuncture, and massage therapy. Despite the inconsistencies, there is growing evidence to suggest that certain ethnomedical practices may be effective in the management of diabetes [2,3]. For example, several studies have shown that certain herbal remedies, such as cinnamon, ginseng, and bitter melon, may have potential benefits in terms of improving glucose control and reducing the risk of complications associated with diabetes. Evidence-based ethnomedicine is an approach that applies scientific principles and methods to evaluate the efficacy and safety of traditional medical practices. This approach is crucial in the development of effective and safe ways to treat diabetes. To date, there have been numerous studies conducted to examine the efficacy and safety of various ethnomedical interventions for diabetes, including herbal remedies, dietary changes, and physical activity [4]. However, it is important to note that not all ethnomedical interventions for diabetes have been thoroughly evaluated, and many remain unproven. Furthermore, some interventions may be associated with significant risks, particularly in terms of drug interactions and adverse effects. As such, it is crucial that any ethnomedical interventions for diabetes be carefully evaluated using rigorous scientific methods and that patients be advised to consult with their healthcare provider before using any such interventions. It is important to note that the results of these studies have been mixed, with some showing promising results, while others have failed to demonstrate significant benefits. In this chapter, the evidence-based current state of ethnomedicine for diabetes was reviewed. We first provide an overview of diabetes and its pathophysiology, followed by a discussion of traditional medicinal practices used to treat the disease. We then present a systematic review of the scientific literature on the use of ethnomedicine for diabetes, focusing on herbal remedies and dietary interventions. Our review found that several medicinal plants offered promising results to treat all types of diabetes. For example, Gymnema sylvestre, a traditional Indian herb, has been shown to reduce blood glucose levels and improve insulin sensitivity [5]. Additionally, the use of bitter melon (Momordica charantia) has been shown to reduce fasting blood glucose levels and improve glucose tolerance in individuals with type 2 diabetes [6]. Another important aspect of ethnomedicine for diabetes is the use of dietary interventions [7]. Traditional diets, such as the Mediterranean diet, have been shown to have beneficial particularly in terms of improving glycaemic control, reducing the risk of cardiovascular disease, and insulin sensitivity [8]. Additionally, the use of low-carbohydrate diets, such as the ketogenic diet, has been shown to improve glycaemic control in individuals with type 2 diabetes [9]. Traditional medicine has a long history of treating the symptoms and managing the condition. However, the efficacy and safety of these traditional practices have not always been scientifically tested, and there is a lack of standardization and regulation in the production and use of traditional remedies for diabetes. This creates a challenge for healthcare providers and patients, who need to ensure that the treatments they use are safe and effective. Additionally, there is a need for further research to understand the mechanisms by which traditional remedies may be effective in managing diabetes and to determine the optimal dosage and administration methods [9]. Finally, it is also important to understand that the use of traditional remedies may interact with conventional medications, leading to adverse effects; for example, the use of Chinese traditional medicine, known as “herb ginseng,” for the treatment of various health conditions, including diabetes sometimes cause the side effect such as dizziness, confusion, and fainting while interacting with the anti-diabetic medications [10]. Therefore, it is important to approach the use of ethnomedicine for diabetes with caution and under the guidance of a qualified healthcare professional. In conclusion, evidence-based ethnomedicine offers a promising approach to the treatment of diabetes. While further research is needed to fully understand the mechanisms and safety of these interventions, the results to date suggest that traditional remedies and dietary interventions have the potential to be effective in the management of this disease. However, it is important to approach the use of ethnomedicine for diabetes with caution and under the guidance of a qualified healthcare professional and to continue to conduct rigorous scientific research to fully understand the benefits and risks associated with these interventions.

Domestic abuse and stalking in higher education (HE) have been overlooked in research in comparison to sexual harassment and sexual violence. This article reports on survey data from 725 students at a UK university using measures of ‘dating violence’ – physical and psychological violence from an intimate partner – and stalking from a US survey instrument (the Administrator Researcher Campus Climate Collaborative (ARC3) survey). According to this measure, 26% of respondents had been subjected to ‘dating violence’ and 16% to stalking behaviours. However, these findings need to be contextualised within a critical discussion of the use of the ARC3 survey tool in the UK context. The ARC3 questions on ‘dating violence’ focus on physical and ‘psychological violence’; the questions therefore omit further types of domestic abuse under UK definitions. In relation to stalking, US definitions – as captured in the ARC3 survey instrument – define specific behaviours. By contrast, in the UK stalking involves behaviours that engender fear or distress in a pattern of behaviour over time. These differences mean that the ARC3 modules on stalking and ‘dating violence’ would need to be significantly adapted to be suitable for use in the UK context.

In order to provide a new direction for the diagnosis and treatment of gastric cancer, the differentially expressed blood-based miRNAs in gastric carcinoma were obtained and analyzed from the datasets GSE113486, GSE112264 and GSE113740 by the SangerBox, the miRNA - target genes prediction, GO and KEGG functional enrichment analyses with DAVID 6.8, and the STRING database with Cytoscape, respectively. The correlation between the key miRNAs expression and the prognosis and diagnostic value of gastric cancer patients were detected by survival prognosis and ROC curve. QRT-PCR was used to detect the possible key miRNAs expression in human blood species. The dataset GSE108307 which shows the miRNAs affected by H. pylori infection was analyzed by GEO2R. The expression level of CagA and the clinically used gastric cancer markers were detected in human blood species for contrast. Five key blood-based miRNAs were determined, including hsa-miR-124-3p, hsa-miR-125a-3p, hsa-miR-29b-3p, hsa-miR-4276, and hsa-miR-575.The detection in human blood species as well as the cross analysis with H. pylori infection and clinically used markers expression suggested the importance and efficacy of the specific miRNAs in the early diagnosis and monitoring of gastric carcinoma. The study identified potential novel blood miRNA biomarkers of gastric cancer by bioinformatics and human blood species detection, which may give a new possibility of the important biomarkers for the diagnosis and prognosis of gastric cancer.

As a radiant light source within the dynamic range of most spacecraft payloads, the moon pro-vides an excellent reference for on-orbit radiometric calibration. This research hinges on the pre-cise simulation of lunar spectral irradiances and the Earth-based Moon observation geometry. The paper leverages the Hapke model to simulate the temporal changes in lunar spectral irradi-ances, utilizing datasets obtained from Lunar Reconnaissance Orbiter Camera (LROC). The re-search also details the transformation process from the lunar geographic coordinate system to the instantaneous projection coordinate system, thereby delineating the necessary observational geometry. The insights offered by this study have the potential to enhance future in-orbit space-craft calibration procedures, thereby boosting the fidelity of data gathered from satellite obser-vations.

Prediction markets are heralded as powerful forecasting tools, but models to describe them often fail to capture the full complexity of the underlying mechanisms that drive price dynamics. To address this issue, we propose a model in which agents belong in a social network, have an opinion about the probability of a particular event to occur, and bet on the prediction market accordingly. Agents update their opinions about the event by interacting with their neighbours in the network, following the Deffuant model of opinion dynamics. Our results suggest that a simple market model that takes into account opinion formation dynamics is capable to replicate the empirical properties of historical prediction market time series, including volatility clustering and fat-tailed distribution of returns. Interestingly, the best results are obtained when there is the right level of variance in the opinions of the agents. Moreover, this paper provides a new way to indirectly validate opinion dynamics models against real data by using historical data obtained from PredictIt, an exchange platform whose data has never been used before to validate models of opinion diffusion.