More than 700 thousand human deaths from mosquito bites are observed annually in the world. It is more than 2 times the number of annual murders in the world. In this regard, the invention of new more effective methods of protection against mosquitoes is necessary. In this article for the first time, comprehensive studies of mosquito neutralization using machine vision and a 1 W power laser are considered. Developed laser installation with Raspberry Pi that changing the direction of the laser with a galvanometer. We developed a program for mosquito tracking in real. The possibility of using deep neural networks, Haar cascades, machine learning for mosquito recognition was considered. We considered in detail the classification problems of mosquitoes in images. A recommendation is given for the implementation of this device based on a microcontroller for subsequent use as part of an unmanned aerial vehicle. Any harmful insects in the fields can be used as objects for control.

In current severe global emergency situation of 2019-nCov outbreak, it is imperative to identify vulnerable and susceptible groups for effective protection and care. Recently, studies found that 2019-nCov and SARS-nCov share the same receptor, ACE2. In this study, we analyzed five large-scale bulk transcriptomic datasets of normal lung tissue and two single-cell transcriptomic datasets to investigate the disparities related to race, age, gender and smoking status in ACE2 gene expression and its distribution among cell types. We didn’t find significant disparities in ACE2 gene expression between racial groups (Asian vs Caucasian), age groups (>60 vs <60) or gender groups (male vs female). However, we observed significantly higher ACE2 gene expression in former smoker’s lung compared to non-smoker’s lung. Also, we found higher ACE2 gene expression in Asian current smokers compared to non-smokers but not in Caucasian current smokers, which may indicate an existence of gene-smoking interaction. In addition, we found that ACE2 gene is expressed in specific cell types related to smoking history and location. In bronchial epithelium, ACE2 is actively expressed in goblet cells of current smokers and club cells of non-smokers. In alveoli, ACE2 is actively expressed in remodelled AT2 cells of former smokers. Together, this study indicates that smokers especially former smokers may be more susceptible to 2019-nCov and have infection paths different with non-smokers. Thus, smoking history may provide valuable information in identifying susceptible population and standardizing treatment regimen.

The current spreading novel coronavirus SARS-CoV-2 is highly infectious and pathogenic and has attracted global attention. Recent studies have found that SARS-CoV-2 and SARS-CoV share around 80% of homology and use the same cell entry receptor, ACE2. These inspired us to study other receptors of SARS-CoV, which may be used for SARS-CoV-2 binding as well. In this study, we screened the gene expression of three receptors (ACE2, DC-SIGN and L-SIGN) in four datasets of normal lung tissue from lung adenocarcinoma patients and two single-cell RNA sequencing datasets from normal lung and bronchial epithelial cells separately. No significant difference in gene expression of these three receptors were found between gender groups (male vs female). We found higher gene expression of DC-SIGN in elder with age>60 and higher gene expression of L-SIGN in Caucasian than Asian. Similar to ACE2, we observed significantly higher DC-SIGN gene expression in the lungs of smokers, especially former smokers. However, smokers upregulate ACE2 and DC-SIGN gene expression in different cell types. In the whole lung, ACE2 is actively expressed in remodeled Alveolar Type II cells of former smokers, while DC-SIGN is largely expressed in monocytes of former smokers and dendritic cells of current smokers. In bronchial epithelium, no obvious gene expression of DC-SIGN and L-SIGN was observed while ACE2 was found to be actively expressed in goblet cells of current smokers and club cells of non-smokers. In conclusion, our findings may indicate that smokers, especially former smokers, and people over 60 have higher risk and are more susceptible to SARS-CoV-2 infection. Also, this study provides hints on possible SARS-CoV-2 pathogenicity mechanisms in lung infection.

A new lateral force-resisting wall panel is presented for applications in mid-rise prefabricated lightweight steel construction in seismic prone regions. This panelised system is composed of a hot-rolled frame and cold-formed studs and tracks, which works as a lateral force resisting system in lightweight steel framing. The proposed hybrid panel system exhibits proper ductility and energy dissipation behaviour. The hysteretic responses of full-scale panel experiments demonstrate that the system can safely resist high cyclic loads. The hot-rolled steel part, on the other hand, can significantly improve the initial lateral stiffness of the total system that will control the maximum allowable drift of multi-story buildings. Finally, in a case study, by applying the proposed system to the design of a mid-rise building in a high seismic area, the performance of the hybrid panels, are compared with those of fully hot-rolled systems (moment resisting frames) and fully cold formed systems. The findings indicate that applying hybrid panels will result in lower weights and better performance in seismic prone regions.

Background: Coronavirus disease 2019 (COVID-19) has emerged as a global threat to human health and disease risk increases with advancing age. The regulation of the ACE2 gene that codes for COVID-19 host receptor ACE2 has been shown to be under epigenetic regulation. Here, we examined whether intensive DNA methylation profiling of the ACE2 gene differed by human host tissue and cell type, gender, and age. Results: Accessing four public datasets, we observed unique human cell-type-specific ACE2 DNA methylation patterns. In human lung tissues, gender differences in DNA methylation at 2 sites related to the ACE2 gene were identified. Further, in freshly isolated airway epithelial cells, DNA methylation near the transcription start site of the ACE2 gene associated with biological age. Conclusion: Epigenetic profiling of host tissue may permit discovery of age and gender-related potential risk factors for COVID-19. How perturbations in ACE2 methylation relate to clinical severity across the ages and gender needs to be determined to guide screening tools and potential epigenetic modification targeting to alleviate COVID-19 morbidity in the elderly.

This study presents the validation process of the Questionnaire on Academic Stress in Secondary Education –QASSE-, designed to assess the wide variety of school sources and situations related to academic stress in adolescence, and their relationship with students’ physical and psychological well-being. Participants were 860 Spanish high school students (52.9% girls) with an average age of 14.62 years (SD = 1.8). Through a cross-validation process, EFA and CFA supported QASSE multifactorial structure with four first-order factors -academic overload, interaction with classmates, family pressure, and future-oriented perspective- and a second-order factor of academic stress, showing a significant and intense relationship with adolescents’ psychological and physical well-being. Results also highlight the effects of the gender*educational level interaction on the students’ stress, with girls showing higher levels of stress in the transition courses between educational phases (sophomore and junior years). The QASSE demonstrates good validity and reliability, showing potential for both research and educational application. The results show the high impact of the QASSE dimensions on psychological and physical well-being in adolescence, highlighting its special usefulness for designing and adjusting educational prevention and intervention actions in this area to the students’ specific characteristics and needs

Automatic garments design class identification for recommending the fashion trends is important nowadays because of the rapid growth of online shopping. By learning the properties of images efficiently, a machine can give better accuracy of classification. Several methods, based on Hand-Engineered feature coding exist for identifying garments design classes. But, most of the time, those methods do not help to achieve better results. Recently, Deep Convolutional Neural Networks (CNNs) have shown better performances for different object recognition. Deep CNN uses multiple levels of representation and abstraction that helps a machine to understand the types of data (images, sound, and text) more accurately. In this paper, we have applied deep CNN for identifying garments design classes. To evaluate the performances, we used two well-known CNN models AlexNet and VGGNet on two different datasets. We also propose a new CNN model based on AlexNet and found better results than existing state-of-the-art by a significant margin.

COVID-19 has affected 210 countries around the world, killed more than 240,000 and infected more than 3.4 million. Bangladesh, a South Asian low-middle-income economy, has experienced a demographic and epidemiological transition with rapid urbanization and a gradual increase in life expectancy. It is the seventh most populous country in the world and population of the country is expected to be nearly double by 2050. The increasing burden of noncommunicable diseases in Bangladesh can be attributable to rapid urbanization and nearly 50% of all slum dwellers of the country live in Dhaka division. In 2017, National Rapid Response Team of IEDCR investigated 26 incidents of disease outbreak. The joint survey of the Power and Participation Research Centre and BRAC Institute of Governance and Development reveals that per capita daily income of urban slum and rural poor drops by 80% due to present countrywide shutdown enforced by the government to halt the spread of Covid-19. 40%-50% of these population took loans to meet the daily expenses.

The consistently positive Australian economic environment and stable population increase have led to a higher demand for new houses in recent years. Prefabrication is a promising method to help alleviate the issues related to housing shortage and affordability due to reduced material wastage, construction delays due to weather conditions, unexpected costs, shortage in labour and onsite risks. With the advancements in automation and manufacturing methods such as Design for Manufacturing and Assembly (DfMA), the quality and precision of prefabricated materials is tightly controlled, and the fabrication and assembly period are reduced. However, the full potential of prefabricated construction is yet to be realised in part due to most of developments being focused on its superstructure. A review of the current available options suitable for houses is necessary to understand the present state of the residential footing industry, which will help evaluate the necessary innovations for the growth of the Australian construction industry considering the local reactive soil conditions. This paper presents a summary of existing footing systems and potential prefabricated footing solutions for low-rise residential structures with one storey to two storeys. This paper also reviews the benefits and challenges of designing, manufacturing, transporting, handling and installing of prefabricated footings on site, which have great influence on the acceptance of these innovative footing systems.

In this paper, we first discuss the research status and application progress of the finite element method and the smoothed particle method. By analyzing the advantages of the smoothed particle method and the finite element method, a new coupling algorithm, namely FEM-SPH algorithm, is proposed. By the method of comparison, it shows that finite element method and SPH method in the simulation of large deformation problems each have advantages and disadvantages, the finite element method smoothed particle coupling algorithm is effective to achieve the performance of high computational efficiency and can naturally simulate large deformation problems across. In the process of calculation, the large deformation unit can be freely into an algorithm to facilitate the calculation accuracy and efficiency of three methods of numerical simulation. Through the study found, FEM-SPH algorithm not only overcome the defect of smooth particle tensile instability, but also overcomes the problem of low efficiency of finite element computation. To further test the FEM-SPH algorithm has advantages in the practical engineering, we have carried out the actual test to the example of the super high speed collision, concluded that, since the target of most of the computational domain is always finite element, smoothed particle focused only in contact with the projectile and target of local area, particle number is not much, the whole calculation process just ten minutes, computational efficiency has been greatly improved, at the same time in the simulation of large deformation, the advantage is very obvious .This provides a criterion for the actual project, depending on the specific material deformation mode and choose a more appropriate conversion algorithm.

Migrations are much more important than currently recognised, for explaining important patterns observed in the European archaeology record – according to this archaeology led model. At a high level, they explain the introduction of different farming, monument building, the spread of metalworking and patterns of trade and exchange. This paper presents an archaeogenetic model based on a strategic review of the Neolithic and Chalcolithic archaeology of Europe, alongside a review of recently published ancient DNA data. The model is archaeology led. It takes archaeology themes and proposes migratory events to explain them. Ancient DNA data and further archaeology evidence is then used to test these proposed migrations- to reject or refine them. The model introduces a new and more strategic way of looking at archaeological cultures - that updates early 20th century approaches to studying archaeology cultures, and integrates with the detailed ‘post processual’ studies of the late 20th Century. The model consists of seven maps – each showing multiple migration events – with key evidence to support each migration map. It proposes a new category of a ‘Black Sea’ related population that makes a major genetic contribution to the Middle Neolithic of Europe. The proposed migrations provide an explanation for the observed patterns of archaeology, for example: • multiple Neolithic migrations that introduced, farming and metalworking into Europe; • a major ‘Black Sea’ related ‘Middle Neolithic’ migration that carried advanced knowledge of astronomy that can be recognised in a variety of types of monument from the Neolithic through to Bronze Age Europe; and, • migrations of related cultures (‘supercultures’) that explain patterns of trade and exchange in Bronze Age western Europe. The model also provides ancient DNA and archaeology based support for the key aspects of Childe’s ‘dawn of civilisation’ in Europe and Egypt and Gimbutas’ ‘Old Europe’ and “three waves of migration from the Steppe”.

This paper presents tea leaves moisture monitoring system based on RF reflectometry techniques. The system was divided into two parts which are the sensor and reflectometer parts. The large coaxial probe was used as a sensor of the system. The reflectometer part plays a role as signal generator and also data acquisition. The reflectometer-sensor system was operated with a graphical user interface at 1.529 GHz at room temperature. The system was able to measure the moisture content of tea leaves ranging 0% m.c to 50% m.c on a wet basis. In this study, up to five kinds of tea leaves bulk were tested. The mean of absolute errors in the moisture measurement for tea leaves was ±2.

The increasing prevalence of obesity and sedentary lifestyles has led to an increased incidence of metabolic syndrome (MetS) worldwide. In Taiwan, middle-aged women are at a greater risk of MetS, type 2 diabetes, and cardiovascular disease than men are because they have more subcutaneous fat and larger waist circumferences compared to men with equal visceral fat levels. This study investigated the effects of calorie restriction supplemented with fish oil (CRF) in middle-aged women with MetS. For 12 weeks, 75 eligible participants were randomly assigned either calorie restriction (CR) or CRF. Both dietary intervention groups were further divided into two age groups: ≤45 and >45 years. The changes in MetS severity, inflammatory status, iron status, and red blood cell fatty acid profile were evaluated. Seventy-one participants completed the trial. Both dietary interventions significantly ameliorated MetS and improved the participants’ inflammatory status. CR significantly increased total iron binding capacity, whereas CRF increased hepcidin levels. Furthermore, CRF significantly increased the n-6/n-3 and arachidonic acid/docosahexaenoic acid ratios. In conclusion, CR and CRF improved the anthropometric and MetS characteristics of early-middle aged women, including body weight, blood glucose levels, triglyceride levels, as well as the scores for the homeostasis model assessment of insulin resistance and quantitative insulin sensitivity cheque index. Dietary intervention was more effective in >45-year-old women than ≤45-year-old women.

Arabic was the language of philosophy, logic, Islamic sciences and rhetorical linguistic sciences. It was used in the writing of all sciences generally and became the language of world culture. Although the other languages of the Islamic world had a little share, but all peoples of Islamic countries; Arabs and non-Arabs, Muslims and non-Muslims attributed to that movement appreciated. Hence, Arab sciences flourished in their bright ages. Arabic language was a cultural container of the ancient Greek and Latin intellectual heritage. As the ancient Greek and Latin sciences and literatures were translated into Arabic in the bright ages of Islam. Arab language was a strong bond for them, as a common human heritage for the centuries to save it from being lost, as Muslims used it to develop their sciences and arts, as Muslims in the East used the Western sciences and literatures in the modern age, because they are not Eastern or Western, but the common efforts of all humanity. Arabic language opened for the dictionaries ​​and other tongues of cross-fertilization, civil friction and simulation. Arabic had become the language of sciences: mathematics, astronomy, engineering, logic, philosophy, mysticism, agriculture, industry and economics by the continuous efforts of scientists in their scientific research, invention, experimentation, knowledge collection and classification in various fields, where orientalists recognized the Arab leadership. That scientific and literary civilization moved to Europe through Italy, Andalusia, Crusades and the Ottoman Caliphate. Europeans learned Arabic language, literature and sciences in the centers of Toledo, Fez and cities of Maghreb.

The aim of this cross-country research is to examine how the profit and loss sharing mudarabah investment deposits are classified and disclosed in the financial statement of Islamic banks. The cross-country study examined the financial statements of fifty-one fully-fledged Islamic banks. The results of the data analysis show that Islamic banks disclose the mudarabah investment account in different ways. The absence of standardized disclosure for mudarabah investment deposit confuses the stakeholders. This research suggests to the regulators to fully or partially adopt the AAOIFI standards specifically for Islamic financial institutions.

This paper presents a thermal runaway prognosis scheme based on the big-data platform and entropy method for battery systems in electric vehicles. It can simultaneously realize the diagnosis and prognosis of thermal runaway caused by the temperature fault through monitoring battery temperature during vehicular operations. A vast quantity of real-time voltage monitoring data was collected in the National Service and Management Center for Electric Vehicles (NSMC-EV) in Beijing to verify the effectiveness of the presented method. The results show that the proposed method can accurately forecast both the time and location of the temperature fault within battery packs. Furthermore, a temperature security management strategy for thermal runaway is proposed on the basis of the Z-score approach and the abnormity coefficient is set to make real-time precaution of temperature abnormity.

Special preparation of SBA-15 materials has been carried out for creating adsorbents exhibiting an enhanced and selective adsorption toward CO2. This creation starts from an adequate conditioning of the silica surface, via a thermo-alkaline treatment to increase the population of silanol species on it. CO2 adsorption is only reasonably achieved when the SiO2 surface becomes aminated after put in contact with a solution of an amino alkoxide compound in the right solvent. Unfunctionalized and amine-functionalized substrates were characterized through X-ray diffraction, N2 sorption, Raman spectroscopy, electron microscopy, 29Si solid-state NMR, and NH3 thermal programmed desorption. These analyses proved that the thermo-alkaline procedure desilicates the substrate and eliminates the micropores (without affecting the SBA-15 capillaries), present in the original solid. NMR analysis confirms that the hydroxylated solid anchors more amino functionalizing molecules than the unhydroxylated material. The SBA-15 sample subjected to hydroxylation and amino- functionalization displays a high enthalpy of interaction, a reason why this solid is suitable for a strong deposition of CO2 but with the possibility of observing a low-pressure hysteresis phenomenon. Contrastingly, CH4 adsorption on amino-functionalized, hydroxylated SBA-15 substrates becomes almost 5 times lesser than the CO2 one, thus giving proof of their selectivity toward CO2.

Tobacco use, most people would say. Smoking tobacco increases the risk of developing many types of cancer and is responsible for approximately one-third of all cancer deaths. The association between tobacco use and lung cancer is well known; lung cancer occurs about 20 times more often in heavy smokers than in nonsmokers [1]. However, many lung cancers are diagnosed in never smokers [2], and most smokers do not develop lung cancer [3,4].

Four Fourier transforms are usually defined, the Integral Fourier transform, the Discrete-Time Fourier transform (DTFT), the Discrete Fourier transform (DFT) and the Integral Fourier transform for periodic functions. However, starting from their definitions, we show that all four Fourier transforms can be reduced to actually only one Fourier transform, the Fourier transform in the distributional sense.

Based on the demographic shift and the related challenges resulting from the growing number of elderly and persons with chronic diseases, the idea of smart home that supports its inhabitants in the daily life, gains importance. The purpose of this paper was to examine in a prototypic Ambient Assisted Living environment if users after interaction with different health-supporting applications intend to use such in the future. Two experimental studies exemplary show possible applications of home-integrated technology that can support, assist and accompany the target group in different contexts, and examine to what extent participants are willing to future use such sophisticated technology at home. The results show that people in general, but especially the old and chronically ill ones are quite fascinated of health-supporting ambient technology and the majority intends to use such ambient assistance in the future (study I). Moreover, serious games for healthcare are shown as a hedonic use of technology in smart homes that have a great potential to retain or improve the physical health, mobility and the overall well-being of the inhabitants (study II). The article provides two examples of ambient technology to leverage the demographic change and presents important user factors for facilitating high user acceptance.

This review paper gives Excel functions for highly precise Colebrook’s pipe flow friction approximations developed by users. All shown codes are implemented as User Defined Functions – UDFs written in Visual Basic for Applications – VBA, a common programming language for MS Excel spreadsheet solver. Accuracy of the friction factor computed using nine to date the most accurate explicit approximations is compared with the sufficiently accurate solution obtained through an iterative scheme which gives satisfying results after sufficient number of iterations. The codes are given for the presented approximations, for the used iterative scheme and for the Colebrook equation expressed through the Lambert W-function (including its cognate Wright ω-function). The developed code for the principal branch of the Lambert W-function has additional and more general application for solving different problems from variety branches of engineering and physics. The approach from this review paper automates computational processes and speeds up manual tasks.

The philosophy of testing statistical hypothesis is a natural consequence and functional extension of mathematical analysis of Probability. Along with the concept of recurrence when applied to random sequences and functions, it leads to the analysis of a priori and posterior which implies testing statistical hypothesis. Testing statistical hypothesis also involves algebraic, functional and dimensional considerations, which are found in the works of Laplace. Aspects of mathematical analysis such as universality of solutions, Laws of Large Numbers, Entropy, Information, and various functional dependencies are the main factors explained in the five properties that lead to implication of testing statistical hypothesis. Various interesting examples with modern scientific significance from genetics, astrophysics, and other areas give methodological access to answers of different problems and phenomena which are involved in the logic of testing statistical hypothesis.

A text obtained by a Large Language Model (LLM) such as GPT4 usually has issues in terms of incorrectness and hallucinations. We build a fact-checking system 'Truth-O-Meter' which identifies wrong facts, comparing the generation results with the web and other sources of information, and suggests corrections. Text mining and web mining techniques are leveraged to identify correct corresponding sentences; also, the syntactic and semantic generalization procedure adopted to the content improvement task. To handle inconsistent sources while fact-checking, we rely on an argumentation analysis in the form of defeasible logic programming. We compare our fact checking engine with competitive approach based on reinforcement learning on top of LLM or token-based hallucination detection. It is observed that LLM content can be substantially improved for factual correctness and meaningfulness.

Age-related diseases (ARDs) are the leading cause of death worldwide, and contribute to 90% of mortality in developed countries. Interestingly, the mortality rates of individual ARDs increase exponentially with age. Processes described by the exponential growth function typically involve a branching chain reaction or, more generally, a positive feedback loop. Here I propose that each ARD is mediated by one or several positive feedback loops (vicious cycles). I then identify critical vicious cycles in five major ARDs: atherosclerosis, hypertension, diabetes, Alzheimer’s and Parkinson’s. I also propose that the progression of ARDs can be halted by selectively interrupting the vicious cycles and suggest the most promising targets. An evolutionary perspective is also offered.

In recent years, the rise of advanced artificial intelligence technologies has had a profound impact on many fields, including education and research. One such technology is ChatGPT, a powerful large language model developed by OpenAI. This technology offers exciting opportunities for students and educators, including personalized feedback, increased accessibility, interactive conversations, lesson preparation, evaluation, and new ways to teach complex concepts. However, ChatGPT poses different threats to the traditional education and research system, including the possibility of cheating on online exams, human-like text generation, diminished critical thinking skills, and difficulties in evaluating information generated by ChatGPT. This study explores potential opportunities and threats that ChatGPT poses to overall education from the perspective of students and educators. Furthermore, for programming learning, we explore how ChatGPT helps students improve their programming skills. To demonstrate this, we conducted different coding-related experiments with ChatGPT, including code generation from problem descriptions, pseudocode generation of algorithms from texts, and code correction. We also verified the generated codes with an online judge system to evaluate their accuracy.

The main foundations of the standard $\Lambda $CDM model of cosmology are that: 1) The redshifts of the galaxies are due to the expansion of the Universe plus peculiar motions; 2) The cosmic microwave background radiation and its anisotropies derive from the high energy primordial Universe when matter and radiation became decoupled; 3) The abundance pattern of the light elements is explained in terms of primordial nucleosynthesis; and 4) The formation and evolution of galaxies can be explained only in terms of gravitation within a inflation+dark matter+dark energy scenario. Numerous tests have been carried out on these ideas and, although the standard model works pretty well in fitting many observations, there are also many data that present apparent caveats to be understood with it. In this paper, I offer a review of these tests and problems, as well as some examples of alternative models.

This paper presents ROSGPT, an innovative concept that harnesses the capabilities of large language models (LLMs) to significantly advance human-robot interaction. We develop ROSGPT as a ROS2 package that seamlessly integrates ChatGPT with ROS2-based robotic systems. The core idea is to leverage prompt engineering with LLMs, specifically ChatGPT, utilizing its unique properties such as ability eliciting, chain-of-thought, and instruction tuning. The concept employs ontology development to convert unstructured natural language commands into structured robotic instructions specific to the application context through prompt engineering. We capitalize on LLMs' zero-shots and few-shots learning capabilities by eliciting \textit{structured} robotic commands from \textit{unstructured} human language inputs. To demonstrate the feasibility of this concept, we implemented a proof-of-concept that integrates ChatGPT with ROS2, showcasing the transformation of human language instructions into spatial navigation commands for a ROS2-enabled robot. This versatile concept can be easily adapted to various other robotic missions. ROSGPT serves as a new stride towards Artificial General Intelligence (AGI) and paves the way for the robotics and natural language processing communities to collaborate in creating novel, intuitive human-robot interactions. The open-source implementation of ROSGPT on ROS 2 is available on GitHub.

When we talk about the Defence Industry (DI), arms transfers, and military expenditures we mostly refer to data accumulated by the Stockholm International Peace Research Institute (SIPRI). In the SIPRI Top 20 list of largest exporters of major arms for 2019, small states hold consecutive positions: Israel takes 8th place, Switzerland is 13th, and Sweden, Norway, and Belarus place 15th, 17th, and 20th respectively. The author analyses the Swiss DI case due to several reasons; its place in SIPRI Top, its sharp rise of Swiss arms exports in the recent year, its Swiss neutrality strategy, the country’s multilingual society, and its all-government approach to the arms industry, though still contributing to the limited scholarly studies on contemporary Swiss DI. This paper aims to explore Swiss DI and its strategies, to identify the country’s defence and security policy influence towards DI, and to discuss the Swiss DI stance and future perspectives in the context of the global arms trade. At the same time, this paper also highlights Swiss DI successes and failures that could be of significant use to other small states aiming to develop or enhance their relevant DIs.

Work has begun in earnest to formulate a post-2020 Global Biodiversity Framework which will outline the vision and targets for the next decade of biodiversity conservation and beyond. However, the performance of the 2011-2020 Strategic Plan for Biodiversity suggests that even a meaningful target can fail to deliver if not accompanied by fit-for-purpose indicators. Here we provide a review of how ‘protected area’ effectiveness was addressed in the 2011-2020 plan and based on this, provide recommendations for fit-for-purpose indicators that will measure how such efforts contribute to the conservation of biodiversity. Indicators need to be built on quantitative data from site-level biodiversity monitoring of species and ecosystems combined with measurements of the state of nature in near-time, informed by remote-sensed products and other technologies. Additionally, indicators need to capture whether the essential elements of good management are in place including the identification of ecological values, threats, and objectives, equitable governance, and sufficient management resources and capacity. These fit-for-purpose indicators will require multilateral collaboration to galvanize support for, and resources to develop, the necessary infrastructure to collate and store information from countries.

Three-dimensional convolutional neural networks (3D CNN) as a type of artificial intelligence (AI) are powerful in image processing and recognition using deep learning to perform generative and descriptive tasks. The advantage of CNN compared to its predecessors is that it automatically detects the important features without any human supervision. 3D CNN are used to extract features in three dimensions where input is a 3D volume or a sequence of 2D pictures e.g., slices in a cone-beam computer tomography scan (CBCT). The main aim of this article was to bridge interdisciplinary cooperation between forensic medical experts and deep learning engineers. With emphasis activating clinical forensic experts in the field with possibly basic knowledge of advanced artificial intelligence techniques with interest in its implementation in their efforts to advance the forensic research further. This paper introduces a novel workflow of 3D CNN analysis of full-head CBCT scans. Authors explore and present 3D CNN method for forensic research design concept in five perspectives: (1) sex determination, (2) biological age estimation, (3) 3D cephalometric landmark annotation, (4) growth vectors prediction, (5) facial soft-tissue estimation from the skull and vice versa. In conclusion, 3D CNN application can be a watershed moment in forensic medicine, leading to unprecedented improvement of forensic analysis workflows based on 3D neural networks.

We consider the financial planning problem of a retiree wishing to enter a retirement village at a future uncertain date. The date of entry is determined by the retiree's utility and bequest maximisation problem within the context of uncertain future health states. In addition, the retiree must choose optimal consumption, investment, bequest and purchase of insurance products prior to her full annuitisation on entry to the retirement village. A hyperbolic absolute risk-aversion (HARA) utility function is used to allow necessary consumption for basic living and medical costs. The retirement village will typically require an initial deposit upon entry. This threshold wealth requirement leads to exercising the replication of an American put option at the uncertain stopping time. From our numerical results, active insurance and annuity markets are shown to be a critical aspect in retirement planning.

Studies on the gait's parameters have been identified on the patients population. Most researchers confirm that the patients walk differently than normal people and they may have a risk for falls. Consistent finding and description of gender, age, and body mass index differences in gait studies is rare in healthy subjects. A cross-sectional study with forty-five young adult (F = 20, M = 25) was conducted. Stadiometer and Physilog 4 inertial sensors were used for data collection. A gait analyser 5.2 software (GaitUp, S.A. Lausanne, Switzerland) was used to determine spatiotemporal parameters. No statistically significant differences were found in any bilateral foot gait parameters with respect to gender, age, and body mass index. Females are found with higher total double support and cadence than males. Cadence also increases with age. Obese people showed lower gait speed, cadence, and total double support. These findings may be beneficial to those who have abnormal gait pattern due to age, body mass index differences, decreased muscle strength, spasticity, and joint mobility. This important informations should be considered to rehabilitate patients with abnormal gait patterns to controlling dynamic balance and riks to falling.

Artificial Intelligence (AI) play an important role in many fields, including medical education, practice, and research. Many medical educators started using ChatGPT at the end of 2022 for many purposes. The aim of this article was to explore the potential uses, benefits and risks of using ChatGPT in integrated pharmacotherapy of infectious disease module education. This study was an experimental study with content analysis of the potential applications of the ChatGPT model for integrated pharmacotherapy of infectious diseases module education was performed. The findings of this study shows that there are many potential uses, benefits and risks associated with the use ChatGPT. In conclusion, medical and health sciences educators can use ChatGPT as a guide in many aspects related to the integrated pharmacotherapy of infectious disease curriculum development, syllabus design, lecture notes preparation and exam preparation with caution.

This paper deals with an analysis of cartographical studies, the real estate cadastre, and its practical implementation, as well as the introduction of cartography into different education modules in university-level studies in Montenegro. There is a discussion of the development, production, and creativity in the fields of cartography and real estate cadastre over time, cartographical projection, scientific results, and recent changes such as advanced computer- and satellite-based technologies, GIS, cartographical visualization, and digital cartography. The impact of these changes on cartographical studies at the University of Montenegro is considered. Particular attention is given to analyses of cartography and the cadastre in institutions, and their connection with the development of cartography teaching modules of Geography, Geodesy and Geoinformatics at the University of Montenegro. The integrated analysis also covers the results of the questionnaire and the significance of the geo-topographical and cartographical heritage of Montenegro, with the aim of carrying these out. It can be seen that the tasks solved by using maps have tended to become more complex and that the cartographical methods employed in this have been always directed towards Montenegro’s most prominent and most urgent problems, including those that appear in the area of education.

One mechanism by which fructose could exert deleterious effect in metabolism and inflammation is via its potency vis-à-vis de Maillard reaction. We employed simulated stomach and duodenum digestion of ovalbumin to test the hypothesis that indeed AGEs are formed by fructose during simulated digestion of an ubiquitous food protein with intrinsic allergenic potential and under model physiological conditions. Methods: OVA was subjected to simulated gastric and intestinal digestion using standard models, in presence of fructose or glucose (0-100 mM). Peptide fractions were analyzed by fluorescence spectroscopy and intensity at Excitation: λ370 nm, Emission: λ 440nm. Results: AGE adducts form between fructose and OVA which can be found in peptide fractions (< 5 kDa) at times (30 min) and concentration ranges (10 mM) plausibly found in the intestines, whereas no reaction occurs with glucose. The reaction is inhibited by chlorogenic acid at concentrations compatible with those found in the gut. The reaction is inhibited by AG, a specific antiglycation agent. Conclusion: Our proof of principle study shows that fructose-AGE formation on an ubiquitous allergenic protein indeed occurs in one hour and thereby may pave the way for the study of yet another mechanism by which the excess fructose in our Western diets is contributing to disease: intestinal AGE formation, absorption and RAGE engagement.

In the context of the increasing migration into Germany that has taken place in recent years and German efforts to establish an inclusive school system, which enables learners from different religious, ethnic, language and social backgrounds with and without disabilities to participate, religious education has become a key topic for interdisciplinary discourse between theology, philosophy, and pedagogy in German schools. The following questions are of special interest: How can we manage diversity in inclusive classroom settings in general, and specifically: how can we do so with regard to worldview diversity? Does worldview diversity in schools exist, and if so, how can we recognize it in its plurality and complexity? How can we acknowledge different worldviews in the context of a changing inclusive school system? In this article, we would like to present the theoretical foundation, the research setting and the first findings of our ongoing pilot studies of worldview education at an inclusive German school. The experiments are part of a larger project context that is also described. The case study presented in this article, in which innovative language and machine learning technology was used for data analysis, illustrates the potential of inclusive methods and didactic concepts such as Universal Design for Learning [1], Learning in the Presence of the Other [2,3] and Reflexive Inclusion [4] for inclusive worldview education in the context of a religiously pluralized and secularized society.

The computing power of smartphones has not received considerable attention in the mainstream education system. Most of the education-oriented smartphone applications (apps) are limited to general purpose services like Massive Open Online Courses (MOOCs), language learning, and calculators (performing basic mathematical calculations). Greater potential of smartphones lies in educators and researchers developing their customized apps for learners in highly specific domains. In line with this, we present Fluid Dynamics, a highly accurate Android application for measuring flow properties in compressible flows. This app can determine properties across the stationary normal and oblique shock, moving normal shock and across Prandtl $-$ Meyer expansion fan. This app can also measure isentropic flows, Fanno flows, and Rayleigh flows. The functionality of this app is also extended to calculate properties in the atmosphere by assuming the International Standard Atmosphere (ISA) relations and also flows across the Pitot tube. Such measurements are complicated and time-consuming since the relations are implicit and hence require the use of numerical methods, which give rise to repetitive calculations. The app is an efficient semi-implicit solver for gas dynamics formulations and uses underlying numerical methods for the computations in a graphical user interface (GUI), thereby easing and quickening the learning of concerned users. The app is designed for the Android operating system, the most ubiquitous and capable surveillance platform, and its calculations are based on JAVA based code methodology. In order to check its accuracy, the app's results are validated against the existing data given in the literature.

The paper presents the design and the implementation of different advanced control strategies that are applied to a nonlinear model of a thermal unit. A data–driven grey–box identification approach provided the physically meaningful nonlinear continuous–time model, which represents the benchmark exploited in this work. The control problem of this thermal unit is important since it constitutes the key element of passive air conditioning systems. The advanced control schemes analysed in this paper are used to regulate the outflow air temperature of the thermal unit by exploiting the inflow air speed, whilst the inflow air temperature is considered as an external disturbance. The reliability and robustness issues of the suggested control methodologies are verified with a Monte–Carlo analysis for simulating modelling uncertainty, disturbance and measurement errors. The achieved results serve to demonstrate the effectiveness and the viable application the suggested control solutions to air conditioning systems. The benchmark model represents one of the key issues of this study, which is exploited for benchmarking different model–based and data–driven advanced control methodologies through extensive simulations. Moreover, this work highlights the main features of the proposed control schemes, while providing practitioners and heating, ventilating and air conditioning engineers with tools to design robust control strategies for air conditioning systems.

The effective dissemination and implementation of health service interventions into practice requires a range of strategic and systematic approaches. This paper applies a conceptual implementation framework to the evaluation of a hospital-wide clinical pharmacy initiative, a redesign of the discharge medication prescription pathway. The influencing factors and strategies used to overcome potential negative influences are described and assessed.

Digital technologies have changed the way supply chain operations are structured. In this article, we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks. A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0, with a specific focus on the mitigation of cyber risks. An analytical framework is presented, based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies. This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning (AI/ML) and real-time intelligence for predictive cyber risk analytics. The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge. This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when AI/ML technologies are migrated to the periphery of IoT networks.

Early reports demonstrated the presence of cells with stem-like properties in bone marrow, with these cells having both hematopoietic and mesenchymal lineages. Over the years, various investigations have purified and characterized mesenchymal stromal/stem cells (MSCs) from different human tissues as cells with multi-lineage differentiation potential under the appropriate conditions. Due to their appealing characteristics and potential, MSCs are leveraged in many applications including medicine, oncology, bioprinting and as recent as treatment of COVID-19. To date, reports indicate mesenchymal stromal/stem cells have varied differentiation capabilities into different cell types and demonstrate immunomodulating and anti-inflammatory properties. Reports indicate that different MSCs microenvironments or niche and the resulting heterogeneity may influence their behavior and differentiation capacity. The potential clinical applications of mesenchymal stromal/stem cells have led to an avalanche of research reports on their properties and hundreds of clinical trials being undertaken. The future looks bright and promising for mesenchymal stem cell research with many clinical trials under way to prove their utility in many applications and in the clinic. This report provides an update on the potential broader use of mesenchymal stromal/stem cells, review early observations of the presence of these cells in the bone marrow and their magnificent differentiation capabilities and immunomodulation.

Smart grid software interconnects multiple Engineering disciplines (power systems, communication, software and hardware technology, instrumentation, big data, etc.). The software architecture is an evolving concept in smart grid systems in which systematic architecture development is a challenging process. The architecture has to realize the complex legacy power grid systems and cope up with current Information and Communication Technologies (ICT). The distributed generation in smart grid environment expects the software architecture to be distributed and to enable local control. Smart grid architecture should also be modular, flexible and adaptable to technology upgrades. In this paper, the authors have made a comprehensive review on architecture for smart grids. An in depth analysis of layered and agent based architectures is presented and compared under various domains.

Organizational diagnosis (OD) is a comprehensive review of an organization's objectives, re-source allocation, and utilization to achieve those objectives. This study employed OD to en-hance the effectiveness of the Department of Special Education within the Government of Punjab. A questionnaire based on Weisbord's six-box organizational model called the Organ-izational Diagnostic Questionnaire (ODQ), was administered to N=1200 participants, consist-ing of heads of top, middle, and bottom tiers at district and tehsil levels of special education schools, centers, and the main office. Out of these, 506 participants voluntarily completed the ODQ survey. The study findings indicated that the employees of the department possess a good understanding of the organization's objectives. However, there is a lack of opportunities for employee participation in departmental discussions, centralized decision-making, irra-tional task distribution, and unsupportive allocation of human resources. Additionally, there is poor communication, unsatisfactory promotions, incentives, and a lack of knowledge shar-ing among employees, as well as poor inter-relationships, conflicts, and ineffective help-seeking mechanisms. The study also revealed low readiness for change in the organization. Respondents' opinions differed significantly based on their qualifications, job experience, years served, and gender. To improve the department's capacity to absorb change, the study recommends enhancing collaboration and inter-departmental communication, soliciting comprehensive input from all tiers, and promoting employee participation, supportive supervision, and communication. The study contributes to the body of knowledge on OD and highlights the need for improved communication, collaboration, and employee participation, as well as a supportive and supervisory support system to enhance the effectiveness of organizations.

Since the 21st century, China's urbanization process has been rapid development, the concept and function of urban public space in the city has been gradually paid attention to. In order to guarantee life and water, most urban construction relies on rivers, and Bridges are the most important way to communicate between urban areas. The main functional part of the bridge is the span structure, that is, the bearing structure of the bridge, and the lower part of the "gray" space formed by the bridge structure. Considering the social level, with the economic growth and urbanization development, people have brought a better living environment and quality of life, and also improved the requirements for urban public environment. In the increasingly tense urban space, how to use and transform the space under the bridge is a problem that needs to be considered and solved. In view of this problem, in this study, we try to solve the micro-transformation of space under Bridges in cities through public art from the perspective of "regional culture" and "art for all". This paper analyzes the micro-transformation of space art under Bridges in two large cities of Shanghai and Foshan, namely, the space under Bridges under Songhong Road in Shanghai, the space under Bridges under Central Of Suzhou River and the space under Bridges under Pingsheng Bridge in Foshan. This paper discusses the cultural intervention of "regional culture" in the micro-transformation of the space under the bridge, and the influence and effect of "art for all" on the public art space under the bridge after the transformation to the community and the public.

: Nanotechnology options to road surface maintenance offers several advantages compared to traditionally used materials. The small particle sizer of hydrophobic Nano-Silane modified Nano-Polymers (NSNP) enables these nanotechnology products to deeply penetrate existing road surfaces, sealing micro-cracks and render surfacings to be water-resistant for extended periods of time. In comparison, traditionally used products contain minimum partial sizes of about 1 – 5 microns, that provide a superficial protection that wears off in a relatively short period of time. These traditional products are often associated with vehicle contamination while drying and requires the re-instatement of road markings. None of these disadvantages are associated with applicable NSNP technologies that are quick drying, with no vehicle contamination risks and is equivalent to a “clear-seal” requiring no reinstatement of road markings. In a similar vein, pot-hole repairs can be done using applicable, easy to use, pre-packed and treated pot-hole repair kits that are water-repellent and quick-drying at a fraction of the costs of conventional cold-mix products. Resurfacing using NME binder slurries can be done labour-intensively on a pre-treated NSNP surfacing, restoring cracked surfacing and providing a water-resistant long-lasting protective layer without the removal of existing cracked areas. The implementation of nanotechnology solutions for road surface maintenance operations is directly associated with ease of use, labour-intensive operations, prevention of considerable deterioration in riding quality due to removal and manual re-instatement of cracked surfaces, time and cost savings and a reduction in the risk of water damage to the sub-structure. TRANSLATE with x English ArabicHebrewPolish BulgarianHindiPortuguese CatalanHmong DawRomanian Chinese SimplifiedHungarianRussian Chinese TraditionalIndonesianSlovak CzechItalianSlovenian DanishJapaneseSpanish DutchKlingonSwedish EnglishKoreanThai EstonianLatvianTurkish FinnishLithuanianUkrainian FrenchMalayUrdu GermanMalteseVietnamese GreekNorwegianWelsh Haitian CreolePersian TRANSLATE with COPY THE URL BELOW Back EMBED THE SNIPPET BELOW IN YOUR SITE Enable collaborative features and customize widget: Bing Webmaster Portal Back TRANSLATE with x English ArabicHebrewPolish BulgarianHindiPortuguese CatalanHmong DawRomanian Chinese SimplifiedHungarianRussian Chinese TraditionalIndonesianSlovak CzechItalianSlovenian DanishJapaneseSpanish DutchKlingonSwedish EnglishKoreanThai EstonianLatvianTurkish FinnishLithuanianUkrainian FrenchMalayUrdu GermanMalteseVietnamese GreekNorwegianWelsh Haitian CreolePersian TRANSLATE with COPY THE URL BELOW Back EMBED THE SNIPPET BELOW IN YOUR SITE Enable collaborative features and customize widget: Bing Webmaster Portal Back

Artificial Intelligence innovations, such as chatbots and specialized education suggestion tools, provide potential interactive and on-demand pedagogical engagement between non-Christians and Christians with Christianity. However, there is little empirical research on the readiness, acceptance, and adoption of A.I.'s involvement in religious education in a secular state, such as Vietnam. This research addresses the literature gap by providing an entrepreneurial analysis and customer perspectives on the ideas of A.I.'s involvement in religious education. Specifically, the study explores whether the Vietnamese across different ages and religious orientations accept and have enough skills to adopt A.I.'s religious education innovation. The interview sample is 32 participants, selected based on their religious orientation (Christians & Non-Christians) and age (Generation X, Generation Y & Generation Z). Most respondents are open to A.I. application in religious education except for the Church's personnel. However, only gen Z generations are fully prepared to adopt this innovation. Theoretically, the research customizes the Unified Theory of Acceptance and Use of Technology model into religious innovation context. Practically, this research acts as market research on the demand for A.I.'s religious innovation in Vietnam, an insight for future religious tech entrepreneurs.

Although ladybirds of European Russia and the Caucasus have been the subject of numerous ecological and faunistic investigations, there is an evident lack of appropriate identification key for them. All previous keys have been published in Russian. The most modern key was published more than 50 years ago and included only about 60 % of species. Guides for identification of Coccinellidae of other countries are not appropriate for European Russia, since do not include many species occurring in the regions. New, original key to subfamilies, genera, and species of ladybirds (Coccinellidae) of the European Russia and Russian Caucasus is presented. All native species recorded in the region and all alien species introduced to this region are included. Some species from the adjacent regions are added. In total, 110 species are keyed and illustrated with line drawings. Photographs of rare and endemic species are provided. Information on the distribution of species within the region under consideration is provided. Synonymy of Chilocorus kuwanae with Ch. renipustulatus is presented and discussed.

This paper evaluates the feasibility of applying Massive MIMO to tackle the uplink mixed-service communication problem. Under the assumption of an available physical narrowband shared channel (PNSCH), devised to exclusively consume data traffic from Machine Type Communications (MTC) devices, the capacity (i:e:, number of connected devices) of MTC networks and, in turn, that of the whole system, can be increased by clustering such devices and letting each cluster share the same time-frequency physical resource blocks. Following this research line, we study the possibility of employing sub-optimal linear detectors to the problem and present a simple and practical channel estimator that works without previous knowledge of the large-scale channel coefficients. Our simulation results suggest that the proposed channel estimator performs asymptotically as well as the MMSE estimator with respect to the number of antennas and the uplink transmission power. Furthermore, the results also indicate that, as the number of antennas is made progressively larger, the performance of sub-optimal linear detection methods approaches the perfect interference-cancellation bound. The findings presented in this paper shed light on and motivate for new and exciting research lines towards a better understanding of the use of massive MIMO in MTC networks.

In the oil palm industry, stands age is an important parameter to monitor the sustainability of cultivation, to develop the growth yield model, to identify the disease or stressed area, and to estimate the carbon storage capacity. This research is focused to estimate and distinguish oil palm stands age based on crown/ canopy density obtained using Forest Canopy Density (FCD) model derived from four indices as follows; Advanced Vegetation Index, Bare Soil Index, Shadow Index, and Thermal Index. FCD model employs multi temporal image analysis resulting four classes of oil palm stands age categorized as seed with FCD value of 29–56% (0 years), young with FCD value of 56–63% (1–9 years), teen with FCD value of 63–80% (10–15 years), and mature with FCD value of >80% (>15 years). Minimum canopy density value is 29% even in the zero years old indicates incomplete land clearance or the type of seed planted in the land.

Besides the Lagrangian and the Eulerian descriptions, the motion of a body can also be expressed relative to the present configuration of the body, known as the relative motion description. It is interesting to consider such a relative motion description in general to formulate the basic system of field equations for solid bodies. In doing so, when the time increment from the present state is small enough, the nonlinear constitutive equations can be linearized relative to the present state so that the resulting system becomes linear. This will be done for thermoelastic materials with a brief comment on the exploitation of entropy principle in general. Relative Lagrangian formulation is based on the well-known ``small-on-large'' idea, and can be implemented for solving problems with large deformation in successive incremental manner. Some applications of such a formulation in numerical simulations are briefly reviewed.

Sulfotransferases (SULTs) family plays a significant role in the biotransformation of a variety of xenobiotics and endogenous compounds by which carcinogenesis and mutagenicity of different malignancies are increasingly affected. Recent data identified various genetically polymorphic SULTs enzymes with significant variations in the enzyme activity. This study aimed to investigate the impact of SULT1A1 gene polymorphism and and its potential risk on females with breast cancer in Jordan using a PCR-RFLP and Sanger Sequencing methods. The analysis showed that 24.7% of the patients and 25.3% of the controls were homozygous for the SULT1A1*1 allele (SULT1A1*1/SULT1A1*1) compared to 8.8% and 5.7% homozygous for the SULT1A1*2 allele (SULT1A1*2/SULT1A1*2) for patients and controls respectively. Most of the patients and controls were heterozygous for SULT1A1*1 allele (SULT1A1*1/SULT1A1*2) with rates of 66.5% and 69.0% in patients and controls respectively. In addition, the frequencies of the mutant SULT1A1*2 allele were 0.42 and 0.4 in the patient and control groups respectively. No significant difference in genotype and allele distribution was noted between the breast cancer and control groups. The risk of breast cancer in individuals carrying the SULT1A1*2 allele was determined by combining the SULT1A1*1/SULT1A1*2 and ULT1A1*2/SULT1A1*2 genotypes. No association was observed between SULT1A1 polymorphism and breast cancer incidence (P = 0.63; OR, 0.93; 95% CI, 0.68–1.26). However, SULT1A1*2 allele was found to increase the risk of breast cancer by 1.26-fold.

In this paper I analyze the three plays produced during the inaugural season (2011) of the Theatre for Young Audiences Research Center of the National Theater Company of Korea and place it within the context of contemporary ideas and realities surrounding Korean youth. In the first part of this paper I explore how Korean youth are perceived by society and the reality in which they live. In the second part I analyze the aforementioned plays, especially through the directions of the production and portrayal of adult and young characters. The last part offers concluding thoughts. Through this study I ask the question of whether if it is possible for theatre to actually portray the realities of adolescents, when in fact the identities of youth are still fluid and the experiences of youth as diverse as those of adults. I suggest that theatre artists break free to depict reality or educate audiences and focus on providing a critical experience to adolescents.

Phospholipid fatty acids (PLFAs) can be used as biomarkers for qualitative and quantitative analyses of soil microbial community diversity. In this study, we collected soil samples at 10-cm intervals to a depth of 1 m from Robinia pseudoacacia plantations of four different ages (10, 15, 25 and 40 years) in a loess area and analysed the soil microbial community structure by PLFA analysis. A total of 97 PLFAs were detected in soils of R. pseudoacacia plantations of different ages. The individual PLFA contents gradually decreased in the 0- to 40-cm soil layers, with little variation in the 40- to 100-cm soil layers. The individual PLFAs were similarly distributed in the soils of R. pseudoacacia plantations of different ages, and there was a clear variation with stand age and soil depth. The individual PLFA contents in the 0- to 20-cm soil layers were highest for the 25-year-old plantation, while those in the 20- to 40-cm soil layers were relatively high for the 25- and 40-year-old plantations; the 16:0 content was the highest among individual PLFAs. The total PLFA content and the PLFA contents of different microbial groups [bacteria, fungi, Gram-positive bacteria (G⁺), Gram-negative bacteria (G^-) and actinomycetes] initially increased before decreasing in the soils of R. pseudoacacia plantations with increasing stand age, whereas these contents gradually decreased with increasing soil depth; the highest PLFA contents was found in the 25-year-old plantation. The total PLFA content and the contents of fungal, G^- and actinomycete PLFAs in the soils of R. pseudoacacia plantations differed significantly among stands of different ages in the 0- to 10-cm, 10- to 20-cm and 30- to 40-cm soil layers, while no significant differences were found in the 20- to 30-cm soil layers; the G⁺ and bacterial PLFAs contents in each of the 0- to 40-cm soil layers were significantly different. The PLFA ratios between different microbial groups differed among the stands of different ages. The fungi/bacteria ratio showed a “decrease-increase-decrease” trend with stand age, while the G⁺/G^- ratio showed an “increase-decrease” trend. The saturated/monounsaturated PLFA ratio initially decreased before plateauing, while the opposite trend was observed for the cyclopropyl/precursor ratio. The PLFA contents of different microbial groups were ranked as follows: bacteria > G^- > G⁺ > actinomycetes > fungi. In the principle component analysis, 18:1ω9c, 10Me18:0, i17:0, a17:0, 18:1ω7c, 18:1ω5c and 18:0 made the greatest contribution to principal component 1, and a14:0, i14:0 3OH, i14:0, i14:1ω7c and 14:0 made the greatest contribution to principal component 2. In conclusion, soil nutrient status and other soil eco-environmental stress factors should be considered in 10- to 25-year-old (particularly ~15-year-old) plots for the management of R. pseudoacacia plantations to prevent forest soil degradation and improve forest stand quality, thereby achieving better soil and water conservation and environmental improvement in R. pseudoacacia plantations.

Two extreme wind-driven wildfire events impacted northern and southern California in late 2017 leading to 46 fatalities and thousands of structures lost. This study describes the meteorological and climatological factors that drove and enabled these wildfire events and quantifies the rarity of such conditions over the observational record. Both extreme wildfire events featured fire-weather metrics that were unprecedented in the observational record in addition to a sequence of climatic conditions that preconditioned fuels. The North Bay fires that affected portions of northern California in early October occurred coincident with strong downslope winds. The vast majority of the fires’ devastating effects and acres burned occurred overnight and within the first twelve hours of ignition. By contrast, the southern California fires of December were characterized by the longest Santa Ana wind event on record and included the largest wildfire in California’s history. Both fire events occurred following an exceptionally wet winter that was preceded by the drought of record in California. Fuels were further preconditioned as the warmest summer and autumn on record occurred in northern and southern California, respectively. Accelerated curing of fuels coupled with the delayed onset of autumn precipitation allowed for critically low dead fuel moisture leading up to the foehn wind events. Fire weather conditions were well forecasted several days prior to the fire. However, the rarity of fire-weather conditions that occurred in the wildland urban interface, along with other societal factors were key contributors to wildfire impacts to communities.

Modern language models are designed to generate text so realistic that it could easily be mistaken for human-authored content. Additionally, they can engage in conversations with humans in a manner that appears coherent and reasonable. The epitome of this technological advancement is ChatGPT, a model based on OpenAI's Generative Pretrained Transformer (GPT) language model. With its ability to produce high-quality content in mere seconds, ChatGPT surpasses other chatbots in terms of capabilities, drawing significant interest and excitement from both the business community and academic researchers. This study offers a comprehensive review of current research on ChatGPT, delving into its technological foundation, supportive mechanisms, and findings regarding its benefits across various fields and application areas. We evaluate and discuss the strengths and weaknesses of ChatGPT based on this review and suggest potential avenues for future research.

The Inventory Déjà Vu Experiences Assessment (IDEA) is the only screening instrument proposed to evaluate Déjà vu (DV) experience. Here we intended to validate the Italian version of IDEA (I-IDEA) and at the same time to investigate the incidence and subjective qualities of DV phenomenon in Italian healthy adult individuals on basis of an Italian multicentre observational study. In this study we report normative data on the I-IDEA, collected on a sample of 542 Italian healthy subjects aging between 18 to 70 years (average age 40, range 18-70) with a formal educational from 1-19 years. From September 2013 to March 2016 were recruited 542 healthy volunteers from ten outpatient neurological clinics in ItalyAll participants (i.e family members of neurological patients enrolled, medicine’s student, physicians) had no neurological or psychiatric illness and they gave informed consent to participate in the study. All subjects enrolled had self-administered the questionnaire and they are able to complete I-IDEA test without any support. In total 396 (73%) of the 542 healthy controls had DV phenomenon. The frequency of DV was inversely related to age as well as to derealisation, jamais vu, precognitive dreams, depersonalization, paranormal activity, remembering dreams, travel frequency and daydreams (all P<0.012). The Italian version of IDEA maintains good properties in Italian version, thus confirming that this instrument is reliable for detecting and characterising the DV phenomenon.

The water cushion depth of stilling basin with shallow-water cushion is a key factor that affects the flow regime of hydraulic jump in the basin. However, the specific depth at which the water cushion is considered as “shallow” has not be stated clearly for now, and only conceptual description is provided. This paper attempts to specify the best water cushion depth based on the flow regime of hydraulic jump and underflow speed; namely, in case of critical hydraulic jump in the basin, the best water cushion depth is located where the minimum distance to the bottom plate of the stilling basin is 1/5~1/4 of the water cushion depth. The theoretical analysis indicates, at different inclinations of discharge chute (θ) and depth ratios of inlet (m), instead of monotonic change, the Froude number (Fr) at inlet of the stilling basin with shallow-water cushion firstly reduces and then increases as the flow velocity at discharge chute inlet (V) increases; the parameters of inflection point (critical flow velocity and critical Fr) increase as the inclinations of discharge chute (θ) and depth ratios of inlet (m) increase. Such regularity is the theoretical basis for selecting representative study cases. The reliability of the large eddy simulation calculation results are verified by a model test; in the paper, 30 cases including five different Froude numbers and six shallow-water cushion depths are selected, for calculating the hydraulic factors such as flow profile, flow regime and flow velocity in the stilling basin with shallow-water cushion; and the varying pattern between the best depth of stilling basin with shallow-water cushion (depth-to-length ratio) and the inflow Froude number is obtained which indicates that the best depth of stilling basin with shallow-water cushion varies little as the change of the Froude number before reaching the critical Froude number; however, the best depth-to-length ratio of stilling basin with shallow-water cushion increases as the Froude number increases after the critical Froude number is reached. The study results in this paper are of reference significance to design and calculation of the stilling basin with shallow-water cushion.

With reference to Planck scale Hubble parameter, super luminal expansion speeds, super luminal rotation speeds and Mach’s principle, we review the current cosmological observations. With our revised assumptions, it is possible to show that, at H₀ =70 km/sec/Mpc, current cosmic temperature, age, radius, mass, mass density and rotational kinetic energy are 2.721 K, 4.41 x 1017 sec, 90 billion light years, 1.14654 x 1054 kg, 0.0482 times the current critical density and 0.6667 times the current critical energy density respectively. Based on the estimated current mass density and current rotational kinetic energy density, current cosmic dark matter density can be shown to be 0.2851 times the current critical density. Initial and current expansion speeds are 3 x 108 m/sec and 3.56 x 109 m/sec respectively. Proceeding further, we developed two interesting methods for understanding cosmic scale factor with reference to a temperature of 3000 K, redshift of 1100 and age of 3,69,000 years. Finally we would like to suggest that, with increasing cosmic age and increasing cosmic expansion speed, current universe is expanding with a speed of 11.885c. Magnitude of the future cosmic expansion speed depends on the magnitude of the future Hubble parameter. By knowing the time to time future cosmic temperatures, corresponding future Hubble parameters can be estimated and corresponding future cosmic expansion speeds can also be estimated.Proceeding further, a unified model of evolving quantum cosmology can be developed.

Background: Access to rehabilitation is crucial for the realization of the right to health and a proper concern of global health. Yet, reliable information to guide rehabilitation service planning is unavailable in many countries in part due to the lack of appropriate indicators. To ensure universal health coverage and meet the central imperative of “leaving no one behind” countries must be able to assess key aspects of rehabilitation policy and provision and monitor how they have discharged their human rights responsibilities towards those most disadvantaged, including people with disability. This article describes the process of developing an expert guided indicator framework to assess governments’ efforts and progress in strengthening rehabilitation in line with the Convention on the Rights of Persons with Disabilities. Methods: A systems methodology - concept mapping - was used to capture, aggregate and confirm the knowledge of diverse stakeholders on measures thought to be useful for monitoring the implementation of the Convention with respect to health related rehabilitation. 56 individuals generated a list of 107 indicators through online brainstorming which were subsequently sorted by 37 experts from the original panel into non overlapping categories. 41 participants rated the indicators for importance and feasibility. Multivariate statistical techniques where used to explore patterns and themes in the data and create the indicators’ organizing framework which was verified and interpreted by participants. Results: A concept map of 11 clusters of indicators emerged from the analysis grouped into three broader themes: Governance and Leadership (3 clusters); Service Delivery, Financing and Oversight (6 clusters); and Human Resources (2 clusters). The RESYST was comprehensive and well aligned with the Convention. On average, there was a moderately positive correlation between importance and feasibility of the indicators (r=.58) with experts prioritizing the indicators contained in the clusters of the Governance and Leadership domain. Two of the most important indicators arose from the Service Delivery, Financing and Oversight domain and reflect the need to monitor unmet needs and barriers in access to rehabilitation. In total, 59 indicators achieved above average score for importance and comprised the two–tiered priority set of indicators. Conclusion: Concept mapping was successful in generating a shared model that enables a system’s view of the most critical legal, policy and programmatic factors that must be addressed when assessing country efforts to reform, upscale and improve rehabilitation services. The RESYST provides a data driven basis for the development of standardized data collection tools to facilitate comparative analysis of rehabilitation systems.

With the increasing of copper consumption, the in-use stock of copper tends to increase. This paper used the “average use life method” to quantify the amount of copper in-use stock, and calculated the average age of in-use stock. It was indicated that the total in-use stock had an overall smooth trends, and reached its peak in 2007 was about 68.9 Mt (million tons), in addition, in-use stock per capita reached its peak ,234 kg/capita in 2001. The results demonstrated that during the period 1992-2002, the average age of copper in-use stock was continually decreased, but gradually increased since the year 2003. The fixed assets depreciation method used in this paper is applied to analyze depreciated copper in-use stock, and to analyze the relationship with economic indicator (GDP). It is demonstrated that it was inconsistent with the theory of Environmental Kuznets Curve (EKC) before 2000, this might be the demand for copper in the service sector is greater than the reduced strength of alternatives. Finally, scenario analysis of future copper in-use stock and depreciated copper in-use stock per capita in the U.S. were presented. The corresponding average age of the in-use stock will have a slight rise in the next decade.

Background: As part of the Heart Healthy Lenoir Project, we developed a practice level intervention to improve blood pressure control. The goal of this study was: i) determine if single nucleotide polymorphisms (SNPs) that associate with blood pressure variation, identified in large case-control studies, are applicable to blood pressure control in subjects from a rural population; ii) measure the association of these SNPs with subjects’ responsiveness to the hypertension intervention; and iii) identify other SNPs that may help understand patient-specific responses to an intervention. Methods and Results: We used a combination of candidate SNPs and genome-wide analyses to test associations with either baseline systolic blood pressure (SBP) or change in systolic blood pressure one year after the intervention in two genetically defined ancestral groups: African Americans (AA) or Caucasian Americans (CAU). Of the 48 candidate SNPs, 13 SNPs associated with baseline SBP in our study; however, one candidate SNP, rs592582, also associated with a change in SBP after one year. Using our study data, we identified 4 and 15 additional loci that associated with a change in SBP in the AA and CAU groups, respectively. Our analysis of gene-age interactions identified genotypes associated with SBP improvement within different age groups of our populations. Moreover, our integrative analysis identified AQP4-AS1 and PADI2 as genes whose expression levels may contribute to the pleiotropy of complex traits involved in cardiovascular health and blood pressure regulation in response to an intervention targeting hypertension. Conclusions: Identification of SNPs associated with the success of a hypertension treatment intervention suggests that genetic factors in combination with age may contribute to an individual’s success in lowering SBP. If these findings prove to be applicable to other populations, the use of this genetic variation in making patient-specific interventions may help providers with making decisions to improve patient outcomes. Further investigation is required to determine the role of this genetic variance with respect to the management of hypertension such that more precise treatment recommendations may be made in the future as part of personalized medicine.

In recent years many different deep neural networks were developed, but due to a large number of layers in deep networks, their training requires a long time and a large number of datasets. Today is popular to use trained deep neural networks for various tasks, even for simple ones in which such deep networks are not required. The well-known deep networks such as YoloV3, SSD, etc. are intended for tracking and monitoring various objects, therefore their weights are heavy and the overall accuracy for a specific task is low. Eye-tracking tasks need to detect only one object - an iris in a given area. Therefore, it is logical to use a neural network only for this task. But the problem is the lack of suitable datasets for training the model. In the manuscript, we presented a dataset that is suitable for training custom models of convolutional neural networks for eye-tracking tasks. Using data set data, each user can independently pre-train the convolutional neural network models for eye-tracking tasks. This dataset contains annotated 10,000 eye images in an extension of 416 by 416 pixels. The table with annotation information shows the coordinates and radius of the eye for each image. This manuscript can be considered as a guide for the preparation of datasets for eye-tracking devices.

This paper describes how to construct a low-cost magnetic levitation system (MagLev). The MagLev has been intensively used in the engineering education, allowing instructors and students to learn through hands-on experiments essential concepts, such as electronics, electromagnetism, and control systems. Built from scratch, the proposed MagLev depends only on simple, low-cost components readily available on the market. In addition to showing how to construct the MagLev, this paper presents a semi-active control strategy which seems novel when applied in the MagLev. Experiments performed in the laboratory have compared the proposed control scheme with the classical PID control. The corresponding real-time experiments illustrate both the effectiveness of the approach and the potential of the MagLev for education.

Global climate change requires urgent solutions. Ambitious tree-planting initiatives, many already underway, aim to sequester enormous quantities of carbon, partly compensating for the anthropogenic CO₂ emissions that are a major cause of rising global temperatures. However, poorly planned and executed tree-planting could actually increase CO₂ emissions and have long-term, deleterious impacts on biodiversity, landscapes and livelihoods. Here, we highlight the main environmental risks of large-scale tree planting and propose ten golden rules, based on some of the most recent ecological research, to implement forest ecosystem restoration that maximizes rates of both carbon sequestration and biodiversity recovery, while simultaneously improving livelihoods. These are: i) Protect existing forest first; ii) Work together (involving all stakeholders); iii) Maximize biodiversity recovery to meet multiple goals; iv) Select appropriate areas; v) Use natural regeneration wherever possible; vi) Select species to maximise biodiversity; vii) Use resilient plant material (with appropriate genetic variability and provenance); viii) Plan ahead for infrastructure, capacity and seed supply; ix) Learn by doing (using an adaptive management approach); and x) Make it pay (ensuring the economic sustainability of the project). We focus on the design of long-term strategies to tackle the climate and biodiversity crises and support livelihood needs. We emphasize the role of local communities and their dependence on benefits from successful reforestation programmes that restore ecosystem functioning and deliver a diverse range of forest products and services. While there is no simple and universal recipe for forest restoration, it is now crucial to build on the public and private interest in this topic to ensure interventions provide effective, long-term carbon sinks and maximise benefits for biodiversity and people.

Large Language Models (LLMs) have revolutionized the field of Artificial Intelligence with their ability to understand and generate natural language discourse. This has led to the use of LLMs in various creative fields such as music, art, and storytelling, which has sparked a debate on the impact of LLMs on human creativity. This article explores the cyclic effect of LLMs on human creativity, where LLMs can generate an ever-evolving cycle of creative output from both humans and machines. The article also highlights the importance of responsible and ethical use of LLMs, including privacy and copyright issues with the training data used by LLMs. The article emphasizes the need for transparency, data security measures, and AI governance policies to protect user data and ensure the safe use of LLMs. It also calls for the development of educational materials and resources to increase public understanding of LLMs and their ethical implications. The article concludes by highlighting the potential of LLMs as powerful tools for communication and education, but also emphasizes the need for ethical considerations to ensure the responsible and beneficial use of LLMs in society.

Sustainability, sustainable development and education for sustainable development are increasingly central concepts, both in social practice and in the field of scientific knowledge. Sociology, and in particular Sociology of Education as a specialised Sociology, can provide relevant contributions in its promotion. This article aims to explore the importance of Sociology of Education in promoting sustainability literacy in higher education, using the Sustainable Development Goals and key competencies (United Nations and UNESCO) as the central reference in this field, and intends, thus, to become an added contribution for this discussion. The article seeks to demonstrate that the learning of sustainability literacy would benefit from the use of a sociological stance throughout this whole process that considers dimensions that are often not directly emphasised and articulated between each other, such as: interconnection of scale levels, sociological imagination, multi-paradigmatic nature, heuristic interdisciplinarity, reflexivity and use of Sociology for action.

In this paper a new approximate procedure is developed for calculating the inclination angle of the end points of statically determinate beams. The method is based on the topology comparison of simple (hinge-roller combination) supported beam and a resemblant cantilever beam. Assuming that the support reactions of the beam are active forces, the virtual displacements at the points of the reaction forces are calculated. Based on these values the inclination angle is calculated. Several examples are considered and the suggested in this paper, while the procedure is applied for various types of structures and loadings. The results, obtained by the suggested numerical procedure, are compared with analytical ones, and they are in good agreement.

The Late Heavy Bombardment Period (4.1 to 3.8 billion years ago) of heightened impact cratering activity on young Earth is likely the driving force for the origin of life. During the Eoarchean, asteroids such as carbonaceous chondrites delivered the building blocks of life and water to early Earth. Asteroid collisions created innumerable hydrothermal crater lakes in the Eoarchean crust which inadvertently became the perfect cradle for prebiotic chemistry. These hydrothermal crater lakes were filled with cosmic water and the building blocks of life. forming a thick prebiotic soup. The unique combination of exogenous delivery of extraterrestrial building blocks of life, and the endogenous biosynthesis in hydrothermal impact crater lakes very likely gave rise to life. A new symbiotic model for the origin of life within the hydrothermal crater lakes is here proposed. In this scenario, life arose around four billion years ago through five hierarchical stages of increasing molecular complexity: cosmic, geologic, chemical, information, and biological. During the prebiotic synthesis, membranes first appeared in the hydrothermal crater lakes, followed by the simultaneous origin of RNA and protein molecules, creating the RNA/protein world. These proteins were noncoded protein enzymes that facilitated chemical reactions. RNA molecules formed in the hydrothermal crater basin by polymerization of the nucleotides on the montmorillonite mineral substrate. Similarly, the initial synthesis of abiotic protein enzymes was mediated by the condensation of amino acids on pyrite surfaces. The regular wet-dry cycles within the crater lakes assisted further concentration, condensation, and polymerization of the RNAs and proteins. Lipid membranes randomly encapsulated amino acids, RNA, and protein molecules from the prebiotic soup to initiate a molecular symbiosis inside the protocells, this led to the hierarchical emergence of several cell components. As the role of protein enzymes became essential for catalytic process in the RNA/protein world, Darwinian selection from noncoded to coded protein synthesis led to translation systems and the genetic code, heralding the information stage. In this stage, the biochemical pathways suggest the successive emergence of translation machineries such as tRNAs, aaRS, mRNAs, and of ribosomes for protein synthesis. The molecular attraction between tRNA and amino acid led to the emergence of translation machinery and the genetic code. tRNA is an ancient molecule that created mRNA for the purpose of storing amino acid information like a digital strip. Each mRNA strand became the storage device for genetic information that encoded the amino acid sequences in triplet nucleotides. As information became available in the digital languages of the codon within mRNA, biosynthesis became less random and more organized and directional. The original translation machinery was simpler before the emergence of the ribosome than that of today. We review three main concepts on the origin and evolution of the genetic code: the stereochemical theory, the coevolution theory, and adaptive theory. We believe that these three theories are not mutually exclusive, but are compatible with our coevolution model of translations machines and the genetic code. We suggest biosynthetic pathways as the origin of the translation machine that provided the framework for the origin of the genetic code. During translation, the genetic code developed in three stages coincident with the refinement of the translation machinery: GNC code with four codons and four amino acids during interactions of pre-tRNA/pre-aaRS /pre-mRNA, SNS code consisting of 16 codons and 10 amino acids appeared during the tRNA/aaRS/mRNA interaction, and finally the universal genetic code evolved with the emergence of the tRNA/aaRS/mRNA/ribosome machine. The universal code consists of 64 codons and 20 amino acids, with a redundancy that minimizes errors in translation. To address the question of the origin of the biological information system in the RNA/protein world, we converted letter codons into numerical codons in the Universal Genetic Code Table. We developed a software called CATI (Codon-Amino Acid-Translator-Imitator) to translate randomly chosen numerical codons into corresponding amino acids and vice versa, gaining insight into how translation might have worked in the RNA/protein world. We simulated the likely biochemical pathways for the origin of translation and the genetic code using the Model-View-Controller (MVC) software framework, and the translation machinery step-by-step. We used AnyLogic software to simulate and visualize the evolution of the translation machines and the genetic code. We conclude that the emergence of the information age from the RNA/protein world was a watershed event in the origin of life about four billion years ago.

Oiola archeological site, located in the mining complex of La Arboleda (Biscay, North Spain) was an important iron smelting center from the Roman Period to the Early Middle Ages and even in more current times (19th-20th centuries). Tap-slags and some plano-convex slags were identified as smelting slags. Samples were analyzed by optical microscopy, X-ray powder diffraction, scanning electron microscopy coupled with electron-dispersive spectroscopy and Raman microspectroscopy to perform a mineralogical and textural characterization. Additionally, thermogravimetric and thermodiffraction analyses were carried out to determine furnace operating temperatures. The mineral assemblage reflects furnace cooling rates and temperatures and the addition of quartz as the main flux to decrease the melting temperature of the iron ore. The comparison of slags from the Roman Period and the Early Middle Age allows to observe changes in the pyrometallurgical process through time.

Large power transformers are generally associated with a maximum capacity rating of 100 MVA or higher. These large liquid dielectric power transformers are a custom-built piece of equipment, thus very expensive, and a backbone element of the power grid. In extreme cases as, for example, severe geomagnetic disturbances, permanently monitoring their condition will enhance their electrical reliability and resilience to guarantee efficient management of its life cycle. However, some traditional monitoring/diagnosis techniques have singular features when applied to large power transformers and their interlinked subsystems. In this context, and since that information is hardly put in evidence and compiled in the literature, this paper reviews the particularities of monitoring and diagnosing those assets.

Hearing impairment is an immensely diagnosed genetic cause, 5% of the total world population effects with different kind of congenital hearing loss (HL). In third-world countries or countries where consanguineous marriages are more common the frequency rate of genetic disorders are at its zenith. Approximately, the incidence of hearing afflictions is ostensibly 7-8:1000 individuals whereas it is estimated that about 466 million peoples suffer with significant HL, and of theses deaf cases 34 million are children’s up to March, 2020. Several genes and colossal numbers of pathogenic variants cause hearing impairment, which aided in next-generation with recessive, dominant or X-linked inheritance traits. This review highlights on syndromic and non-syndromic HL (SHL and NSHL), and categorized as conductive, sensorineural and mixed HL, which having autosomal dominant and recessive, and X-linked or mitochondrial mode of inheritance. Many hundred genes involved in HL are reported, and their mutation spectrum becomes very wide. Mapping of pathogenic genes in consanguinity family is facilitated to understand the disease history. Review presents the bases of HL and also focused on various genetic factors that cause deafness like the basics of genetic inheritance, and classic and well-characterized inherited factors of it. It also overviews the application of linkage analysis, SNPs genotyping and whole exome sequencing methods, in mapping and identification of new locus, causative genes and their variants in families inherited with HL. Conclusively, this review supports researchers in understanding the location of chromosome, the causative genes and specific locus which causing deafness in humans.

Background: Appendicular skeletal muscle (or lean) mass (ALM) estimated using dual-energy X-ray absorptiometry (DXA) is considered to be a preferred method for sarcopenia studies. However, DXA is expensive, has limited portability, and requires radiation exposure. Bioelectrical impedance analysis (BIA) is inexpensive, easy to use, and portable; thus BIA might be useful in sarcopenia investigations. However, a large variety of models have been commercially supplied by different companies, and for most consumer products, the equations estimating ALM are not disclosed. It is therefore difficult to use these equations for research purposes. In particular, the BIA equation is often age-dependent, which leads to fundamental difficulty in examining age-related ALM loss. The aims of the current study were as follows: (1) to develop and validate an equation to estimate ALM using multi-frequency BIA (MF-BIA) based on theoretical models, and (2) to establish sarcopenia cutoff values using the equation for the Japanese population. Methods: We measured height (Ht), weight, and ALM obtained using DXA and a standing-posture 8-electrode MF-BIA (5, 50, 250 kHz) in 756 Japanese individuals aged 18 to 86-years-old (222 men and 301 women as developing equation group and 97 men and 136 women as a cross validation group). The traditional impedance index (Ht²/Z₅₀) and impedance ratio of high and low frequency (Z₂₅₀/Z₅) of hand to foot values were calculated. Multiple regression analyses were conducted with ALM as dependent variable in men and women separately. Results: We created the following equations: ALM = (0.6947 × (Ht²/Z₅₀)) + (−55.24 × (Z₂₅₀/Z₅)) + (−10,940 × (1/Z₅₀)) + 51.33 for men, and ALM = (0.6144 × (Ht²/Z₅₀)) + (−36.61 × (Z₂₅₀/Z₅)) + (−9332 × (1/Z₅₀)) + 37.91 for women. Additionally, we conducted measurements in 1624 men and 1368 women aged 18 to 40 years to establish sarcopenia cutoff values in the Japanese population. The mean values minus 2 standard deviations of the skeletal muscle mass index (ALM/Ht²) in these participants were 6.8 and 5.7 kg/m² in men and women, respectively. Conclusion: The current study established and validated a theoretical and age-independent equation using MF-BIA to estimate ALM and provided reasonable sarcopenia cutoff values.

This study was designed to assess variation of possible phytochemical compounds in the ethanolic extracts of Gigantochloa scortechinii rhizome. Destructive sampling was done by using selective random sampling method on four consecutive rhizomes from healthy clumps and was conducted at two natural forests and one secondary forest (planted). Homogenized sample were extracted using solvent extraction (70% ethanol) method. Ethanolic extracts of G. scortechinii rhizome were qualitatively analyzed using GC/MS GC2010 Plus, Shimadzu to determine the composition of phytochemical compounds and identified using FFNSC 1.3, NIST11, PMW_tox2, and Wiley229 spectral library. A qualitative variation was observed with a total of 56 compounds were identified and differentiated between study site and rhizome age. Results revealed that G. scortechinii rhizome contains various phytochemical compounds with potential as a plant of phytopharmaceutical importance. This is the first finding on the spatial and age-related effects of phytochemical compounds in a consecutive rhizome and of G. scortechinii rhizome specifically.

The performance in terms of minimal Bayes’ error probability for detection of a high-dimensional random tensor is a fundamental under-studied difficult problem. In this work, we consider two Signal to Noise Ratio (SNR)-based detection problems of interest. Under the alternative hypothesis, i.e., for a non-zero SNR, the observed signals are either a noisy rank-R tensor admitting a Q-order Canonical Polyadic Decomposition (CPD) with large factors of size Nq  R, i.e, for 1  q  Q, where R, Nq ! ¥ with R1/q/Nq converge towards a finite constant or a noisy tensor admitting TucKer Decomposition (TKD) of multilinear (M1, . . . ,MQ)-rank with large factors of size Nq  Mq, i.e, for 1  q  Q, where Nq,Mq ! ¥ with Mq/Nq converge towards a finite constant. The detection of the random entries (coefficients) of the core tensor in the CPD/TKD is hard to study since the exact derivation of the error probability is mathematically intractable. To circumvent this technical difficulty, the Chernoff Upper Bound (CUB) for larger SNR and the Fisher information at low SNR are derived and studied, based on information geometry theory. The tightest CUB is reached for the value minimizing the error exponent, denoted by s?. In general, due to the asymmetry of the s-divergence, the Bhattacharyya Upper Bound (BUB) (that is, the Chernoff Information calculated at s? = 1/2) can not solve this problem effectively. As a consequence, we rely on a costly numerical optimization strategy to find s?. However, thanks to powerful random matrix theory tools, a simple analytical expression of s? is provided with respect to the Signal to Noise Ratio (SNR) in the two schemes considered. A main conclusion of this work is that the BUB is the tightest bound at low SNRs. This property is, however, no longer true for higher SNRs.

Due to its spatio-temporal variability, the mismatch between the weather and demand patterns challenges the design of highly renewable energy systems. A principal component analysis is applied to a simplified networked European electricity system with a high share of wind and solar power generation. It reveals a small number of important mismatch patterns, which explain most of the system's required backup and transmission infrastructure. Whereas the first principal component is already able to reproduce most of the temporal mismatch variability for a solar dominated system, a few more principal components are needed for a wind dominated system. Due to its monopole structure the first principal component causes most of the system's backup infrastructure. The next few principal components have a dipole structure and dominate the transmission infrastructure of the renewable electricity network.

One important motivation for the implementation of the Water Framework Directive is the creation of non-market environmental benefits such as improved ecological quality, or greater opportunities for open-access river recreation via microbial pollution remediation. Pollution sources impacting on ecological or recreational water quality can be uncorrelated but non-market benefits arising from riverine improvements are typically conflated within benefit valuation studies. Using stated preference choice experiments, we seek to disaggregate these sources of value for different river users, thereby allowing decision makers to understand the consequences of adopting alternative investment strategies. Our results suggest anglers derive greater value from improvements to the ecological quality of river water, in contrast to swimmers and rowers for whom greater value is gained from improvements to recreational quality. We also find three distinct groups of respondents: a majority preferring ecological over recreational improvements, a substantial minority holding opposing preference orderings and a small proportion expressing relatively low values for either form of river quality enhancement. As such, this research demonstrates that the non-market benefits which may accrue from different types of water quality improvements are nuanced in terms of their potential beneficiaries and, by inference, their overall value and policy implications.

Both SARS-CoV-2 (COVID-19) and SARS coronaviruses (CoVs) are members of the subgenus Sarbecovirus. To understand the origin of SARS-CoV-2, protein sequences from sarbecoviruses were analyzed to identify highly-specific molecular markers consisting of conserved inserts or deletions (termed CSIs) in the spike (S) and nucleocapsid (N) proteins that are specific for either particular clusters/lineages of these viruses or are commonly shared by specific lineages. Three novel CSIs in the N-terminal domain of the spike protein S1-subunit (S1-NTD) are uniquely shared by the SARS-CoV-2, BatCoV-RaTG13 and most pangolin CoVs, distinguishing this cluster of viruses (SARS-CoV-2r) from all others. In the same positions, where these CSIs are found, related CSIs are also present in two other sarbecoviruses (viz. CoVZXC21 and CoVZC45 forming CoVZC cluster), which form an out group of the SARS-CoV-2r cluster. These three CSIs are not found in the SARS-CoVs. However, both SARS and SARS-CoV-2r CoVs contain two large CSIs in the C-terminal domain of S1 (S1-CTD), which binds the human ACE-2 receptor, that are absent in the CoVZC cluster of CoVs. These results indicate that while the S1-NTD of the SARS-CoV-2r viruses possesses the sequence characteristics of the CoVZC cluster of CoVs, their S1-CTD resembles the SARS viruses. Thus, the spike protein of SARS-CoV-2r viruses has likely originated from a recombination event between the S1-NTD of the CoVZC viruses and the S1-CTD of SARS viruses. This inference is also supported by the amino acid sequence similarity of the S1-NTD and S1-CTD from SARS-CoV-2 compared to the CoVZC and SARS CoVs. We also present evidence that one of the pangolin-CoV_MP789, whose receptor-binding domain is most similar to the SARS-CoV-2, is also derived by a recent recombination between the S1-NTD of the CoVZC CoVs and the S1-CTD of a SARS-CoV-2 related virus. Several other identified CSIs are specific for others clusters of sarbecoviruses including a clade consisting of bat SARS-CoVs (BM48-31/BGR/2008 and SARS_BtKY72). Structural mappings studies show that the identified CSIs are located within surface-exposed loops and form distinct patches on the surface of the spike protein. These surface loops/patches are predicted to interact with other host components and play important role in the biology/pathology of SARS-CoV-2 virus. Lastly, the CSIs specific for the SARS-CoV-2r clade provide novel means for development of new diagnostic and therapeutic targets for these viruses.

Despite increasing research efforts, there is a lack of consensus on defining aging or health. To understand the underlying processes, and to foster the development of targeted interventions towards increasing one’s health, there is an urgent need: (1) to find a broadly acceptable and useful definition of health, based on a list of features (which may or may not be molecular); (2) to operationalize features of health so that it can be measured; (3) to identify predictive biomarkers and (molecular) pathways of health, and (4) to suggest interventions, such as nutrition and exercise, targeted at putative causal pathways and processes. Based on a survey of the literature, we propose to define health as a state of an individual characterized by the core features of (a) physiological function, (b) cognitive function and (c) physical function, amended, specifically in case of humans, by (d) lack of disease, and by (e) reproductive function. Often used concepts such as lack of frailty, allostatic load, or self-reported health (in case of human), and indices such as the Healthy Aging Index can be viewed as projections or surrogates of our definition. We further define aging as the set of all processes in an individual that reduce its “wellbeing”, that is, its health or survival or both. We define biomarkers of health by their attribute of predicting future health better than chronological age. We define healthspan pathways as molecular features of health that relate to each other, specifically by belonging to the same molecular pathway. Our conceptual framework may integrate diverse operationalizations of health and guide precision prevention efforts that are a key to reducing the need for medical and nursing care.

This paper identifies a criterion for choosing the largest set of rejected hypotheses in high-dimensional data analysis where Multiple Hypothesis testing is used in exploratory research to identify significant associations among many variables. The method neither requires predetermined thresholds for level of significance, nor uses presumed thresholds for false discovery rate. The upper limit for number of rejected hypotheses is determined by finding maximum difference between expected true hypotheses and false hypotheses among all possible sets of rejected hypotheses. Methods of choosing a reasonable number of rejected hypotheses and application to non-parametric analysis of ordinal survey data are presented.

Electrification coverage in Sarawak is the lowest at 78.74%, compared to Peninsular Malaysia at 99.62% and Sabah at 82.51%. Kapit, Sarawak with its 88.4% populations located in rural areas and mostly situated along the main riverbanks has great potential to generate electrical energy by hydrokinetic system. Yearly water velocity data is the most significant parameter to perform hydrokinetic analysis study. Nevertheless, the data retrieved from local river databases are inadequate for river energy analysis, thus hindering its progression. Instead, flow rates and rainfall data had been utilised to estimate the water velocity data. This signifies no estimation of water velocity in an unregulated river by using water level data had been made. Therefore, a novel technique of estimating the daily average water velocity data in unregulated rivers is proposed. The modelling of regression equation for water velocity estimation was performed and two regression model equations were generated to estimate both water level and water velocity on-site and proven to be valid as the coefficient of determination values had been R² = 87.4% and R²=87.9%, respectively. The combination of both regression model equations can be used to estimate long-term time series water velocity data for type-C unregulated river in remote areas.

Meat-based diets are still the norm and vegans and vegetarians represent only a small minority of the population. A transition respectively behavioural change towards a diet with less meat can only occur with the adoption of a positive attitude towards dietary changes based on reasons and motivations. The main aim of this study is to validate the so-called meat attachment scale (MEAS) for Germany in order to analyse if this construct is a barrier towards a diet with less meat in this country. The findings show that the MEAS can be applied in Germany and a similar structure as reported for Spain and other countries could be found. Furthermore, a correlation analysis demonstrated that food neophobia and MEAS are not correlated with each other. That is, that meat attachment represents an independent and single predictor for trust in food (processing) technologies as e.g. plant-based proteins or cultured meat.

The attributes of electroplating as a low-cost, simple, scalable and manufacturable semiconductor deposition technique for the fabrication of large-area and nanotechnology-based device applications are discussed. These strengths of electrodeposition are buttressed experimentally using techniques such as X-ray diffraction, Ultraviolet-visible spectroscopy, Scanning electron microscopy, Atomic force microscopy, Energy-dispersive X-ray spectroscopy and photoelectrochemical cell studies. Based on the structural, morphological, compositional optical, and electronic properties evaluated results, it is evident that electroplating possesses the capabilities of producing high-quality semiconductors usable in producing excellent devices. In this paper, we will describe the progress of electroplating technique mainly for the deposition of semiconductor thin film materials, their treatment processes and fabrication of solar cells.

Increasing numbers of researchers are interested in the importance of dietary fiber for the gut microbiota, microbiotal metabolite SCFA, energy metabolism and gut health of the host. However, studies have demonstrated that long-term and longitudinal observation may be needed to evaluate the effect of dietary fiber better, and few such works have been made in chickens. Therefore, we successively fed low-fiber, high--fiber and low-fiber diets to two breeds of chickens during different growth periods (1—8, 9—20 and 21—50 weeks), aiming to longitudinally observe the long-term effect of altered dietary fiber on the gut microbiota, SCFA and development of cecum of chickens with age. The results showed that the composition and function of the gut microbiota, SCFA and the development of the cecum were different during different periods, which was largly affected by dietary fiber. However, the causes of some effects were different during the different periods. For example, compared with that in low-fiber chickens at 8 weeks, dominant fiber-degradation bacteria such as Bacteroidetes, Alloprevotella and SCFA-producing bacteria such as Faecalibacterium increased due to a high-fiber diet at 20 weeks, while due to a high feed intake in 50 weeks. Moreover, the concentration of SCFA in 20 weeks was significantly higher than in 8 weeks and 50 weeks, but the causes of this difference were also distinct. It was proposed that a long-term observation was needed to evaluate the effect of dietary fiber better on chickens. The metabolite pathways of ATP-binding cassette (ABC) transporters encoded by Firmicutes were enriched in 8 weeks, while a two-component system and β–glucosidase encoded by Bacteroidetes were enriched in 20 and 50 weeks. The trend was the same in two breeds of chickens except for Alloprevotella. In addition, the total content of SCFA in the contents of cecum was also affected by the size of the cecum. Surprisingly, the length of the cecum shortened from 20—50 weeks, maybe due to reduced dietary fiber.

COVID-19 emerged in Wuhan and is later declared as a pandemic by World Health Organization. Different-aged people have varying gender-wise immunity control properties that necessitates understanding COVID-19 impact on age and gender which does not exist, currently. In this paper, COVID-19 surveillance variables are extensively studied along with hospitalization, tests-performed, and recovery data. Dataset is curated from three sources; however, age and gender data belong to Belgium, particularly. Visualizations, frequencies, Pearson’s and polyserial correlation, student’s t-test, and Cramer’s V are used for enhanced analysis. Results show higher mortality rate in males and need of more ventilators to combat severe symptoms.

In considering knowledge graphs in a diverse range of domains of interest, graph neural networks have demonstrated significant improvements in node classification and prediction when applied to graph representation with learning node embedding to effectively represent hierarchical properties of graphs. DiffPool is a deep-learning approach using a differentiable graph pooling technique that generates hierarchical representations of graphs. In operation DiffPool is a differentiable graph pooling technique that generates hierarchical representations of graphs. DiffPool learns a differentiable soft cluster assignment for nodes at each layer of a deep graph neural network with nodes mapped sets of clusters. However, control of the learning process is difficult given the complexity and large number of parameters on an `end-to-end’ model. To address this difficulty we propose an novel approach termed FPool which is predicated on the basic approach adopted in DiffPool (where pooling is applied directly to node representations). Methods designed to enhance data classification have been developed and evaluated using a number popular and publicly available sensor data sets. Experimental results for FPool demonstrate improved classification and prediction performance when compared to alternative methods. Moreover, FPool shows an important reduction in the training time over the basic DiffPool framework.

Augment reality (AR) is crucial for immersive human-computer interaction (HCI) and vision of artificial intelligence (AI). Labeled data drove object recognition in AR. However, manual annotating data is expensive and labor-intensive, and furthermore, scanty labeled data limits the application of AR. Aiming at solving the problem of insufficient training data in AR object recognition, an automated vision data synthesis method called BAGAN is proposed in this paper based on the 3D modeling and GAN algorithm. Our approach has been validated to have better performance than other methods through image recognition task on natural image database ObjectNet3D. This study can shorten the algorithm development time of AR and expand the application scope of AR, which is of great significance to immersive interactive systems.

Disrupted biological function, manifesting through the hallmarks of aging, poses as one of the largest threats to healthspan and risk of disease development, such as metabolic disorders, cardiovascular ailments, and neurodegeneration. In recent years, numerous geroprotectors, senolytics, and other nutraceuticals have emerged as potential disruptors of aging and may be viable interventions in the immediate state of human longevity science. In this review, we focus on the decrease of nicotinamide adenine dinucleotide (NAD+) with age and the supplementation of NAD+ precursors, such as nicotinamide mononucleotide (NMN) or nicotinamide riboside (NR), in combination with other geroprotective compounds to restore youthful NAD+ levels. Furthermore, these geroprotectors may enhance the efficacy of NMN supplementation while concurrently providing their own numerous health benefits. By analyzing the prevention of NAD+ degradation through inhibition of CD38 or supporting protective downstream agents of SIRT1, we provide a potential framework of the CD38/NAD+/SIRT1 axis through which geroprotectors may enhance the efficacy of NMN supplementation and reduce the risk of age-related diseases, thereby potentiating healthspan in humans.

Backward electromagnetic waves are extraordinary waves with contra-directed phase velocity and energy flux. Unusual properties of the coherent nonlinear optical coupling of the phase-matched ordinary and backward electromagnetic waves with contra-directed energy fluxes are described which enable greatly-enhanced frequency and propagation direction conversion, parametrical amplification, as well as control of shape of the light pulses. Extraordinary transient processes that emerge in such metamaterials in pulsed regimes are described. The results of the numerical simulation of particular plasmonic metamaterials with hyperbolic dispersion are presented, which prove the possibility to match phases of such coupled guided ordinary and backward electromagnetic waves. Particular properties of the outlined processes in the proposed metamaterial are demonstrated through numerical simulations. Potential applications include ultra-miniature amplifiers, frequency changing reflectors, modulators, pulse shapers, and remotely actuated sensors.

Remote sensing technology provides a new way to explore the earth for geoscience applications. In the context of continuous deepening of geological research and the vigorous development of geospatial information science, 3D geological modeling technology has become a research hotspot in the intersection of earth science and information science. The traditional 3D geological modeling technology refers to underground 3D modeling using geological data. This modeling method can only display the underground scene in 3D visualization, but cannot display the surface in detail. In this study, remote sensing technology is adopted to improve the traditional 3D geological modeling method, so that geological modeling can be integrated with remote sensing image, and a new 3D geological modeling method based on remote sensing technology is developed. This method can perform integrated 3D visualization of underground and aboveground scenes, which provides a new way for disaster prevention and reduction, geological prospecting and tectonic interpretation. The new 3D geological modeling method is mainly applied in the geological field, and has made new progress in multi-source heterogeneous geological data fusion, large-scale high-precision modeling, geological grid subdivision, attribute modeling technology, remote sensing image fusion and other aspects. Taking the Ya'an area as an example, this paper makes use of the new generation of 3D geological modeling technology to carry out 3D geological modeling and visual display. The 3D visualization in Ya'an area verifies the feasibility and effectiveness of the new 3D geological modeling method based on remote sensing technology in the current data environment.

This article describes the use of the PI ProcessBook software tool for visualization and indirect monitoring of occupancy of SHC rooms from the measured operational and technical quantities for monitoring of daily living activities for support of independent life of elderly persons. The proposed method for data processing (predicting the CO₂ course using neural networks from the measured temperature indoor T_i (°C), temperature outdoor T_o (°C) and the relative humidity indoor rHi (%)) was implemented, verified and compared in MATLAB SW tool and IBM SPSS SW tool with IoT platform connectivity. Within the proposed method, the Stationary Wavelet Transform de noising algorithm was used to remove the noise of the resulting predicted course. In order to verify the method, two long-term experiments were performed, (specifically from February 8 to February 15, 2015, from June 8 to June 15, 2015) and two short-term experiments (from February 8, 2015 and from June 8, 2015). For the best results of the trained ANN BRM within the prediction of CO₂, the correlation coefficient R for the proposed method was up to 90%. The verification of the proposed method confirmed the possibility to use the presence of persons of the monitored SHC premises for rooms ADL monitoring.

Pipeline integrity is an important area of concern for the oil and gas, refining, chemical, hydrogen, carbon sequestration, and electric-power industries, due to the safety risks associated with pipeline failures. Regular monitoring, inspection, and maintenance of these facilities is therefore required for safe operation. Large standoff magnetometry (LSM) is a non-intrusive, passive magnetometer-based mea- surement technology that has shown promise in detecting defects (anomalies) in regions of elevated mechanical stresses. However, analyzing the noisy multi-sensor LSM data to clearly identify regions of anomalies is a significant challenge. This is mainly due to the high frequency of the data collection, mis-alignment between consecutive inspections and sensors, as well as the number of sensor measurements recorded. In this paper we present LSM defect identification approach based on ma- chine learning (ML). We show that this ML approach is able to successfully detect anomalous readings using a series of methods with increasing model complexity and capacity. The methods start from unsupervised learning with "point" methods and eventually increase complexity to supervised learning with sequence methods and multi-output predictions. We observe data leakage issues for some methods with randomized train/test splitting and resolve them by specific non-randomized splitting of training and validation data. We also achieve a 200x acceleration of support-vector classifier (SVC) method by porting computations from CPU to GPU leveraging the cuML RAPIDS AI library. For sequence methods, we develop a customized Convolutional Neural Network (CNN) architecture based on 1D convolutional filters to identify and characterize multiple properties of these defects. In the end, we report the scalability of the best-performing methods and compare them, for viability in field trials.

To date, several different approaches are available to study sediment dynamics at reach or watershed scale, based on very different hypothesis. One of such assumptions, the so-called “morphodynamic equilibrium hypothesis” is becoming little unpopular for its embedded simplifications. The aim of this work is to demonstrate how this approach proves yet effective in modelling landscape morphodynamics at the watershed scale, for what concerns the longitudinal profile of a river and the sedimentary aspects. The application of a 1-D model based on the equilibrium hypothesis has been implemented for several large rivers worldwide. Geomorphological parameters have been analysed, which describe the evolution of longitudinal profile (concavity) and sediments characteristics (aggrading and fining), and the results show a reasonably good correspondence with qualitative estimation of the same parameters. At the scale of analysis and for the chosen systems, which show high inertia to geomorphological changes likely owing to their longitudinal extension, the model can detect where the present conditions reflect a big disturbance to the “natural equilibrium” thus allowing water managers to identify present issues to be addressed.

In this paper, using the discrete time model, we consider the average age of all files for a cached-files-updating system where a server generates N files and transmits them to a local cache. In order that the cached files are fresh, in each time slot the server updates files with certain probabilities. The age of one file or its age of information (AoI) is defined as the time the file stays in cache since it was last time sent to cache. Assume that each file in cache has corresponding request popularity. In this paper, we obtain the distribution function of the popularity-weighted average age over all files, which gives a complete description of this average age. For the random age of single file, both the mean and its distribution have been derived before by establishing a simple Markov chain. Using the same idea, we show that an N dimensional stochastic process can be constituted to characterize the changes of N file ages simultaneously. By solving the steady-state of the resulting process, we obtain the explicit expression of stationary probability for an arbitrary state-vector. Then, the distribution function of the popularity-weighted average age can be derived by mergering a proper set of stationary probabilities. For the possible applications, the distribution function can be utilized to calculate the probability that the average age violates certain statistical guarantee.

In the paper, the results of an investigation into trace elements found in slag sulphides from 14 archaeological Bronze Age settlements of the Cis-Urals, Trans-Urals and North and Central Kazakhstan are presented. The study used Cu-(Fe)-sulphides as indicator minerals. Cu-(Fe)-S minerals in slags are primarily represented by covellite and chalcocite, as well as by rarer bornite and single chalcopyrite grains. Slag sulphides formed relic clasts and neogenic droplets of different shapes and sizes. Supergenic ores in the Bronze Age in Urals and Kazakhstan played a significant role in the mineralogical raw material base. In sulphides, the main indicator elements Fe, Co, Ni, As, Se, Te, Sb, Ag, Pb, and Bi are important markers of copper deposit types. Sulphides from olivine Cr-rich spinel containing slags of Ustye, Turganik, and Kuzminkovskoe 2 are characterised by As-Co-Ni assemblages and confined to copper deposits in ultramafic rocks. Olivine sulphide-containing slags from Kamenny Ambar, Konoplyanka and Sarlybay 3 are characterised by Co-Se-Te assemblage and confined to mafic rocks. Glassy sulphide-containing slags from Katzbakh 6, Turganik, Ordynsky Ovrag, Ivanovskoe, Tokskoe, Bulanovskoe 2, Pokrovskoe, Rodnikovoe, and Taldysay are characterised by Ag-Pb-(Ba)-(Bi) assemblage and confined to cupriferous sandstone deposits. High As, Sb, Sn and Ba contents found in slags can be seen as indicators of alloying or flux components in primary copper smelting. These include samples from Ustye, Katzbakh 6, Rodnikovoe, and Taldysay sites, where high Ba and As slag contents are identified. The compilation of a database with a broad sample of sulphide compositions from Bronze Age slags and mines in the Urals and Kazakhstan will permit the further identification of ore types and raw materials associated with a particular deposit.

The paper presents the results of the theoretical and practical research on developing the infrastructure for assessment of overall risk (explosion / occupational / terrorist attack) associated with unwanted events such as major accidents that can occur at explosive storehouses for civilian use. The scientific research outlined in this article was carried out within the Nucleu Project PN 16 43 02 15 - “Research on increasing safety levels at technical facilities for storage of explosives for civil use”.

Hand gestures may play an important role in medical applications for health care of elderly people, where providing a natural interaction for different requests can be executed by making specific gestures. In this study we explored three different scenarios using a Microsoft Kinect V2 depth sensor then evaluated the effectiveness of the outcomes. The first scenario utilized the default system embedded in the Kinect V2 sensor, which depth metadata gives 11 parameters related to the tracked body with five gestures for each hand. The second scenario used joint tracking provided by Kinect depth metadata and depth threshold together to enhance hand segmentation and efficiently recognize the number of fingers extended. The third scenario used a simple convolutional neural network with joint tracking by depth metadata to recognize five categories of gestures. In this study, deaf-mute elderly people execute five different hand gestures to indicate a specific request, such as needing water, meal, toilet, help and medicine. Then, the requests were sent to the care provider’s smartphone because elderly people could not execute any activity independently. The system transferred these requests as a message through the global system for mobile communication (GSM) using a microcontroller.

Diffuse large B cell lymphoma (DLBCL), the most frequent type of non-Hodgkin lymphoma in adulthood, remains challenging clinical issues. Despite enhanced remission rates can be achieved, there are one-third of patients who will not respond to current treatment or will relapse with resistant disease, necessitating ongoing efforts on effective treatment strategies and agents. The vacuole H+-ATPase inhibitor bafilomycin A1 is broadly used to block late stage of autophagy flux at high concentration. In this study, we show that, to our surprise, bafilomycin A1 effectively inhibited and killed DLBCL cells at nanomolar concentrations (5nM). Bafilomycin A1 targeted cell cycle regulators cyclin D1 and cyclin E2 to induce cell cycle arrest in G0/G1 phase. Meanwhile, it induced caspase-dependent apoptosis with concomitant cleaved caspase-3 and Parp. Furthermore, we found that bafilomycin A1 inhibited autophagy flux at both early and late stages of the autophagy flux through activating ERK and mammalian target of rapamycin signaling, as well as by inhibiting the degradation of autolysosomes. We speculated that bafilomycin A1 as autophagy inhibitor might enhance the effect of DLBCL chemotherapeutic drug rituximab. Accordingly, our results provided evidence that the combination of bafilomycin A1 with rituximab enhanced the inhibition of DLBCL cells notably. Taken together, our data suggest that bafilomycin A1 may be a promising candidate drug in the therapy of diffuse large B cell lymphoma.

Matiyasevich's theorem states that there is no algorithm to decide whether or not a given Diophantine equation has a solution in non-negative integers. Smorynski's theorem states that the set of all Diophantine equations which have at most finitely many solutions in non-negative integers is not recursively enumerable. We prove: (1) Smorynski's theorem easily follows from Matiyasevich's theorem, (2 ) Hilbert's Tenth Problem for Q has a negative solution if and only if the set of all Diophantine equations with a finite number of rational solutions is not recursively enumerable.

Changes in curricula, publication policy and information technology, notably in China have led to concentrations in the role of STEM (science, technology, engineering and mathematics) education in early childhood and applauded to proliferations of imported up-to-date reading materials and mobile apps in English. This paper proposes a longitude study of a Chinese toddler learning STEM by reading picture books and playing with tablet and suggests new horizons in parenting and in STEM education during children's early years. The present study carried out from 2016, when the participant reached one year old, eligible to learn to speak and to concentrate on the picture books read by parents who had filled a language background questionnaire with information on themselves and the participant. Tablet playing brought about for the two-year-old toddler and collections of STEM books in English was added for the second year. Data collection lasted for two years with an iLab video camera, capturing utterances and motions for five minutes per week transcribed by VoiceScript software. Tests were given quarterly at private home by tapping in mobile app "Bilingual Child Learning" which consists of 20 basic STEM themes before scores were collected. Findings indicate that (1) it is accessible for children of very early years to be engaged in English STEM resources, (2) kids' limited English dominance does not impede learning STEM, (3) and to think in English in early STEM contributes to children's English.

In this work, we derive the spectral efficiency, secrecy outage probability, and bit error rate of a communication system assisted by a large intelligent surface (LIS). We consider a single-antenna user and an array of antennas at the transmitter side and the possibility of a direct link between transmitter and receiver. Additionally, there is a single-antenna eavesdropper with a direct link to the transmitter, which is modeled as a Nakagami-m distributed fading coefficient. The channels from transmitter to the LIS and from the LIS to the user may or may not have the line-of-sight (LoS) and are modeled by the Nakagami- m distribution. Moreover, we assume that the LIS elements perform non-ideal phase cancellation leading to a residual phase error that assumes a Von Mises distribution. We show that the resulting channel can be accurately approximated by a Gamma distribution whose parameters are analytically estimated using the moments of the equivalent signal-to-noise ratio. We also provide an upper bound for the error probability for M-QAM modulations. With the derived formulas, we analyze the effect of the strength of the LoS link by varying the Nakagami parameter, m.