Snakebite envenomations (SBE) are a significant global public health threat due to their morbidi-ty and mortality. It is a neglected public health issue in many tropical and subtropical countries. Brazil is in the top ten countries affected by SBE, with 32,160 cases reported in Brazil only in 2020, posing a high burden for this population. We describe the data structure of the Snakebite data on Notifiable Disease Information System (SINAN) made available by the Brazilian Minis-try of Health from 2007 to 2020. In addition, we also provide R scripts that allow a quick and automatic updating of data from the SINAN according to its availability. The data presented in this work is related to clinical and demographic information of SBE cases. Also, data on out-comes, laboratory results, and treatment is available. The database is available and freely acces-sible; however, preprocessing, adjustments, and standardization are necessary due to incom-pleteness and inconsistencies. Regardless of these limitations, it provides a solid basis for as-sessing different aspects and the national burden of envenoming.

Coronaviruses are highly transmissible and pathogenic viruses for humans and animals. The vast quantity of information collected about SARS-CoV-2 during the pandemic helped to unveil details on the mechanisms behind the infection, which are still largely elusive. Recent research demonstrated that different class I/II human leukocyte antigen (HLA) alleles might define an individual susceptibility to SARS-CoV-2 spreading, contributing to the differences in the distribution of the infection through different populations; additional studies suggested that the homolog of the HLA in cats, the Feline Leukocyte Antigen (FLA), plays a pivotal role in the transmission of viruses. With these premises, this study aimed to exploit a bioinformatic approach for the prediction of the transmissibility potential of two distinct Feline Coronaviruses (FCoVs) in domestic cats (Feline enteric Coronavirus, FeCV and Feline Infectious Peritonitis Virus, FIPV) using SARS-CoV-2 as the reference model. We performed an epitope mapping of nonapeptides deriving from SARS-CoV-2, FeCV and FIPV glycoproteins and predicted their affinities for different alleles included in the three main loci in class I FLAs (E, H and K). The predicted complexes with the most promising affinities were then subjected to molecular docking and molecular dynamics simulations to provide insights into the stability and binding energies in the cleft. Results showed the FLA proteins encoded by alleles in FLA-I H (H*00501 and H*00401) and E (E*01001 and E*07001) loci are largely responsive to several epitopes deriving from replicase and spike proteins of the analyzed coronaviruses. The analysis of the most affine epitope sequences resulting from the prediction can stimulate the development of anti-FCoV immunomodulatory strategies based on peptide drugs.

Fire hazards present a multifaceted global challenge that endangers human lives and environmental safety. Despite advancements in fire risk management technologies and methods, fires continue to be a prime concern for human security. The Arabian Gulf region, influenced by its climatic and environmental conditions, is especially susceptible to these threats. The Emirate of Sharjah, part of the United Arab Emirates, has made significant progress in reinforcing fire safety measures within residential structures, achieving a decrease in the number of fire-related accidents compared to neighboring Emirates. However, the incidence rate remains relatively high. This study undertook a thorough review and assessment of the existing Fire Management System (FMS) for Sharjah's residential sector, leading to the recommendation of a more robust framework. Through a series of literature reviews, interviews with stakeholders, and surveys, using analytical techniques such as the Delphi method and Failure Mode Effect and Criticality Analysis, vital factors that influence the FMS's effectiveness were pinpointed. The study exposed that the current FMS was largely reactive. In response, a proactive framework incorporating nine essential components was designed to strengthen the Sharjah FMS. These components span across various domains such as fire assurance, assessment of fire risks, management of accidents, evaluation of performance, training programs, research and development initiatives, digital services, monitoring of regulatory compliance, firefighting strategies, automated responses to fires, recovery processes, as well as the use of resilient materials and architectural design considerations. Furthermore, the research introduced two specific fire indexes, the HRBFI and the EFRI. Anchored in the principles of Systems Thinking and Industry 4.0, this proposed framework is aimed at streamlining Sharjah's approach to fire management in dwellings, with the objective of diminishing the frequency of fire incidents yearly. The ultimate aspiration of this framework is to enhance the Emirate's standing in terms of safety and to guarantee a living environment that is safeguarded against the risk of fires..

One of the interactions that has been studied in recent decades under the ecohydrological approach is infiltration, which is difficult to determine because the existing methods for estimation depends on certain variables that are difficult to establish or identify, and in other cases, the implementation of instrumentation is expensive. Given this, saturated hydraulic conductivity has been the descriptive variable of the infiltration process by recent authors, being understood as the conduction of water that occurs through the soil and its composition through the vegetation cover. The present design generated an easily accessible portable instrumentation model for the monitoring and collection of infiltration data in situ for basins and ecosystems with different land uses, in an automated manner with the objective of determining the vegetation patterns necessary to sustain the infiltration function. The INDI-INECOL tension infiltrometer [1] was chosen as the reference instrument. It evaluates the saturated hydraulic conductivity based on a column of water that descends through the system and it is exchanged in the soil by the air between the pores. To automate data collection, a measurement system has been proposed through a SCADA system, which is defined as a control, action, decision, storage and data recording system. This system collects field data from a sensor VL053L0X connected to a master station, in our case an Arduino board UNO, connected through the serial port and by a graphical user interface programmed on Python, to display, storage and enrichment of the sensor data and finally to be exported in files suitable for Microsoft Excel.

The surging electricity demand driven by a growing global population, coupled with the increasing electrification of industries, transportation, and power-intensive appliances, poses a substantial challenge to electricity systems worldwide. This challenge is further compounded by the pressing issue of climate change. To address climate change and mitigate the environmental consequences of fossil fuel use, renewable energy sources are expected to play a pivotal role. However, certain renewable sources, such as wind and solar, exhibit stochastic behavior, resulting in unpredictable power output and significant fluctuations. This intermittency presents a challenge in maintaining a stable and reliable power supply. To overcome this challenge and ensure a balanced electricity grid, the strategic deployment of energy storage devices throughout the power system becomes critically important. Energy storage technologies play a vital role in mitigating the mismatch between renewable power generation and consumption. Additionally, they enable the storage of surplus energy generated from renewable sources during periods of high production for later use during periods of low or no generation. Each technology possesses unique characteristics and applications, providing flexibility and diversity in energy storage solutions. This work provides an overview of different energy storage technologies and explores their role in establishing a sustainable power system.

Probiotics have become a potential way to change the microbiota, which allows for more personalized ways to improve health results. This abstract gives an outline of the most important parts of personalized microbiota regulation through probiotics. It focuses on effectiveness and mechanisms, clinical applications, safety and tolerability, formulations and delivery methods, and customized approaches. Many studies have looked into how and why probiotics change the microbiome. These studies show that probiotics can change the makeup and function of microbial communities. Probiotics have been shown to help treat a number of health problems, such as digestive problems, immune system problems, metabolic problems, and mental health problems. It is important for the success of probiotics to find out if they are safe and can be tolerated. Studies have shown that probiotics are usually safe for most people, but there are some things that need to be taken into account to make sure they are safe, especially for people who are weak. Formulations and transport methods are very important for making sure that probiotics are alive, stable, and delivered to the right places in the GI tract. Probiotic strains work better in the gut because of improvements in how probiotic preparation technologies protect and control the release of probiotic strains. Personalized methods take into account how each person's microbiome and health are different. By using individual microbiota profiling, custom probiotic approaches can be made to address specific microbial imbalances and promote a healthier microbial environment, which could improve treatment results. Even though individual methods show promise, there are still problems, such as the need to standardize microbiota profiling techniques, figure out how to understand data, and keep track of people over time. For personalized probiotics to reach their full potential and change the way patients are cared for based on the microbiota-host relationship, more study, technological advances, and teamwork are needed. In conclusion, probiotics can be used to change your microbiome in a way that is specific to you and your health goals. By using the power of individualized microbiota profiling, personalized probiotic treatments might be able to help with certain health problems and make the microbial environment better. Putting personalized probiotics into clinical practice and changing the way patients are cared for will require more study and partnerships between different fields.

Global warming is one of the problems of human civilization and decarbonization policy is the main solution to this problem. In this work, we propose an alternative method of using the gravity-assist by the asteroids to increase the orbital distance of the Earth from the Sun. We can manipulate the orbit of asteroids in the asteroid belt by solar sailing and propulsion engines to guide them towards the Mars orbit and a gravitational scattering can put asteroids in a favorable direction to provide an energy loss scattering from the Earth. The result would be increasing the orbital distance of the earth and consequently cooling down the Earth’s temperature. We calculate the increase in the orbital distance of the earth for each scattering and investigate the feasibility of performing this project.

In the Republic of Serbia, no comprehensive scientific multimethod research has been conducted to identify weaknesses and opportunities for improving the disaster risk management system. Regarding that, in the paper, author presents project description ,,Strengthening Integrated Disaster Risk Management System in Serbia - DISARIMES” which shall enable strengthening the disaster risk management system through research, development and innovative solutions implementation in the preparation, mitigation, response, remediation and post-disaster phases. The scientific importance of the projected research is reflected in the creation of assumptions for the advancement of theoretical and empirical knowledge in the scientific field of disaster risk management, bearing in mind that it is a relatively young scientific discipline in Serbia. The results of the project research will make it easier for decision makers in Serbia to understand the shortcomings of the system, but also provide innovative opportunities to improve their functioning in conditions of increasingly frequent and serious disasters. Establishing a scientific and professional society in the field of disaster risk management will create sustainable and necessary conditions for the transfer and improvement of knowledge and experience of importance for raising the level of operability of the system of protection and rescue of the Republic of Serbia in the event of disasters. A key contribution of the research findings will be to create a sustainable knowledge base that will be supported by the relevant amount of information regarding innovative capabilities and solutions identified as necessary to raise social resilience to a much higher level. In order to achieve the set goals, DISARIMES makes it possible, through a large number of SWOT analyses and other multimethod studies, to clearly identify and systematize the objective deficiencies and barriers encountered by the disaster risk management system in Serbia in all its stages before, during and after disasters, to identify and implement the appropriate solutions based on this. The objectives of the project are: to assess and identify strengths (advantages), weaknesses (disadvantages), opportunities (innovation potential) and threats for the disaster risk management system in Serbia; to develop and update RDI (research, development, innovation) Roadmap – knowledge databases with innovative solutions and other relevant information for improvement of the disaster risk management system; to fully deploy the DISARIMES scientific-professional network involving a broad range of the disaster risk management scientists and civil protection professions and organisations; to prepare the ground for the disaster risk management policy innovations.

In two dimensional disordered lattices, presence of interaction makes particles less localized than the non-interacting ones within the range of disorder strength W ≤ 4 and interaction strength V ≤ 4. If the interaction strength is higher, then particles localize more. Although, a localization-delocalization transition is not found, a transition with changes in the dominant correlations is observed. The nature of correlations between the particles as nearest neighbors become dominant beyond certain disorder strengths.

Phenotypic studies require large datasets for accurate inference and prediction. Collecting plant data in a farm can be very labor intensive and costly. This paper presents the design, architecture (hardware and software) and deployment of a distributed modular agricultural multi-robot system for row crop field data collection. The proposed system has been deployed in a soybean research farm at Iowa State University.

Abstract: The COVID-19 pandemic has disrupted global energy markets and caused significant socio-economic impacts worldwide. The pandemic has also impacted the energy sector, with demand for energy reducing due to lockdowns and reduced economic activity. Hence, this paper aims to provide a comprehensive and analytical review of the impact of COVID-19 on the energy sector and discuss the potential role of artificial intelligence (AI) in mitigating some of these effects. This review examines the changes in energy demand patterns resulting from the pandemic and the implications for the energy industry, including the shifts in policymaking, communication, digital technology, energy conversion, environmental, energy market, and power system operation. The analysis of the energy pattern is discussed according to the timeframes which include pre-, mid-, and post-pandemic periods. Furthermore, we explore how AI can be used to improve energy efficiency, optimize energy use, and reduce energy wastages. The potential for AI to contribute to developing more efficient and sustainable energy systems has also been addressed. Lastly, we highlighted AI’s challenges, which play a significant role in the energy sector's response to the COVID-19 pandemic. The recommendations for AI applications in the energy sector for the transition to a more sustainable energy future are outlined. Information corroborated in this review is expected to provide important guidelines for crafting future research areas and directions in preparing the energy sector for any unforeseen circumstances or pandemic-like situations.

Woody and non-woody plant species conservation is one of the ecosystem services provided by agroforestry (AF) systems across the agricultural landscapes. Little attention has been paid in as-sessing the plant diversity conservation of AF systems. The study was, thus, aimed to investigate plant species diversity, structure, and composition of three AF systems in Gedeo zone of south eastern Rift–valley Agricultural landscape of Ethiopia. The study was conducted in three agroforestry systems, namely, enset based, coffee–enset based (C-E based AF) and coffee-fruit trees–enset based (C-Ft-E based AF) agroforestry systems. Twenty farms representative of each AF system were randomly selected and inventory of the floristic diversity was employed in a 10×10 meter sample plot per farm. A total of 52 perennial woody and non–woody plant species belonging to 30 families were recorded. Of all species identified 33 (63.5%) were native, of which two species were registered as endemic. The highest proportion of native species was recorded in enset based AF (93.3%) and the least were in C–Ft–E based AF (59%). According to IUCN Red List and local criteria, 13 species were recorded as of interest for conservation in all AF systems. The woody species Prunus africana was identified as both vulnerable by IUCN Red List and rare for 25% of species that least occurred. The Shannon diversity index and richness showed that C–Ft–E based AF systems were significantly different from the two remaining AF systems. However, the species abundance and evenness did not show significant differences between the three AF systems. In general, retaining such number of woody and non–woody perennial plant species richness under AF systems of the present study underlines their potential for biodiversity conservation.

This paper discusses the concept of fractional derivative with complex order from the application point of view. It is shown that a fractional derivative is hermitian, if and only if the order is real. The hermitian part of complex order derivatives behave like allpass filters with almost logarithmic phase.

: This paper presents a couple of meal monitoring systems for senile dementia patients by using electronic weight and temperature sensors. These monitoring systems enable to convey the information of the amount of meal taken by the patients in real-time via wireless communication networks onto the mobile phones of their families or nurses in charge. Thereby, the nurses can easily spot the most desperate patient to take care of while the families can have relief to see the crucial information for survival of their parents at least three times a day. Meanwhile, the senile dementia patients tend to suffer the burn of their tongues because they can hardly recognize the temperature of hot meals served and therefore avoid the burn of tongues. This phenomenon can be discarded by utilizing the meal temperature monitoring system which displays alarm to the patients when the meal temperature is above the reference. These meal monitoring systems can be easily implemented by utilizing low-cost sensor chips and Arduino UNO boards so that elder-care hospitals and nursing homes can afford to exploit them with no additional cost. Hence, we believe that the proposed monitoring systems would be a potential solution to provide a great help and relief not only for the professional nursing nurses working in elder-care hospitals and nursing homes, but also for the families of the dementia patients.

Osteoimmunology was coined about twenty years ago to identify a strict cross talk between bone niche and immune system both in physiological and pathological activities, including cancer. Several molecules are involved in the complex interaction between bone niche, immune and cancer cells. The Receptor Activator ok NF-kB (RANK)/RANK Ligand (RANKL/Osteoprotegerin (OPG) pathway plays a crucial role in bone cells/cancer interactions with subsequently immune system control failure, bone destruction, inhibition of effect and metastasis outcome. The bidirectional cross talk between bone and immune system could became a potential target for anticancer drugs. Several studies evidenced a direct anticancer role with improved survival of bone-targeted therapies such as bisphosphonates and RANKL antagonist Denosumab. Conversely, initial data evidenced a possible anti-bone resorption effect of systemic anticancer drugs through and immunomodulation activity, i.e. new generation antiandrogens (Abiraterone) in prostate cancer. All data could open a future rationale of combined bone, immunologic and targeted therapies in cancer treatment.

Requirements for cloud services include security and privacy. Although many security patterns, privacy patterns, and non-pattern-based knowledge have been reported, knowing which pattern or combination of patterns to use in a specific scenario is challenging due to the sheer volume of options and the layered cloud stack. To deal with security and privacy in cloud services, this study proposes the Cloud Security and Privacy Metamodel (CSPM). CSPM uses a consistent approach to classify and support existing security and privacy patterns. In addition, CSPM is used to develop a security and privacy awareness process to develop cloud systems. The effectiveness and practicality of CSPM is demonstrated via several case studies.

To identify the exchange coefficients of a nonlinear polynomial tricompartmental general system of α+β , we follow the procedure; firstly, the recommended solution is to introduce an adequate time t*>0 in a determinable manner. That is, after injecting quantity a into the main compartment, wait a moment for the exchange in the polynomial α+β order nonlinear general system to settle, and then compare this compartment to compartment 2 at t*. Secondly, applying the Taylor formula will linearize the system and identify the exchange coefficients. Finally, we will prove that the linearization method is stable.

Uchino first initiated the study of generalized Reynolds operators on associative algebras. Recently, related research has become a hot topic. In this paper, we first introduce the notion of generalized Reynolds operators on Hom-Lie triple systems associated to a representation and a 3-cocycle. Then, we develop cohomology of generalized Reynolds operators on Hom-Lie triple systems with coefficients in a suitable representation. As applications, we use the first cohomology group to classify linear deformations and we study the obstruction class of an extendable order $n$ deformation. Finally, we introduce and investigate Hom-NS-Lie triple system as the underlying structure of generalized Reynolds operators on Hom-Lie triple systems.

This study addressed the need for efficient data collection in micro-mobility using low-end hardware, focusing on developing a system capable of handling large real-time data streams. We proposed a novel data collection system that leverages incremental learning techniques, enabling AI-based services for micro-mobility passengers through smartphones. Our approach utilizes 3-axis acceleration sensors integrated into micro-mobility devices, collecting motion data in real-time. This data is processed through an incremental learning pre-processing server, employing the Broad Learning System algorithm, to ensure robust performance in noisy, real-world environments. The use of incremental learning is pivotal, allowing our system to adapt continuously to new data, enhancing the accuracy and relevance of the AI services provided to passengers. This research not only advances the technical capabilities in micro-mobility data handling but also has the potential to enhance the overall passenger experience through improved AI-based services.

The present study compared the contralateral suppression and the amplitude of distortion product otoacoutsic emissions (DPOAEs) between smokers and non-smokers to determine the influence of smoking. Thirty smokers and thirty non-smokers within the age range of 18-40 years with a normal hearing sensitivity were considered for the study. For both the groups, DPOAEs were measured and the efferent auditory system functioning was measured by presenting the white noise of 50 dB HL to the contralateral side, while recording the DPOAEs. There was no significant effect of age on the amplitude of DPOAEs in both the groups. However, there were significant differences in the amplitude of DPOAEs between smokers and non-smokers. The amount of suppression and DPOAE amplitude were reduced in smokers when compared to non-smokers. The study found no significant correlation between the amount of smoking and amount of suppression between smokers and non-smokers. However, there were significant correlations between the amount of smoking and DPOAE at low and mid frequencies between smokers and non-smokers. Therefore, the present study highlights the increased damage to the efferent auditory system risk and the smoking ill-effects on the efferent auditory system.

This study aims to develop a performance evaluation system that can facilitate performance evaluation at region, hospital, and department levels to enable better cost management for sustainable development. A multi-level system of performance evaluation informs a hierarchical assessment of cost management from regions to hospitals to departments using diagnosis-related group (DRGs). Various metrics are developed employing the variances between targets and actuals where targets are determined from two perspectives: benchmarking using external regional prices and change management using internal data. Targets for the latter are statistically based and specifically incorporate variability. The model is applied to two hospitals, twenty departments, nine DRGs and 1071 inpatients. The analyses indicate that the approach can provide a practical evaluation tool that allows for particular characteristics at multiple levels. The system provides macro-micro and external-internal perspectives in performance, enabling high-level variances to be decomposed thereby identifying sources of performance variability and financial impact.

Sector coupling is one of the emerging topics in recent energy and climate change policy discussions. It can play a significant role in creating the pathway of a renewable-based energy system in the European energy sector. The North Sea region is very likely to play a key role in the transition to a sustainable energy system. Though different energy modelling approaches allow a versatile use, they lead to the problem of an unclear understanding of specific aspects of sector coupling, and the relevance of existing tools and techniques to model and analyze such a system. This paper is aimed at providing a comprehensive understanding of sector coupling and its incorporation in energy system models. Followed by a thorough literature review on sector coupling and energy system modelling, the paper outlines an approach to select an appropriate tool based on the specific rationales of the research. The paper also presents ‘Oemof’ as an open model tool to address the complex challenges of energy systems. The conclusions from the literature review provide a detailed understanding of the concept of sector coupling and indicate that it can be advantageous from the viewpoints of decarbonization, flexibility, network optimization, and system efficiency. To solve the coupling barriers, diversified techno-socio-economic circumstances should be taken into account through the use of model collaboration. It is also demonstrated how a list of appropriate tools for model collaboration can be picked up methodologically from an available wide range of models. Finally, ‘Oemof’ is hypothesized as a progressive tool to design a sector-coupled and renewable-based energy system in the North Sea region.

In 2011, commercial aviation contributed approximately 3.5% of global anthropogenic climate change through the emission of greenhouse gases during flight and operational non-CO2 climate effects. Over the last few years, numerous aviation-related organisations have set goals to reduce aviation’s climate impact. These goals, however, lack alignment, are poorly or ambiguously defined, or are internally inconsistent. This increases uncertainty about what aviation should work towards, how various stakeholders can contribute, and introduces problems with respect to accountability. In order to address this issue, this paper presents a comprehensive definition of a climate neutral air transport system as an “air transport system of which the climate effects of all its greenhouse gases and non-carbon dioxide effects throughout the entire life-cycle of each element of the system is balanced”. The proposed definition spans relevant system and encompasses all life cycle phases. To achieve a climate neutral air transport system by 2050, all life-cycle greenhouse gas emissions and non-CO2 climate effects remaining after in-sector reduction should be neutralised, as should all remaining non-CO2 climate forcing from emissions prior to 2050. Clarity on governance is furthermore needed, as the goal and associated targets proposed should be adopted globally.

Background: Underreporting of Visceral Leishmaniasis (VL) in India remains a problem to public health controls. Effective and reliable surveillance systems are critical for monitoring disease outbreaks and public health control programs. However, in India, government surveillance systems are affected by levels of scarcity in resources and therefore, uncertainty surrounds the true incidence of asymptomatic and clinical cases, affecting morbidity and mortality rates. The State of Bihar alone contributes up to the 40\% of the worldwide VL cases. The inefficiency of surveillance systems occurs because of multiple reasons including delay in seeking health care, accessing non-authentic health care clinics, and existence of significant asymptomatic self healing infectious cases. This results in a failure of the system to adequately report true transmission rates and number of symptomatic cases that have sought medical advice (thus, high underreporting of cases). Objectives and Methods: There are several methods to estimate the extent of underreporting in the surveillance system. In this research, we use a mathematical dynamic model and two different types of data sets, namely, monthly incidence for 2003-2005 and yearly incidence from 2006-2012 from the Bihar's 21 most VL affected districts out of its 38 districts. The goals of the study are to estimate critical metrics to measure level of transmission and to evaluate the estimation process between the two data sets and 21 districts. In particularly, our focus is on (i) estimating infection transmission potential, underreporting level in incidence and proportion of self-healing cases, (ii) quantifying reproduction number of the$R_0$, and (iii) comparing underreporting incidence levels and proportion of self-healing cases between the two periods 2003-2005 and 2006-2012 and between 21 districts. Results: Our research suggests that the number of asymptomatic individuals in the population who eventually self-heal may have a significant effect on the dynamics of VL spread. The estimated mean self-healing proportion (out of all infected) is found to be $\sim 0.6$ with only 7 out of 21 affected districts having self-healing proportion less than $0.5$ for both data sets. The estimated mean underreporting level is at least $64$\% for the state of Bihar. The estimates of the basic reproduction numbers obtained are similar in magnitude for most of the districts, being in the range of (0.88, 2.79) and (0.98, 1.01) for 2003-2005 and 2006-2012, respectively. Conclusions: The estimates for the two types (monthly and yearly) of temporal data suggest that monthly data are better for estimation if less number of data points are available, however, in general, using such data set results in larger variances in parameters as compared to estimates obtained through aggregated yearly data. Estimated values of transmission related metrics are lower than those obtained from earlier analyses in the literature, and the implications of this for VL control are discussed. The spatial heterogeneity in these control metrics increases the risk of epidemics and makes the control strategies more complex.

Ship speeds extracted from AIS data vary with ice conditions. We extrapolated this variation with SAR data to a chart of expected icegoing speed. The study is for the Gulf of Bothnia in March 2013 and for ships with ice class 1A Super that are able to navigate without icbreaker assistance. The speed was normalized to 0-10 for each ship. As the matching between AIS and SAR was complicated by ice drift during the time gap, from hours to two days, we calculated a set of local SAR statistics over several scales. We used random tree regression to estimate the speed. The accuracy was quantified by mean squared error (MSE), and the fraction of estimates close to the actual speeds. These depended strongly on the route and the day. MSE varied from 0.4 to 2.7 units² for daily routes. 65 % of the estimates deviated less than one unit and 82 % less than 1.5 units from the AIS speeds. The estimated daily mean speeds were close to the observations. Largest speed decreases were provided by the estimator in a dampened form or not at all. This improved when ice chart thickness was included as one predictor.

This article describes a novel topical composition constituted by gamma-amino butyric acid (GABA) and microbial chondroitin sulfate. This composition, formulated by the author and manufactured in a certified facility in the United States of America, exhibits potential for non-invasive intervention in anxiety management, sleep quality enhancement, and promotion of brain-related functions like meditation and nonlocal consciousness. The core component comprises GABA, a key inhibitory neurotransmitter within the central nervous system, complexed with a suitable carrier molecule, microbial chondroitin sulfate. This complexation aims to enhance transdermal absorption and optimize delivery of GABA to target tissues. The proposed mechanism of action involves modulation of GABAergic signal transduction pathways. Application of the topical composition allows GABA penetration into the skin and potentially deeper tissues, where it interacts with GABA receptors. This interaction leads to mental calmness and relaxation as assessed by electroencephalography. The influence of GABAergic signaling on brain circuits demonstrated in this article, when associated with meditation and nonlocal consciousness, suggests potential for the composition to support these practices. The advantage of such an approach consists in avoiding the potential systemic side effects associated with oral or injectable administration of GABA, anxiolytics or hypnotics. Furthermore, the combination of GABA and microbial chondroitin sulfate may offer synergistic benefits, potentially enhancing the overall biological effects. In conclusion, this article presents a novel topical approach for managing anxiety, enhancing sleep quality, and potentially facilitating meditation and nonlocal consciousness through modulation of GABAergic signaling pathways. While further research is necessary, the potential for a non-invasive and potentially side-effect-free intervention in these areas is promising.

A key goal of modern neuroscience involves understanding how connections in the brain form and function. Such a knowledge is essential to better inform how defects in the exquisitely complex steps of nervous system growth underlie neuropsychiatric and neurodevelopmental disorders. In the last 40 years, studies of the nervous system in the fruit fly Drosophila melanogaster enabled the discovery of a wealth of molecular and genetic mechanisms that drive the development of these synaptic connections – specialized cell-to-cell connections that are the essential substrate for information flow and processing in the nervous system. The major driver of knowledge focused on studies at the neuromuscular junction due to its ease of examination. Analogous studies in the central nervous system lagged behind due to a lack of genetic accessibility of specific central neuron classes, appropriate synaptic labels compatible with cell-type specific access, and high resolution, quantitative imaging strategies. However, understanding how synapses in central circuits form remains a prerequisite to understanding brain development. In the last decade, a host of new tools and techniques made possible the extension of genetic studies of synapse organization into central circuits and greatly enhanced our understanding of central synapse formation, organization, and maturation. In this review, we consider the current state-of-the-field, focusing on two major elements. We first discuss the tools, technologies, and strategies developed to visualize and quantify synapses in vivo in genetically identifiable neurons of the Drosophila CNS. Second, we explore in depth how these tools enabled a clearer understanding of synaptic development and organization in different circuits of the fly brain and discovered novel molecular mechanisms that underlie synapse formation. These studies establish multiple brain regions in the fly as powerful in vivo genetic models that offer novel insights into synaptogenic regulators and mechanisms of neural development.

In the first year of its appearance, the 2019 coronavirus disease (COVID-19) has affected more than 150 million individuals and killed 3 million people worldwide. The pandemic has also triggered numerous global initiatives to tackle the newly emerging disease, including the development of SARS-CoV-2 vaccines and the attempt to discover potential pharmacological therapies. Nonetheless, despite the success of SARS-CoV-2 vaccines development, COVID-19 therapy remains challenging. Several repurposed drugs that were documented to be useful in small clinical trials have been shown to be ineffective in larger studies. Additionally, the pathophysiology of SARS-CoV-2 infection displayed the predominance of hyperinflammation and immune dysregulation in inducing multiorgan damage. Therefore, the potential benefits of both immune modulation and suppression in COVID-19 have been extensively discussed. Here, we reviewed the roles of immunomodulation as potential COVID-19 pharmacological modalities based on the existing data and proposed several new immunologic targets to be tested in the foreseeable future.

Manufacturing is a significant sector of the economy in many nations and is frequently regarded as an engine of economic expansion, particularly in developing nations. Despite its importance, the metal sector is seen as unsafe due to frequent and high accident rates as well as worker health issues. Therefore, the primary goal of this research is to create a safety model with the goal of development in occupational safety and health in order to reduce workplace injuries, diseases, and deaths in the Akaki Basic Metal Industry. The hypothesized model was developed and tested on a sample 215 respondents who worked for production businesses. The Statistical Package for the Social Sciences (SPSS) version 23.0 was used to enter and analyze the acquired data, and the Analysis Moment of Structure (AMOS) version 21 software was used to build the model. Through the use of structural equation modeling (SEM) and confirmatory factor analysis (CFA), research models were examined and confirmed. A good-fit structural model (PCLOSE=0.001, Goodness of Fit Index=0.971, Root Mean Square Error of Approximation=0.121, Comparative Fit Index=0.986 and TLI =0.906) indicated that Safety culture, safety police and safety climate constructs direct influence on firm productivity. The new structural model can be used to provide better understanding of the links between firm productivity indicators and contributing components, and make stronger recommendations for effective intervention in construction projects

Nanomaterials such as pH-responsive polymers are promising for targeted drug delivery systems, due to the difference in pH between tumor and healthy regions. However, there is a significant concern about the application of these materials in this field due to their low mechanical resistance, which can be mitigated by combining these polymers with mechanically resistant inorganic materials such as mesoporous silica nanoparticles (MSN) and hydroxyapatite (HA). Mesoporous silica has interesting properties such as high surface area and hydroxyapatite has been widely studied to aid in bone regeneration, providing special properties adding multifunctionality to the system. Furthermore, fields of medicine involving luminescent elements such as rare earth are an interesting option in cancer treatment. The present work aims to obtain a pH-sensitive hybrid system based on silica and hydroxyapatite with photoluminescent and magnetic properties. The nanocomposites were characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), nitrogen adsorption methods, CHN elemental analysis, Zeta Potential, scanning electron microscopy (SEM), and transmission electron microscopy (TEM), vibrational sample magnetometry (VSM), and photoluminescence analysis. Incorporation and release studies of the antitumor drug doxorubicin were performed to evaluate the potential use of these systems in targeted drug delivery. The results showed the luminescent and magnetic properties of the materials and showed suitable characteristics for application in the release of pH-sensitive drugs.

The past years have shown the widespread vulnerability of agro-food systems and rural diets to external perturbations such as wars, climate events, and pandemics. Experiencing numerous obstacles, Cuba constitutes an example of success in the transition to agroecological sustainability models. This article characterizes how processes of agricultural change, local development, and industrial degrowth have impacted food availability and dietary diversity among rural livelihoods in the municipality of Yaguajay, Sancti Spíritus, for the past forty years (1980s-2020s). It integrates findings from focus groups, repeated nutritional surveys, and interviews carried out between 2016 and 2022 among residents of the towns of Yaguajay and La Picadora. The goal is to identify effects and response strategies within agro-food systems of rural populations. Distinguishing between periods of abundance and shortage, our findings show two counterpoints: intensive sugar monocrop cultivation which resulted in high dietary variety; and economic crises in 1990s and during the last period of the pandemic, which have led to significant dietary adjustments. The article concludes underscoring the importance of comprehensive assessments of dietary strategies to elicit what agroecological transitions mean for local realities and of the value of food consumption and small-holder production experiences to understand the limits to sustainable transformations.

Agricultural extension and advisory services in Africa have significant impact on food security as well as economic and social development. Recent moves towards a pluralistic delivery system, including the emergence of private-sector led initiatives in many countries are subject of policy and academic discourse. Our study used an adapted, fit-for-purpose market systems development framework to review available research in extension and advisory services in selected sub-Sahara Africa countries. Using a literature survey methodology, we report evidence of multiple actors in extension delivery, findings that point towards evolution towards mixed delivery as well as objectives. While there are significant uptake of cost-recovery approaches among commercially-oriented farmers, many smallholder farmers still depended on donor-funded services. Our review adds to existing knowledge through incorporating a market systems development framework, which extends the often-used willingness to pay approach, and highlights the need for merger of the public and private-sector objectives to achieve developmental outcomes.

With confirmed COVID-19 cases surpassing the 8.5 million mark around the globe, there is an imperative need to deepen the efforts from the international scientific community to gain comprehensive understanding of SARS-CoV-2. Although the main clinical manifestations are associated with respiratory or intestinal symptoms, reports of specific and non-specific neurological signs and symptoms, both at presentation or during the course of the acute phase, are increasing. Approximately 25-40% of the patients present neurological symptoms. The etiology of these neurological manifestations remains obscure, and probably involves several direct pathways, not excluding the direct entry of the virus to the Central Nervous System (CNS) through the olfactory epithelium, circumventricular organs, or disrupted blood-brain barrier (BBB). Furthermore, neuroinflammation might occur in response to the strong systemic cytokine storm described for COVID-19, or due to dysregulation of the CNS angiotensin system. Descriptions of neurological manifestations in patients in the previous coronavirus (CoV) outbreaks have been numerous for the SARS-CoV and lesser for MERS-CoV. Strong evidence from patients and experimental models suggests that some human variants of CoV have the ability to reach the CNS and that neurons, astrocytes and/or microglia can be target cells for CoV. A growing body of evidence shows that astrocytes and microglia have a major role in neuroinflammation, responding to local CNS inflammation and/or to dysbalanced peripheral inflammation. This is another potential mechanism for SARS-CoV-2 damage to the CNS. In this work we will summarize the known neurological manifestations of SARS-CoV-2, SARS-CoV and MERS-CoV, explore the potential role for astrocytes and microglia in the infection and neuroinflammation, and compare them with the previously described human and animal CoV that showed neurotropism. We also propose possible underlying mechanisms by focusing on our knowledge of glia, neurons, and their dynamic intricate communication with the immune system.

This study investigates the evolution of the vegetation and beach dune system at Enebrales Beach in Huelva, Spain, from 2003 to 2022. Utilizing orthophotographs and advanced GIS techniques, we analyzed changes in natural surface areas, vegetation cover, and dune stability. The results demonstrate significant ecological improvements: a recovery of 25,300 m² in dunes and 7,400 m² in beach areas, and a total vegetation cover increase of nearly 10,000 m². Interventions, including reforestation with native species and the stabilization of dune ridges, have been effective in enhancing the coastal ecosystem's resilience. Additionally, the beach's carrying capacity increased, allowing for approximately 2,000 more users without compromising ecological integrity. These findings underscore the importance of continued conservation efforts and adaptive management to maintain and further improve the ecological health and sustainability of Enebrales Beach Dune.

Switzerland, a wealthy country, has a cutting-edge healthcare system, yet per capita, it emits over one ton of CO2, ranking among the world's most polluting healthcare systems. To estimate the carbon footprint of the healthcare system of Geneva’s canton, we collected raw data on the activities of its stakeholders. Our analysis shows that when excluding medicines and medical devices hospitals are the main greenhouse gas emitter by far, accounting for 48% of the healthcare system’s emission, followed by nursing homes (20%), private practice (18%), analysis laboratories (7%), dispensing pharmacies (4%), the homecare institution (3%) and the ambulance services (

Abstract: Mast cell (MC) specific proteases are of particular interest for space biology and medicine due to their biological activity in regulating targets of a specific tissue microenvironment. MC tryptase and chymase obtain the ability to remodel connective tissue through direct and indirect mechanisms. Yet, MC specific protease expression under space flight conditions has not been adequately investigated. Using immunohistochemical stainings, we analyzed in this study the protease profile of the jejunal, gastric and hepatic MC populations in three groups of Mongolian gerbils - vivarium control, synchronous experiment, and 12-day orbital flight on the Foton-M3 spacecraft, - and in two groups - vivarium control and anti-orthostatic suspension - included in the experiment simulating effects of weightlessness in the ground-based conditions. After a space flight, there was a decreased number of MCs in the studied organs combined with an increased proportion of chymase-positive MCs and MCs with a simultaneous content of tryptase and chymase; the secretion of specific proteases into the extracellular matrix increased. These changes in the expression of proteases were observed both in the mucosal and connective tissue MC subpopulations of the stomach and jejunum. Notably, the relative content of tryptase-positive MCs in the studied organs of the digestive system decreased. Space flight conditions simulated in the synchronous experiment caused no similar significant changes in the protease profile of MC populations. The space flight conditions resulted in an increased chymase expression combined with a decreased total number of protease-positive MCs apparently due to participating in the processes of extracellular matrix remodeling and regulating the state of the cardiovascular system.

Sensors and actuators are fundamental units in Cyber-Physical and Internet of Things systems. Because they are included in a variety of systems, using many technologies, it is very useful to characterize their functions abstractly by describing them as Abstract Entity Patterns (AEPs), that are patterns that describe abstract conceptual entities. For concreteness, we study them here in the context of autonomous cars. An autonomous car is a complex system because, in ad-dition to its own complex design, it interacts with other vehicles and with the surrounding in-frastructure. To handle these functions, it must incorporate various technologies from different sources. An autonomous car is an example of a Cyber-Physical System, where some of its func-tions are performed by Internet of Things units. Sensors are extensively used in autonomous cars to measure physical quantities; actuators are commanded by controllers to perform appro-priate physical actions. From AEPs we can derive concrete patterns, a structure combining re-lated AEPs is an Entity Solution Frame (ESF). Both sensors and actuators are susceptible to mali-cious attacks due to the large attack surface of the system where they are used. Our work is in-tended to make autonomous cars more secure, which also increases their safety. Our final objec-tive is to build a Security Solution Frame for sensors and actuators of autonomous cars that will facilitate their secure design. A Security Solution Frame is a solution structure that groups to-gether and organizes related security patterns. This article is the first stage of a secure unit that can be used to design not only secure autonomous cars but also any system where sensors and actuators are used. This paper concentrates on AEPs and ESFs for sensors and actuators; that is, on the functional aspects of these devices.

This paper shows the results of applying high-resolution Unmanned Aircraft System (UAS) photogrammetric surveying on a large landslide. A real case study, where permanently installing GCPs could be complex, where natural shaped and formed land pose severe limitations in deploying ground targets with optimal geometric configuration. We analysed performances in terms of survey accuracy obtained by performing photogrammetric surveys through the Zenmuse P1 DJI optical camera and Phantom 4 Pro 2. In combination with DJI Matrice 300 UAS, the P1 camera allows direct georeferencing through GNSS observations in RTK mode. Photogrammetric surveys, performed through different georeferencing methods, have been compared. Several targets have been permanently installed on the ground over the maximum vegetation height to guarantee long-lasting reference over the years in the area, which is characterised by a diffuse short vegetation coverage. Multitemporal UAS surveys have been then compared using Digital Image Correlation (DIC) algorithms, and deformation maps have been produced. Afterwards, DIC results were compared with observations made by the GNSS ground-based permanent receivers resulting in a standard deviation of 0,077 m. Through results analysis, good accordance between ground-based GNSS observations and DIC analysis on the photogrammetric surveys have been identified for the same time span. To conclude, this type of landslide presents a moderate deformation speed; in such a case, effective deformations monitoring could be achieved using pseudo-direct georeferencing, which permitted a 0.24 m accuracy on the whole tested area.

In this study, we examine the relationship of bank level lending and borrowing decisions and the risk preferences on the dynamics of the interbank lending We develop an agent-based model that incorporates individual bank decisions using the temporal difference reinforcement learning algorithm with empirical data of 6600 S. banks. The model can successfully replicate the key characteristics of interbank lending and borrowing relationships documented in the recent literatur A key finding of this study is that risk preferences at individual bank level can lead to unique interbank market structures which are suggestive of the capacity that the market responds to surprising

A single Information security is of pivotal concern for consistently streaming information over the widespread internetwork. The bottleneck flow of incoming and outgoing data traffic introduces the issue of malicious activities taken place by intruders, hackers and attackers in the form of authenticity desecration, gridlocking data traffic, vandalizing data and crashing the established network. The issue of emerging suspicious activities is managed by the domain of Intrusion Detection Systems (IDS). The IDS consistently monitors the network for identifica-tion of suspicious activities and generates alarm and indication in presence of malicious threats and worms. The performance of IDS is improved by using different signature based machine learning algorithms. In this paper, the performance of IDS model is determined using hybridization of nestrov-accelerated adaptive moment estimation –stochastic gradient descent (HNADAM-SDG) algorithm. The performance of the algorithm is compared with other classi-fication algorithms as logistic regression, ridge classifier and ensemble algorithm by adapting feature selection and optimization techniques

Abstract: The aim of the present study was to identify the age and sex-related associations between marital status with PA and TV time. We used data from Vigitel, an annual telephone survey started in 2006 in Brazil. We applied a complex sample logistic regression model to estimate the odds for PA and TV time comparing marital statuses according to age and sex subgroups, independent of obesity, hypertension, diabetes, self-assessed poor health, and smoking. Our sample included 561,837 individuals with a TV time > 3 h/day (prevalence = 25.2%) and PA > 150 min/week (prevalence = 35%). Compared to single individuals, married men and women were less likely to watch TV more than 3 h/day in participants > 30 years old. When compared to single, married participants were less likely to do more than 150 min of PA/week at younger age groups. Married women older than 40 years were more likely to do more than 150 min of PA/week than the single ones, while there were no differences among married men by age group. In conclusion, married individuals are less likely to spend more than 3 hours a day watching TV than single individuals. Single men and women were more likely to do more than 150 min of PA/week at younger age groups and married women older than 40 years were more likely to do 150 min of PA/week than single women.

This research focuses on developing a Student Performance Evaluation System to enhance effectiveness and oversight in higher education. The system aims to address challenges faced by instructors in evaluating student performance using a distributed system approach. Agile methodology is employed in development, and database replication techniques are applied for data synchronization. System features include registration, assessment form creation, assessment submission, statistical visualization, and access to assessment history. The system is designed to improve efficiency and transparency in the assessment process. Key features of the system include registration process, assessment form creation, assessment submission, statistical visualization, and access to assessment history. Its goal is to enhance efficiency and transparency throughout the assessment process. The article details the system workflow and the roles played by Admins, Instructors, and students in system usage. Additionally, it discusses the back-end development model and pathways, as well as the performance testing results. Performance testing indicates that the system achieves high throughput of up to 21.55 requests per second, with an average response time of only 34 milliseconds and an error rate of zero percent. These results affirm that the system efficiently handles user loads and nearly instantaneously responds to requests, providing an optimal user experience in the context of student performance evaluation in higher education.

The low relative humidity (RH) levels in a greenhouse during the daytime in a strawberry (Fragaria × ananassa Duch) cultivation period negatively affect the growth of strawberry related to photo-physiology. Therefore, this study was conducted to confirm an efficient RH management method by analyzing the phenotypic characteristics related to photo-physiology by controlling the RH in a greenhouse during the daytime with a fog system. Strawberry plants were grown respectively in a greenhouse affected by natural RH changes (control) and in a greenhouse with 40% ~ 50% RH adjusted during the daytime using a fog system. In the greenhouse, with controlled RH, the temperature decreased, and the RH was higher in the initial growth stage of strawberry planting than the control. It was observed a significant increase in the survival rate of the strawberry plant, as well as the incidence of powdery mildew, was lowered. In addition, the photosynthetic rate and OJIP chlorophyll a fluorescence transients related to photosystem II efficiency of strawberry leaves were significantly higher in the fog treatment than in the control. In winter, during the day, the number of days on which the temperature dropped below 20℃ has increased, the greenhouse temperature with controlled RH was lower due to the fog system. When the yield per strawberry plant in January and February was investigated, the control was higher than the RH treatment. Therefore, RH management using a fog system must be controlled at a level where a temperature range is adequate for plant growth, in which the efficient control of these parameters increases strawberry productivity.

Our recent study detected the expression of a tissue Renin-Angiotensin System (tRAS) in human intervertebral discs (IVDs). The present study sought to investigate the impact of angiotensin II receptor type 1 (AGTR1) antagonist losartan on human nucleus pulposus (NP) cell inflammation and degeneration induced by tumor necrosis factor-α (TNF-α). Human NP cells (4 donors, Pfirrmann grade 2-3, 30-37 years old, male) were isolated and expanded. TNF-α (10 ng/mL) was used to induce inflammation and degeneration. We examined the impact of losartan supplementation and measured gene expression of tRAS, anabolic, catabolic, and inflammatory markers in NP cells after 24 h and 72 h of exposure, respectively. T0070907, a PPAR-gamma antagonist, was applied to examine the regulatory pathway of losartan. Losartan (1 mM) significantly impaired TNF-α induced increase of pro-inflammatory (nitric oxide and TNF-α), catabolic (matrix metalloproteinases), and tRAS (AGTR1a and Angiotensin Converting Enzyme) markers. Further, losartan maintained the NP cell phenotype by upregulating aggrecan and downregulating collagen type I expression. In summary, losartan showed anti-inflammatory, anti-catabolic, and positive phenotype modulating effects on human NP cells. These results indicate that tRAS signaling plays an important role in IVD degeneration, and tRAS modulation with losartan could represent a novel therapeutic approach.

Objective: To investigate the causal relationships between intestinal microbiome biomarkers and colorectal cancer (CRC) and its subtypes. Method: The meta-analysis method was used to integrate the largest genome-wide association study data from the MiBioGen consortium (n=18,340). Single nucleotide polymorphisms (SNPs) significantly associated with intestinal microbial relative abundance were extracted as instrumental variables (IVs). Based on the Finnish database (R9 version) with 326,322 participants, the two-sample Mendelian randomization (MR) analysis was adopted to explore the causal relationships between intestinal microbes and CRC and its specific subtypes, such as colon cancer and rectal cancer. Result: A total of 3,310 SNPs were screened as IVs. The MR analysis revealed significant associations between various microbial traits and CRC, including its subtypes. Specific microbes, such as Erysipelotrichaceae, exhibited protective effects, while others, like Orato, were demonstrated as risk factors. Notably, specific biomarkers (e.g., Streptococcus thermophilus) for CRC were determined. This study provides new insights and potential targets for the pathogenesis, diagnosis, and treatment of CRC. Conclusion: Significant causal relationships exist between intestinal microbes and CRC and its pathological types. Specific microbes, such as Erysipelotrichaceae, play a protective role, whereas others, like Orato, serve as risk factors. These findings offer new insights into the pathogenesis of CRC and provide a foundation for future prevention and treatment strategies.

This study explores the relationship between positive and negative habits and their rewards over time. Using a bibliographic and documentary approach, we analyze how the temporality of rewards influences the formation and maintenance of habits. We developed the "habit chart", which shows that positive habits, such as reading, healthy eating, physical exercise, meditation and personal relationships, offer incremental and lasting rewards. In contrast, negative habits such as sugar consumption, excessive use of social media and a sedentary lifestyle provide immediate gratification followed by a sharp decline. The analysis was based on studies such as those by Warburton et al. (2006), Lally et al. (2010), and Hu (2003) for positive habits, and Malik et al. (2010) and Kross et al. (2013) for negative habits. We conclude that practical strategies, such as financial incentives and creating enabling environments, can make long-term rewards more tangible, promoting the adoption of healthy behaviors. This study reinforces the importance of the temporality of rewards in habit formation and suggests evidence-based interventions to improve quality of life and general well-being.

Identification of drug targets and biochemical investigations on mechanisms of action is a are major issues in modern drug development. The present article reviews the classical “one drug” – “one target” paradigm. Novel methods for target deconvolution and for investigation of resistant strains based on protein mass spectrometry have shown that multiple gene products and adapta-tion mechanisms are involved in responses of pathogens to xenobiotics. This review is focused on protozoan pathogens. The conclusions can, however, be extended to chemotherapies against other pathogens or cancer. For this review we have searched Pubmed (pubmed.ncbi.nlm.nih.gov) and Web of Science (webofscience.com) using the key words listed below (status May 2024)

Context. During the COVID-19 pandemic, patient care was mainly organised around the hospital. Pre-hospital care has, to our knowledge, never been evaluated. Objective: To evaluate the impact of pre-hospital pathways on hospitalisation during the last part of the pandemic. Design. This was a monocentric retrospective analysis of prospectively collected medical records. Data from patients admitted to our institute between 1 February and 7 March 2022 were analysed. Main Outcome Measure(s): The primary outcomes were defined as the number of hospitalisations, resuscitations, and deaths at the time of interview and in the subsequent 30 days. The main explanatory variables were times from onset of symptoms to care, age, gender, News2 score, comorbidities, and pre-hospital pathways and their duration. Results: Three pre-hospital pathways have been identified: a pathway in which the patient consults a general practitioner for a test (PHP1); a pathway in which the patient consulted for care (PHP2); and no pre-hospital pathway and direct admission to hospital (PHP3). Factors independently associated with outcome (hospitalisation) were being male (OR 95% CI; 2.21 [1.01–4.84], p=0,04), News2 score (OR 95% CI; 2.04 [1.65–2.51], p<0.001), obesity (OR 95% CI; 3.45 [1.48–8.09], p=0.005), D-dimers > 0.5 µg/ml (OR 95% CI; 3.45 [1.47–8.12], p=0.005), prolonged time from symptoms to hospital care (PHP duration) (OR 95% CI; 1.07 [1.01–1.14], p=0.03). All things being equal, patients with a “PHP2” pre-hospital pathway had a higher probability of hospitalisation compared to those with a “PHP3” pre-hospital pathway (OR 95% CI; 4.31 [1.48–12.55], p=0.007). Conclusions. Along with recognised risk factors such as gender, News 2 score, and obesity, the patient’s pre-hospital pathway is an important risk factor associated with hospitalisation.

This paper is concerned with the optimal linear quadratic Gaussian (LQG) control problem for discrete time-varying system with multiple input delays and multiplicative noises. The main contributions are two-fold. Firstly, when the state variables can be observed exactly, we obtain a necessary and suffcient condition for the multiple-delays system in terms of the non-homogeneous relationship between the state and costate, which is the solution to the coupled forward and backward stochastic difference equations. Secondly, when the state variables are partially observed, we derive a suboptimal linear output feedback controller for the discrete-time system based on the obtained results of the optimal LQG control. Numerical examples are shown to illustrate the proposed algorithm.

With increasing constraints on energy and resource markets and the non-decreasing trend in energy demand, the need for relevant clean energy generation and storage solutions is growing and is gradually reaching the individual home. But small-scale energy storage is still an expensive investment in 2022 and the risk/reward ratio is not yet attractive enough for individual homeowners. One solution is for homeowners not to store excess clean energy individually but to produce hydrogen for mutual use. In this paper a collective production of hydrogen for a daily filling of a bus is considered. Following our previous work on the subject, the investigation consists of finding an optimal buy/sell rule to the grid, and the use of the energy with an additional objective: mobility. The dominant technique in the energy community is reinforcement learning, which is however difficult to use when the learning data is limited as in our study. We chose a less data-intensive and yet technically well-documented approach. Our results show that rulebooks, different but more interesting than the usual robust rule, exist and can be cost-effective. But they require fine-tuning as to not deteriorate system performance. In some cases, it is worth missing the H2 production requirement in exchange for higher economic performance.

The magnetic navigation system (MNS) with gradient and uniform saddle coils is one of the effective systems to manipulate various medical magnetic robot due to its compact structure and uniformity of the magnetic field and field gradient. However, it has limited operating time and large inductance effect due to the high current density and numerous turns of coils, respectively. In this paper, we propose an optimization methodology of the MNS considering the current density and inductance of the coils. We introduce objective functions, constraints, and design variables of the MNS. Then, the MNS was designed by an optimization algorithm. The constructed MNS was compared with the conventional MNS, and it could generate 22 % stronger magnetic field or field gradient while the maximum three-dimensional rotating magnetic field was improved by 42 %. We also demonstrated an unclogging performance of a helical robot was improved by 54 % with the constructed MNS.

In real financial market, the delayed market feedback and the delayed effect of government macro-control are inevitable. And both the delay of market feedback and the delay of macro-control effect bring about the mathematical difficulties in studying stabilization and synchronization of the hyper-chaotic financial system. However, employing Lyapunov function method, differential mean value theorem, suitable bounded hypotheses and pulse control technology results in the globally asymptotical stabilization and synchronization criteria. It is the first paper to drive the stabilization and synchronization criteria under the assumptions of the double delays. Finally, numerical examples illuminate the effectiveness of the proposed methods.

This paper reports on the changing dynamics of a small town’s social-ecological system (SES) concerning oil and gas industry boom-bust economic cycles and both the vulnerability and resilience of the town over the past 30 years. With the goal to understand how resource-based single industry impact social-ecological systems, we developed indicators of human and environmental well-being and assessed them. Seven indicators include labor force distribution, education, oil price, household income, water quality, air quality, and land cover land use. Over this period, Drayton Valley, Canada quadrupled in size, with more than 20% of the population working in the oil and gas sector. Median income rose to 42% above the national average despite the population lagging national benchmarks for educational attainment. There have also been dramatic fluctuations in levels of fluoride, phosphorus, and other chemicals in water quality samples, implying a correlation with fossil fuel extractive activities over this period. Land cover land use change analysis shows a decreased area of water bodies, wetland, and forests, and increased built capital and agricultural land. While economic boom cycles have led to cash inflows, an exclusive focus on the benefits of the oil and gas industry may leave those dependent on the industry vulnerable to social and environmental risk factors during bust cycles that are beyond their control in the everchanging global oil economy. This phenomenon which has been referred to as the “resource curse” suggests the need to anticipate cyclical (or more sustained) periods of low levels of oil and gas production. These results suggest that single boom-bust economies impact every aspect of social-ecological systems. Therefore, a sustainable development plan that comprehensively considers not only economic growth, but also diversification, environment protection, and strategic land use planning is indispensable to ensure the long-term development of communities that depend upon extractive industries.

The ubiquity of mobile sensors (such as GPS, accelerometer and gyroscope) together with increasing computational power have enabled an easier access to contextual information, which proved its value in next generation of the recommender applications. The importance of contextual information has been recognized by researchers in many disciplines, such as ubiquitous and mobile computing, to filter the query results and provide recommendations based on different user status. A context-aware recommendation system (CoARS) provides a personalized service to each individual user, driven by his or her particular needs and interests at any location and anytime. Therefore, a contextual recommendation system changes in real time as a user’s circumstances changes. CoARS is one of the major applications that has been refined over the years due to the evolving geospatial techniques and big data management practices. In this paper, a CoARS is designed and implemented to combine the context information from smartphones’ sensors and user preferences to improve efficiency and usability of the recommendation. The proposed approach combines user’s context information (such as location, time, and transportation mode), personalized preferences (using individuals past behavior), and item-based recommendations (such as item’s ranking and type) to personally filter the item list. The context-aware methodology is based on preprocessing and filtering of raw data, context extraction and context reasoning. This study examined the application of such a system in recommending a suitable restaurant using both web-based and android platforms. The implemented system uses CoARS techniques to provide beneficial and accurate recommendations to the users. The capabilities of the system is evaluated successfully with recommendation experiment and usability test.

Geopolitical situations, such as the Ukraine–Russia war, the Israel–Hamas war, and pandemics, can disrupt supply chains, such as the rerouting of oil tankers via South Africa to avoid the impact of the Israel–Hamas conflict. These events will probably occur again, but they are black swan events and difficult to predict. How can firms manage these events to minimise disruption to their supply chains? This paper proposes that a blockchain architecture has the potential to build resilience in supply chains and give them the flexibility to withstand the challenges of black swan events. The decentralisation ability of blockchain technology enables separation of the discrete elements of a sustainable supply chain so contagion does not impact the overall sustainable supply chain. To achieve flexibility in a sustainable supply chain ecosystem requires governance, leadership, and management. Also, artificial intelligence (AI), in conjunction with blockchain, is a technology that can enhance the flexibility and resilience of the supply chain. Thus, AI can act as a controller, co-ordinator, and an integrator in sustainable supply chain systems.

Software-defined networking (SDN) divides a traditional network into a programmable data plane and a centralized control plane. This technology is expected to transform traditional network companies that provide flexible and intelligent network operations. The core component utilized to oversee every data plane action is the controller in the control plane. In order to achieve optimal performances, the controller’s performance and capabilities are therefore crucial. There are lots of controller research available in existing literature. Nevertheless, no qualitative comparison study of OpenFlow-enabled distributed but logically centralized controllers exists for them. This article also includes a quantitative investigation of the performance of several distributed but logically centralized SDN controllers in custom network scenarios using Mininet, as well as a thorough qualitative comparison of them. More precisely, we give a qualitative evaluation of their attributes and classify and categorize 13 distributed but logically centralized SDN controllers according to their capabilities. Additionally, we offer a comprehensive SDN emulation tool called Mininet-based SDN controller performance assessment in this study. Using six performance metrics—bandwidth, round- trip time, delay, jitter, packet loss, and throughput—this work also assesses five distributed but logically centralized controllers against two custom network scenarios (uniform and non-uniform host distribution). Our investigation shows that the OpenDayLight controller performs the best across all performance criteria, with the exception of delay, packet loss and round trip time, where the Ryu controller excels. In the entire experiment, the HyperFlow and ONOS controller performs the worst in terms of all performance metrics. Finally, we discuss detailed research findings on the performance. These experimental results provide a decision-making guideline when selecting a controller.

Although global life expectancy has increased over the past 20 years due to improvements in managing infectious diseases, one in five people still succumbs to infections. Humanity is tirelessly working towards developing vaccines and antimicrobial agents in response to this ongoing threat. However, pathogens continue to acquire numerous resistance mechanisms and proliferate. Meanwhile, the COVID-19 pandemic has prompted us to recognize that focusing solely on the killing strategies of immunology and microbiology in complex and multisystemic infectious diseases is insufficient for understanding survival. In essence, there is a need for a treatment approach centered on disease tolerance, capable of alleviating pathology and/or promoting physiological functions in conjunction with the existing strategies of host immune response and pathogen destruction. Against this backdrop, this narrative review comprehends and introduces microbiome therapeutics, which recently garnered attention as next-generation treatments regarding two defense strategies against infectious diseases. First, we delineate the application of existing probiotics and then the microbiome in infectious diseases. Subsequently, we expand this concept to encompass host microbiome crosstalk and present related microbiome therapeutics' current status and direction. Ultimately, the review presents a fresh perspective on understanding microbiome therapeutics in infectious diseases based on a cooperative defense system.

Cerebral ischemia, which is a leading cause of disability and mortality worldwide, sets off a chain of molecular and cellular pathologies that are associated with some central nervous system (CNS) disorders, mainly including ischemic stroke, Alzheimer's disease (AD), Parkinson's disease (PD), epilepsy and other CNS diseases. In recent times, despite significant advancements in the treatment of the pathological processes underlying various neurological illnesses, effective therapeutic approaches specifically targeted at minimizing the damage of such diseases remain absent. Remarkably, ischemia causes severe damage to cells in Ischemia-associated CNS Diseases. Cerebral ischemia initiates oxygen and glucose deprivation, which subsequently promotes mitochondrial dysfunction, including MPTP opening, mitophagy dysfunction, and excessive mitochondrial fission, triggering various forms of cell death, such as autophagy, apoptosis, as well as ferroptosis. Ferroptosis, a novel type of regulated cell death (RCD), is characterized by iron-dependent accumulation of lethal reactive oxygen species and lipid peroxidation. Mitochondrial dysfunction and ferroptosis both play critical roles in the pathogenic progression of Ischemia-associated CNS Diseases. In recent years, growing evidence has indicated that mitochondrial dysfunction interplays with ferroptosis to aggravate cerebral ischemia injury. However, the potential connections between mitochondrial dysfunction and ferroptosis in Cerebral Ischemia have not yet been clarified. Thus, we analyze the underlying mechanism between mitochondrial dysfunction and ferroptosis in Ischemia-associated CNS Diseases. We also discovered that GSH depletion and GPX4 inactivation cause lipoxygenase activation and calcium influx following cerebral ischemia injury, resulting in MPTP opening and mitochondrial dysfunction. Additionally, dysfunction in mitochondrial electron transport and an imbalanced fusion-to-fission ratio can lead to the accumulation of reactive oxygen species and iron overload, which further contribute to the occurrence of ferroptosis. This creates a vicious cycle that continuously worsens cerebral ischemia injury. In this study, our focus is on exploring the interplay between mitochondrial dysfunction and ferroptosis, which may offer new insights into potential therapeutic approaches for the treatment of Ischemia-associated CNS Diseases.

Safe, high-quality and economical electric energy transportation is the basic requirements of modern power system operation. Transformer, as one of the core equipment of power system and national grid system, has the characteristics of diverse types, variable models and wide deployment. It is the basic equipment for power system to realize voltage change and electric energy distribution. Because the power system transformer needs to operate with load for a long time, the probability of failure is usually higher than that of other power equipment in general. This paper starts from the transformer fault and fault diagnosis. Firstly, the transformer fault types, traditional transformer fault diagnosis techniques and the advantages of machine learning in transformer fault diagnosis are reviewed. Secondly, the application of information system theory and information entropy in transformer fault diagnosis is introduced. Then it introduces machine learning technology, feature selection and extraction technology in transformer fault diagnosis, and machine learning algorithms such as support vector machine and extreme learning machine for transformer fault diagnosis. Finally, the potential development trend of information system theory, information entropy and machine learning in transformer fault diagnosis is forecasted. The combination of transformer fault prediction and machine learning algorithm is helpful for power system maintenance personnel to accurately predict the running state of power equipment, and also provides a new method and technology for the safe and reliable operation and regular maintenance of power system.

Lipid nanoparticles have an interesting part of drug delivery system. In this study, the modification of the convention nano-lipid based soybean lecithin was demonstrated. Ginger oil derived Zingiber officinale was used along with lecithin, cholesterol and span 80 to fabricate nano-lipid (GL nano-lipid) using thin-film method. Through TEM and confocal microscope, GL nano-lipid exposes the liposome- like morphology. The average size of the resultant nanoparticles was 249.1nm with monodistribution (PDI= 0.021). The ζ-potential of GL nano-lipid was negative as similar to as prepared nano-lipid based lecithin. GL nano-lipid express the highly stable over 60 days of storage at room temperature in term of size, ζ-potential. A shift of pH value from alkaline to acid was detected in lecithin nano-lipid, while with the incorporation of ginger oil, pH value of nano-lipid dispersion was around 7.0. Furthermore, due to the rich of shogaol-6 and other active compounds in ginger oil, the GL nano-lipid is endowed with intrinsic antibacterial feature. In addition, the sulforhodamine B (SRB) assay and live/dead imaging revealed the excellent biocompatibility of GL nano-lipid. Notably, GL nano-lipid was capable to carry the hydrophobic agents as curcumin and perform a pH-dependent release profile. A subsequent characterization are a suitable potential for drug delivery system.

Glycine is an important neurotransmitter in vertebrates, performing both excitatory and inhibitory actions. Synaptic levels of glycine are tightly controlled by the action of two glycine transporters, GlyT1 and GlyT2, located on the surface of glial cells and glycinergic or glutamatergic neurons, respectively. Glycinergic neurotransmission in invertebrates has so far only been investigated in a very limited number of species, and, although it was suggested that its functions are to some extent conserved with vertebrates, the evolution of glycinergic neurotransmission remains very poorly understood. Here, by combining phylogenetic and gene expression analyses, we characterized the glycine transporter complement of amphioxus, an important invertebrate model for studying the evolution of chordates. We show that amphioxus possesses three glycine transporter genes, two of which (GlyT2.1 and GlyT2.2) are closely related to GlyT2 of vertebrates, while the other (GlyT) is a member of an ancestral clade of deuterostome glycine transporters. While expression of GlyT2.2 is predominantly non-neural, GlyT and GlyT2.1 are widely expressed in the amphioxus nervous system and are characterized by differential expression in neurons and glia, respectively. However, in vertebrates, glycinergic neurons express GlyT2 and glia GlyT1, suggesting that the evolution of the chordate glycinergic system was accompanied by complex genetic remodeling leading to the paralog-specific inversion of gene expression. Albeit this genetic divergence between amphioxus and vertebrates, we found strong evidence for a general conservation of the role of glycinergic neurotransmission during larval swimming, allowing us to hypothesize that the neural networks controlling the rhythmic movement of chordate bodies are homologous.

Although the dockless bike-sharing system, which can be regarded as a typical example of the resource-sharing system, has been increasingly popular for years with people especially in China, the imbalanced distribution of shared bikes gradually becomes a major problem for both bike-sharing companies and their customers. To solve the imbalance problem, we aim to investigate the long-term performance of a system under the influence of some key factors (with an emphasis on the unequal demand between different nodes), which can guide us to discover the causes of the problem and offer several valuable suggestions to the operators. According to the fundamental principle of a dockless bike-sharing system, we propose a model reduction method to reduce the complexity of the theoretical network models, which are developed based on the Markovian queueing theory with the consideration of higher-demand nodes and lower-demand nodes. The theoretical network models provide us with steady-state probabilities of having a certain number of bikes at one node, which are used as an important part of the optimization model for solving the imbalance problem by carrying out an operator-based relocation strategy. The objective of the optimization model is to maximize the total profit and determine the optimal relocation frequency. It is found that most of the shared bikes are possible to gather at one low-demand node eventually in the long run under the influence of the different arrival rates at different nodes, but the decrease of the number of bikes at the high-demand nodes is more sensitive to the unequal demands and may cause a great loss for operators, which should be payed attention to especially when solving the relocation problems.

In this article authors shows chosen problems of technical state diagnosis with the use of identification and technical diagnostics methods such as experimental modal analysis. Relations between methods of dynamic state evaluation and methods of technical state evaluation were indicated. Example modal analysis results illustrate the complexity of projecting dynamic state researches into diagnostic researches of state evaluation.

Dermal interstitial fluid (ISF) is a novel source of biomarkers that can be considered as an alternative to blood sampling for disease diagnosis and treatment. Nevertheless, in vivo extraction and analysis of ISF are challenging. On the other hand, microneedle (MN) technology can address most of the challenges associated with dermal ISF extraction and is well-suited for long-term, continuous ISF monitoring as well as in situ detection. In this review, we first briefly summarise the different dermal ISF collection methods and compare them with MN methods. Next, we elaborate on the design considerations and biocompatibility of MNs. Subsequently, the fabrication technologies of various MNs used for dermal ISF extraction, including solid MNs, hollow MNs, porous MNs and hydrogel MNs, are thoroughly explained. In addition, different sensing mechanisms of ISF detection will be discussed in detail. Subsequently, we identify the challenges and propose the possible solutions associated with ISF extraction. A detailed investigation is provided for the transport and sampling mechanism of ISF in vivo. Also, the current in vitro skin model integrated with the MN arrays will be discussed. Finally, future directions to develop a point-of-care (POC) device to sample ISF are proposed.

Linear programming formulations of forest ecosystem management (FEM) problems proposed in the 60s have been adapted and improved upon over the years. Generating management alternatives for forest management planning is a key step in building these models. Global forests are diverse, and a variety of models have been developed to simulate management alternatives. Climate change has made forest management calculations even more complex, requiring flexibility, diverse parameters, models, and methods. Despite this complexity, consistent concepts can be applied in developing management alternatives for forest management planning. This work describes iGen, a flexible forest prescription generator that applies the AI technique Rule-Based System (AI-RBS). iGen projects the state and associated inputs and outputs for a set of management units using rules from its knowledge base. An Inference Engine uses the rules to simulate a set of prescriptions in a tree-like graph structure. Without needing IT specialists, forest managers can describe the potential development of their forest through variables, rules, formulas, functions, and procedures. A key feature of iGen is that it is not limited to, adapted to, or focused on any specific region, landscape, forest condition, projection method, or yield function. Instead, it aims to maximize generality, enabling it to address a broad range of FEM problems. This article introduces iGen, explaining its concepts, structure, and algorithms through two FEM problems: natural regeneration with shelterwood harvests and plantation/coppice. For data and iGen source programs, visit github.com/…/iGen.

The purpose of this research is to present a thorough evaluation of the energy management system, which consists of hybrid energy storage systems, and its control algorithms, which may be used in electric vehicles. This paper outlines the characteristics of electric vehicles, research methods, analysis of the hybrid energy storage system architecture, converter topology, and energy management techniques. The strength and co-occurrence of keywords over the past ten years are shown in this study using a systematic research framework for performing a literature review and using keyword analysis techniques. The study reveals a pattern of recently and frequently used terms in works of literature. Consequently, their suitability, benefits, and drawbacks are assessed. In this study, the hybrid energy storage system and converter circuit architecture are evaluated and rated. Non-isolate DC-DC converter converter connected to SC is a suitable configuration for the hybrid converter because it is simple to build, reliable, and has minimal loss/weight/cost, which improves vehicle performance. In terms of the application of control strategies, it is shown that deterministic and fuzzy rule-based control techniques are successfully assessed using real-scale vehicle experiments and selected for manufacturing. On the other hand, real-time optimization-based energy management techniques have been effectively shown in lab-scale tests and may be used in a future real-scale vehicle.

A tabletop system can facilitate multi-user collaboration in a variety of settings including small meetings, group work, and education and training exercises. The ability of identifying the users touching the table and their positions can promote collaborative work among participants, so methods have been studied that involve the attaching of sensors to the table or chairs or to the users themselves. An effective method of recognizing user actions without placing a burden on the user would be some type of visual process, so the development of a method that processes multi-touch gestures by visual means is desired. This paper describes the development of a multi-touch tabletop system using infrared image recognition for user position identification and presents the results of touch-gesture recognition experiments and a system usability evaluation. Using an FTIR touch panel and infrared light, this system picks up the shadow area of the user’s hand by infrared camera in relation to user touch operations and estimates user position by image recognition. The multi-touch gestures prepared for this system include an operation to change the direction of an object to face the user and a copy operation in which two users generate duplicates of an object. The average recognition rate of the change-direction gesture and copy gesture were found to be 96% and 85%, respectively. In addition, the system usability evaluation revealed that prior learning was easy and that system operations could be easily performed.

The effect of prostaglandin E1 (PGE1) encapsulated in nanoparticles (Nano PGE1) on motor dysfunction and muscle atrophy induced by sciatic nerve injury (SNI) was investigated in rats, and was compared with PGE1 encapsulated in lipid microspheres (Lipo PGE1) or PGE1 clathrated in cyclodextrin (PGE1-CD). The hind limb muscle weight ratio decreased until 2 weeks after SNI. All 3 PGE1 formulations significantly improved SNI-induced motor dysfunction. Nano PGE1 significantly promoted recovery from muscle atrophy at 2 and 3 weeks after SNI. Lipo PGE1 was also effective, but multiple doses were required. Compared with the SNI control group, the Nano PGE1 group showed upregulation of vascular endothelial growth factor (VEGF) and agrin expression in the injured sciatic nerve and atrophic muscles. Nano PGE1 accumulated prominently at the site of nerve injury and persisted for longer than Lipo PGE1 or PGE1-CD. Expression of all EP receptors was detected in the normal sciatic nerve, and EP2 expression increased after SNI. Finally, Nano PGE1 promoted ERK1/2 and Akt phosphorylation. These findings suggest that PGE1 released from nanoparticles accumulates at sites of nerve injury and increases VEGF production by augmenting ERK1/2 phosphorylation via EP receptor signaling, thus promoting tissue repair and regeneration.

Background: Radiotherapy is an important part of the medical therapy concept treating tumors in the head and neck region; however, the impact on the field of dentistry could be im-mense. The objective of this study was to evaluate the microtensile bond strength (µTBS) of uni-versal adhesives and to compare the results of different application modes (etch-and-rinse and self-etch) on irradiated and sound human dentin. Methods: Dentin specimen of 180 extracted human wisdom teeth were divided in two superordinate groups. Ninety teeth received either no irradiation (control group) or the high-level therapeutic dose of 60 Gy (test group) applied frac-tionally (2 Gy/day, 5 days/week, 6 weeks). Samples from each group were randomly divided in-to six subgroups assigned to three established universal adhesives (Futurabond® U, VOCO; AdheSE® Universal, Ivoclar Vivadent; Xeno® Select, Dentsply) in both conceivable application modes: etch-and-rinse and self-etch (n = 15). Bond strength was assessed with a universal testing machine immediately after application and light curing of the adhesive materials. Statistical analysis was performed using two-way ANOVA (p<0.01) and Tukey's test (p<0.05). Results: The effect of dentin irradiation and application mode for the adhesive restoration was found to be significant (p<0.01, ANOVA). In all groups, a decrease of µTBS could be observed when used on irradiated dentin. However, no significant influence of high level radiation on the bond strength of Futurabond® U and AdheSE® Universal in both modes could be evaluated (p>0.05, Tukey´s test). Solely in the case of the adhesive system Xeno® Select, significantly reduced bond strength could be determined in self-etch mode after irradiation (group 60 Xse) compared to the control group (0 Xse) (p<0.05, Tukey´s test). Conclusions: Within the limitations of an in vitro study, some effects of high-level tumor irradiation on the bond strength of universal adhesives can be detected. However, these effects were strongly depending on the used material and application mode.

Recent studies have shown that the endogenous cannabinoid system (ECS) of the brain is essentially involved in the pathogenesis of Parkinson's disease (PD), influencing its symptoms by regulating the level of endogenous cannabinoids and altering the activation of cannabinoid receptors (CBR). Therefore, modulation of ECS with new drugs developed for this purpose may prove to be a promising strategy in the treatment of PD. However, fine regulation of ECS is quite a challenge due to the functional diversity of CBR in the basal ganglia. Our review analyses the effects of ECS modulators on experimental PD models and in patients with PD, as well as presents the outlooks for the development of new cannabinoid drugs for the treatment of motor and non-motor symptoms in PD.

Animal-focused research has been crucial for scientific advancement however, in this matter, rodents are still taking a starring role. Coming out from merely being supportive of evidence found in rodents, the use of fish models has slowly taken a more central role and expanded its overall contributions in areas such as social sciences, evolution, physiology, and recently in translational medical research. In neurosciences, zebrafish has been widely adopted, contributing to our understanding of the genetic control of brain processes, and the effects of pharmacological manipulations. However, discussion continues regarding the paradox of function versus structure, when fish and mammals are compared, and on the potentially evolutionarily conserved nature of behaviour across fish species. From the behavioural stand point we explored aversive/stress and social behaviour in selected fish models, and refer to the extensive contributions of stress and monoaminergic systems. We suggest that, in spite of marked neuroanatomical differences between fish and mammals, stress and sociality are conserved at the behavioural and molecular levels. We also suggest that stress and sociality are mediated by monoamines in predictable and non-trivial ways, and that monoamines could “bridge” the relationship between stress and social behaviour. To reconcile the level of divergence with the level of similarity, we need neuroanatomical, pharmacological, behavioural, and ecological studies conducted in the laboratory and in nature. These areas need to add to each other to enhance our understanding of fish behaviour and ultimately how this all may translate to better model systems for translational studies.

Energy transitions are reshaping the global energy system. Such shift has taken the power system to become a critical infrastructure for achieving economic development of every nation in the planet, therefore, guaranteeing its security is crucial, not only for energy purposes but as a part of a national security strategy. This paper presents a multi-dimensional index developed to assess energy security of electrical systems in the long term. This tool, named Power System Security Index (PSIx), and which has been previously used for the evaluation of a country in two different time frames, is applied to evaluate the member countries of the Latin American Energy Organization, located within the Latin America and the Caribbean region, in order to measure their performance on energy security. Mixed results were obtained from the analysis, with clear top performers in the region such as Argentina, while there are others with broad areas of opportunity, as it is the case of Haiti.

The delivery of therapeutical molecules through the skin, particularly to its deeper layers is impaired due to the stratum corneum layer, which acts as barrier to foreign substances. Thus, for the past years, scientists have focused on the development of more efficient methods to deliver molecules to skin distinct layers. Microneedles, as a new class of biomedical devices, consists on an array of microscale needles. This particular biomedical device had been drawing attention due to their ability to breach the stratum corneum, forming micro-conduits to facilitate the passage of therapeutical molecules. The microneedle device has several advantages over conventional methods, such as better medication adherence, easiness and painless self-administration. Moreover, it is possible to deliver the molecules swiftly or over time. Microneedles can vary in shape, size and composition. The design process of a microneedle device must take in account several factors, like the location delivery, the material and manufacturing process. Microneedles have been used in a large number of fields from drug and vaccine application, cosmetics, therapy, diagnosis, tissue engineering, sample extraction, cancer research, wound healing, among others.

Alzheimer’s Disease (AD) is a neurodegenerative condition that currently has no known cure. The principles of the expanding field of network medicine (NM) have recently been applied to AD research. The main principle of NM proposes that diseases are much more complicated than one mutation in one gene, and incorporate different genes, connections between genes, and pathways that may include multiple diseases to create full scale disease networks. AD research findings as a result of the application of NM principles have suggested that functional network connectivity, myelination, myeloid cells, and genes and pathways may play an integral role in AD progression, and may be integral to the search for a cure. Different aspects of the AD pathology could be potential targets for drug therapy to slow down or stop the disease from advancing, but more research is needed to reach definitive conclusions. Additionally, the holistic approaches of network pharmacology in traditional Chinese medicine (TCM) research may be viable options for the AD treatment, and may lead to an effective cure for AD in the future.

Pursuing "intelligent justice" necessitates an impartial, productive, and technologically driven methodology for judicial determinations. This scholarly composition proposes a framework that harnesses Artificial Intelligence (AI) innovations such as Natural Language Processing (NLP), ChatGPT, ontological alignment, and the semantic web, in conjunction with blockchain and privacy techniques, to examine, deduce, and proffer recommendations for the administration of justice. Specifically, through the integration of blockchain technology, the system affords a secure and transparent infrastructure for the management of legal documentation and transactions while preserving data confidentiality. Privacy approaches, including differential privacy and homomorphic encryption techniques, are further employed to safeguard sensitive data and uphold discretion. The advantages of the suggested framework encompass heightened efficiency and expediency, diminished error propensity, a more uniform approach to judicial determinations, and augmented security and privacy. Additionally, by utilizing explainable AI methodologies, the ethical and legal ramifications of deploying intelligent algorithms and blockchain technologies within the legal domain are scrupulously contemplated, ensuring a secure, efficient, and transparent justice system that concurrently protects sensitive information upholds privacy.

Considering the actual world economical trends, one of the most important questions is now and in the future: how to reduce power consumption of electronic systems. Since the invention of computers, the electrical energy consumption step by step increased. Now when not only computers, but electric vehicles, robots, automation, and unmanned aerial vehicles play a very important role of our life, the main problem of system designers is how to reduce energy consumption in these systems. But also the existing already working systems must be revised in order to decrease their electric power consumption. The importance of this subject (energy control) shows that a huge number of research publications and survey papers deal with it. Just focusing on the last one or two years (2021 and 2022) the search hit 221000 titles (103000 hits only in 2022). Analyzing all the research areas is almost impossible, but focusing on some important research subjects, where one of the main topic is “energy saving methods” can give an overview about the subject. The paper focuses on the area of industrial robotic systems, electric vehicles, and embedded systems.

In several mammalian species including humans, complex stimulation patterns such as cognitive challenge and physical exercise lead to improvements in organ function, organism health and performance, as well as possibly longer lifespans. The hypothesis is presented here that activity-dependent transcriptional programs, induced by these environmental stimuli, temporarily and lightly de-differentiate somatic cells such as neurons and muscle cells into a state that resembles functionally younger cells to allow cellular remodeling and adaptation of the organism to environmental change. This cellular adaptation program targets several process classes that are heavily implicated in aging, such as mitochondrial metabolism, cell-cell communication, intracellular signaling and epigenetic information processing and leads to functional improvements in these areas. I reverse engineer these activity-dependent gene programs, identify critical molecular nexus points such as CREB, MEF2 and cFos and speculate as to how one might leverage them to prevent and attenuate human aging-related decline of body function, enhance human performance and restore more youthful levels of function and morphology. The findings presented here can serve as a basis for the study and development of effective longevity efforts as the underlying gene programs could be used as markers for treatment success and as targets for therapy development.

Integrated Model of Distributed Systems is used for modeling and verification. In formalism, the distributed system is modeled as a collection of server states and agent messages. The evolution of the system takes the form of actions that transform the global system configuration (states and messages) into a new configuration. Formalism is used in the Dedan verification environment for finding different kinds of deadlocks: communication deadlocks in the server view and resource deadlocks in the agent view. For other purposes, a conversion has been developed to equivalent models: to Petri nets for structural analysis and do Distributed Autonomous and Asynchronous Automata (DA3) for easy graphical modeling in terms of system components. In addition, it is possible to simulate a verified system on distributed components in DA3. The automata have two forms: Server-DA3 (S-DA3) for the server view and Agent-DA3 (A-DA3) for the agent view. DA3 formalism is compared to other concepts of distributed automata known from the literature.

The paper presents the possibility of using KINECT v2 module to control an industrial robot by means of gestures and voice commands. It describes elements of creating software for off-line and on-line robot control. The application for KINECT module was developed in C# language in Visual Studio environment, while the industrial robot control program was developed in RAPID language in RobotStudio environment. The development of a two-threaded application in RAPID language allowed to separate two independent tasks for the IRB120 robot. The main task of the robot is performed in thread no. 1 (responsible for movement). Simultaneously working thread no. 2 ensures continuous communication with the KINECT system and provides information about the gesture and voice commands in real time without any interference in thread no. 1. The applied solution allows the robot to work in industrial conditions without negative impact of communication task on the time of robot’s work cycles. Thanks to the development of a digital twin of the real robot station, tests of proper application functioning in off-line mode (without using a real robot) were conducted. Obtained results were verified online (on the real test station). Tests of correctness of gesture recognition were carried out, the robot recognized all programmed gestures. Another test carried out was the recognition and execution of voice commands. A difference in the time of task completion between the actual and virtual station was noticed - the average difference was 0.67 s. The last test carried out was to examine the impact of interference on the recognition of voice commands. With a 10dB difference between the command and noise, the recognition of voice commands was equal to 91.43%. The developed computer programs have a modular structure, which enables easy adaptation to process requirements.

Unmanned aerial vehicle (UAV) usage is increasing drastically worldwide as UAVs are used in various industries for many applications, such as inspection, logistics, agriculture, and many more. This is because performing a task using UAV makes the job more efficient and reduces the workload needed. However, for a UAV to be operated manually or autonomously, the UAV must be equipped with proper safety features. An anti-collision system is one of the most crucial and fundamental safety features that UAVs must be equipped with. The anti-collision system allows the UAV to maintain a safe distance from any obstacles. The anti-collision technologies are of crucial relevance to assure the survival and safety of UAVs. Anti-collision of UAVs can be varied in the aspect of the use of sensors and the system’s working principle. This article provides a comprehensive overview of anti-collision technologies for UAVs. It also presents drone safety laws and regulations that prevent a collision at the policy level. The process of anti-collision technologies is studied from three aspects: Obstacle detection, collision prediction, and collision avoidance. A detailed overview and comparison of the methods of each element and an analysis of their advantages and disadvantages have been provided. In addition, the future trends of UAV anti-collision technologies from the viewpoint of fast obstacle detection and wireless networking are presented.

Nowadays, many Muslim-majority countries have implemented a dual banking system, namely the sharia and conventional systems. The development of Islamic banks is to fulfill the Muslims' need for the existence of halal transactions in financial institutions. However, in some countries, it turns out that conventional banks still dominate the country's economy. Because of that, it is necessary to see whether there are differences in financial risk and Earnings management between Islamic and conventional banks. The samples are conventional and Islamic banks in Southeast Asia, analyzed by the purposive sampling method from 2010-2019. The analytical tool used is the statistical difference test and economometrics analysis using generalized least square (GLS) regression with panel data (time series and cross-sectional data). These models are intended to forecasting the macroeconomics effects in applying dual banking system in one country or region. The results using non parametrics means difference test showed that the first hypothesis is accepted It means that Earnings management in conventional banks is greater than in Islamic banks. The Random Model Effect (REM) for second and third hypotheses testing on Conventional banks shows the Bankruptcy Risk and NPL do not affect the dependent variable Earnings Management (LLP). While fixed effect model testing on Islamic banks, the second and third hypothesis testing is rejected. Therefor Islamic Banks the value of Bankruptcy Risk (z-score) and the value of Non-Performing Loans (NPL) do not affect Earnings management. It also means that hypothesis 2 and 3 are rejected both in conventional as well as Islamic Banking. Sensitivity analysis for conventional as well as Islamic banking altogether using fixed effect model shows that the second and third hypotheses show that the independent variables (Bankruptcy Risk and NPL) do not affect the dependent variable Earnings Management (LLP). These results can be concluded that Islamic bank are enganged in less earnings management. Therefor in the the long run there are still more research that should conduct in comparing dual banking system in one region.

The complement system is part of the innate immune response, where it provides immediate protection from infectious agents and plays a fundamental role in homeostasis. Complement dysregulation occurs in several diseases, where the tightly regulated proteolytic cascade turns offensive. Prominent examples are atypical hemolytic uremic syndrome, paroxysmal nocturnal hemoglobinuria and Alzheimer’s disease. Therapeutic intervention targeting complement activation may allow treatment of such debilitating diseases. In this review, we describe a panel of complement targeting nanobodies that allow modulation at different steps of the proteolytic cascade, from the activation of the C1 complex in the classical pathway to formation of the C5 convertase in the terminal pathway. Thorough structural and functional characterization has provided a deep mechanistic understanding of the mode of inhibition for each of the nanobodies. These complement specific nanobodies are novel powerful probes for basic research and offer new opportunities for in vivo complement modulation.

The use of pesticides such as rotenone can lead to toxicity, dysfunction and neuronal death in humans. The Copaifera Reticulata Ducke Oil-Resin (CPOR) is widely used by the natives of the Amazon, however, studies on its potential neuroprotective effect are lacking. This study investigated the cytoprotective effect of CPOR on total cell cultures of the ventral midbrain (VMC), hippocampus (HC) and cerebral cortex (CCC) exposed to rotenone at different concentrations. The total cell cultures of VMC, HC and CCC were exposed for 72 or 24 hours to rotenone, CPOR and rotenone + CPOR. Cell viability was measured using the MTT test and compared using one-way ANOVA. Exposure to rotenone reduced the cell viability of CMV, HC and CCC. Exposure to CPOR reduced the cell viability of CMV. The cell viability of CMV exposed simultaneously to rotenone and CPOR was higher compared to rotenone alone. The cell viability of HC exposed simultaneously to rotenone and CPOR was higher than that exposed to rotenone. CMVs are more vulnerable to rotenone toxicity and more sensitive to CPOR. Considering simultaneous exposure, CPOR revealed a possible neuroprotective effect against rotenone damage only for VMC and HC.

The analysis presented is based on actual GHU energy demand. The special feature of this load is the existence of strong daily fluctuations in energy consumption, especially during the summer months. This study presents a methodology for managing such loads with the main objective of maximizing the operating efficiency of MG.

Background: Human Immnodeficiency virus (HIV) continues to take a heavy toll on the lives of many people with worst impact on health and wellbeing for the affected individuals in fragile states. The HIV situation in Somalia is not clearly known and experiences of the people living with HIV in this war-torn region unexpressed. This pilot qualitative study sought to explore the experiences of people living with diagnosed HIV in Mogadishu and their resilience in access to care and social support. Method: Face-to-face in-depth interviews were conducted in Somali in May 2013 among patients who were receiving Antiretroviral therapy (ART) from the HIV clinic in Mogadishu. Participants were recruited through drug dispensers at the HIV clinic in Benader Hospital. These were tape recorded, transcribed and translated for content analysis. Results: Three women and four men who were living with HIV shared the following narratives. Their perception was that they had either got HIV from their spouces or through health care contamination. They were very knowledgable about the realities of HIV, how the medication works, nutritional requirements and drug adherence. They were always willing to go an extra mile to secure a good life for themselves. However the external HIV stigma impacted their access to care. They faced challenges in their homes and at work which compelled them to seek support from non-governmental organisations (NGOs) or close family members. This stigma often affected their disclosure to the wider community due to the uncertainity of the repercussions, leading to a life of extreme loneliness and financial difficulties. The participants’ coping mechansms included living together and starting their own NGO for support with very strong optimism about their prognosis. Conclusions: The people living with diagnosed HIV in Mogadishu are highly knowledgeable about HIV transmission, the realities of living with diagnosed HIV infection and efficacy of HIV treatment. Our small sample suggests adequate access to ART through NGOs. However, widespread HIV stigma limits HIV status disclosure to the families and communities which creates a risk of self isolation and ill health. But affected individuals have developed resilient mechanisms of managing the risks. They strive to remain employed for economic security, adhere to HIV treatment, engage in support groups and maintain utmost optimism about their prognosis.

Obesity is invariably accompanied by autonomic dysfunction, although data in pediatric populations are conflicting. We conducted a systematic review and meta-analysis of 12 studies (totaling 1102 participants) comparing obese and normal-weight subjects (5-18 years of age), defined as body mass index &gt;95th or &lt;85th percentile, respectively. Using a random-effects model, we report the standardized mean differences (SMD) of sympathetic and vagal indices, calculated by heart rate variability. Autonomic dysfunction was present in the obese group, based on the average SMD in the standard deviation of sinus intervals (at -0.5340), and on the ratio of low (LF) to high (HF) frequency spectra (at 0.5735). There was no difference in sympathetic activity, but the heterogeneity among the relevant studies weakens this result. SMD in HF (at 0.5876), in the root mean square of successive differences between intervals (at -0.6333), and in the number of times successive intervals exceeded 50ms divided by the total number of intervals (at -0.5867) indicated lower vagal activity in the obesity group. Thus, autonomic dysfunction is present in obese children and adolescents, attributed to lower vagal activity. Further studies on autonomic function are needed in various pediatric cohorts, placing emphasis on sympathetic activity.

This paper introduces the AltumView Sentinare smart activity sensor for senior care and patient monitoring. The sensor uses an AI chip and deep learning algorithms to monitor the activity of people, collect activity statistics, and notify caregivers when emergencies such as falls are detected. To protect privacy, only skeleton (stick figure) animations are transmitted instead of videos. The sensor is highly affordable, accessible, and versatile. It was a CES 2021 Innovation Award Honoree, and has been selected by Amazon as one of only three fall detection devices integrated into its Alexa Together urgent response service, and has received very positive reviews from Amazon customers. It has also been used in different senior care settings in about ten different countries. The paper presents the main features of the system, the evidences and lessons learned from its practical applications, and future directions.

Soil tillage intensity influences the distribution of nutrients, and soil’s physical and me-chanical properties, as well as gas flows. The impact of reduced tillage on these indices in spring barley cultivation is still insufficient and requires more analysis on a global scale. This study was carried out at Vytautas Magnus University, Agriculture Academy (Lithu-ania) in 2022–2023. The aim of the investigation was to determine the effect of the tillage systems on the soil temperature, moisture content, CO2 respiration and concentration in spring barley cultivation limited by the semi-humid subarctic climate. Based on a long-term tillage experiment, five tillage systems were tested: deep and shallow mold-board ploughing, deep cultivation-chiselling, shallow cultivation-chiselling, and no-tillage. Shallow ploughing technology was found to be better at conserving soil moisture and maintaining a higher temperature. Deep cultivation had a lower moisture content and lower soil temperature. Shallow cultivation fields in most cases increased CO2 emissions and CO2 concentration. The results show that in direct sowing fields, most cases had a positive effect on crop density. Direct sowing fields resulted in significantly lower grain yields of spring barley in the years studied.

The dairy industry relies heavily on milk pasteurization to ensure the safety and quality of milk products. Pasteurization is a process that involves heating milk to a specific temperature for a set period of time to kill harmful bacteria and other pathogens while preserving its nutritional value. recent years, newer techniques such as High Temperature Short Time (HTST) pasteurization have gained popularity due to their efficiency and effectiveness. HTST pasteurization involves rapidly heating milk to a high temperature for a short duration of time, followed by rapid cooling. This process helps to minimize the loss of flavor and nutrients in milk while ensuring its safety. However, there is still a need in the market for a compact and remotely controlled process plant for milk pasteurization. The proposed work aims to address this need by designing a process plant that is not only compact but also remotely controlled, allowing for efficient and convenient operation. can control the process plant remotely, allowing for flexibility and convenience in monitoring and managing the pasteurization process from anywhere with an internet connection

The rapid growth of Earth's global geospatial data necessitates an efficient system for organizing the data, facilitating data fusion from diverse sources, and promoting interoperability. Mapping the spheroidal surface of the planet presents significant challenges, as it involves balancing distortion and splitting the surface into multiple partitions. The distortion decreases as the number of partitions increases, but at the same time the complexity of data processing increases, since each partition represents a separate data set and is defined in its own local coordinate system. In this paper, we propose the dual orthogonal equidistant cylindrical projection method to mitigate distortion and reduce the number of partitions. Additionally, we use the rotation of projection cylinders to effectively minimize average angular and areal distortions of the Earth’s landmass and reduce the interruption of continental plates caused by partition edges. By incorporating auxiliary latitudes and proposing an approximate authalic latitude, we further enhance the mapping of the ellipsoid onto the sphere, simplifying calculations. Experimental results demonstrate a substantial reduction in distortion and interruption of continental plates. With only two partitions, an average landmass angular distortion of less than 3.56 degrees and an average normalized surface distortion of less than 1.07 were achieved.

The theoretical limits of water sorbate based chemical sorption heat storage are investigated in this study. First, a classification of \textit{thermochemical heat storage} is proposed based on bonding typology. Then, thermodynamics of chemical solid/gas sorption is introduced. The analysis of the reaction enthalpy from the literature indicates that this value is only slightly varying for one mole of water. Using this observation, and with the help of thermodynamical considerations, it is possible to derive conclusions on energy efficiency of closed and open heat storage systems. Whatever the salt, the main results are 1) the energy required for evaporation of water is, at least, 65% of the available energy of reaction and 2) the maximum theoretical energy efficiency of the system is about 1.8.

The link between language processing and motor systems has been the focus of increasing interest to Cognitive Neuroscience. Some classical papers studying Event Related Potentials (ERPs) induced by linguistic stimuli have found differences in electrophysiological activity when comparing action and non-action words; more specifically, a bigger p200 for action words. On the other hand, a series of studies have validated the use of a grip force sensor (GFS) to measure language-induced motor activity during both isolated words and sentence listening, finding that action words induce an augmentation in the grip force around 250-300 ms after the onset of the stimulus. The purpose of the present study is to combine both techniques to assess if the p200 is related to the augmentation of the grip force measured by a GFS. We measured ERP and GFS changes elicited by listening to action and non-action words while maintaining an active grasping task in 10 healthy subjects. Our results show that the amplitude of the p200 in central electrodes is correlated to the augmentation in the GFS around 300 ms induced by linguistic stimuli. To our knowledge, this is the first study where the electrophysiological activity and the changes in the grip force induced by auditory language processing are put together, opening new venues of interpretation for the sensorimotor interaction in language processing.

Introduction: The COVID-19 pandemic highlighted the necessity for rapid, efficient testing at large-scale events. Developing rapid and efficient testing methods was critical, especially for events with a high risk of virus spread. The queueing theory offers a powerful tool to manage the flow of people through testing centers. This study uses the M/M/c model to examine how different floor plan configurations impact the efficiency of RADT testing centers. Aim of the study: This research applies queueing theory to optimize the Rapid Antigen Diagnostic Test (RADT) processes at mass gatherings. The study uses the M/M/c queueing model to evaluate the dynamics of RADT centers configured in U-shaped and straight-line layouts. The primary goal is to assess the feasibility of using RADTs efficiently at events and mass gathering entrances, aiming to enhance throughput and minimize wait times. Methodology: The study involved 500 healthy participants, managed by medical staff across a U-shaped and a straight floor plans. Agile management techniques were employed to enhance operational efficiency. The process stages included queue number issuance, registration, sample collection, sample mixing, and results dissemination. Results: Both floor plans enabled the completion of RADT screening in approximately 2 minutes per participant. The U-shaped layout slightly outperformed the straight-line setup in efficiency, demonstrating its effectiveness in optimizing the testing process. Conclusion: This study confirms the feasibility of implementing Rapid Antigen Diagnostic Test (RADT) processes at mass gatherings. It was found that the U-shaped floor plan configuration is particularly effective, indicating its potential suitability for future mass testing scenarios.

This paper proposes a new kind of airship actuator configuration for surveillance and environmental monitoring missions. We present the design and application of a 6-propeller electrical airship (Noamini) with independent tilting propellers, allowing improved and flexible maneuverability. The vehicle has different combinations of differential propulsion and can be used in 2, 4 or 6 motors configuration. We developed a high-fidelity airship simulator for the Noamini airship, which was used to test and validate a control-guidance approach. Incremental Nonlinear Dynamic Inversion (INDI) is used for the velocity/attitude control to follow a high-level L1 guidance reference in a simulated waypoint tracking mission with wind and turbulence. The proposed framework will be soon implemented in the onboard control system of the Noamini, an autonomous airship for environmental monitoring and surveillance applications.

Crack inspection is important to monitor the structural health of pavement structures and to facilitate an easier rehabilitation process. Currently, pavement crack inspection is conducted manually, which is inefficient and costly at the same time. For solving the problem, this work has developed a robotic system for automated data collection and analysis in real-time. The robotic system navigates on the pavement and collects visual images from the surface. A deep learning-based semantic segmentation framework named RCDNet was proposed and implemented on the onboard computer of the robot to identify cracks from the visual images. Simulation results show that the deep learning model obtained 96.29% accuracy for predicting the images. The proposed robotic system was tested on both indoor and outdoor environments and was observed that it can complete inspecting a 3m × 2m grid within 10 minutes and a 2.5m × 1m grid within 6 minutes. This outcome shows that the proposed robotic method can drastically reduce the time of manual inspection. Furthermore, a severity map based on the results from visual images was also generated to provide an idea of which locations should be paid more attention to repair in a test grid.

Others have proposed that living systems are characterized by the possession of a kind of information unique to them. This information, variously called semantic, symbolic, or coding information conveys meaning from senders to recipients, most commonly among genome and other cellular components, different cells, organisms, etc., enabling all biological functions. Unlike other kinds of information, it is only indirectly quantifiable and does not increase by copying. Here, the term system information is used to encompass the entire package of coding information enabling all organisms of a species to complete their life cycles through possession of its copy (Crkvenjakov and Heng 2021). System information grows in a nonreductive evolution only during speciation proper by the acquisition of novel functions by daughter species. Contemporary science agrees that species are units of evolution but has failed to recognize and parse the importance of phases of speciation and stasis for evolution. Confinement of system information change to speciation only explains for the first time why there are species and why their number increases nearly exponentially throughout evolution. More importantly, here we define that evolution as a process operating on a planetary scale, while chance based, is non-random mathematically since it obeys the Laws of Information which dictate the behavior of System information in organisms. Growth and persistence of system information on the non-degenerative portion of Tree of Life follow the law of conservation, which states that its growth is as parsimonious (minimal) as possible and the persistence of parental system information the maximal possible in each unit speciation step. This formulation is a restatement of Loewnstain's (1999) principle of information economy and our lock-in law (Crkvenjakov and Drmanac 2007). The principle holds that since, on chance assumption, the system information change cost is directly proportional to time, more costly pathways of achieving the same new functional goal will be, almost without exception, competed out by the less costly ones. As a corollary of the conservation law, the speciation law states that speciation follows the most economical way of growth of system information while conserving the existing one, which is horizontal information transfer by molecular sex (uptake of exogenous nucleic acid into the progeny genome) by exchange among two parents from maximally possible divergent lineages. The speciation law dictates that molecular sex mode be used since it is the most parsimonious one. The molecular sex cost in information bits is zero to the recipient, which is not the case with the generally accepted mode of vertical accumulation of information bits in a population gene pool within a lineage.

Evidence on adult mammalian neurogenesis and scarce studies with human brains led to the idea that adult human neurogenesis occurs in the subgranular zone (SGZ) of the dentate gyrus and in the subventricular zone (SVZ). However, findings published from 2018 rekindled controversies on adult human SGZ neurogenesis. We systematically reviewed studies published during the first decade of characterization of adult human neurogenesis (1994–2004) – when the two-neurogenic-niche concept in humans was consolidated – and compared with further studies. The synthesis of both periods is that adult human neurogenesis occurs in an intensity ranging from practically zero to a level comparable to adult mammalian neurogenesis in general, which is the prevailing conclusion. Nonetheless, Bernier and colleagues showed in 2000 intriguing indications of adult human neurogenesis in a broad area including the limbic system. Likewise, we later showed evidence that limbic and hypothalamic structures surrounding the circumventricular organs form a continuous zone expressing neurogenesis markers encompassing the SGZ and SVZ. The conclusion is that publications from 2018 on adult human neurogenesis did not bring novel findings on location of neurogenic niches. Rather, we expect that the search of neurogenesis beyond the canonical adult mammalian neurogenic niches will confirm our indications that adult human neurogenesis is orchestrated in a broad brain area. We predict that this approach may, for example, clarify that human hippocampal neurogenesis occurs mostly in the CA1-subiculum zone and that the previously identified human rostral migratory stream arising from the SVZ is indeed the column of the fornix expressing neurogenesis markers.

Objective: On March 11, 2020 the WHO declared that COVID-19 is pandemic. Among the risk factors for many infectious diseases, a role of the ABO blood group system is reported in the literature. We argue whether it is necessary to investigate the relationship between ABO blood groups and susceptibility to SARS-CoV-2 infection and if we should consider some blood groups as potential risk factors for COVID-19. Results: Based on the scientific evidence reported in this letter, we believe that further studies are needed to investigate how the ABO polymorphism influences the host susceptibility, individual response and clinical risk for SARS-CoV-2 infection.

The tumor microenvironment is known to have increased levels of cytokines and metabolites, such as glutamate, due to their release from the surrounding cells. A normal cell around the tumor that responds to the inflammatory environment is likely to be subsequently altered. We will discuss how these abnormalities will support tumor survival via the actions of gap junctions (GJs) and hemichannels (HCs) which are composed of hexamer of connexin 43 (Cx43) protein. In particular, we will discuss how GJ intercellular communication (GJIC) in glioma cells, the primary brain tumor, is a regulatory factor and its attenuation leads to tumor invasion. In contrast, the astrocytes, which are normal cells around the glioma, are "hijacked" by tumor cells, either by receiving the transmission of malignant substances from the cancer cells via GJIC, or perhaps via astrocytic HC activity through the paracrine signaling which enable the delivery of these substances to the distal astrocytes. This astrocytic signaling would promote tumor expansion in the brain. In addition, brain metastasis from peripheral tissues has also been known to be facilitated by GJs formed between cerebral vascular endothelial cells and cancer cells. Astrocytes and microglia are generally thought to eliminate cancer cells at the blood brain barrier. In contrast, some reports suggest they facilitate tumor progression as tumor cells take advantage of the normal functions of astrocytes that support the survival of the neurons by exchanging nutrients and metabolites. In summary, GJIC is essential for the normal physiological function of growth and allowing the diffusion of physiological substances. Therefore, whether GJIC is cancer promoting or suppressing may be dependent by what permeates through GJs, when it is active, and to which cells. The nature of GJs, which has been ambiguous in brain tumor progression, will need to be re-visited and understood together with new findings on Cx proteins and HC activities.

The endocannabinoid system (eCB) began to be studied from the identification of the molecular structures present in the cannabis sativa plant. The ECS is constituted of cannabinoid receptors, endogenous ligands and all the associated enzymatic apparatus responsible for maintaining homeostasis. Several physiological effects of cannabinoids are exerted through interaction with various receptors such as CB1 and CB2 receptors, vanilloid receptors, and the recently discovered [GPCRs (GPR55, GPR3, GPR6, GPR12 and GPR19). Endogenous ligands such anandamide and 2-arachidonoylglycerol might modulate these receptors. eCB has proved to play a critical role in some human diseases and has been extensively studied due to its wide therapeutic potential and because it is a promising target for the development of new drugs. Phytocannabinoids and synthetic cannabinoids have shown varied affinities to eCB, which are relevant to the treatment of various diseases. They may also have potential as lead compounds in the development of cannabinoid-based pharmaceuticals for a variety of diseases. Furthermore, Integrative and Complementary Health Practices (ICHP) appear to influence the endocannabinoid system through modulation. This review will show a description of ECS components and discuss how phytocannabinoids, other exogenous compounds, and PICS may operate the eCB balance.