Circles, semicircles and its derived circular sectors are ubiquitous both in human creations and in the natural realm. However, mathematically speaking they have always represented a certain level of enigma or even mysticism since ancient times for being such a perfect shape that enclosed the irrational value that we now call π. Such figure was relatively unknown until the seventeenth century; polymaths like Guarini even equated it, after so many centuries, to the Archimedes fraction of 22/7 or sometimes 25/8 which, giving a value 3.125 introduces a considerable degree of error; Eventually, Lambert had to demonstrate, well advanced the eighteenth century that π was actually an irrational number. In recent years, the author has worked with sections of spheres and other curved bodies as related to radiative heat transfer and applied to the finding of form factors pertaining to such special geometries, to the point of defining new postulates. The main theorems so far enunciated refer to the radiative exchange between circles and half disks, but recently the possibility to treat circular sectors has arrived, thanks to the research already conducted in which, by virtue of Cabeza-Lainez first postulate, we are able to know the form factor of any spherical segment over itself, discarding in this way, the former uncertainties that appeared when dealing with the inner side of spherical surfaces. As it is known, to find the exact expression of the configuration factor by integration alone is mostly a tedious task and the results are not readily available as it has been frequently proved. In the said problem of the circular sectors, the author could integrate the first two steps of the basic formulation for radiant exchange. Subsequently, the novelty of the procedure lies in introducing a finite differences approximation for the third and fourth integrals which still remain unsolved, once that we have been able to find the first and second integrals of the form factor. This possibility had not been identified by former research. This sole output provides us with an ample variety of scenarios previously unforeseen. As a consequence, we would be able to analyze with more precision but freely, the spatial transference of radiant heat for figures composed of circular sectors such as spherical sectors like quarters or octaves of spheres. Many architectural, industrial or aircraft modules and objects fall into this category. We already know that spherical shapes cannot be discretized with any accuracy as there are no spherical tiles of the same size, therefore we hope to overcome with our finding a persistent extent of error. In this situation we are able to reduce a considerable amount of hindrances in the progress of thermal radiation science, due to the advances hereby presented. As the new formulations found can be adapted for algorithms, they will be integrated in simulation procedures with significant avail. Our achievement may be considered timely in the effort invested to square the elements of mathematics for radiative transfer. Important sequels are already being derived for radiation in the entrance to tunnels, aircraft design, low-energy building construction and also lighting and HVAC industries to cite just a few.

Advanced Finite Element (FE) modeling and simulations were performed on vehicular crashes into a Three-bar Metal Bridge Rail (TMBR). The FE models of a sedan, a pickup truck, and a TMBR section were adopted in the crash simulations subject to Manual for Assessing Safety Hardware (MASH) Test Level 2 (TL-2) and Test Level 3 (TL-3) requirements. The test vehicle models were first validated using full-scale physical crash tests conducted on a two-bar metal bridge using a sedan and a pickup truck with similar overall physical properties and sizes to their respective vehicles used in the simulations. The validated vehicular models were then used to evaluate the crash performance of the TMBR using MASH Evaluation Criteria for structural adequacy, occupant risk, and post-impact trajectory. The TMBR met all MASH TL-2 requirements but failed to meet the MASH TL-3 Criteria H and N requirements when impacted by the sedan. The TMBR was also evaluated under in-service conditions (behind a 1.52-m wide sidewalk) and impacted by the sedan under MASH TL-3 conditions. The simulation results showed that the TMBR behind a sidewalk met all safety requirements except for the occupant impact velocity in the longitudinal direction, which exceeded the MASH limit by 3.93%.

The maritime industry contributes to over 80% of global trade and ranks as the sixth-largest emitter of greenhouse gases. The International Maritime Organization has taken strides to reduce these emissions, while the European Union spearheads efforts to establish sustainable maritime transport. However, meeting decarbonisation targets poses significant challenges, with the potential implications of adopting an EU Emission Trading System (ETS) on shipping allowances, particularly at specific borders. If not managed effectively, this could result in diversifying regular container shipping routes away from EU ports, potentially leading to increased shipping emissions and disrupting the logistics trade and security chain. These challenges are exacerbated by the International Maritime Organization's lack of a carbon fee on bunkering, which creates an imbalance. The ETS Directive has fostered unfair competition between EU and non-EU ports due to discrepancies in applying emission unit allowances. It is imperative to implement preventive measures to contain and prevent the shift of operations from EU ports to nearby ports, ensure equitable treatment of EU transhipment ports and their competitors, and thwart carbon leakage. Additionally, the recent Houthis attacks on the Red Sea have significantly impacted shipping costs on the Cape of Good Hope route to Europe, necessitating increased allowances to and from Europe.

The advanced industrial systems are characterized by complex event-driven processes. The specification and computer analysis are illustrated by the common problem of a servo drive with the PWM controller. A mathematical model from the class of Cauchy problems with non-liner control logic is presented to resolve the task discussed. The designed model is performed in two stages: the mathematical model specification (modeling) and implementation (simulation). Two approaches to make a model specification are considered, the first one is the traditional structural technique, and the advanced method is based on the finite state machine paradigm. Structural and finite state software models are built in progressive simulation tools. Computer implementation of the software models of hybrid systems is performed using platform built-in libraries with numerical methods and algorithms for correct event detection. The results of computational experiments for transient processes of phase variables are qualitatively identical, that proves the adequacy of the developed models. The algorithm for asymptotic event detection is considered in detail. This technique demonstrated the best results by the one-sidedness criterion, which is explained by using the author’s algorithm for the integration step determining and the event function dynamics monitoring in the vicinity of the event limits.

: This study explores the perceptions of Chinese learners in Spain regarding the use of social networks for informal Spanish language learning. The objective is to identify the challenges and benefits of using social networks to address the real needs of students in learning Spanish. A qualitative phenomenological approach was adopted, focusing on participants’ perceptions before and after using social networks. Eight Chinese students were selected for the study. The study was conducted in Valencia and Barcelona, Spain, from 1 September 2023 to 20 March 2024, and three commonly used social media networks were compared. The results indicate positive perceptions towards social media as a tool for learning Spanish, highlighting its usefulness in improving language skills and enhancing cultural awareness. Additionally, Xiaohongshu and Bilibili emerged as the most popular platforms for Spanish language learning among Chinese students. This study concludes that social media effectively meets the authentic needs of Chinese students learning Spanish in Spain, enhancing both language skills and cultural adaptation. This multifaceted approach reflects the complexity of learning Spanish in the digital age, combining personal passion, professional aspirations, and cultural adaptation needs.

Abstract: Extensive research shows nurses’ work environment to be particularly stressful. This study develops, explores, and psychometrically tests a new profession specific ques-tionnaire identifying generalized and specific resistance resources, that make it possible to measure resources to manage work-related stress. An exploratory study design was em-ployed. The questionnaire was developed inspired by the MEASURE approach and the salutogenic theory of health. Building on the results from a literature review of nursing re-search and salutogenesis, supplemented by twelve interviews with hospital nurses, an item pool was generated. A first version was pilot tested in a group of nurses who were studying to become specialist nurses. A second version of the questionnaire was psycho-metrically tested on nurses in close patient care (n = 475), analysed using Principal Com-ponent Analysis as the extracting technique to identify the underlying structure of the questionnaire. The Principal Component Analysis revealed a four-component model of 19 items. “Manageability as a resource for handling the workload” was the strongest compo-nent, accounting for 21 % of the explained variance. “Contacts with patients as resources for nurses’ job satisfaction” (17.8 %). “Professional attitudes are labelled as resources to nursing” (15 %). “Colleagues are important resources for remaining in the nursing profes-sion” (11 %). The structure of the questionnaire indicates its usefulness in clinical practice for measuring resistance resources.

Autonomous aircraft are the key enablers of future urban services, such as postal and transportation systems. Digital Twins (DT) are promising cutting-edge technologies that can transform the future transport ecosystem into an autonomous and resilient system. However, since DT is a data-driven solution based on AI, proper data management is essential in implementing DT as a Service (DTaaS). One of the challenges in DT development is the availability of real-life data, particularly for training algorithms and verifying the functionality of DT. The current article focuses on data augmentation through synthetic data generation. This approach can facilitate the development of DT in case the developers do not have enough data to train the Machine Learning (ML) algorithm. The current twinning approach provides a prospective ideal state of the engine used for proactive monitoring of the engine’s health as an anomaly detection service. In line with the track of Unmanned Aircraft Vehicles (UAV) for Urban Air Mobility in Smart Cities applications, this paper focuses specifically on the common Hybrid turbo-shaft in drones/helicopters. However, there is a significant gap in real-life similar synthetic data generation in the UAV domain literature. Therefore, Rolling Linear Regression and Kalman Filter algorithms were implemented on noise-added data, which simulate the data measured from the engine in a real-life operational lifecycle. For both thermal and hybrid models, the corresponding DT model has shown high efficiency in noise filtration and a certain amount of predictions with a lower error rate on all engine parameters, except the engine torque.

Fluidic larger-scale integration (LSI) resides at the heart of comprehensive sample-to-answer automation and parallelization of assay panels for frequent and ubiquitous bioanalytical testing in decentralized the point-of-use / point-of-care settings. This paper develops a novel “digital twin” strategy with an emphasis on rotational, centrifugo-pneumatic flow control. The underlying model systematically connects retention rates of rotationally actuated valves as a key element of LSI to experimental input parameters; for the first time, the concept of band widths in frequency space as the decisive quantity characterizing operationally robustness is introduced, a set of quantitative performance metrics guiding algorithmic optimization of disc layouts is defined, and the engineering principles of advanced, logical flow control and timing are elucidated. Overall, the digital twin enables efficient design for automating multiplexed bioassay protocols on such “Lab-on-a-Disc” (LoaD) systems featuring high packing density, reliability, configurability, modularity and manufacturability to eventually minimize cost, time and risk of development and production.

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

Several problems of radiative transfer are yet unsolved because of the difficulties of the calculations involved in them, especially if the intervening shapes are geometrically complex. The main goal of our investigation in this domain is to convert the formulas that were previously derived, into a graphical interface based on the projected solid-angle principle. Such procedure is now feasible by virtue of several widely diffused programs for Algorithms Aided Design (AAD). Accuracy and reliability of the process is controlled by means of the analytical software DianaX developed at an earlier stage by the authors. With this new approach the often cumbersome procedure of lighting and thermal exchange calculations can be simplified and made available for the neophyte, with the undeniable advantage of reduced computer time.

The increase in arrivals of new forest pests highlights the need for effective phytosanitary legislation and measures. This paper introduces legislation targeted at prevention and management of potential introductions of forest pests and pathogens. A summary is given on plant health regulations on a global and regional level with detailed information on the situation in the European Union (EU). The current and new European legislation is discussed and a particular focus is given on eradication and contingency plans for Fusarium circinatum.

Before 1985 growth hormone (GH) was extracted from human pituitaries, and its therapeutic use was limited to children with severe GH deficiency (GHD). The availability of unlimited amount of recombinant GH (rhGH) allowed to investigate the efficacy of rhGH therapy in a number of con-ditions other than GHD. Nowadays, patients with Turner syndrome, SHOX deficiency, Noonan syndrome, Prader-Willi syndrome, idiopathic short stature, chronic kidney disease, and children born small for gestational age can be treated with rhGH in order to improve adult height. In pa-tients with Prader-Willi syndrome rhGH therapy also improves body composition and cognitive function. Large post-marketing multinational studies in a huge number of pediatric patients demonstrated a good safety profile for rhGH. Recently, long-acting formulations of rhGH have been approved and licensed for GHD, and clinical trials are ongoing for other conditions. In this paper, we will review the use of rhGH for the treatment of children with conditions other than GHD.

This feature study attempts on setting a granules involving mesoscopic matter-aggregation context as a problem of passing locally by the matter-aggregating system from classical stochastic (mesoscopic limit) to a quantum description (nanoscale quantum-size effect limit). A d-dimensional entropy-production aggregation of the granules-involving matter is considered in terms of a (sub)diffusive realization. It turns out that when taking a full d-dimensional pathway of the aggregation toward the nanoscale, one is capable of disclosing a Heisenberg type (diffusional) relation, setting up an upper uncertainty bound for the (sub)diffusive very slow granules-including environment that matches the quantum limit of h/2pm (m– average mass of a granule; h – the Planck’s constant) for the diffusion coefficient of the aggregation, likely first proposed by Fürth in 1933, and qualitatively foreseen by Schrödinger some years before, both in the context of a diffusing particle cluster. The classical-quantum passage uncovered here, also termed insightfully the quantum-size effect (as borrowed from the quantum dots’ parlance), works properly for the three-dimensional (d=3) case, making use of a substantial physical fact that the (nano)granules interact readily via their surfaces with the also granular surroundings in which they are immersed. This natural observation is embodied in the basic averaging construction of the diffusion coefficient of the aggregation of interest. Certain, possibly biomedical, applications of the model can also be viewed by prospective inspection of tiny inhomogeneities in nanofibrillar and/or lamellar matter for which certain numerical realizations are plausible to prepare based on thorough nanoscale experiments.

In the paper, by convolution theorem for the Laplace transforms and analytic techniques, the author finds necessary and sufficient conditions for complete monotonicity, monotonicity, and inequalities of several functions involving polygamma functions. By these results, the author derives a lower bound of a function related to the sectional curvature of the manifold of the beta distributions. Finally, the author poses several guesses and open problems related to monotonicity, complete monotonicity, and inequalities of several functions involving polygamma functions.

The Science-Sustainability poses an interdisciplinary paradox. On the one hand, the science for sustainability has increased in OECD economies in and in China as well as in the US in particular; on the other hand; the sustainability situation has worsened (Co2 emission has risen). On the face value, the adverse correlation shows a paradox. However, without explicating the science-sustainability relationship, it leads to a premature conclusion. In this study, we have drawn on three concrete questions for concrete answers. First, whether and how interdisciplinary sciences—energy science and environmental science—contribute to the sustainability. Second, whether and how the Sino-US inter-institutional analysis varies in the science-sustainability paradox. The empirical analysis from a panel data in the interdisciplinary and inter-institutional context show mixed patterns in three ways. First, the increase in the environmental science shows an improvement in the sustainability; the energy science shows a decline in the sustainability. Second, the Chinese environmental science has a comparative advantage to American environment science for the sustainability development, and the Chinese energy science has a comparative disadvantage to the US in the sustainability development. Third, the environmental science mediates the energy science in the science-sustainability relationships. Standing alone, the increase in the energy science harms sustainability; mediated by environmental science, it benefits sustainability. The study explains the adverse role of energy science in Jevons Paradox. The study also offers some policy paths for further research how capitalisms differently innovate, form strategies, and implement the practice.

This study re-introduces a protein-free rapid test method for nucleic acids on paper based lateral flow assays utilizing special multichannel nitrocellulose membranes and DNA-Gold conjugates, achieving significantly enhanced sensitivity, easier protocols, reduced time of detection, reduced costs of pro-duction and advanced multiplexing possibilities. It is shown for the first time a protein-free nucleic acid based lateral flow assay (NALFA) with a limit of detection of 1 pmol of DNA. The total production duration of such an assay was successfully reduced from the currently known several days to just a few hours. The simplification and acceleration of the protocol make the method more accessible and practical for various applications. The developed method supports multiplexing, enabling the sim-ultaneous detection of up to six DNA targets. This multiplexing capability is a significant improve-ment over traditional line tests and offers more comprehensive diagnostic potential in a single assay. The approach significantly reduces the run time compared to traditional line tests, which enhances the efficiency of diagnostic procedures. The protein-free aspect of this assay minimizes the prevalent complications of cross-reactivity in immunoassays especially in cases of multiplexing. It is also demonstrated that the NALFA developed in this study is amplification-free and hence does not rely on specialized technicians, nor does it involve labour-intensive steps like DNA extraction and PCR processes. Overall, this study presents a robust, efficient, and highly sensitive platform for DNA or RNA detection, addressing several limitations of current methods documented in the literature. The advancements in sensitivity, cost reduction, production time, and multiplexing capabilities mark a substantial improvement, holding great potential for various applications in diagnostics, forensics, and molecular biology.

(1) In an era where sustainable behavior is increasingly crucial, understanding the discrepancy between individuals' sustainability-oriented values and their actual behaviors, known as the inner-outer gap, is vital. This study explores the potential of the Tripartite Structure of Sustainability (TSS) framework to address this gap within the context of sustainable education. By reviewing literature from the databases APA, ERIC, and Web of Science, we systematically examined factors influencing sustainable actions. (2) Employing a qualitative content analysis approach, we analyzed 56 articles over a 15-year period, identifying 83 factors that either bridge or reinforce the inner-outer gap. These factors were categorized within the TSS framework, which segments sustainability-oriented actions into individual, social, and self-transcendent domains, alongside their activation points: stable, situational, or automated. (3) Our analysis revealed that self-focused factors often reinforce the gap, suggesting a hindrance to sustainable behavior. Conversely, self-transcendent factors consistently bridged the gap, promoting sustainability. Social factors showed variable impacts based on the ethical and sustainable context they were placed in, suggesting that the social environment's orientation significantly influences sustainable behavior. (4) The study concludes that the TSS framework offers a promising approach to advancing sustainability in education by facilitating a paradigm shift towards holistic and interconnected perspectives. This shift is critical for fostering sustainable behaviors, thereby contributing to the field of educational psychology and offering practical implications for educators aiming to nurture a sustainable future.

(1) Background: The COVID-19 pandemic had a devastating impact on the world, causing widespread illness and death. It is essential to focus on prevention strategies to limit the spread of the disease. Despite the advent of vaccines, maintaining a vigilant approach to prevention remains paramount. While vaccines are essential, they do not guarantee absolute immunity, and their protective effect may diminish over time; (2) Methods: We reviewed effective strategies to prevent COVID-19 transmission. We focused on me-ta-analyses (MA), literature reviews (LR) and the health care context. Various prevention measures and interventions were reviewed. Both es-tablished practices and unresolved issues were considered; (3) Results: Standard precautions (SP) as the cornerstone of infection control, with hand hygiene and mask use as key components. Debate about the relative importance of droplet versus aerosol transmission led to differences in recommendations between agencies at the onset of the pandemic. We have clarified the role of personal protective equipment (PPE), including eye protection. The effectiveness of masks in pre-venting transmission is reviewed. The use of surgical masks is recommended to prevent droplet transmission, while eye protection is recommended in combination with masks. Although data show some risk reduction, the clear superiority of N95/FFP2 over surgical masks remains unproven. In terms of room occupancy, ventilation is critical in reducing the risk of transmission in poorly ventilated environments. The use of negative pressure isolation rooms (NPIRs) is being investigated. The presence of viral RNA on surfaces does not necessarily indicate infectivity, and the risk of transmission by surface contact is low if surfaces are properly maintained and hand hygiene is practised regularly. Testing for SARS-CoV-2 in asymptomatic persons in healthcare settings may help prevent transmission; (4) Conclusions: Prevention of SARS-CoV-2 transmission requires a multifaceted approach, including reducing particle emissions from infected persons by wearing masks, eliminating aerosols by ventilation, ensuring physical separation, and protecting exposed persons with masks and eye protection.

The diverse socio-economic and environmental impacts that the set-up of a new photovoltaic installation has must be weighed carefully in order to reach the best possible solution. Among the different photovoltaic systems there are several classification criteria, depending on the technology, application and the size of the modules that define them. The size (installed nominal capacity) stands out as an impartial and critical measure in the decision making process. In this article we use a multi-criteria decision making method to analyse the responses of five experts to a detailed questionnaire in which several different criteria are correlated with various photovoltaic installation sizes. The limitation associated to the low number of experts is addressed with a robustness and sensitivity analysis. With this study we seek first, to apply and demonstrate the feasibility of a methodology which combines technical information with multi-criteria decision making methods, and second, to obtain a clear result oriented that increases the benefits of a forthcoming photovoltaic installation of modules in distributed generation adding up to 1GW total peak power in standard conditions. We observe a consistent result in which smaller photovoltaic modules are the ideal solution that maximises the socio-economic benefits of any installation. If a decision has to be taken about the type of photovoltaic plant to be installed, the conclusion is clear: given a certain size, small, easily scalable installations are the best solution for stake-holders, for the inhabitants, and for the environment.

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

India’s increasing reliance on equated monthly installments (EMIs) has reshaped household financial behavior in ways that pose significant risks to long-term economic stability. This paper examines the growing trend of EMI-driven debt accumulation, highlighting its detrimental effect on household savings and the rising financial vulnerability across demographic groups. Leveraging data from the Reserve Bank of India (RBI), CRISIL, and the National Statistical Office (NSO), the study delves into how debt dynamics are shifting within Indian households, particularly in the context of broader economic trends. Retail credit has expanded rapidly, growing from 12.1% of GDP in 2017 to 19.4% by 2023, with housing loans now making up nearly half of all retail loans. Concurrently, the growth of unsecured loans, such as credit card debt, has surged at an annual rate of 21.3% between 2021 and 2024, reflecting the increasing ease of borrowing for consumers. However, this boom in credit has coincided with a marked drop in household financial savings, which fell to a 47-year low of 5.3% in FY22, underscoring a troubling shift from saving to borrowing. The younger population, particularly those under 35, have been the most active in taking on debt, with loans to this group nearly doubling between 2015 and 2021 due to the rise of fintech platforms and non-banking financial companies. This shift has contributed to a steep rise in debt-service-to-income ratios, amplifying the financial risks for these households in the face of potential economic shocks. By connecting these micro-level household debt trends to broader macroeconomic risks, this paper reveals how India’s EMI culture could deepen the impact of future financial crises, leading to widespread defaults and destabilizing the economy. The study calls for proactive regulatory measures and enhanced financial literacy programs to curb the growing reliance on consumer credit and mitigate the risks of a broader financial collapse.

As UAVs are increasingly employed across various industries, the demand for robust and accurate detection has become crucial. LiDAR has developed as a vital sensor technology because to its ability to offer rich 3D spatial information, particularly in applications such as security and airspace monitoring. This review systematically explores recent innovations in LiDAR-based drone detection, deeply focusing on the principle and components of LiDAR sensor, its classifications based on different parameters and scanning mechanisms, as well as the approaches for processing LiDAR data. The review briefly compares several deep learning approaches, including point-based, voxel-based, and hybrid models, that have improved drone detection, tracking, and classification. We also explore the integration of multi-modal sensor fusion, which combines LiDAR data with other complimentary modalities to improve UAV detection and tracking in complex environments such as GNSS-denied zones.

Underreporting is the main limitation of the spontaneous reporting systems. This study aims to reduce underreporting enhancing public participation in vaccinovigilance through an SMS-based reporting system integrated with electronic immunization registries (IRs). Using the VigiVax software, parents of vaccinated children aged 2 years or younger received a single SMS inquiry about adverse events following immunization (AEFI). Responses were collected, validated by health operators and integrated with the information on IRs. AEFI reports were automatically submitted to the Italian Pharmacovigilance system. Among 254,160 SMS messages sent, corre-sponding to 451,656 administered doses (AD), 71,643 responses were collected (28.2% response rate), 21,231of them (8.3%) reporting an AEFI. After seriousness assessment based on clinical criteria, 50 reports (0,24%) were classified as serious. Among these, causality assessment identi-fied 31 reports at least potentially related to the vaccination (RR: 6.86/100,000 AD). Febrile seizures following MMRV vaccination accounted for 11 of these 31 cases, with an incidence of 32 per 100,000 AD. No fatal outcomes were reported. Our findings support the highly favorable risk profile of pediatric vaccinations and the possibility to improve spontaneous reporting through the integration of digital technologies.

After reviewing the history of the struggle between human beings and plant diseases, insects and weeds, especially reviewing the thoughts of plant protection in ancient Chinese agricultural books, the target recognition of plant pests and the six types of plant protection methods and 36 subdi-vision measures were summarized. Then the development overview of pesticide application technology was focused and reviewed systematically by combining the development timeline of pesticide application and the key technologies including the performance measurement and the simulation and modeling of pesticide spraying system. And three suggestions for further research were proposed from the perspectives of human-being and environmental health, the sustainable and eco-friendly application medium, and the efficiently application equipment system in plant protection.

The involvement of the angiotensin II type 1 receptor in the Frank-Starling Law of the Heart, where the various activations are very limited, allows simple analysis of the kinase systems involved and thence extrapolation of the mechanism to that of angiotensin control of activation of cardiac and skeletal muscle contraction. The involvement of phosphorylation of the myosin light chain in the control of contraction is accepted but not fully understood. The involvement of troponin-I phosphorylation is also indicated but of unknown mechanism. There is no known signal for activation of myosin light chain kinase or Protein Kinase C-βII other than Ca²⁺/calmodulin but the former is constitutively active and thus has to be under control of a regulated inhibitor, the latter kinase may also be the same. Ca²⁺/calmodulin is not activated in Frank-Starling, i.e. there are no diastolic or systolic [Ca²⁺] changes. I suggest here that that the regulated inhibition is by myosin light chain phosphatase and/or β-arrestin. Angiotensin activation is by translocation of the β-arrestin from the sarcoplasm to the PM thus reducing its kinase inhibition action in the sarcoplasm, this reduced inhibition has been wrongly attributed to a mythical downstream agonist property of β-arrestin.

This study presents a method for the rapid and accurate generation of two-dimensional (2D) orthomosaic maps using selected image data collected by drone-captured video. The focus is on developing a real-time method capable of creating maps more quickly than image selection. The scale-invariant feature transform (SIFT) algorithm is applied to drone images to extract features in various scale regions. For feature point matching, a matching method based on the fast library for approximate nearest neighbors (FLANN) was adopted. A comparison of the computational speed of the FLANN with that of the k-nearest neighbors (KNN) and brute force matcher during the matching process revealed FLANN's superior capability for real-time data processing. The random sample consensus (RANSAC) algorithm was employed to enhance the accuracy of the matching by removing outliers, effectively identifying and eliminating mismatches, and reinforcing the reliability of feature point matching. The combination of SIFT, FLANN, and RANSAC algorithms demonstrates the capacity to process drone-captured image data in real time, facilitating the generation of precise 2D orthomosaic maps. The proposed method was assessed and validated using imagery obtained as the drone executed curvilinear and straight flight paths, confirming its accuracy and operational efficiency concurrently with the image capture process.

A multitude of factors influence our well-being and health in everyday life. Some of which we are totally aware like a delayed train, car exhausts, or continuous work stress. Other factors influence us on a subconscious level, making them, however, not less important to address. One of these factors is the built environment surrounding us almost every second of our lives. The idea of biophilic design states the importance of natural elements implemented in architectural structures to improve the occupants’ health and well-being. Adding to this field of research, this article targets the impact of biophilic design on positive emotions and productivity by using novel approaches like Facial Emotion Recognition (FER) with Residual Masking Networks, and sentiment detection using Large Language Models. Two separate but related studies were conducted and their results reported here. The first study measured emotions of people when confronted with images of different kinds of architecture, via FER (Facial Emotion Recognition) and also via a user survey. We distinguish between self-stated emotions entered through a survey by study participants, and emotions detected from studying the participants’ faces through AI from our FER (Facial Emotion Recognition) system. We found clear trends for most detected emotions, and significant evidence for self-stated emotions, that architecture implementing biophilic design evokes more positive emotions than one that does not. The second study measures the influence of natural elements on productivity and team-engagement. We found that natural elements do influence productivity and sentiment positively; however, only the change in sentiment was shown to be significant. As our sample size, especially for the second study, was relatively small, future research will apply these ideas in a larger setup to acquire further evidence for the importance of biophilic design for human well-being and health.

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

Socio-ecologic, socio-economic, and socio-technical transitions are opportunities that require fundamental changes in the system. These will encounter matters associated with security, service adoption by end-users, infrastructure and availability. The purpose of this study is to examine and overcome the risks to take advantage of opportunities through the novel Risky-Opportunity Analysis Method (ROAM). A novel quantitative method is designed to determine when, after making some changes, the risks become acceptable so that the opportunity does not deviate from the objectives. The approach provided a quantitative evaluation of the possible changes in parallel with digitization, towards providing a green Service Supply Chain (SSC). The result of ROAM shows that the most cost-effective change to increase the resilience of the system is a solution (SMS) which is different from that identified by a TOPSIS multi-criteria method. Real-word decisions in change management should tackle the complexity of systems and uncertainty of events during and after transition through a careful analysis of the alternatives. A case-study was carried out to evaluate the alternatives of an ancillary service in the Payment Service Providers (PSP). The comparison of the ROAM results with the traditional TOPSIS of the case-study unveils the priority of the ROAM in practice when the alternatives are Risky-Opportunities. The existing risk assessment tools do not take advantage of risky opportunities. To this aim, the current article introduces the term Risky-Opportunity, and two indexes Stress and Strain of the alternatives that are designed to be employed in the new quantitative ROAM approach.

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

Conclusions: Our findings suggest that the NMS-E represents a valuable preoperative diagnostic tool for endometriosis, effectively correlating with the disease's severity and surgical outcomes. Incorporating the NMS-E into clinical practice could significantly enhance the management of endometriosis by addressing current diagnostic limitations and guiding surgical planning.

Microarray gene expression-based detection and classification of medical conditions have been prominent in research studies over the past few decades. However, extracting relevant data from the high-volume microarray gene expression with inherent nonlinearity and inseparable noise components raises significant challenges during data classification and disease detection. So, this paper proposes a two-level strategy involving feature extraction and selection methods before the classification step. The feature extraction step utilizes Short Term Fourier Transform (STFT), and the feature selection step employs Particle Swarm Optimization (PSO) and Harmonic Search (HS) metaheuristic methods. The classifiers employed are Non-Linear Regression, Gaussian Mixture Model, Softmax Discriminant, Naive Bayes, SVM (Linear), SVM (Polynomial), and SVM (RBF). The two-level extracted relevant features are compared with raw data classification results, including Convolutional Neural Network (CNN) Methodology. Among the methods, STFT with PSO feature selection and SVM (RBF) classifier produced the highest accuracy of 94.47%.

The pH-related metabolic paradigm has rapidly grown in cancer research and treatment. In this contribution, this recent oncological perspective has been laterally for the first time in order to integrate neurodegeneration within the energetics of the cancer acid-base conceptual frame. At all levels of study, molecular, biochemical, metabolic and clinical, the intimate nature of both processes appears to be opposite mechanisms occurring at the far ends of a physiopathological intracellular pH/extracellular pH (pHi/pHe) spectrum. This wide-ranged original approach now permits an increase in our understanding of these opposite processes, cancer and neurodegeneration, and, as a consequence, allows to propose new avenues of treatment based upon the intracellular and microenvironmental hydrogen ion dynamics regulating and deregulating the biochemistry and metabolism of both cancer and neural cells. Under the same perspective, the etiopathogenesis and special characteristics of multiple sclerosis (MS) becomes an excellent model for the study of neurodegenerative diseases and, utilizing this pioneering approach, we find that MS appears to be a metabolic disease even before an autoimmune one. Also within this paradigm, several important aspects of MS, from mitochondrial failure to microbiota functional abnormalities, are analyzed in depth.

Background: In chronic obstructive pulmonary disease (COPD), there are two known classifications for assessing what is called disease severity. One is the Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification, which is based on the post-bronchodilator value of FEV1 (% reference). The other is the STaging of Airflow obstruction by Ratio (STAR). Methods: We reanalyzed data from our outpatient cohort study, which included 141 participants with COPD from 2015 to 2023. We compared mortality and COPD-specific health status between the GOLD 1 to 4 groups and the STAR 1 to 4 groups. Results: By simple calculation, GOLD and STAR severity classes coincided in 75 participants (53.2%). The weighted Bangdiwala B value with linear weights was 0.775. The participants were observed for up to 95 months, with a median of 54 months. Death was confirmed in 29 participants (20.5%). In univariate Cox proportional hazards analyses, there was a significant difference in mortality between the GOLD 1 and GOLD 3+4 groups, with the GOLD 1 group used as the reference [Hazard Ratio 4.222 (95% CI 1.298 - 13.733), p=0.017]. However, there was no statistically significant predictive relationship between STAR 1 and STAR 2, or between STAR 1 and STAR 3+4. The St. George's Respiratory Questionnaire (SGRQ) Total and COPD Assessment Test (CAT) scores were significantly different between all GOLD groups, except for the CAT score between GOLD 1 and GOLD 2. The SGRQ Total and CAT scores were significantly different between STAR 1 and STAR 3+4, but not between STAR 1 and STAR 2. Conclusion: From the perspective of all-cause mortality and COPD-specific health status, the GOLD classification is more discriminative than STAR.

Despite great technical capabilities, the theory of non-contact temperature measurement is usually not fully applicable to the use of measuring instruments in practice. While black body calibrations are in practice well established and easy to accomplish, this calibration protocol is never fully applicable to measurements of real objects under real conditions. Currently, the best approximation to real world radiation thermometry is grey body radiation thermometry, which is supported by most measuring instruments to date. Nevertheless, the metrological requirements necessitate traceability, therefore real body radiation thermometry is required for temperature measurements of real bodies. This article documents the current state of temperature calculation algorithms for radiation-thermometers and the creation of a traceable model for radiation thermometry of real bodies that uses a digital twin model of the system of measurement to compensate for the loss of data, caused by spectral integration, which occurs when thermal radiation is absorbed on the active surface of the sensor. To solve this problem, a hybrid model with variable scalar inputs is proposed, in which the scalar input parameters are calculated to correspond to the system of measurement. The method for calculating the effective parameters is proposed and verified with the theoretical model of non-contact thermometry. The sum of effective instrumental parameters is presented for different temperatures to show that the rule of radiation thermometry of grey bodies, according to which the sum of instrumental emissivity and instrumental reflectivity equals to 1, does not hold in radiation thermometry for real bodies. Using the derived models of radiation thermometry, the uncertainty of radiation thermometry due to the uncertainty of spectral emissivity is analysed by simulated measurements along the temperature ranges of various radiation thermometers, enabling traceable non-contact temperature measurements with known measurement uncertainty under any known conditions.

The official recommendations to manage COVID-19 in the outpatient setting focus on high-cost drugs (remdesivir, nirmatrelvir-ritonavir, molnupiravir), suffering from many problems. Therefore, one may consider also other treatments meeting these criteria: • promising effectiveness, based on favorable randomized controlled trials (RCTs) of sufficient validity. Even without definitive evidence, physicians and informed patients can consider them if they are also: • safe, to the state of knowledge • with a very favorable opportunity cost • biologically plausible/not implausible • accessible • without major commercial sponsors in the trials promoting them, and with researchers without major conflicts of interests. The main focus is on a limited group of functional foods and some their active ingredients, with further mention of other substances of different origin, yet fully meeting all the aforementioned criteria. The functional foods and substances described and discussed certainly do not cover all the known effective therapies for COVID-19 (in one case also for Long-COVID), but the only therapies proposed in this paper currently satisfy all the above criteria. The supporting scientific evidence will favor meta-analyses of RCTs that include the most definitive outcome: all-cause mortality, i.e. the outcome that most fully informed people tend to prioritize. Furthermore, the reported evidence favors clinical studies of the most valid design, i.e. RCTs.

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

We assume that poetic devices have an implicit goal: producing an overall sound scheme that will induce the reader to associate intended and expressed meaning to the sound of the poem. Sounds may be organized into categories and assigned presumed meaning as suggested by traditional literary studies. In my work, I have extracted automatically the sound grids of all the sonnets by William Shakespeare and have combined them with the themes expressed by their contents. In a first experiment I have computed lexically and semantically based sentiment analysis obtaining an 80% of agreement. In a second experiment sentiment analysis has been substituted by Appraisal Theory thus obtaining a more fine-grained interpretation which in some cases contradicts the first one. The computation for the second poet - regarded by many critics the best of last century - includes both vowels and consonants. In addition, it combines automatic semantically and lexically based sentiment analysis with sound grids. The results produce visual maps that clearly separate poems into three clusters: negative harmony, positive harmony and disharmony where the latter instantiates the need by the poet to encompass the opposites in a desperate attempt to reconcile them.

Endometrial preparation is crucial in in vitro fertilization (IVF) protocols to create optimal conditions for embryo implantation and pregnancy. Successful embryo nidation requires a receptive endometrium, which is influenced by factors such as endometrial thickness, hormonal environment, autocrine and paracrine growth factors, and the presence of resident and non-resident stem cells within the endometrium basalis. Synchronization between endometrial and embryonic development is also essential. Endometrial preparation, whether achieved through spontaneous cycles, natural cycles with minimal support, ovulation induction, or hormone replacement therapy (HRT), results from a combination of biochemical and biophysical conditions, each independent of the others. These conditions are difficult to pinpoint within a fixed period (Window of Implantation, WOI) using any specific examination due to the variability in estrogen and progesterone production rates, their metabolic clearance rates (MCR) when administered exogenously, and their metabolism when given systemically, topically, or orally. These variations also occur in different phenotypes and over different durations. Moreover, the synchronization of endometrial preparation with incomplete decidualization and the uncertain duration of the implantation window pose challenges. It is also unknown if there are compliance mechanisms similar to diapause seen in other species. This review aims to outline a clinical approach that, while not an absolute clinical recommendation due to the lack of definitive certainties, assists in understanding complementary phenomena and provides a useful orientation for clinical practice.

(1) Introduction: Every two hours, a Romanian woman is diagnosed with cervical cancer [1] as the country ranks second in Europe in terms of mortality and incidence rate [2]. This paper aims to identify the main reasons that have led to this situation, focusing on the measures taken by the Romanian Ministry of Health for the prevention of this type of cancer national - programs for cervical cancer screening and HPV vaccination. (2) Materials and methods: We performed a study based on available secondary data from the National Statistics Institute, World Health Organization and Bucharest Institute of Oncology in order to assess the burden associated with cervical cancer and placing it in the context of known global and European incidence and mortality rates, thus evaluating the importance of this health issue in Romania. The second component of our study was a cross-sectional study, using a 14 questions questionnaire, applied to the women participating in the National Screening Program for Cervical Cancer, aimed to evaluate the women’s level of knowledge about screening and HPV vaccination and their access cervical cancer specific health-care services. (3) Results: The results of the research shows that a high percentage of women postpone the routine checks due to lack of time and financial resources and indicate that low level of knowledge about the disease and the specific preventive methods determines low participation screening and HPV vaccination programs implemented in Romania contributing to the country’s situation of cervical cancer. (4) Conclusions: The national programs have complicated procedures, are underfunded, and do not motivate enough health care workers. This combined with the lack of information adds up to an extremely low number of women screened and vaccinated. Our conclusion is that the Romanian Ministry of Health must take immediate action by conducting major awareness campaigns, implementing measures to make the programs functional and ensuring coherent funding.

The goods and services produced by forest vegetation ecosystem are the driving force for the rapid, high-quality and sustainable development of human society. In history, with the increase of population and economic development, there is an increasing demand for the quantity and variety of forest vegetation ecosystem products and services in a country or a region. To meet the demands, most of the original forest has become farmland, plantation and grass and crops land. As a result, the plant water relationship changed from equilibrium to non-equilibrium, which easily led to soil drought, soil degradation and vegetation decline in dry years or waste of soil water in rainy years in most of water-limited regions. In order to solve the question and realize the sustainable utilization of soil water resources and the high-quality sustainable development of forest, it is necessary to apply the limit theory of plant utilization of soil water resources and the vegetation carrying capacity theory in the critical period of plant-water relationship regulation to adjust the relationship between plant growth and soil moisture to obtain the maximum yield and benefit and realize high-quality and sustainable development.

Safety limits application has always been a traditional approach to ensure the safe operation of electro-mechanical systems within many industries including automated vehicles, robotics, aerospace, traditional automotive, railways, manufacturing, etc. In all of these applications, control and safety limits are usually hard-coded into the production firmware and are fixed throughout the entire product life cycle. Currently, due to the evolving needs of automated systems like automated vehicles and robots, this traditional approach does not address all the use cases and scenarios to ensure safe operation. Especially for data-driven machine learning applications that constantly evolve and learn over time, it is important to be able to adjust the safety limits application strategy to be more flexible and adaptable based on different Operational Design Domains (ODDs) and scenarios. Our ITSC conference paper ~\cite{4} introduced the concept of a new safety limits application strategy called the Dynamic Control Limits Application (DCLA) strategy that supports the flexible application of diverse limits profiles based on the parameters involved within the dynamic scenario at different layers of the Autonomy software stack.This paper extends the DCLA strategy to derive the complete methodology for safety limits application based on ODD elements, scenario identification and scenario classification using Decision Making Engines. It leverages the layered architecture introduced in the ITSC conference paper to implement the Decision Making (DM) algorithms. Another important extension is the use of cloud infrastructure that is based on the Vehicle-to-Infrastructure (V2I) technology to store the scenarios and the limits mapping to serve as a ground truth and/or a backup mechanism in case of errors or failures associated with the main Decision Making (DM) Engine. There is also a focus on providing a more comprehensive list of scenarios and a custom built experimental dataset to cover the maximum ODD elements, and multiple tables of safety limits to be chosen from, which eventually helps in creating different safety limits application profiles. These distinct safety limits application profiles are based on the scenario parameters that are perceived by the system upon which the Decision Making algorithms are applied or trained. This systematic approach can be used within the industry for any of the future automated vehicles and systems until Level 5 Autonomy.

There is scientific consensus that organismal aging did not evolve by natural selection (NS) because it lacks individual benefit. Nonetheless it exists, leading to much speculation about its origins, and when the diminishing force of selection begins. Both concepts are based upon two misconceptions; that aging occurs in and of itself and is caused by the declining strength of NS during the reproductive lifespan. Although lacking individual benefit, aging evolved by NS as a tradeoff of survival for reproduction. Based upon regulatory dynamics that participate in this tradeoff, aging begins once reproductive success has been achieved through offspring nurturing. Thereafter, the strength of NS wanes to exponentially accelerate aging, leading to death. Assumptions of the theory are that: (1) a life-long, “holistic” regulatory mechanism whose genic expression is modified epigenetically, originates in ontogenesis; (2) the regulatory mechanism of the last developmental stage becomes redundantly expressed during “morphostasis”, a non-aging, life interval of peak vitality to ensure completion of reproduction through nurturing, and (3) thereafter, loss of regulatory redundancy causes aging which reduces the strength of natural selection and allows accumulation of randomly occurring somatic damage.

There is a balanced plant-water relationship in the primary vegetation of desert area. With the increase of population and social development in desert areas, people’s need for forest vegetation ecosystem’s goods and service have been changed. To meet the growing demand for plant community goods and services, more original vegetation has been changed into non-native vegetation such as in China loess plateau. However, with the plant growth, sometime soil drying happens and then becomes gradually serious with times in most of desert regions. Serious drying of soil eventually result in soil degradation, vegetation decline and agriculture failure，which influence the produce and supply of forest vegetation goods and service in market in dry year or waste of soil water resources in wet year, which wastes precious nature resources. In order to solve these problems, the soil water resources have to be used in sustainable way and plant-water relationship have to be regulated on Carrying Capacity of Soil Water for Vegetation in the key period of plant water relationship regulation, to carry out sustainable use of nature resources, high-quality and sustainable development of forest and grass or high-quality produce of fruit and crop in desert re-gions.

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

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

This article explores the intersection of innovative leadership and climate change, aiming to provide outstanding contributions to the existing body of knowledge in this field. The article identifies the critical role of innovative leadership in driving sustainable solutions and strategies for addressing climate change. It examines the defining characteristics and behaviors of innovative leaders and explores how their transformative leadership approaches can create a positive impact on climate change mitigation and adaptation efforts. The article also highlights the importance of fostering innovation within organizations and societies to tackle the complex challenges posed by climate change. Through a comprehensive review of relevant literature and case studies, this article presents novel insights, theoretical frameworks, and practical implications for policymakers, organizations, and individuals involved in climate change leadership.

Information is the currency of life, but the origin of prebiotic information remains a mystery. We propose transitional pathways from the cosmic building blocks of life to the complex prebiotic organic chemistry that led to the origin of information systems. The prebiotic information system, specifically the genetic code, is segregated, linear, and digital and probably appeared during biogenesis four billion years ago. In the peptide/RNA world, lipid membranes randomly encapsulated amino acids, RNA, and protein molecules, drawn from the prebiotic soup, to initiate a molecular symbiosis inside the protocells. This endosymbiosis led to the hierarchical emergence of several requisite components of the translation machine: tRNAs, aaRS, mRNAs, and ribosomes. When assembled in the right order, the translation machine created biosynthetic polypeptides, a process that transferred information from mRNAs to proteins. This was the beginning of the prebiotic information age. The molecular attraction between tRNA and amino acids led to different stages of the translation machines and the genetic code. tRNA is an ancient molecule that designed and built mRNA for storing the information of its cognate amino acid. Each mRNA strand became the storage device for the genetic information that encoded the amino acid sequences in triplet nucleotides. As information appeared in the digital languages of the codon within mRNA, and the genetic code for protein synthesis evolved, the prebiotic chemistry then became more organized and directional. The origin of the genetic code is enigmatic; herein we propose an evolutionary explanation: the demand for a wide range of specific enzymes in the peptide/RNA world was the main selective pressure for the origin of information-directed protein synthesis. We review three main concepts on the origin and evolution of the genetic code: the stereochemical theory, the coevolution theory, and the adaptive theory. These three theories are compatible with our coevolution model of the translation machines and the genetic code. We suggest biosynthetic pathways as the origin of the specific translation machines which provided the framework for the origin of the genetic code. During translation, the genetic code developed in three stages coincident with the refinement of the translation machines: GNC code developed by the pre-tRNA/pre-aaRS /pre-mRNA machine, SNS code by the tRNA/aaRS/mRNA machine, and finally the universal genetic code by the tRNA/aaRS/mRNA/ribosome machine. Our hypothesis provides the logical and incremental steps for the origin of the programmed protein synthesis. In order to understand the prebiotic information system better, we converted letter codons into numerical codons in the Universal Genetic Code Table. We have developed a software called CATI (Codon-Amino Acid-Translator-Imitator) to translate randomly chosen numerical codons into corresponding amino acids and vice versa. This conversion has granted us insight into how the translation might have worked in the peptide/RNA world. There is great potential in the application of numerical codons to bioinformatics such as barcoding, DNA mining, or DNA fingerprinting. We constructed the likely biochemical pathways for the origin of translation and the genetic code using the Model-View-Controller (MVC) software framework, and the translation machinery step-by-step. Using AnyLogic software we were able to simulate and visualize the entire evolution of the translation machines and the genetic code. The results indicate that the emergence of the information age from the peptide/RNA world was a watershed event in the origin of life about four billion years ago.

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

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

Low Power Wide Area Networks (LPWAN) enable a growing number of Internet-of-Things (IoT) applications with large geographical coverage, low bit-rate, and long lifetime requirements. LoRa (Long Range) is a well-known LPWAN technology that uses a proprietary Chirp Spread Spectrum (CSS) physical layer, while the upper layers are defined by an open standard - LoRaWAN. In this paper, we propose a simple yet effective method to improve the Quality-of-Service (QoS) of LoRa networks by fine-tuning specific radio parameters. Through a Mixed Integer Linear Programming (MILP) problem formulation, we find optimal settings for the Spreading Factor (SF) and Carrier Frequency (CF) radio parameters, considering the network traffic specifications as a whole, to improve the Data Extraction Rate (DER) and to reduce the packet collision rate and the energy consumption in LoRa networks. The effectiveness of the optimization procedure is demonstrated by simulations, using LoRaSim for different network scales. In relation to the traditional LoRa radio parameter assignment policies, our solution leads to an average increase of 6% in DER, and a number of collisions 13 times smaller. In comparison to networks with dynamic radio parameter assignment policies, there is an increase of 5%, 2.8%, and 2% of DER, and a number of collisions 11, 7.8 and 2.5 times smaller than equal-distribution, Tiurlikova's (SoTa), and random distribution, respectively. Regarding the network energy consumption metric, the proposed optimization obtained an average consumption similar to Tiurlikova's, and 2.8 times lower than the equal-distribution and random dynamic allocation policies. Furthermore, we approach the practical aspects of how to implement and integrate the optimization mechanism proposed in LoRa, guaranteeing backward compatibility with the standard protocol.

This work presents an illustrative application of the newly developed “Second-Order Features Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations (2nd-FASAM-NODE)” methodology to determine most efficiently the exact expressions of the first- and second-order sensitivities of NODE-decoder responses to the neural net’s underlying parameters (weights and initial conditions). The application of the 2nd-FASAM-NODE methodology will be illustrated using the Nordheim-Fuchs phenomenological model for reactor safety, which describes a short-time self-limiting power transient in a nuclear reactor system having a negative temperature coefficient in which a large amount of reactivity is suddenly inserted. The representative model responses that will be analyzed in this work include the model’s the time-dependent total energy released, neutron flux, temperature and thermal conductivity. The 2nd-FASAM-NODE methodology yields the exact expressions of the first-order sensitivities of these decoder responses with respect to the underlying uncertain model parameters and initial conditions, requiring just a single large-scale computation per response. Furthermore, 2nd-FASAM-NODE methodology yields the exact expressions of the second-order sensitivities of a model response requiring as few large-scale computations as there are features/functions of model parameters, thereby demonstrating its unsurpassed efficiency for performing sensitivity analysis of NODE-nets.

Aquaculture is rapidly becoming one of the pivotal sectors in the farm economy, driven by the increasing demand for high-quality animal protein at an affordable cost, especially with the escalating human population. However, the expansion of high-density fish populations also brings forth a challenge – the rapid transmission and spread of infectious disease agents among them. To combat this, vaccination is emerging as a reliable and standardized method for providing immunity against viral and bacterial outbreaks. The ideal vaccine is expected to be safe, effective, economical, and easily administered. The fish vaccination industry continually publishes new information on fish immunology and vaccinology, contributing to the improvement of vaccine formulation and efficacy. This review aims to offer insights into the current status of bacterial, viral, and parasitic diseases, discuss existing vaccinations, and address potential industry-threatening diseases like infectious edwardsiellosis, motile aeromonas septicemia, TiLV, salmon anemia, vibriosis, and white spot disease. Technological advancements have played a crucial role in enhancing our understanding of fish immunological mechanisms, leading to improved vaccine administration and the development of recombinant live attenuated, subunit, DNA, and RNA vaccines. However, challenges such as oral tolerance, vaccine degradation, and stressful environments persist, impacting vaccine efficacy. Addressing these challenges and gaining a deeper understanding of the fish immune system and host-pathogen interactions will be pivotal for future improvements, contributing to the sustainability of aquaculture and enhancing global food security.

The document sets out three differentiated proposals for the transport of medicines through RPAS with their respective regulations, adapted to different operational categories: open category, special category and military scope. In the open category, an economical and efficient solution is prioritized for urban and rural areas, complying with weight and height regulations, in addition to guaranteeing the stability and quality of medications during transportation. The special category allows more complex operations and in more adverse conditions, such as densely populated areas and long routes, incorporating advanced security measures and training for personnel. In the military field, RPAS are used in conflict zones and hard-to-reach areas, ensuring the safe and rapid delivery of medical supplies under extreme conditions. Success stories in different countries are highlighted, demonstrating significant improvements in delivery times and risk reduction for health personnel.

This case study explores the transformative effects of emergent digital technologies, particularly augmented reality (AR), on literacy engagement and reading for pleasure. The United Arab Emirates Ministry of Education implemented the UAE Storytime programme, utilising AR to create an interactive literacy experience for young learners. The programme incorporated bilingual episodes, featuring stories based on local and global contexts, with 3D objects and interactive games to enhance understanding. The results indicate a positive correlation between the use of AR and literacy engagement. A high proportion of learners scanned the QR codes to access the AR objects, which enhanced their engagement and understanding of the stories. The programme fostered a learner agency, engaged family members in the learning process, and established a sense of global community. The study recommends the integration of similar initiatives into the curriculum to promote collaboration, creativity, and holistic learning experiences.

Research question/problem: This comprehensive review and comparative analysis aims to investigate the significance of enhancing oxygen provision in the context of COVID-19, focusing on the implications for healthcare policies and services.Background/context: The study addresses the shift in the oxygen dissociation curve of blood in COVID-19 patients, emphasizing the impact on oxygen delivery to tissues and the challenges it poses for clinical management. It also explores the disruption of healthcare systems due to the pandemic and the integration of social determinants of health in clinical environments.Methodology: The research incorporates a thorough literature review, comparative analysis of diverse approaches to oxygen delivery, and examination of successful interventions through case studies and best practices. Data collection techniques include the review of scholarly articles, case studies, and policy documents.Results/Key findings: The study highlights the imperative for augmented oxygen supply and the significance of maintaining appropriate oxygen saturation levels, especially in the context of respiratory illnesses like COVID-19. It also emphasizes the positive correlation between increased oxygen saturation levels and life expectancy, indicating potential health benefits of enhanced oxygen availability.Conclusions/Implications: The findings underscore the need for a structured approach to oxygen therapy and the importance of equitable distribution of oxygen to underserved regions. The implications of the research extend to enhancing healthcare policies and services regarding oxygen provision during the COVID-19 pandemic, especially in rural and remote areas.

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

In this paper we focus on the association of sound and sense harmony in the collection of sonnets written by Shakespeare in the XVI° beginning of XVII° century and propose a new four-dimensional representation to visualize them by means of the system called SPARSAR. To compute the degree of harmony and disharmony, we have automatically extracted the sound grids of all the sonnets and have combined them with the semantics and polarity expressed by their contents. We explain in details the algorithm and show the representation of the whole collection of 154 sonnets and comment them extensively. In a second experiment, we use data from manual annotation of the sonnets for Satire detection using the Appraisal Theory Framework, to gauge the system's accuracy in matching these data with the output of the automatic algorithm for sound-sense harmony. The results obtained with an 94.6% accuracy confirm the obvious fact that the poet has to account for both sound and meaning in the choice of words.

Traffic Inspection (TI) work in this article is positioned as a specific module of road traffic with its primary function oriented towards monitoring and controlling safe traffic and the execution of significant events within a particular geographic area. Exploratory research on the significance of event execution in simple, complicated and complex traffic flow and process situations is related to the activities of monitoring and controlling functional states and performance of categorical variables, which include objects and locations of road infrastructure, communication infrastructure and networks of traffic inspection resources. It is emphasized that the words “work” and “traffic” have the semantic status as synonyms (in one world language), which is explained in the design of the Agent-based model of the complexity of content and contextual structure of TI work at the singular and plural level with 12 points of interest (POI) in the thematic research. An Event Execution Log (EEL) was created for on-site data collection with eight variables, seven of which are independent (event type, activities, objects, locations, host, duration-period and periodicity of the event) and one dependent (significance of the event) variable. The structured data set includes 10,994 input-output vectors in 970 categories collected in the EEL created by 32 human agents (traffic inspectors) over a 30-day period. An algorithmic presentation of the methodological research procedure for preprocessing and final data processing in the ensemble of machine learning models for classification and selection of TI tasks is given. Data cleaning was performed on the available dataset to increase data consistency for further processing. Vector elimination was carried out based on the Location variable, such that the total number of vectors equals the number of unique categories of this variable, which is 636. The main result of this research is the Classification modeling of the significance of events in TI work based on machine learning techniques and the Stacking ensemble. The created machine learning models for event significance classification modeling have high accuracy values. To evaluate the performance metrics of the Stacking ensemble of models, the confusion matrix, Precision, Recall, ND F1-score are used.

This work is a physical review, with elements of additions and thinning, on the methods of theoretical studies of nonlinear electrophysical phenomena in crystals with ion-molecular chemical bonds (CIMB). Crystals of this class include ionic dielectrics (characterized by high ionic conductivity), layered crystals, a special case of which are hydrogen-bonded crystals (HBC), defined as proton semiconductors and dielectrics (PSD).A scientific review (comparative analysis and justification of various approximations) was carried out on the methods of constructing and solving a generalized quasi-classical kinetic equation describing the mechanism of nonlinear relaxation polarization and conductivity processes in dielectric materials with ion-molecular chemical bonds (a special case is hydrogen-bonded crystals (HBC)) in a wide temperature range (1-1550 K) and polarizing field strengths (0.1-1000 V/m) at alternating field frequencies of the order of 1 kHz - 1000 MHz. The most important variant of the equations of the kinetic theory of dielectric relaxation in this work is the generalized non-linear by polarizing field quasi-classical kinetic equation of ionic (in HBC, proton) relaxation, based on the particle number balance equation (conductivity ions) in potential wells and having (in these models) the meaning of the ion current continuity equation (in HBC, protons), solved by the method of successive approximations by decomposition into infinite power series by degrees of a small dimensionless comparison parameter. It was found that in the area of ​ ​ weak fields (0.1-1 MW/m) at temperatures T = 50 - 550 K, for a number of ionic dielectrics (including HBC and similar dielectric properties and lattice structure) the generalized quasi-classical kinetic equation transforms to the linearized Fokker – Planck equation and, in the region of low (50-100K) and higher temperatures (250-550 K) begin to manifest non-linear polarization effects due to respectively proton tunneling (in the case of HBC) and volume charge relaxation (in the case of the HBC and for a wider class of ionic dielectrics). At ultra-low (1-10 K) temperatures in the region of weak fields (0.1-1 MW/m) and ultra-high temperatures (550-1550 K) in the region of strong fields (10-1000 MW/m), the contribution of this kind of effects to polarization is significantly enhanced. The effect of nonlinearities on relaxation times for microscopic acts of proton transitions across a potential barrier (assumed to be parabolic) is investigated. Nonlinear effects at volume-charge polarization in the hydrogen-bonded crystals (HBC) in alternating electric field, in radio frequency range are investigated. From the solution of the system of nonlinear Fokker-Planck equations (macroscopic kinetic equation) and Poisson, with blocking electrodes, using Fourier series, a recurrent (convenient for use in any approximation of perturbation theory) expression is constructed for complex amplitudes of relaxation modes of volumetric charge. Complex dielectric permittivity (CDP) is calculated as a series decomposition over even frequency harmonics of a variable field. The effect of quantum proton transitions and polarizing field parameters (strength, frequency) on the nonlinear properties of proton semiconductors and dielectrics has been established.

The SARS-CoV-2 virus that causes the COVID-19 disease has wreaked havoc on the world community in terms of every imaginable parameter. The research output on COVID-19 has been nothing short of phenomenal, especially in the medical and biomedical sciences, where the search for a potential vaccine is being conducted in earnest. Much of the advanced research has been distributed in the leading medical journals, including the Journal of the American Medical Association (JAMA), where the latest research is distributed on a daily basis. The purpose of this paper is to provide some perspectives on 44 interesting and highly topical research papers that have been published in JAMA, at the time of writing, within the past two weeks. The diverse topics include public health, general medicine, internal medicine, oncology, paediatrics, geriatrics, and biostatistics.