The wealth of data obtained during the past 20 years using Laser-Induced Breakdown Spectroscopy (LIBS) indicates that the technique is very promising to detect small chemical contents of alloying elements. The potential of LIBS was looked more seriously during the past two decades or so as more data were obtained on Aluminum and steel to study the phenomena in the condition of local thermodynamic equilibrium and time-delay between a Q-switch laser and an intensified CCD camera. Since the past decade, some data on compounds were also shown to be useful in determining small concentrations of harmful elements. This manuscript is intended to show that the technique of LIBS performance is very promising in fields such as micro-machining, in alloying element analysis, surface cleaning and environmental applications even with lightweight spectrometers having a relatively low resolution, which can potentially be air-borne.

3.9 million individuals rely on kidney replacement therapy worldwide. They experience height-ened susceptibility to cardiovascular diseases and mortality, alongside an increased risk of in-fections and malignancies, with inflammation being key to explaining this intensified risk. This study utilized semi-targeted metabolomics to explore novel metabolic pathways related to in-flammation in this populations. We collected pre and post-session blood samples of patients who had already undergone one year of chronic hemodialysis. And used liquid chromatography and high resolution mass spectrometry to perform a metabolomic analysis. Afterwards, we employed both univariate (Mann-Whitney test) and multivariate (logistic regression with LASSO regulari-zation) to identify metabolites associated with inflammation. In the univariate analysis, in-dole-3-acetaldehyde, 2-ketobutyric acid, and urocanic acid showed statistically significant de-creases in median concentrations in the presence of inflammation. In the multivariate analysis, metabolites positively associated with inflammation include allantoin, taurodeoxycholic acid, norepinephrine, pyroglutamic acid, and L-hydroorotic acid. Conversely, metabolites showing negative associations with inflammation include benzoic acid, indole-3-acetaldehyde, methio-nine, citrulline, alphaketoglutarate, n-acetyl-ornithine and 3-4-dihydroxibenzeneacetic acid. Non inflamed patients exhibit preserved autophagy and reduced mitochondrial dysfunction. Under-standing inflammation in this group hinges on the metabolism of arginine and the urea cycle. Additionally, the microbiota, particularly uricase-producing bacteria and those metabolizing tryptophan, play critical roles.

Real assets in the energy market are subject to ecological uncertainty due to the penetration of renewables. We illustrate this point by analysing electrolysers, a class of assets which recently became the subject of a large interest, as they lead to the production of the desirable green hydrogen and green ammonia. The latter has the advantage of being easily stored and has huge potential in decarbonising both the fertilizer and shipping industries. We consider the optimization of green ammonia production with different types of electricity procurement in the context of stochastic power and ammonia markets, a necessary assumption to translate the features of renewable, hence intermittent, electricity. We emphasise the importance of using stochastic prices to effectively model the volatile nature of the price dynamics, illustrating the project risks that can be mitigated by hedging activities. This study shows the pivotal role of flexibility when dealing with fluctuating renewable production and volatile electricity prices to maximise profits and better manage risks.

Green carbon-based materials (GCM), i.e. carbon materials produced using renewable biomass or recycled wastes, ought to be used in order to processes become sustainable and carbon neutral. Carbon nanomaterials, like for example carbon dots and nanobichar families, and carbon materials, like for example activated carbon and biochar substances, are sustainable materials with great potential to be used in different technology applications. In this review, the following four applications were selected, and the works published in the last two years (since 2022) critically reviewed: agriculture; water treatment; energy management; and, carbon dioxide reduction and sequestration. GCM improved the performance of the technological applications under revision and play an important role in the sustainability of the processes, contributing to the mitigation of the climate change, namely by reducing emission and increase sequestration of CO2eq..

The implementation of green roofs as sustainable urban drainage systems provides benefits for stormwater control and the environment and is always more encouraged. In this paper, the estimation of the probability of vegetation survival without irrigation has been proposed as a guide to choose the proper values for the design parameters; in particular the growing medium thickness has been related to the average return interval of the water content at the end of the dry period. Moreover the study represents an improvement of the analytical probabilistic approach since a chain of consecutive rainfall events has been considered, in order to take into account the possibility that the storage capacity is not completely available at the beginning of each event because of the pre-filling from more than one previous rainfall as typically happens for green roofs. Finally, developed equations have been validated by means of their application to two case studies, respectively in northern and southern Italy.

Green development ensures the socioeconomic development that incorporates environmental issues while remaining economically viable for owners and tenants. Government as the authority of the state should provide favorable incentives, policy and regulatory pressure for green development. The present study aims to investigate the government policies and regulations for green development in Bangladesh and make a critical discussion of the initiatives. The study is descriptive in nature and collects secondary information. Evidence suggests that environmental degradation and climate change related risks and vulnerabilities have intensified in Bangladesh. The government of Bangladesh (GOB) is concerned about green development and formulates various Acts, regulations and policy initiatives since 2010. Major green development initiatives observed in the financial institutions due to the mandatory requirements by Bangladesh Bank but green bond and green insurance in capital market are yet to be developed. The GOB required taking proper policy initiatives for the garments and leather industries to ensure pollution free production system which ensures green trade initiatives. The environmental taxes and ecological compensation mechanisms should be revised. Urban green space and Government green procurement are still less concerning matter. The GOB should make effective collaboration with all related stakeholders to ensure the green development.

Relevance of the subject. Keyword selection is critical to finding relevant literature and requires justification for querying abstract databases and other sources to ensure accuracy and completeness. The topic of Energy Systems is of great importance due to the introduction of renewable energy sources, modern control methods, and complex energy systems during the energy transition. The aim of this study. The goal of this paper was to identify keywords that would be useful to subject matter experts when collecting literature on a particular topic, based on entries in the IEEE Terms field. Data. Bibliometric data were exported from the IEEE Xplore platform in the following order: for 2019-2023, 2000 records sorted by relevance, for 2024, 1680 records current as of April 11, 2024. Analytical methods applied and software used. VOSviewer, Scimago Graphica implementing the Clauset-Newman-Moore algorithm and agglomerative hierarchical clustering method implemented in Multidendrograms. Results. The main issues of the Energy Systems topic are presented in tabular and graphical formats. The fpgrowth utility offers flexible data preparation options, which makes it worthwhile to conduct a separate study to analyze the score of co-occurrence terms given by its algorithm.

A mathematical procedure enabling the transformation of an arbitrary tessellation of a surface into a bi-colored complete graph is introduced. Polygons constituting the tessellation are represented by vertices of the graphs. Vertices of the graphs are connected by two kinds of links/edges, namely, by a green link, when polygons have the same number of sides, and by a red link, when the polygons have a different number of sides. This procedure gives rise to a semi-transitive, complete, bi-colored Ramsey graph. The Ramsey number was established as R_trans (3,3)=5. Shannon entropies of the tessellation and graphs are introduced. Ramsey graphs emerging from random Voronoi and Poisson Line tessellations were investigated. The limits ζ=lim┬(N→∞)⁡〖N_g/N_r 〗, where N is the total number of green and red seeds, N_g and N_r, were found ζ=0.272±0.001 (Voronoi) and ζ= 0.47±0.02 (Poisson Line). The Shannon Entropy for the random Voronoi tessellation was calculated as S= 1.690±0.001 and for the Poisson line tessellation as S =1.265±0.015.

A decanter centrifuge has been employed to successfully separated phosphoric acid and rare-earth-element (REE)-containing particles from phosphoric acid sludge with concentrations ranging from 1,000 to 2,200 ppm REEs. Operating efficiently with up to 35 wt.% solids, the centrifuge was demonstrated to achieve approximately 95% phosphoric acid recovery and 90% REEs recovery in a single pass, eliminating the need for additional processing steps. This breakthrough supports a proposed REEs oxide recovery process integrating phosphoric acid (PA), elemental phosphorus (P4), and REEs into two potential pathways: PA-REO and PA-P4-REO. These processes aim to reintroduce recovered phosphoric acid into the main product to significantly increase output and revenue. Post-separation, phosphorus-rich particles can be converted to P4, while REEs-containing solids undergo further treatment including acid leaching, extraction/stripping, precipitation, and calcination to produce a marketable rare-earth oxide (REO) material. Techno-economic analysis indicates promising profitability, with the PA-REO process showing a delta net present value (∆NPV) of $441.8 million and an expected return within a year of construction, while the PA-P4-REO process yields a ∆NPV of $178.7 million over a 12-year return period. Both pathways offer robust financial prospects and demonstrate the feasibility of commercial-scale REEs recovery from phosphoric acid sludge.

Inherited retinal diseases (IRDs) are extremely heterogeneous with at least 350 causative genes, complicating the process of genetic diagnosis. We analyzed samples of 252 index cases with IRDs using the Blueprint Genetics panel for “Retinal Dystrophy” that includes 351 genes. The cause of disease could be identified in 55% of cases. A clear difference was obtained between newly-recruited cases (74% solved) and cases that were previously analyzed by panels or whole exome sequencing (26% solved). As for the mode of inheritance, 75% of solved cases were autosomal recessive (AR), 10% were X-linked, 8% were autosomal dominant, and 7% were mitochondrial. Interestingly, in 12% of solved cases, structural variants (SVs) were identified as the cause of disease. The most commonly identified genes were ABCA4, EYS and USH2A, and the most common mutations were MAK-c.1297_1298ins353 and FAM161A- c.1355_1356del. In line with our previous IRD carrier analysis, we identified heterozygous AR mutations that are not the cause of disease in 36% of cases. The studied IRD panel was found to be efficient in gene identification. Some variants were mis-interpreted by the pipeline and therefore multiple analysis tools are recommended to obtain more accurate annotation of potential disease-causing variant.

This study investigates why young adults live with their parents in Sweden. As young adults’ living arrangements affect decisions about marriage, education, childbirth, and participation in the workforce, more knowledge for policy makers is crucial to implementing effective policies to support young adults and promote financial independence and well-being. Using a data set from 1998 to 2021 at the municipal level in Sweden, we used a spatial autoregressive panel data model to examine the proportion of young adults living at home and regional disparities. The study uncovers intraregional variations, illustrating how different municipalities within Sweden exhibit different patterns of young adults living at home. Our findings reveal that economic factors, such as unemployment, significantly impact this pattern. The dynamics of the housing market, demographic factors, cultural differences, and location-specific characteristics also play an essential role in explaining this pattern. The findings suggest that the key drivers are the lack of rental housing, high unemployment rates, a high degree of urbanisation, interregional migration, and lack of social capital.

This prospective single-center study was designed to assess the clinical utility of the FilmArray® blood culture identification (BCID) panel for improving the diagnostic accuracy in neonatal sepsis. Results obtained using the FilmArray® BCID panel were correlated with results of blood culture in all consecutive neonates with suspicion of early-onset (EOS) and late-onset sepsis (LOS) attended in our service over a 2-year period. A total of 102 blood cultures from 92 neonates were included, 69 (67.5%) in cases of EOS and 33 (32.3%) in LOS. The FilmArray® BCID panel was performed in negative culture bottles at a median of 10 hours of blood culture incubation (range 7.5-20 hours), without differences by the type of sepsis. The FilmArray® BCID panel showed a 66.7% sensitivity, 100% specificity, 100% positive predictive value, and 95.7% negative predictive value. There were four false-negative cases, three of which of Streptococcus epidermidis in neonates with LOS and one case of Granulicatella adiacens in one neonate with EOS. We conclude that the use of the FilmArray® BCID panel in negative blood cultures from neonates with clinical suspicion of sepsis is useful in decision-making of starting or early withdrawal of empirical antimicrobials because of the high specificity and negative predictive values of this assay.

Genotype imputation is widely used to enrich genetic datasets. The operation relies of panels of known reference haplotypes with typically whole-genome sequencing data. How to choose a reference panel has been widely studied and it is essential to have a panel that is well matched to the individuals who require imputation of missing genotypes. However, it is broadly accepted that such an imputation panel will have an enhanced performance with the inclusion of diversity; haplotypes from many different populations. We investigate this observation in this work by examining in fine detail exactly which reference haplotypes are contributing at different regions of the genome. This is achieved using a novel method of inserting synthetic genetic variation into the reference panel in order to track the performance of leading imputation algorithms. We show that while diversity may globally improve imputation accuracy, there can be occasions where incorrect genotypes are imputed following the inclusion of more diverse haplotypes in the reference panel. We however demonstrate a technique for retaining and benefitting from the diversity in the reference panel whilst avoiding the occasional adverse effects on imputation accuracy. What is more, our results elucidate more clearly the role of the diversity in a reference panel than has been shown in previous studies.

Innovative urban farming plays a vital role in enhancing food security, nutrition, livelihood resilience, and environmental sustainability in Sub-Saharan African cities. Despite this, agricultural policy and extension services have largely ignored urban contexts. Recently, national and international initiatives have started addressing this oversight by promoting circular innovations in urban food systems. To boost productivity, it is crucial to understand the challenges, opportunities, and prospects associated with innovative urban farming. Therefore, exploratory qualitative research, specifically focus group discussions, was conducted in Alimosho Local Government Area of Lagos, Nigeria, to gather the perspectives of various stakeholders. The analysis, using mind maps and a consensus index, compared views from private urban farming practitioners and local public sector representatives. Urban farmers see significant potential in innovative technologies such as hydroponics, aquaponics, recirculating aquaculture systems (RAS), drip irrigation, sack farming, and waste upcycling to improve productivity. However, they express frustration over the lack of public sector support for embracing these circular innovations. Conversely, public sector representatives cite urban farmers' behavioral and educational shortcomings, particularly their lack of internal coordination and commitment to adopting innovations. These discrepancies underscore the complex interactions between urban farmers and local public agricultural policymakers and extension agents. The study highlights the need for fundamental changes in both public and private sectors to address the challenges in urban farming innovations. Establishing local-level dialogues, as demonstrated in this study, can provide valuable insights for developing urban farming and policy in Sub-Saharan Africa.

Sustainability experienced significant global momentum in recent decades. The emergence of the sustainability movement in the Financial Sector was prompted by the increasing global climate change resulting from environmental deterioration. Primarily associated with the Financial Sector, it has increasingly been recognised that Financial Institutions are significant contributors to global climate change, both via direct and indirect means. This has resulted in a heightened emphasis and demand from stakeholders for the implementation of Sustainability Principles on a worldwide scale. This study presents a methodology that utilises the various dimensions of Sustainable Finance through the concept of Triple Bottom Line to determine the factors influencing the Sustainability Performance of Financial Institutions. The suggested approach is grounded and supported by the current body of literature. The study presents a hypothesis to investigate the correlation between factors of Green Finance Practices and Sustainability Performance of Banking Sector. The suggested framework can be utilised by regulatory bodies and individual financial institution of a country to identify the elements that influence the Sustainability Performance of Banking Sector.

Accurate cloud quantification is essential in climate change research. In this work, we construct an automated computer vision framework by synergistically incorporating deep neural networks and finite sector clustering to achieve robust whole sky image-based cloud classification, adaptive segmentation, and recognition under intricate illumination dynamics. A bespoke YOLOv8 architecture attains over 95% categorical precision across four archetypal cloud varieties curated from extensive annual observations (2020) at a Tibetan highland station. Tailor-made segmentation strategies adapted to distinct cloud configurations, allied with illumination-invariant image enhancement algorithms, effectively eliminate solar interference and substantially boost quantitative performance even in illumination-adverse analysis scenarios. Compared with the traditional threshold analysis method, the cloud quantification accuracy calculated within the framework of this paper is significantly improved. Collectively, the methodological innovations provide an advanced solution to markedly escalate cloud quantification precision levels imperative for climate change research, while offering a paradigm for cloud analytics transferable to various meteorological stations.

Climate change (CC) poses severe consequences, particularly in sub-Saharan Africa, where poverty rates may escalate by 2050 without significant climate and development action. The health impacts are diverse, encompassing communicable and non-communicable diseases. Mozambique, a climate-vulnerable nation, has experienced significant natural disasters in the past 42 years, impacting its health system. This study aims to assess Mozambique’s health sector vulnerability and adaptation needs to climate change. Following a methodology proposed by the World Health Organization and Intergovernmental Panel for Climate Change, a six-step vulnerability and adaptation assessment was conducted. The Health Vulnerability Index (HVI), integrating historical climate, epidemiological, and socio-economic data at the district level (n=162), was computed using exposure, sensitivity, and adaptive capacity dimensions. The Results revealed spatial patterns in exposure to climate variables, extreme weather events, and variations in sensitivity and adaptive capacity across the country. The HVI mirrored the exposure findings. Notably, high vulnerability was observed in several districts, while major urban centers displayed lower vulnerability. These findings highlight the country’s vulnerability to climate change and underscore the potential for adverse impacts on livelihoods, the economy, and human health. The study provides a foundation for developing strategies and adaptation actions.

Visualization techniques are a powerful communication tool between construction stakeholders. The advancement of technology from 2D drawings to 3D models, Virtual Reality (VR), and Augmented Reality (AR) has emphasized the crucial role of efficient communication of ideas, designs, and concepts in preventing project delays and other issues in the Architecture, Engineering, and Construction (AEC) industry. Contemporary innovations such as web-based virtual reality cloud platforms that facilitate collaborative AEC projects and Head-mounted Displays that enable the viewing of VR environments are some of the latest technological developments that are emerging in the construction industry. These technological advances have the potential to improve communication, increase project efficiency, and enhance the quality of construction work. The purpose of this research is to identify existing trends and potential future directions by appropriating the state of the art of the intellectual growth of Virtual reality and Augmented Reality. The study used scientometric analysis in reviewing existing publications to scientifically map the evolution of VR and AR in the AEC sector. The study observed an emerging but little amount of publications on VR and AR in construction. While Africa contributes little significance, advancement in VR and AR research is led by United States and America. The study expresses concern over the dearth of research and the low amount of collaborations amongst institutions in diverse countries. The study concludes that VR and AR research in the AEC sector must be afforded the needed focus and attention. In recent times, the global Coronavirus pandemic has shown that technology such as VR and AR is inevitable in the success of a project.

The Circular Economy is matter of recent discussions and quite popular, however the meaning has not been understood by most Business stakeholders. This Case study proposes to illustrate the Circular Economy importance and its status now. The contribution that UAE education sector can make to the Circular Economy is immense and is the focus of this study. Circular Economy awareness and its inner meaning can be only spread by the education sector and the author emphasizes the role of the education can play in implementing the Circular Economy. The study shows the way for the future Managers and Business stakeholders to participate in this crucial endeavor of Businesses to follow the Circular Economy. The ADKAR change management can be adopted to inspire the CE initiatives of the UAE Education sector.

The aim of this paper is to apply a new lane separation methodology for the maritime sector emissions attributed to the different vessel types and marine traffic loads in the Mediterranean and the Black Sea defined via the European Marine and Observation Data network (EMODnet), developed in 2016. This methodology is implemented for the first time on the Copernicus Atmospheric Monitoring Service Global Shipping (CAMS-GLOB-SHIP v2.1) nitrogen dioxide (NOX) emissions inventory, on the Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI) nitrogen dioxide (NO2) tropospheric vertical column densities and on the LOTOS-EUROS (LOng Term Ozone Simulation – EURopean Operational Smog) chemical transport model simulations. By applying this new, EMODnet-based lane separation method to the CAMS-GLOB-SHIP v2.1 emission inventory, we find that cargo and tanker vessels account for approximately 80% of the total emissions in the Mediterranean, followed by fishing, passenger, and other vessel emissions with contributions of 8%, 7% and 5%, respectively. Tropospheric NO2 vertical column densities sensed by TROPOMI for 2019 and simulated by the LOTOS-EUROS CTM have been successfully attributed to the major vessel activities in the Mediterranean; the mean annual NO2 load of the observations and the simulations reported for the entire maritime EMODnet-reported fleet of the Mediterranean is in satisfactory agreement, 1.26 ± 0.56x1015 molecules cm-2 and 0.98 ± 0.41x1015 molecules cm-2, respectively. The spatial correlation of the annual maritime NO2 loads of all vessel types between observation and simulation ranges between 0.93 and 0.98. On seasonal basis, both observations and simulations show a common variability. The winter-time comparisons are in excellent agreement for the highest emitting sector, cargo vessels, with the observations reporting a mean load of 0.98 ± 0.54 and the simulations of 0.81 ± 0.45x1015 molecules cm-2 and correlation of 0.88. Similarly, the passenger sector reports 0.45 ± 0.49 and 0.39 ± 0.45x1015 molecules cm-2 respectively, with correlation of 0.95. In summertime, the simulations report a higher decrease in modelled tropospheric columns than the observations, however still resulting in a high correlation between 0.85 and 0.94 for all sectors. These encouraging findings will permit us to proceed with creating a top-down inventory for NOx shipping emissions using S5P/TROPOMI satellite observations and a data assimilation technique based on the LOTOS-EUROS chemical transport model.

The development of major economic sectors can provide the bedrock on which long-lasting national economic prosperity is formed. Iceland’s tourism sector is an example of a rapidly expanded industry in recent years, to the extent that it has become the largest sectoral contributor to the nation’s economy. The growth of the sector has led to a number of sustainability impacts, thus presenting opportunities and challenges in terms of meeting the seventeen Sustainable Development Goals (SDGs) of the United Nations. Using the case study of Iceland, this paper aims to advance conceptual understanding of the synergies and trade-offs between a nation’s tourism sector and performance across the 169 targets of the SDGs. Empirical results were derived from four theme-based focus groups, comprised of expert participants, who were tasked with completing scoresheets concerning their perception of the extent of synergies and trade-offs for each target. The majority (126 in number) of the mean scoresheet outcomes for the SDG targets revealed neither synergies nor trade-offs. However, 32 synergies and 11 trade-offs were identified. Many of the target synergies related to new economic opportunities, such as jobs, employment and training for young people. Target trade-offs tended to be environmental and social. In particular, concern was voiced about the greenhouse gas emissions of the Icelandic tourism sector, which derives from international aviation, cruise ships and rental car usage. The outcomes of this study are of particular relevance to tourism companies, policy-makers and governance institutes, all of whom are increasingly endeavouring to link their activities with the fulfilment of the SDGs, maximising synergies, mitigating the extent of any potential trade-offs, and potentially transforming trade-offs into synergies. Furthermore, the results are likely of interest to academics focused on researching the broad sustainability impacts of economic sectors and their contribution to meeting the visionary goals of the SDGs.

Garment sector has crucial working field in Turkey.It has also very high risky occupational health conditions and safety.The objective of this study is to define level of job level, work-related stress’ symptoms, social support and coping mechanisms of garment workers and to determine any related factors.This study is descriptive and cross-sectional. The study population comprised garment workers in the 16-65 age range. The data was collected by Assessment Form, The Brief Stress Coping Profile and Brief Job Stress Questionnaire. The level of work-related stress was statistically higher among the workers who had chronic disease, low economic, education status and poor quality of sleep. Psychological and physical physiological reactions to stress were found higher among women workers and those with chronic disease.It also was seen that job stress scores had a meaningful relationship with “emotional expression involving others” (r =.20) and “Avoidance and suppression” coping profile (r =.16; p <.01).Psychological symptom scores were found to have a low level of meaningful relationship with “Seeking help for solution” (r =-.08), “changing point of view” (r=.13) and “emotional expression involving others” coping profiles (r=.21). Work-related stress causes many health and behavioral problems. Work related reasons and coping profiles have powerful effects on stress.

Identifying the determinants of human behavior is useful to adjust interventions and lead the civil society towards a stronger commitment with climate change mitigation and adaptation objectives, achieving greater support for successfully implementing environmental policies. Existing research has largely focused on case studies of pro-environmental behaviors (PEBs) in developed economies but there is yet very little evidence for developing countries. This study provides estimations of the effect of internal factors, such as sociodemographic variables, and four psychological dimensions (climate change knowledge, environmental attitudes, self-efficacy, trust in sources of environmental information) on PEBs. Data was obtained through a survey applied with future decision makers - university students - from Colombia (n = 4769) and Nicaragua (n = 2354). Indices were generated for PEBs and the psychological dimensions using z-scores and Principal Component Analysis. Partial correlations were evaluated through the Ordinary Least Squares method. Our results suggest that, in order to reach the planned emission reduction targets, policy approaches should more strongly focus on educating and motivating citizens and prepare them for contributing to the environmental cause, as well as provide individual solutions to combat climate change, rather than providing only information on its causes and consequences.

Over the course of the pandemic due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), multiple new clinical manifestations, as the consequence of the tropism of the virus, have been recognized. That includes now the neurological manifestations and conditions, such as headache, encephalitis, as well as olfactory and taste disorders. We present a series of ten cases of RT-PCR confirmed SARS-CoV-2 infected patients diagnosed with viral-associated olfactory and taste loss from four different countries.

The purpose of this paper is to test the Kuznets Environmental Curve (KEC) hypothesis for 10 MENA (Middle East and North Africa) countries during the period 1987-2017. To do this, the translogical functional form has been adopted to estimate the relationship between Toxic Gases (TG) emissions, energy consumption and GDP per capita. The results confirm the presence of KEC, GDP per capita and energy consumption have a positive influence on TG emissions, and the presence of a feedback relationship between GDP per capita and energy consumption. As a result, the environmental framework of the selected countries improves as their level of growth has become more advanced. In addition, to reduce TG emissions, MENA countries are expected to significantly increase the use of renewable energy and a more efficient energy policy.

Nowadays, one of the biggest concern of human being is greenhouse gas emission, especially carbon dioxide emission in developed and under-developing countries. In this study, connectionist models including LSSVM (Least Square Support Vector Machine) and evolutionary methods are employed for predicting the amount of CO₂ emission in six Latin American countries, i.e., Brazil, Mexico, Argentina, Peru, Chile, Venezuela, and Uruguay. The studied region is modelled based on the available input data in terms of Million tons including oil (Million tons), gas (Million tons oil equivalent), coal (Million tons oil equivalent), $R_{ew}$ (Million tons oil equivalent), and Gross Domestic Product (GDP) in terms of billion US dollars.} Moreover, the available patents in the fields of climate change mitigation in six Latin American countries namely Brazil, Mexico, Argentina, Peru, Chile, Venezuela, and Uruguay has been reviewed and analyzed. The results show that except Venezuela, all other mentioned countries have invested in renewable energy R&D activities. Brazil and Argentina have the highest share of renewable energies which account for 60% and 72% respectively.

Meningiomas are the most prevalent primary intracranial tumors. The majority are benign but can undergo dedifferentiation into advanced grades classified by World Health Organization (WHO) into Grades 1 to 3. Meningiomas tremendous variability in tumor behavior and slow growth rates complicate their diagnosis and treatment. A deeper comprehension of the molecular pathways and cellular microenvironment factors implicated in meningioma survival and pathology is needed. This review summarizes the known genetic and epigenetic aberrations involved in meningioma, with a focus on Neurofibromatosis type 2 (NF2) and non-NF2 mutations. Novel potential biomarkers for meningioma diagnosis and prognosis are also discussed, including epigenetic-, RNA-, metabolomics, and protein-based markers. Finally, the landscape of available meningioma-specific animal models is overviewed. Use of these animal models can enable planning of adjuvant treatment, potentially assisting in preoperative and postoperative decision-making. Discovery of novel biomarkers will allow, in combination with WHO grading, more precise meningioma grading, including meningioma identification, subtype determination, and prediction of metastasis, recurrence, and response to therapy. Moreover, these biomarkers may be exploited in the development of personalized targeted therapies that can distinguish between the 15 diverse meningioma subtypes.

This paper presents a mathematical modeling approach utilizing a fuzzy modeling framework for fixed wing aircraft systems with the goal of creating a highly desirable mathematical representation for model-based control design applications. The starting point is a mathematical model comprised of fifteen non-linear ordinary differential equations representing the dynamic and kinematic behavior applicable to a wide range of fixed wing aircraft systems. Here the proposed mathematical modeling framework is applied to the AIRBUS A310 model developed by ONERA. The proposed fuzzy modeling framework takes advantage of sector non-linearity techniquesto recast all the non-linear terms from the original model to a set of combined fuzzy rules. The result of this fuzzification is a more suitable mathematical description from the control system design point of view. Therefore, the combination of this fuzzy model and the wide range of control techniques available in the literature for such kind of models will enable us to avoid common control design methods, such as gain scheduling, where stability issues can be extremely challenging.

Italy has been defined as the "logistics platform" of the Mediterranean Sea. The Italian port system, with 11,6 million TEUs handled and 61,4 million passengers by 2022 (Assoporti data Jan‐Dec 2022) [1] is the key to guarantee this condition through adequate levels of reliability, safety and sustainability. This contribution addresses port logistics and shipping, focusing on primary issues related to the energy sector with a specific focus on what can be observed in the Italian context. Specifically, decarbonization of the maritime sector and related infrastructural problems (e.g. Cold Ironing or alternative fuels, where the uncertainty about resources availability and related cost do not allow for an easy strategic planning by both the shipowner and the port authority), as well as policies such the Emission Trading System (ETS) will be analyzed. All these issues, if addressed with a critical review, could represent the driving force of the national port sector for its growth and its competitiveness at a global scale.

The medical sector is of the utmost importance in every country for well-known reasons such as their economic development, national security, quality of life, and so on. Many researchers were dedicated to this topic, however, in Romania there are limited studies on this subject. One reason is that most of the businesses in this sector are individual enterprises or small family businesses. In our research paper we deploy several analysis methods to see the financial sustainability of companies operating in the medical industry. By analyzing a sample of 23931 companies and we have concluded that their performance has increase in the peak of the pandemic and that the financial stability is high. Our results are in line with other similar studies that were conducted in other regions.

The agricultural sector's progress towards climate neutrality is of great importance not only in the climate but also in the economic and social context. The agricultural sector is the 3rd largest emission-generating sector both in Latvia and Europe, and it directly and/or indirectly affects all other sectors. Climate-neutral agriculture is highly dependent on innovations that ensure maximum efficient farming, which not only reduces emissions but also ensures competitiveness in the market, but all of this is fundamentally influenced by well considered policies. Although the goals of the Green Deal are united, each country's situation must be thoughtfully considered individually to evaluate the best action plan for integrating the EU's common agricultural policy without reducing harvest. In addition, due to the complicated structure of the sector, it tends to be very difficult or even impossible to determine the real obstacles and mistakes that delay the progress of sustainable farming. Therefore, this research aims to create a system dynamics model using Latvia as a case study, which would not only provide an insight into the system’s structure but also identify the system's weak links and allow for the development of recommendations. The results could help policymakers in any country to make rational, non-controversial decisions simultaneously in the context of economic and Green Deal objectives. The results of the study demonstrate that to increase economic competitiveness and reduce emissions in agriculture, the most important aspect is the ability to invest in innovations and new technologies that would achieve not only the lowest emissions, but also the highest productivity and competitiveness in the market. It was found that by investing in the level of manure management it is possible to reduce GHG emissions in dairy farming by 8%, while by improving feed quality, manure management and thermoregulation all together, resulted in 60% GHG emission reduction. In addition, in a comprehensive improvement of the new innovations, the case study company managed to increase milk yield by 69%.

Offshore grids can have a key role in the transition of the energy system to sustainability. Although they require extensive infrastructure investments, they open up for the exploitation of additional resources and may be important to provide for part of the increasing electricity demand driven by sector coupling. This paper quantifies the socio-economic value of offshore grids and identifies their major drivers, performing energy system optimization in a model application of the Northern-central European energy system and the North Sea offshore grid towards 2050. The increasing wake loss with the size of hub-connected wind farms is integrated in the modelling. We find that without sector coupling no offshore grid may develop, and that the higher the level of sector coupling, the higher the value of offshore grids. Therefore, it can be strongly stated that offshore grid infrastructure development should not be discussed as a separate political topic, but seen in connection to sector coupling.

Today, across the most critical problems faced by hospitals and health centers are those caused by the existence of patients who do not attend their appointments. Among others, this practice generates waste of resources and increases the patients’ waiting list. To handle these problems, hospitals are actively trying to implement methods to reduce the idle time caused by patient no-shows. Many scheduling systems developed require predicting whether a patient will show up for an appointment or not. Although, a challenging problem resides in obtaining these estimates precisely. The goal of this work is to analyze how objective factors influence a patient not to attending their appointment, to identify the main causes that contribute to a patient’s decision, and to be able to predict whether or not the patient will attend the scheduled appointment. As a result, the obtained model is tested on a real dataset collected in a health center linked to the University of Vale do Itajaí (UNIVALI), which includes 25 features and about 5000 samples. The algorithm that produced the best results for the available dataset is the Random Forest classifier. It reveals the best recall rate (0.91), since it measures the ability of a classifier to find all the positive instances and achieves a receiver operating characteristic curve rate of 0.969.

We present a method to turn results of model-based optimisations into resilient and comprehensible control strategies. Our approach is to define priority lists for all available technologies in a district energy system. Using linear discriminant analysis and the results of the optimisations, these are then assigned to discrete time steps using a set of possible steering parameters. In contrast to the model-based optimisations, the deduced control strategies do not need perfect foresight but solely rely on data about the present. Our result indicate that the results of the control strategies obtained using the proposed method are comparable to the results of the linear optimisations, in our case in terms of emissions and prices.

Nowadays tourism is growing as a gigantic, global business accounting for 10.4 % of Global GDP and 10% of global employment (Joppe, 2020). This review paper aims to explore the risks borne for tourism sector by the outbreak of corona-virus in 2020. Tourism sector is a highly vulnerable sector and the costs that will be borne from corona-virus pandemic will be devastating, particularly for the countries relying on this sector as a basic source of income. The paper suggests possible solutions and adaptation routes, while at the same time reviews lessons of the past from other pandemics and crisis. This paper is very useful for tourism policy makers and governments in countries where tourism contributes a significant part of their GDP, but also for other economic sectors closely but indirectly connected in the tourism value chain.

The aim of this short communication is to find out the legal set up that complies with the environmental management in the textile sector of Bangladesh. This sector is the one of the biggest contributor to the economy of the nation. This sector contributes 81% to the total export earnings involving an immense number of stakeholders to its production processes. It is also true that this sector is largely responsible for the overall environmental pollution through its effluent discharge. The findings suggest that there are both international and national legal guidelines exist for environmental management in the said sector. In order to improve the environmental standards rehearsing lawful instruments is compulsory for the said industries.

A two-year experiment was conducted with a local maize hybrid under full irrigation (F), deficit irrigation (D) and rainfed conditions (R) to estimate maize evapotranspiration in Bosnia and Herzegovina. Three approaches (Allen & Pereira (A&P), SIMDualKc (SD), and Vegetation Index (VI)) were used to estimate the actual crop coefficient (Kc act), actual basal crop coefficient (Kcb act), and actual crop evapotranspiration (ETc act) were applied with the dual crop coefficient method and remote sensing (RS) data. While Kcb act from all approaches matched FAO56 tabulated values, SD showed differences, in comparison to A&P, of up to 0.24 in D and R conditions, especially in initial and mid-season stages. VI demonstrated very good performance in all treatments. In F, the obtained Kc act for all approaches during the initial and end stages were higher than the tabulated values, ranging from 0.71-0.87 for Kc ini act and from 0.80-1.06 for Kc end act, while the mid-season period showed very good agreement with the literature. Maize crop evapotranspiration range is 769-813 mm, 480-752 mm, and 332-618 mm for F, D and R, respectively. The results confirmed the suitability of both approaches (SD and VI) to estimate maize crop evapotranspiration under F, with the VI approach demonstrating an advantage in calculating Kcb act, Kc act, and ETc act values under water stress conditions. The 67.6% increase in grain yields with irrigation emphasizes the need to transition from rainfed to irrigation-dependent agriculture, even for drought-resistant crops like maize.

The increasing cancer burden is a major health concern in Arab countries with variations in cancer profiles. Given the limited oncology research output and scarce data on cancer trial participation in the Arab region, this study explored the therapeutic cancer trial landscape in Arab countries over the past 20 years. A bibliometric analysis of the PubMed database was conducted on primary publications of therapeutic trials with a participating Arab center. Arab countries participated in 320 published cancer-related therapeutic trials (2000‒2021). There was a consistent increase in the number of trials, sample size, multiregional site participation, and number of randomized trials. However, most trials were small, did not receive external funding, and included a single Arab site. Compared with Arab-only trials, trials with joint non-Arab sites were larger (p = .003) and more likely to be externally funded (p < .001). Citation numbers and journal impact factors were higher in trial publications with joint non-Arab authorship than those without (p < .001, for both). Despite improving conduct and publication records of oncology trials with Arab centers, cancer trial participation remains limited in Arab countries. Concerted efforts are required to encourage sponsorship and international collaboration in this region.

Until now, the literature on Chinese International Online Shopping (CIOS) (B2C export from China) mainly concentrated on the potential income that it constitutes for Chinese international trade. However, regarding International Online Consumers' (IOCs) purchase behaviors, research does not provide insight into the impact of Countries' Level of Economic Development (CLED) on the IOCs' preferences and choices about Chinese brands. Based on 9971 purchases about Chinese mobile phone brands, countries' macroeconomic data, and a multinomial logistics model (MLM), we examined IOCs' preferences and choices about Chinese brands. The result shows that the CLED influences IOCs' preferences and choices. Consequently, accounting of CLED in consumers’ preferences and choices introduces a new dimension in understanding IOCs' behaviors and attitudes towards Chinese mobile phone brands. This work contributes to Chinese brands' globalization research from the perspective of CLED. Such a model can be used to guide e-retailers and brand managers.

The resource curse indicates that economic growth performs poorly in countries with significant natural resources. Nevertheless, certain countries rich in energy managed to protect their resource riches in the long run. It is necessary to enforce effective policies in resource-rich countries to fully leverage the advantages which can come from the abundance of natural resources. This study aimed to evaluate how oil-rich countries would avoid resource flows by successful fiscal and management policies. By taking the guidance of Norway and implementing fiscal policy focused on tax rules on its oil management, it is proposed that oil-exporting countries benefit significantly. The framework attempts to mitigate this resource curse and utilise oil revenues in the interest of the country.

Background: Maternal mortality (MM) is a matter of serious concern in low income developing countries (LDCs). Perspective: A great reduction has been observed regarding the maternal deaths globally after huge efforts since 1990 todate. However, the situation continues to be either stagnant or worsening in developing countries, suggesting that the efforts to cope with this issue are either insufficient or not properly implemented. We need to first diagnose the problem areas that are a great hurdle in the road to success towards the reduction of MM. Postpartum haemorrhage and preeclampsia are one of the most common causes of MM. Malnutrition, neurological dysfunction and cancer are among the non-obstetric causes. Trained medical and paramedical staff can be of great help in this regard by increasing awareness among masses at grass root level. Target set by Millennium Development goal has minimized the MM by 44%. But it has not met the target set by Millenium Development Goals 5 and a lot of measures need to be taken in this regard. Conclusions: Majority of the MDs are preventable and can be avoided by adopting appropriate frameworks, linked data sets, surveillance, birth attendants training, preparation for births, etc. Delay in decision to get healthcare, access to healthcare center and receiving these facilities are the main factors in MM.

The research aims to present an innovative methodology to execute the Heritage conservation processes in a collaborative and interdisciplinary BIM project, with an effective management of the deterioration suffered over time, emphasizing the structures and coatings. The research begins with the architectural survey using scanning techniques (TLS) and terrestrial photogrammetry (SfM) and taking as a study the Duomo of Molfetta (Italy), a unique Romanesque architecture of Puglia (Italy). The methodological process is mainly aided by the precise semantic segmentation of global point clouds, a semi-automatic process assisted by classification algorithms implemented in the post-processing software, and which has allowed the classification of the unstructured information provided by the remote sensing equipment when identifying the architectural-structural systems of a building with high historical values. Subsequently, it has been possible to develop an efficient Scan-to-HBIM workflow, where the Heritage-BIM (HBIM) project has fulfilled the function of a database by incorporating and organizing all the information (graphic and non-graphic) to optimize the tasks of auscultation, identification, classification, quantification and, in turn, facilitating the parametric modeling of unique structures and architectural elements. The results have shown great effectiveness in the processes of characterization of architectural and artistic heritage, focusing on the deformations and deterioration of the masonry in columns, and making multidisciplinary conservation work in an HBIM project more flexible. But there are still some difficulties for the automatic interpretation of 3D point cloud data, related to specific systems of the historical architecture. In conclusion, human action and interpretation continues to be a fundamental pillar to achieve precise results in a heritage environment.

The field of personalized medicine is undergoing a transformative shift through the integration of multi-omics data, which encompasses genomics, transcriptomics, proteomics, and metabolomics. This synergy allows for a comprehensive understanding of individual health by analyzing genetic, molecular, and biochemical profiles. The generation and integration of multi-omics data enable more precise and tailored therapeutic strategies, improving the efficacy of treatments and reducing adverse effects. However, several challenges hinder the full realization of personalized medicine. Key hurdles include the complexity of data integration across different omics layers, the need for advanced computational tools, and the high cost of comprehensive data generation. Additionally, issues related to data privacy, standardization, and the need for robust validation in diverse populations remain significant obstacles. Looking ahead, the future of personalized medicine promises advancements in technology and methodologies that will address these challenges. Emerging innovations in data analytics, machine learning, and high-throughput sequencing are expected to enhance the integration of multi-omics data, making personalized medicine more accessible and effective. Collaborative efforts among researchers, clinicians, and industry stakeholders are crucial to overcoming these hurdles and fully harnessing the potential of multi-omics for individualized healthcare.

A study of cryogenic drilling in sandwich composites has been carried out. Materials used have been carbon fiber reinforced polymer sandwich sheets with inner foamed polyvinyl chloride core, composites with aerospace, marine, construction and automotive applications, including protec-tion structure of Polar engineering equipment. Experimental tests have been performed in lam-inates with 12 mm and 6 mm of thickness, drilling with liquid nitrogen as refrigerant to reach temperatures below -120ºC under different cutting conditions, in particular, drill rotation speeds between 2000 rpm and 6000 rpm and feed rates between 200 mm/min and 600 mm/min. Variables as thrust forces and circularity error have been measured, due to the importance of its effect on the hole quality, as an operation prior to a possible assembly. A design of experiments has been allowed determining relationships between variables, identifying the influence of cutting condi-tions on the thrust force and the circularity at inlet and outlet holes.

In the context of improving aircraft safety, this study focuses on the development and evaluation of a graphene-based ice detection system using an environmental chamber. The research is driven by the need for more accurate and efficient ice detection methods, crucial in mitigating in-flight icing hazards. The methodology employed involves testing flat graphene-based sensors in a controlled environment, simulating a variety of climatic conditions that could be experienced in an aircraft during its entire flight. The environmental chamber enabled precise manipulation of temperature and humidity levels, thereby providing a realistic and comprehensive test bed for sensor performance evaluation. The results were significant, revealing the graphene sensors’ heightened sensitivity and rapid response to the subtle changes in environmental conditions, especially the critical phase transition from water to ice. This sensitivity is the key to detecting ice formation at its onset, a critical requirement for aviation safety. The study concludes that graphene-based sensors, tested under varied and controlled atmospheric conditions, exhibit a remarkable potential in enhancing ice detection systems for aircraft. Their lightweight, efficient and highly responsive nature makes them a superior alternative to traditional ice detection technologies, paving the way for more advanced and reliable aircraft safety solutions.

This paper presents a study about the integration of Piezoelectric Energy Harvesting Systems (PE-EHS) in building envelopes for powering Fiber Bragg Grating (FBG) sensors, enabling efficient and low-consumption monitoring with the objective to leverage Structural Health Monitoring (SHM). The research includes preliminary tests conducted in a real environment to validate the PE-EHS when fully integrated into the façade, capturing mechanical vibrations generated mainly by wind loads. Based on these activities, the final configuration of PE-EHS is defined to provide a complete system for façade monitoring. This integrated system includes the Piezoelectric Generator (PEG), Supercapacitor (SC), Power Conditioner Circuit (PCC), Fibre Optic Sensing (FOS) Interrogator, and the IoT Gateway trans-mitting measurement data within an Internet of Things (IoT) monitoring platform. This configuration is tailored to address the challenges related to the structural integrity of building envelopes. Results demonstrate a potential for a stand-alone solution in the façade sector, but, raising issues for certain limitations, requiring further investigation. In particular, the study emphasizes constraints related to the energy production of PE-EHS for façade integration. It highlights the necessity to carefully consider these limitations within the broader context of their applicability, providing insights for the informed deployment of Piezoelectric Energy Harvesting technology in building envelope monitoring.

In this paper, a continuous power management for a decentralized DC microgrid (DCMG) is proposed to achieve voltage regulation and power balance even under system uncertainty and voltage sensor failure. The DCMG system achieves a continuous power management through only the primary controller to reduce the computational burden of each power agent. To enhance the reliability and resilience of the DCMG system under voltage sensor failure, a DC bus voltage (DCV) sensor fault detection algorithm is proposed. In this algorithm, the DCV sensor failure is detected by comparing the measured DCV with the estimated DCV. When the power agent identifies the DCV sensor failure, it changes the operation properly according to the proposed control mode decision algorithm to maintain the stability of the DCMG system. When uncertain conditions such as the power variation of the distributed generations, sudden grid disconnection, DCV sensor failure, electricity price change, and critical battery status occur, the DCMG system is changed to transitional operation modes. These transitional operation modes are employed to transmit the power agent information to other agents without digital communication links (DCLs) and to accomplish power sharing even under such uncertain conditions. In the transitional operation modes of the DCMG system, the DCV levels are temporarily shifted to an appropriate level, enabling each power agent to detect the uncertainty conditions, and subsequently to determine its operation modes based on the DCV levels. Simulation and experimental results under different test conditions confirm the reliability and effectiveness of the proposed control scheme.

This study introduces numerical advancements in an alternative design for the SPS Beam Dump Facility (BDF) at CERN. The design envisions a high-power operation target made of flowing liquid lead. The BDF is a proposed versatile facility at CERN, intended for both beam-dump-like and fixed-target experiments. The target behavior is assessed, assuming a proton beam with a momentum of 400 GeV/c, a pulse frequency of 1/7.2 Hz, and an average beam power of 355 kW. An evaluation is conducted using various Computational Fluid Dynamics (CFD) codes to analyze the behavior of liquid lead and to predict the thermal stress on the target vessel induced by the pulsed heat source generated by the charged particle beam. The comparison increases the reliability of the results, investigating the dependencies on the CFD modeling approach. The beam is modeled as a volumetric heat source with data coming from beam-lead interaction simulations provided by CERN and obtained with the Monte-Carlo code FLUKA. The velocity field and stress profiles are utilized to enhance the design of the lead loop and verify its viability and safety when operated with a liquid metal target.

Analyzing BRCA1/2 tumor pathogenic variants (TPVs) in epithelial tubal/ovarian cancers (EOC) has become an essential part of the diagnostic workflow in many centers to guide treatment options and genetic cascade testing. However, there is no standardization of testing procedures, including techniques, gene assays, or sequencers used, and data on the execution of tumor tests remains scarce. Therefore, we evaluated characteristics of BRCA1/2 tumor testing in advanced-stage EOC with real-world national data. Pathology reports of patients diagnosed with EOC in 2019 in the Netherlands were obtained from the Dutch Pathology Registry (PALGA), and data regarding histological subtype and BRCA1/2 tumor tests were extracted. A total of 999 patients with advanced-stage EOC were included. Tumor tests were performed for 502 patients (50.2%) and BRCA1/2 TPVs were detected in 14.7%. Of all tests, 48.6% used hybrid capture techniques and 26.5% used PCR-based techniques. More than half of the tests (55.0%) analyzed other genes in addition to BRCA1/2. Overall, this study highlights the heterogeneity in the execution of BRCA1/2 tumor tests. Despite a lack of evidence of quality differences, we emphasize that adequate reporting and internal and external quality monitors are essential for high-quality implementation and execution of reliable BRCA1/2 tumor testing, which is crucial for identifying all patients with BRCA1/2 TPVs.

High Education Institutions (HEI) play a key role in fostering sustainability since students will be future active society members. By providing them with the knowledge, skills, and mindset needed to address environmental challenges, they can contribute to increase sustainability in a long-term approach. With the effects of climate change strongly affecting water availability across planet, it is increasingly relevant to understand if higher education students are aware of this situation, to develop adequate measures to promote sustainable behaviors regarding water uses. This study aimed to assess students’ perceptions regarding water efficiency through a questionnaire submitted in 7 HEI in Portugal. Students recognized the importance of water with older students, women and science students demonstrating a greater awareness. Inspite of this 27% students do not know what the average water consumption in Portugal is and only 18% accurately reported the consumption range in Portugal. There is also a lack of knowledge (&gt;50% students) if common water efficiency measures are applied in their HEI. The main information sources identified by the students were “social communication” and “internet/social media”, revealing that water efficiency knowledge transfer in high education can be improved.

Mexican yuca (Yucca decipiens Trel.) is native to the semidesert region across north-central Mexico. Based on its empirical medicinal uses, the flour produced from leaves and stems of yuca was evaluated to determine its agro-industrial and medicinal uses (food, beer, and mezcal). The flour was characterized based on the granulometry, rheology, texture, and functional properties, which were analyzed with the RStudio software. The results indicate that the water absorption capacity of yuca flour (data here) is similar to wheat flour; however, it absorbs half the volume of oil than wheat flour. Therefore, it has a hydrophilic behavior similar to that of wheat and a lower oil requirement for formulas. The expansion capacity of yuca flour is like that of wheat flour, showing an ideal gluten content for agro-industrial purposes (food) that require this structural component. The flour had a remarkable foam formation, high stability, and low-fat content. These results are particularly important for foods that require foaming properties. Fermentation matched the parameters of the 56-60 Physicochemical Test Methods of the Cereal &amp; Grains Association; consequently, their flours are classified as equal to flours produced from soft and weak wheat, supporting their use for fermentation processes. The internal friction values (0.85-0.92) suggest a limited flow; however, its high density shows a fine granulometry that facilitates the sacking, handling, and storing of the flour, complying with the Mexican standards, and allowing it to be added to combinations aimed to enrich food.

Serpentine (Mg₃Si₂O₅(OH)₄), like quartz, dolomite and magnesite minerals, is a versatile mineral group characterized by silica and magnesium silicate contents with multiple polymorphic phases. Among the phases composed of antigorite, lizardite, and chrysotile, lizardite and chrysotile are the most prevalent phases in the serpentinites studied here. The ΣLREE/ΣHREE ratios of the samples are between 0.16 and 4 ppm. While Ce shows a strong negative anomaly (0.1–12), Eu shows a weak positive anomaly (0.1–0.3). This indicates that fluid interacts significantly with rock during serpentinization, and Highly Incompatible Elements (HIEs) gradually become involved in the serpentinization process. The large differential thermal analysis (DTA) peak at 810–830 °C is an important sign of dehydration, transformation reactions and thermal decomposition, and is com-patible with H₂O phyllosilicates in the mineral structure losing water at this temperature. In SEM images, chrysotile, which has a fibrous structure, and lizardite, which has a flat appearance, trans-form into talc as a result of dehydration with increasing temperature. Therefore, the sudden tem-perature drop observed in DTA graphs is an indicator of crystal form transformation and CO₂ loss. In this study, the mineralogical and structural properties and the formation of serpentinites were examined for the first time using thermo-gravimetric analysis methods. In addition, the mineralogical and physical properties of serpentinites can be recommended for industrial use as additives in polymers or in the adsorption of organic pollutants. As a result, the high refractory nature of examined serpentine suggests that it is well-suited for applications involving high temperatures. This includes industries such as metallurgy and steel production, glass manufacturing, ceramic production, and the chemical industry.

Fruits are commonly used, fresh or processed, to prepare different industrial products with superior nutritional and health-promoting properties. Currently, the demand for processed fruit products has motivated the rapid growth of the fruit processing industries, persuading them to produce an enormous amount of by-products with less utilization. Furthermore, people's shifting dietary habits and lack of awareness of nutritional properties result in an avoidable load of fruit by-products. The knowledge of the value of by-products urges exploration with proper documentation, emphasizing the health benefits of some such products. Hence, this review is prepared by carefully analyzing the recent literature on industrial applications of fruit by-products and their nutritional and health-promoting properties. The use of fruit by-products in food industries for various purposes has been reported in the past and has been reviewed and described here. Fruit by-products are a good source of nutrients and bioactive components, including polyphenols, dietary fibers, and vitamins, implying that they could have an important role for novel, value-added functional food properties. Furthermore, fruit by-products are used as the substrate for the production of organic acids, essential oils, enzymes, fuel, biodegradable packaging materials, and preservatives.

Cancer associated cachexia (CAC) is a critical contributor to pancreatic ductal adenocarcinoma (PDAC) mortality. Thus, there is an urgent need for new strategies to mitigate PDAC-associated cachexia; and the exploration of dietary interventions is a critical component. We previously observed that a ketogenic diet (KD) combined with gemcitabine enhances overall survival in the autochthonous LSL-KrasG12D/+; LSL-Trp53 R172H/+; Pdx1-Cre (KPC) mouse model. In this study, we investigated the effect and cellular mechanisms of a KD in combination with gemcitabine on the maintenance of skeletal muscle mass in KPC mice. For this purpose, male and female pancreatic tumor-bearing KPC mice were allocated to a control diet (CD), a KD, a CD + gemcitabine (CG), or a KD + gemcitabine (KG) group. We observed that a KD or a KG mitigated muscle strength decline over time and presented higher gastrocnemius weights compared CD-fed mice. Mechanistically, we observed sex-dependent effects of KG treatment, including the inhibition of autophagy, and increased phosphorylation levels of eIF2α in KG-treated KPC mice when compared to CG-treated mice. Our data suggests that a KG results in preservation of skeletal muscle mass. Additional research is warranted to explore whether this diet-treatment combination can be clinically effective in combating CAC in PDAC patients.

This article aims to analyze household energy data to predict electricity self-sufficiency and identify the key features that impact it. For this purpose, we use SHAP (Shapley Additive Explanations), LightGBM (Light Gradient Boosting Machine), and a correlation heatmap-based framework to analyze 12 months of energy and questionnaire survey data collected from over 200 smart houses in Kitakyushu, Japan. We use the SHAP summary plot to identify the impact-wise order of key features influencing the electricity self-sufficiency rate (ESSR). Using SHAP, we demonstrated that key features are; housing types, average monthly electricity bill, floor heating, electric capacity, number of washing and drying machines, fee plans, occupation of household head, total floor area, average monthly gas bill, cooking equipment, etc. Furthermore, we adopted the LightGBM classifier with $\ell^1$ regularization to extract the most significant features and predict the electricity self-sufficiency rate of households. This LightGBM-based model can also predict the electricity self-sufficiency rate of households that did not participate in the questionnaire survey. A heat map is also used to analyze the correlation among household variables. The findings discussed in this article offer valuable insights for energy policymakers to achieve the targets of energy self-sufficient houses.

The construction of an anaerobic digester coupled with post-digestion low level aeration for agricultural wastewater treatment is described. The digester employs underwater speakers to accelerate the anaerobic digestion process while retaining solids to reduce the strength of the effluent. The digester effluent is sent to a holding tank and fed at a low flow rate to an aeration tank to effect partial nitrification of the wastewater. The outlet of this tank is sent to a settling tank to retain biomass that developed in the aeration tank and the effluent is sent to a small, constructed wetland to further reduce wastewater nitrogen and phosphorus. The wetland was planted with the broadleaf cattail, Typha latifolia, and hence to a retention basin. The system has reduced energy consumption due to both the use of underwater sonic treatment and low-level aeration that is not designed to achieve full nitrification/denitrification but rather to achieve a mixture of ammonium, nitrite, and nitrate that might foster the development of a consortium of organisms (i.e. nitrifiers, Anammox bacteria) that can remediate wastewater ammonium at low cost. Biogas is sent to an inground condenser where different treatments may be tested to remove carbon dioxide and hydrogen sulfide. The system is meant to serve as a complex where various technologies and practices can be evaluated to improve the treatment of agricultural wastewater.

Melatonin is an important hormone with a methoxy-indole structure. It is secreted regularly by the pineal gland of mammals. It takes part in many chemical, biological, and physiological activities of the body. Melatonin, acts as a basic hormone, and is responsible for circadian rhythm regulation and sleep control. It has been shown to occur in the highest concentration in organisms during the night times. In living organisms, many activities that have physiological, biological, hormonal, and psychological characteristics follows a certain rhythm. Body temperature, hormone levels, sleep-wakefulness, and some other cognitive functions in humans also change with the circadian rhythm. Its synthesis and release begin with darkness and end with light. This review aims to explore the functions of melatonin such as its stimulating effects on antioxidant enzymes, reducing lipid peroxidation, and protecting brain tissue from oxidative damage. It also has properties that stop the proliferation of cancer cells and prevent tumor growth. Melatonin, which was previously known only as an animal hormone, has been found to also exist in plants. Research has shown that melatonin is present in almost all plant species analyzed to date and that it performs functions similar to those in animals. In plants, it plays a vital role in dealing with various abiotic and biotic stresses. Melatonin acts as an important antioxidant in post-harvest technology and extends the post-harvest life of fruits and vegetables. It also takes part in the regulation of stress-specific genes and the activation of pathogenesis-related proteins and antioxidant enzymes. The most prominent roles of melatonin in plants include regulating circadian rhythm, growth, and development, and increasing tolerance to a wide range of environmental stress factors. The review reveals the effects of melatonin as an extremely important secondary metabolite, on human, animal, and plant metabolism. The use of PRISMA guidelines was used for reporting, search, selection, and synthesis. Information up to 2024 was searched from search engines for the occurrence, nature and function of melatonin. Key words such as structural function, hormonal function, secretion and metabolism were used in the search of publications.

Deep convolutional neural networks (CNNs) have revolutionised computer vision technology by automatically learning hierarchical representations of image data, leading to state-of-the-art performance in visual recognition tasks. This article presents a comprehensive review of deep CNNs, from their evolution and architectures to the current state-of-the-art research. The review also provides the core concepts and building blocks of CNNs and their concise mathematical representations. Furthermore, it explores applications of deep CNNs in three popular domains, including medical diagnosis, remote sensing, and facial recognition. This review will benefit researchers and practitioners in computer vision and artificial intelligence, as well as industry professionals seeking to leverage the latest advancements in deep learning technologies.

Background: Handheld cameras may increase access to teleretinal diabetic retinopathy screenings (TDRS), as they are more economical and nimbler than traditional desktop cameras. However, their use in safety-net clinical settings is less understood. Methods: The Los Angeles County Department of Public Health collaborated with the Los Angeles County Department of Health Services (DHS) to pilot the use of handheld cameras in DHS’s TDRS program. This study assessed screening metrics and interviewed TDRS coordinators and photographers about their experiences using these cameras. Results: Handheld cameras are harder to operate and performed less optimally on key screening metrics (e.g., image quality) compared to desktop cameras. However, this challenge appeared to be linked to the selected model, rather than to all handheld cameras. The adoption of handheld cameras in DHS was aided by their integration into an existing agency infrastructure that already supports the use of desktop cameras; these operational supports include an established workflow, a data platform, and experienced photographers. Conclusions: The use of handheld cameras for TDRS is a promising practice for assuring equitable access to screenings. Handheld cameras are portable, smaller in size, and lower in cost than desktop cameras. Future projects should invest in and assess the performance of higher-quality models of these cameras, especially their use in safety-net clinical settings.

Severe malaria is a major public health concern in Angola, particularly among adults, with limited data on clinical outcomes and manifestations. The study therefore assessed the clinical manifestations and outcome of severe Plasmodium falciparum malaria in adult patients admitted to Hospital Central Dr. António Agostinho Neto of Lubango, Angola. The study retrospectively reviewed the individual records of patients over 14 years old, admitted for severe malaria during the first trimester of 2021 and 2022. World Health Organization (WHO) criteria were used to define severity. A total of 640 patients were recorded into the study, 167 in 2021 and 473 in 2022, distributed across the departments; Intensive Care Unit (ICU; n=81), Medicine (MED; n=458) and Infectiology (INF; n=101). The median age was 26 years and 59.4% were males. The most common manifestation of severe malaria was renal impairment (37.4%). The overall mortality rate was 7% and decreased considerably from 10.2% in 2021 to 5.9% in 2022. The increase in malaria cases during 2022 with increased in prevalence of life-threatening signs like renal impairment, jaundice and impaired conscience, underscores the urgent need for enhanced malaria control and surveillance strategies to mitigate morbidity and mortality, highlighting the potential for antimalarial drug resistance.

The need for industrial and commercial machinery to maintain high torque while accurately following a variable angular speed is increasing. To meet this demand, induction motors (IMs) are commonly used with variable speed drives (VSDs) that employ a field-oriented control (FOC) scheme. Over the last thirty years, IMs have been replacing independent connection direct current motors due to their cost-effectiveness, reduced maintenance needs, and increased efficiency. However, IMs and VSDs exhibit nonlinear behavior, uncertainties, and disturbances. This paper proposes a robust combined adaptive passivity-based control (CAPBC) for this class of nonlinear systems that applies to angular rotor speed and stator current regulation inside an FOC scheme for IMs´ VSDs. It uses general Lyapunov-based design energy functions and adaptive laws with σ-modification to assure robustness after combining control and monitoring variables. Lyapunov’s second method and Barbalat Lemma prove that the control and identification error tends to be zero over time. Moreover, comparative experimental results with standard Proportional Integer controller (PIC) and direct APBC, show the proposed CAPBC effectiveness and robustness under normal and changing conditions

Egg-laying is one of the key aspects of female reproductive behavior in insects. Egg-laying has been studied since the dawn of Drosophila melanogaster as a model organism. The female’s internal state, hormones, and external factors, such as nutrition, light, and social environment, affect egg-laying output. However, only recently, neurobiological features of egg-laying behavior have been studied in detail. Fruitless and doublesex, two key players in the sex determination pathway, have become focal points in identifying neurons of reproductive significance in both central and peripheral nervous systems. The reproductive tract and external terminalia house sensory neurons that carry the sensory information of egg maturation, mating and egg-laying. These se include the presence of male accessory gland products and mechanical stimuli. The abdominal neuromere houses neurons that receive information from the reproductive tract, including sex peptide abdominal ganglion neurons (SAGs), and send their information to the brain. In the brain, neuronal groups like aDNs and pC1clusters modulate egg-laying decision-making, and other neurons like oviINs and oviDNs are necessary for egg-laying itself. Lastly, motor neurons involved in egg-laying, which are mostly octopaminergic, reside in the abdominal neuromere and orchestrate the muscle movements required for laying the egg. Egg-laying neuronal control is important in various evolutionary processes like cryptic female choice, and using different Drosophila species can provide intriguing avenues for the future of the field.

Current research suggests that polycystic ovary syndrome (PCOS) might originate in utero and implicates the placenta in its pathogenesis. Kisspeptin (KISS1) and neurokinin B (NKB) are produced by the placenta in high amounts, and they have been implicated in several pregnancy complications associated with placental dysfunction. However, their placental expression has not been studied in PCOS. We isolated mRNA after delivery from the placentae of 31 PCOS and 37 control women with term, uncomplicated, singleton pregnancies. The expression of KISS1, NKB, and neurokinin receptors 1, 2, and 3 was analyzed with real-time polymerase chain reaction, using β-actin as the reference gene. Maternal serum and umbilical cord levels of total testosterone, sex hormone binding globulin (SHBG), free androgen index (FAI), androstenedione, dehydroepiandrosterone sulfate (DHEAS), Anti-Mullerian hormone (AMH), and estradiol were also assessed. NKB placental mRNA expression was higher in PCOS versus controls in pregnancies with female offspring. NKB expression depended on fetal gender, being higher in pregnancies with male fetuses. NKB was positively correlated with umbilical cord FAI and AMH, and KISS1 with cord testosterone and FAI; there was also a strong positive correlation between NKB and KISS1 expression. Women with PCOS had higher serum AMH and FAI and lower SHBG than controls. Our findings indicate that NKB might be involved in PCOS-related placental dysfunction, and warrant further investigation. Studies assessing the placental expression of NKB should take fetal gender into consideration.

Abstract: Cherubism is a rare genetic disorder characterized by painless bilateral expansion of the mandible and maxilla. We present an unusual case of a 50-year-old female patient with Ramon syndrome, a rare variant of cherubism, accompanied by gingival fibromatosis. The patient exhibited symptoms of short stature, mental retardation, rheumatoid arthritis, epilepsy, hirsutism, and gingival enlargement. Clinical examination revealed generalized gingival inflammation with plaque and attachment loss. Radiographically, bilateral defined multilocular radiolucencies were observed in the mandibular body and ramus. The patient underwent a non-surgical phase, including oral hygiene motivation and periodontal debridement, followed by a surgical phase involving gingivoplasty and internal bevel gingivectomy with open flap debridement. Histopathological analysis confirmed the presence of fibroblasts, multinucleated giant cells, and fibrous connective tissue. The patient's son also presented with bilateral facial swelling and similar radiographic findings, indicating familial inheritance of cherubism. The case demonstrates the clinical, radiographic, and histopathological features of cherubism associated with gingival fibromatosis and highlights the challenges in diagnosis and management. Regular follow-up and maintenance are essential for long-term stability and prevention of recurrence. This report contributes to the limited literature on cherubism in older patients and emphasizes the importance of early identification and intervention in affected individuals.

A risk of ischemic stroke increases exponentially after menopause. Even a mild-ischemic stroke can result in increased frailty. Frailty is a state of increased vulnerability to adverse outcomes, which subsequently increases risk of cerebrovascular events and severe cognitive decline, particularly after menopause. Several interventions to reduce frailty and subsequent risk of stroke and cognitive decline have been proposed in laboratory animals and patients. One of them is whole body vibration (WBV). WBV recuperates cerebral function and cognitive ability that deteriorates with increased frailty. The goal of the current study is to test the efficacy of WBV in reducing post-ischemic stroke frailty and brain damage in reproductively senescent female rats. Reproductively senescent Sprague–Dawley female rats were exposed to transient middle cerebral artery occlusion (tMCAO) and randomly assigned to either WBV or control groups. Animals placed in the WBV group underwent 30 days of WBV (40 Hz) treatment performed twice daily for 15 min each session, 5 days each week. The motor functions of animals belonging to both groups were tested intermittently and at the end of treatment period. Brains were then harvested for inflammatory markers and histopathological analysis. The results demonstrate a significant reduction in inflammatory markers and infarct volume with significant increases in brain-derived neurotrophic factor and improvement in functional activity after tMCAO in middle-aged female rats that were treated with WBV as compared to the control group. Our results may facilitate a faster translation of the WBV intervention for improved outcome after stroke, particularly among frail women.

This study evaluates the antimicrobial efficacy of chitosan nanoparticles (CNP), varying in size, against E. coli, S. aureus, E. faecalis, C. albicans, and clinical isolates of Mycobacterium tuberculosis (MTB), as well as the antimicrobial effects of aqueous extracts and lyophilized powders of Allium (garlic) species. CNP were synthesized through ionotropic gelation and characterized by Z potential, hydrodynamic diameter (Dynamic Light Scattering, DLS) and SEM. Aqueous garlic extracts were prepared via decoction. We assessed antimicrobial activity using disk diffusion and broth microdilution methods; besides a modified agar proportion method in blood agar was used for antimicrobial activity against MTB. CNP inhibited MTB growth at 300 μg for 116.6 nm particles and 400 μg for 364.4 nm particles. The highest antimicrobial activity was observed against E. faecalis with nanoparticles between 200 and 280 nm. Allium sativum extract produced inhibition for C. albicans at 100 μg. The results indicate that CNP possess significant antimicrobial properties against a range of pathogens, including MTB, at high concentrations. On the other hand, aqueous Allium sativum extracts exhibited antimicrobial activity, but given their instability in solution, the use of lyophilized Allium sativum powder is preferable.

Previous studies have suggested that digitization of finance leads to growth in the economy in several middle- and high-income countries, but research in low- and lower-middle-income countries (LLMICs) remains limited. This research aimed to examine the trends, barriers, relationships, and prospects of finance digitization in LLMICs. This study used analytical and descriptive cross-sectional study designs. Sixty-six countries were purposively selected based on the available data on the Global Findex and the World Development Indicators databases. Descriptive analysis was used to identify the trends in the finance digitization indicators, correlation analysis was used to assess the nature of the association between finance digitization and the economy, and exponential smoothing was used to predict future outcomes in digital finance. The results indicated that the adoption and utilization of finance digitization increased in these countries, but the growth rates varied by region and income group. Low-income countries reported the highest rates of subscriptions to digital finance accounts and storing money in digital accounts, while lower-middle-income countries (LMICs) reported higher rates of inbound/outbound digital transactions, borrowings, and savings using digital channels. Sub-Saharan Africa reported the highest rates of digital finance account subscriptions, digital savings, and digital borrowings, while Europe and Central Asia reported the highest rates of in/out digital transactions. Barriers to digitization in these countries included poor access to the internet, high cost of digital finance products, and lack of a mobile phone, with low-income countries facing more challenges. The analysis revealed a negative significant relationship between finance digitization and Gross National Income growth and a positive significant correlation between finance digitization and other economic growth indicators (gross savings and Gross Domestic Product). Finance digitization was predicted to continue to rise in these countries for the next decade. The study recommended that policymakers should promote the adoption of digital finance and address the barriers and risks of finance digitization in LLMICs, as it had positive effects on economic growth.

During puberty and emerging sexuality, adolescents experience important physical, mental, and social transformations. In the process of dealing with these changes, adolescents can become potentially vulnerable to mental health problems.The aim was to identify and synthesize published research evidence on sexuality-related mental health stressors among adolescent girls and boys, identify gaps (if any) in current knowledge, and contribute to knowledge about the experiences of emerging sexuality and health among adolescents, to further inform research, practice, and policy initiatives in sexual health.A scoping literature review of peer-reviewed articles published between 1990 and 2018. MEDLINE, CINAHL, EMBASE, PsycINFO, Global health, ERIC, and Sociological Abstracts databases were searched for research studies that reported experiences of sexuality related mental health issues and symptomatology of adolescents. We targeted studies conducted with adolescent populations between ages 11-24 years living in LMICs.Data from 12 published research papers, including 8 qualitative studies, 3 quantitative studies, and 1 mixed method study, were systematically analyzed. Four major themes and 4 sub themes were identified regarding sexual health and mental health of adolescents: 1) Relationship of sexuality and mental health; 2) Social and cultural influences; 3) Challenges in seeking sexuality information and services among adolescents; and 4) Educational needs among adolescents related to sexuality; and 4) Educational needs among adolescents related to sexuality. Lack of social support, Unmet needs for accessible adolescent friendly sexual health services, counseling, and age-appropriate information may be associated with several mental health stressors and symptoms, such as sadness, depressive and anxiety symptomatology, regret, fear, embarrassment, low self-esteem, guilt, shame, and anger. Therefore, tackling sexuality-related stressors could play an important role in addressing the overall wellbeing of young people. Future studies need to generate a deeper understanding of the concept of sexual health and its relation to mental health in diverse contexts. Health care professionals need to be aware of sexuality-related experiences of adolescent girls and boys by offering effective youth-friendly sexual and reproductive health education to support overall mental health and improve the experiences of emerging sexuality in adolescents.

Although numerous articles have been published to address drivers or barriers of corporate social responsibility (CSR), some parts of the world have received less attention. In this study, I reviewed the literature, from 2010 to 2021, to identify drivers and barriers of CSR in the the Middle East and North Africa (MENA) region and compare them with the findings in western countries. (2) Methods: For this study, I used a structured literature review method. By setting the inclusion and exclusion criteria, only 28 articles remained from selected database; (3) Results: The findings revealed some CSR drivers, such as leadership styles, profitability, reputation, moral commitment, and environmental conservation are common in both regions. There are also some differences between CSR drivers, for example religious beliefs, low concentration of ownership, and company characteristics are some of the drivers in the MENA region. Maintaining social license to operate, avoiding the risks of community opposition, pressure from the government, and consumer demand tend to be more important in western countries. Common barriers in both regions are lack of financial resources, cost, lack of CSR knowledge and awareness, and ownership concentration. This review also highlighted that lack of law enforcement, lack of stakeholder communication, lack of management commitment, lack of interests, corruption, and financial debts are some of the addressed barriers of CSR in the MENA region, while cost/benefit ratio, lack of customer interest, and lack of scientific frameworks are the special barriers in western countries. (4) Conclusions: While researchers in western countries have more focus on energy sector, there is a lack of research about drivers and barriers of CSR in the MENA region in several industries, including oil and gas.

Based on hospital capacities, facts from past experience with the coronavirus disease 2019 (COVID-19) virus and the number of dark infections during the second wave (DII = 2D2), a reasonable limiting value of 140/D2 for the 7-day incidence per 100,000 persons (MSDIHT) and a second wave herd immunization threshold fraction value of 0.26 in Germany were calculated. If the MSDIHT is held below this limiting value, the German hospital system can cope with the number of new seriously infected persons without any triage decisions. On the basis of the SIRV epidemics model, the classical threshold values for herd immunization were calculated for 18 countries. For these countries, the dates regarding when herd immunization against the second COVID-19 wave will be reached were estimated

In today’s rapidly evolving digital landscape, the significance of password guessing techniques in both offensive and defensive strategies is paramount. Passwords serve as a crucial line of defense for both individuals and corporations, safeguarding their sensitive systems and data. Therefore, assessing the effectiveness of these access credentials is a critical task. However, existing research in this field often encounters limitations, such as a lack of sufficient training data and extended model training times. Current methods often struggle with limited training data and lengthy training times. This paper introduces BBPE-AE, a novel Auto Encoder Network (AE) designed for password guessing. BBPE-AE utilizes Byte-level Byte Pair Encoding (BBPE) to extract frequent tokens from password datasets without length restrictions, employing a dynamic window technique to capture complex patterns. Experimental results on Hotmail and Myspace datasets demonstrate exceptional performance, achieving high similarity rates (BLEU-Unigram: 0.90, BLEU-Bigram: 0.82 for Hotmail; BLEU-Unigram: 0.90, BLEU-Bigram: 0.81 for Myspace). BBPE-AE generates realistic passwords that meet HIBP (Have I Been Pwned) standards, minimizing duplication. These findings highlight the effectiveness of BBPE-AE in enhancing security by generating realistic passwords, ultimately safeguarding sensitive systems and data.

Corporate governance has received increasing attention from practitioners and politicians after the collapse of large companies due to accounting errors and failure to disclose information that reflects the true financial condition of companies. Voluntary risk disclosure includes several aspects, including financial risks, including risks of interest rate, exchange rate, liquidity as well as risks of operations. In Jordan, the most common type of business is family businesses, where boards of directors usually serve the interests of the family that owns the majority stake in the company.This study identifies the moderate effect of family in the link joining the audit committee with the voluntary risk disclosure of financial institutions in Jordan. It's population is the Jordanian commercial banks registered and operating in Jordan during the period extending from 2017 to 2023.Significantly, it concluded with revealing that the characteristics of the audit committee; namely, independence, experience, and committee size, obviously impact disclosure of voluntary risk in the selected banks. However, the results made it obvious that the number of audit committee meetings did not affect the degree of voluntary risk disclosure. In addition, the results view family ownership as moderately affecting the relationship joining some audit committee characteristics with voluntary risk disclosure.

Enterprise risk management (ERM) was introduced in the 1990s and has become an expectation by boards of directors and regulators as a sign of good management and good corporate governance. However, many organizations struggle to implement ERM, and still seek practical ad-vice on ERM implementation. This article explains many of the reasons why organizations are unsuccessful in their efforts at implementation and provides practical solutions by an experienced risk manager and consultant, an ex-Chief Risk Officer, and an academic, all who has writ-ten extensively in the subject. This article should be of interest to practitioners involved in implementing ERM, to consultants in ERM, and to academics teaching courses on ERM, risk management, and related topics. This article also provides a base against which further future re-search can be done as ERM best practices continue to evolve.

Children with central nervous system (CNS) malignancies often suffer from high symptom burden and risk of death. Pediatric palliative care is a medical specialty, provided by an interdisciplinary team, which focuses on enhancing quality of life and minimizing suffering for children with life-threatening or life-limiting disease, and their families. Primary palliative care skills which include basic symptom management, facilitation of goals-of-care discussions, and transition to hospice can and should be developed by all providers of neuro-oncology care. This chapter will review the fundamentals of providing primary palliative care

Background/Objectives: Consumption of a high energy density diet (HED) leads to increased body weight and fat mass, gut dysbiosis, and obesity. The aim of this study was to characterize the initial response to HED consumption, as well as identify any sex differences, on body composition, systemic inflammation, gut microbiome, and fecal fat excretion in rats. Methods: Male and female Sprague-Dawley rats were fed a low energy density (LED) for 10 days and then were switched to HED for four weeks. Food intake was measured twice a week, body weight and body composition were measured weekly. Serum samples were collected to measure inflammatory cytokines/chemokines. Fecal samples were collected for microbiome analysis and lipid content. Results: Both males and females experienced increases in body weight, fat mass and fecal fat excretion, while males were more susceptible to significant weight gain, particularly in the diet-induced obesity-prone (DIO-P) group. Males showed elevated TGF-β levels, while females exhibited increases in IP-10, RANTES, and FGFb. Changes in gut microbiota composition revealed a reduction in beneficial species like Bacteroides uniformis and Parabacteroides distasonis and an increase in species such as Akkermansia muciniphila. Sex differences in fat metabolism were shown in the greater fecal fat excretion observed in males. Conclusions: Our study demonstrates that short-term consumption of a high-energy diet elicits notable sex-specific differences in body weight, body composition, inflammatory markers, gut microbiota, and fat excretion in Sprague-Dawley rats. These findings underscore the importance of considering sex as a biological variable in studies of diet-induced obesity and its metabolic consequences.

New information suggests female autistic spectrum disorder (ASD) is much more common than previously thought, with a likely prevalence of 6% and with 80% undiagnosed at the age of 18. ASD then becomes a common comorbidity of female mental illness with nearly one in five women who develop a mental illness being autistic. ASD has heretofore been regarded as a pediatric condition and though now thought to be life long it is still not well recognized by adult health services. Most mental illness first presents in the teens and early twenties. Comorbid ASD is more difficult to diagnose due to diagnostic overshadowing, and ASD comorbidity maks the mental illness more severe and mor difficult to treat. Recognized ASD is readily treatable with an approach sympathetic to neurodiversity. Improving the pathway from adolescence to adulthood by increasing knowledge of autism in adult health services would dramatically improve female mental health at surprisingly little extra cost. It is low hanging fruit in a very fraught area of healthcare. This paper will examine the extent of the problem. It will explore solutions and quantify the gains of appropriate therapy.

This research develops the Osteoporosis Knowledge, Attitude, and Behaviors Questionnaire (OKABQ) with the intent to evaluate levels of osteoporosis knowledge, attitude and behavior change. The aims of the study were to develop and validate the OKABQ; and to establish a mediation model of the research. A quantitative, descriptive, and instrumental study was conducted in two phases: Phase I—development of the scale through Delphi Method by osteoporosis experts; Phase II—evaluation of the validity and reliability of the scale and construction of a mediation model using SmartPLS. In Phase I, the content validity index (CVI) of the questionnaire was higher than 0.96 and the inter-rater reliability (IRR) kappa was 1.00. In Phase II, exploratory factor analysis showed that two predominating factors of attitude as a mediation were addressed by the 26-item OKABQ. The indirect effect results from the estimated model indicates that attitude mediates the relationship between knowledge and behaviors (β = 0.114, t = 2.627, p < 0.001), which is positive and statistically significant. We concluded that the OKABQ is a valid measure of osteoporosis knowledge, attitude and behaviors for women with osteoporosis. These assessment results could assist healthcare providers in mitigating insufficiency on health education.

Background: Ventilator-associated pneumonia (VAP) is among the most common healthcare-associated infections in Pediatric Intensive Care Units (PICUs). Because of the lack of a gold-standard diagnostic test, early diagnosis of VAP is challenging. We investigated whether bronchial biomarkers interleukin-4 (IL-4), plasminogen activator inhibitor-1 (PAI-1) and soluble receptor for advanced glycation end products (RAGE) could contribute in early VAP diagnosis through their fluctuation in time in critically ill pediatric patients. Methods: Bronchial secretions were collected from PICU patients with VAP on days 1 and 6. PAI-1, RAGE and IL-4 levels were measured by ELISA. Protein concentrations between high and low VAP suspicion patients were compared using unpaired Student’s t or Mann–Whitney U tests. Results: Twenty PICU patients, with median age 7.75yrs (range 0.5-15.3), mechanically ventilated for ≥48hrs with increased oxygenation requirements and VAP clinical/laboratory signs were enrolled. They were divided in VAP high-suspicion (n=12) or low-suspicion (n=8) groups based on Clinical Pulmonary Infection Score (cutoff:6). ΡΑΙ-1 και RAGE levels did not differ between high- or low-VAP suspicion groups the 1st or 6th days (p-value&gt;0.05). IL-4 was not detected in bronchial secretions. Conclusion: Bronchial concentrations of IL-4, PAI-1 and RAGE in critically ill children are not correlated with high- or low-VAP suspicion.

This article explores the relationship between Wang Yangming's philosophy and the new quality productivity, revealing how the new quality productivity, while inheriting the core ideas of Yangming's philosophy, achieves a higher level through innovation and development. The new quality productivity emphasizes the integration and innovation of knowledge, technology, and information, characterized by knowledge-driven innovation, information technology support, sustainable green development, and global collaborative development. The fusion of Yangming's philosophy and the new quality productivity holds significant theoretical and practical implications.

Keywords: Innovation ecosystems, Economic sustainability, Hydrocarbon-based economies, Economic diversification, Qualitative approach

Abstract：This paper uses the balanced panel data from 29 provinces (autonomous regions and municipalities) in China for a total of 17 years from 2000 to 2016 as a research sample, and establishes an empirical model to examine the impact of environmental regulations and technological innovation on the quality of economic growth. Then this paper test technological innovation as a threshold variable, in which play a regulatory role. Taking the provincial balanced panel data as a research sample, a fixed effect model, a system GMM model, and a panel threshold model were established for empirical testing and the robustness test. Based on the empirical results, this article draws the following conclusions: from a national perspective, environmental regulations and technological innovation can significantly promote the quality of economic growth; from a regional perspective, there are regional differences in impact effects. Under the constraints of environmental regulations, the promotion effect of technological innovation on the quality of economic growth will be reduced; the impact of environmental regulation on the quality of economic growth will have a "threshold effect", and environmental regulation can significantly promote the quality of economic growth only after crossing the threshold and the threshold of technological innovation.

While current studies have focused on adoption and the relevant content of the app to become a decision support system, very few studies have focused on the farmer's intention and initial decision to adopt. Based on a survey of 394 smallholder farmers this study investigated Mexican farmers’ willingness to adopt an agricultural advice app. A Structural Equation Modelling approach, based on the Unified Theory of Acceptance and Use of Technology (UTAUT) was applied. To understand farmers’ adoption decision, extended constructs were studied (e.g. mastery-approach goals) along with farmers’ age and participation in an innovation hub. Results showed that the intention to adopt the app is predicted by how farmers believe that technical infrastructure exists and by the expectation of the farmers using the app to acquire new knowledge. The multi-group analysis revealed that performance expectancy is a relevant predictor of the intention to adopt, whereas the mastery-approach goal is relevant only for younger and farmers not connected to the innovation hub. The results may well be a baseline to research further suitable non-financial incentives for different farmers’ groups, then encourage initial adoption and enhance uptake. The findings are useful for practitioners and app developers designing digital decision support tools.

Introduction: Parkinson’s disease (PD) patients harboring recessive gene variants exhibit a distinct clinical phenotype with an early disease onset and relatively mild symptoms. Data concerning individualized therapy for autosomal recessive PD forms are still scarce. Methods: Demographic and treatment data of a cohort of PD carriers of recessive genes (9 homozygous or compound heterozygous PRKN carriers, 4 Heterozygous PRKN carriers and 3 biallelic PINK1 carriers) were evaluated. Results: The average Levodopa Equivalent daily dose (LEDD) was 806.8±453.5 (range 152-1810) in PRKN carriers and 765±96.6 (range 660-850) in PINK1 carriers. The majority responded to low/moderate doses of Levodopa. The response to Dopamine Agonists (DA) was often favorable both as initial and longitudinal therapy. 8/13 PRKN and 1/3 PINK1 carriers were treated with amantadine successfully, and this also applied to patients who could not tolerate Levodopa or DA. Conclusions: In the era of personalized treatment, the therapeutic approach in recessive PD gene carriers might differ as compared to idiopathic PD. Lower LEDD doses were efficient even in patients with a very long disease duration, while a few patients were doing well without any Levodopa treatment decades after disease initiation. DA or amantadine could be used as a first and main line treatment regimen if well tolerated. Literature data on therapeutic strategies in carriers of pathogenic mutations in recessive PD genes, including device-aided treatments will be further discussed.

Biocomposite membranes based on polylactic acid (PLA) and cellulose nanocrystals (CNCs) were developed using a scientific approach. Dicumyl peroxide (DCP) was used as a polymerization ini-tiator, while tin octoate (Sn(Oct)2) and triphenylphosphane (P(C6H5)3) were used as catalysts. A torque rheometer was used to mix the components of the biocomposite, and thin films was prepared by solvent casting. Fourier transform infrared (FTIR) spectroscopy confirmed the coupling between the PLA and CNCs. Field emission scanning electron microscopy (FESEM) showed that the CNCs were well-dispersed in the PLA matrix with an unimodal particle size distribution and a maximum particle size of around 200 nm. Thermogravimetric analysis (TGA) and differential scanning calo-rimetry (DSC) analysis demonstrated good thermal stability and improved biodegradability of the biocomposite membrane compared to pure PLA. Mechanical characterization showed a Young's modulus of 1.65 GPa, which is comparable to that of other composite materials, and a maximum tensile strength of 20.31 MPa, which is higher than that of pure PLA. These results suggest that the developed biocomposite membrane has potential applications in water filtration, food packaging, and biomedical devices.

Recurrent Neural Networks (RNNs) have significantly advanced the field of machine learning by enabling the effective processing of sequential data. This paper provides a comprehensive review of RNNs and their applications, highlighting advancements in architectures such as Long Short-Term Memory (LSTM) networks, Gated Recurrent Units (GRUs), Bidirectional LSTM (BiLSTM), and stacked LSTM. The study examines the application of RNNs in different domains, including natural language processing (NLP), speech recognition, financial time series forecasting, bioinformatics, autonomous vehicles, and anomaly detection. Additionally, the study discusses recent innovations, such as the integration of attention mechanisms and the development of hybrid models that combine RNNs with convolutional neural networks (CNNs) and transformer architectures. This review aims to provide machine learning researchers and practitioners with a comprehensive overview of the current state and future directions of RNN research.

Confronting the dual challenges of rapid urbanization and climate change, although extensive research has investigated the influencing factors and practical strategies of urban carbon emissions and urban vibrancy, respectively, the unclear mutual nexus between them and the development strategy of collaborative optimization requires further in-depth analysis. This study explores the delicate balance between urban vibrancy and low-carbon sustainability within the confines of Beijing’s Fifth Ring Road. By integrating OpenStreetMap, land use, population, and building carbon emission data, we have developed a reproducible method to estimate total carbon emission and emission intensity per capita. Furthermore, we have introduced vibrancy index data to distinguish the vibrancy evaluation of residential and non-residential land and applied cross-combinational classification technology to dissect the spatial correlation between urban carbon emissions and urban vibrancy. The results reveal that the four combination typologies show more significant differences and regularity in residential land. Based on the discovery of spatial correlation, this study puts forward corresponding development strategy suggestions for each typology based on geographical location and the requirements of urban development policies of these four combination typologies. In conclusion, our study highlights the importance of integrating carbon emissions and urban vibrancy comprehensively in sustainable urban planning and proposes that various land use combinations need targeted development strategies to achieve this goal, which need to consider population, energy, service facilities, and other diverse aspects.

This qualitative research investigates the impact of Supplier Relationship Management (SRM) on e-commerce innovation adoption. Through semi-structured interviews and document analysis, the study explores how SRM practices influence organizational capabilities to innovate in the context of digital commerce. Key themes emerged, emphasizing the critical role of trust, communication, collaboration, strategic alignment, technology integration, organizational culture, leadership, and external factors in shaping e-commerce innovation. Trust was found to be foundational, fostering transparent communication and collaborative relationships that facilitate innovation. Effective communication channels and collaborative initiatives enabled organizations and suppliers to leverage combined expertise, driving the development of innovative e-commerce solutions. Strategic alignment ensured that both parties worked towards shared goals, supported by technology integration that enhanced operational efficiency and decision-making. Organizational culture and leadership were identified as crucial in creating environments conducive to continuous innovation. External factors such as market dynamics, regulatory requirements, and technological advancements influenced innovation strategies, highlighting the need for adaptive and responsive SRM practices. The findings underscore the interconnectedness of these factors within the SRM framework, offering insights into how organizations can enhance their innovation capabilities and competitiveness in the digital economy. By strategically managing SRM practices and integrating sustainable initiatives, organizations can navigate challenges, seize opportunities, and achieve sustained success in e-commerce innovation.

This study examines the latest innovation in wooden pile foundation models using a combination of wood and concrete materials for house construction on swampy land. The focus of the research is on developing joints and materials that enhance the load-bearing capacity and stability of building structures on swampy terrain. The methods used include field observations, laboratory experiments, and descriptive analysis. The results show that the combination of wood and concrete in foundation piles can increase structural strength, reduce deformation, and extend the service life of buildings. The new joint techniques developed in this research are effective in improving structural integrity and minimizing the negative impacts of soft soil conditions. The conclusion emphasizes the importance of material innovation and joint techniques in construction on swampy land, providing practical guidance for construction practitioners and researchers in this field.

This paper presents a Modified Gate Diffusion Input (MGDI) design with four inputs for Quantum-dot Cellular Automata (QCA) technology. QCA is a promising nanotechnology that offers benefits such as low power consumption, and high density, making it a potential alternative to CMOS technology. The proposed planar cell design has advantages over previous designs, including a 19% reduction in the number of cells, a 29% reduction in total energy consumption, and a 44% reduction in average energy loss at the same occupancy level. The proposed block is capable of implementing 21 basic combinational functions and various sequential functions. The simulation of functions in 18nm technology and energy consumption calculation indicates that the resulting circuits have improvements of 41%, 27%, 27%, and 20% compared to multiplexers, comparators, four-bit parity circuits, and single-bit memory, respectively. Additionally, the number of cells in the proposed circuits has improved by 10%, 7%, 22%, and 19%, respectively.

The interactive approach implies that a heterogeneous group of actors cooperates to identify, develop, and introduce innovative solutions into the ground. 20-year studies showed this approach as the most suitable to support innovation and knowledge sharing in the agri-food system. With the introduction of the EIP initiative in the EU policy, this approach has become a privileged tool to support innovation within the CAP, via the implementation of Operational Groups. The present study aims to analyse how the interaction process works in the implementation of the OGs in Italy, and its effectiveness. An online survey submitted to 270 OGs and 10 in-depth case studies were used to analyse interaction process and its effectiveness in the Italian OGs. The results show that the EIP AGRI in Italy helped to capture the real issues of farmers and other actors in the rural territories. Furthermore, participation in the OGs supported the creation and strengthening of relationships between partners. The major difficulties were identified in maintaining active interaction in all phases of the projects and with all partners involved and in the traditional approach used for dissemination of results, both within and outside the partnership. The study showed how complex is to describe the processes triggered by the interactive approach, being it influenced by the type of relationships existing between partners and by other external factors.

In this article we estimate the value of “Non-R&D Innovation Expenditures” in Europe. We use data from the European Innovation Scoreboard-EIS of the European Commission from the period 2010-2019. We test data with the following econometric models i.e.: Pooled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects, WLS. We found that “Non-R&D Innovation Expenditures” is positively associated among others to “Innovation Index” and “Firm Investments” and negatively associated among others to “Human Resources” and “Government Procurement of Advanced Technology Products”. We use the k-Means algorithm with either the Silhouette Coefficient and the Elbow Method in a confrontation with the network analysis optimized with the Distance of Manhattan and we find that the optimal number of clusters is four. Furthermore, we propose a confrontation among eight machine learning algorithms to predict the level of “Non-R&D Innovation Expenditures” either with Original Data-OD either with Augmented Data-AD. We found that Gradient Boost Trees Regression is the best predictor for OD while Tree Ensemble Regression is the best Predictor for AD. Finally, we verify that the prediction with AD is more efficient of that with OD with a reduction in the average value of statistical errors equal to 40,50%.

As a representative of Exponential Organizations, MI went from obscurity to the Fortune 500 in just ten years. Mi's success is inextricably linked to its outstanding business model. This paper summarizes the elements of MI's business model from four perspectives: value proposition, value creation, value delivery, and value capture, as well as its measures for developing into an exponential organization. Expecting to provide theoretical references for the transformation and upgrading of manufacturing organizations.

Background: South Africa’s public healthcare sector is overburdened, especially its under-resourced primary healthcare delivery system. This burden could be relieved by alleviating the population’s ill-health, focusing on the social determinants of health. These include living conditions and levels of social cohesion. In an attempt to address the aforementioned ‘challenge landscape’, this article considers socio-economic empowerment of those marginalised members of society living at the base of the pyramid (BOP) to improve factors contributing to poor health. We propose that Innovation Platforms (IPs) offer opportunities to achieve this by drawing diverse stakeholders together, which should include marginalised individuals, to pool resources and knowledge and collaborate around a specific set of challenges. Method: A Grounded Theory approach is utilised to develop the framework comprising concept definition from a systemized literature review. It is evaluated through various progressive stages through three phases of evaluation: 1) the initial framework was subjected to scrutiny in a theoretical case study, 2) a first-pass semi-structured interview and later four more semi-structured interviews with subject matter experts, and 3) an instrumental case study to refine the framework and to understand its application in a particular situation (this included four stakeholder interviews and a workshop and feedback session with the project champion). Results: This article contributes to the extant literature by addressing the lack of guidance on stakeholder engagement practices critical to the proper functioning of IPs in the context of overcoming the complex challenges associated with social determinants of health. The final output of the study is a refined management tool for stakeholder engagement in IPs. The tool provides practical recommendations to support policy makers, researchers and practitioners in 1) establishing IPs, 2) identifying areas for improvement and 3) identifying reasons for an IP’s failure and lessons to learn.

The move to a low carbon economy is very important for enhancing international competitiveness. The eco-innovation is the critical factor of the green paradigm. This study is designed to investigate deeply the determinants of eco-innovation of manufacturing firms in Korea by suggesting anticipated regulations, self-regulations, and industry-specific characteristics as external factors and open information sources as internal factors. The data used in the analysis is 1946 sample firms from Korean Innovation Survey 2010 based on the Oslo Manual. Using the multi-variate probit analysis and the zero-inflated negative binomial (ZINB) regression analysis, we have found out that the anticipated regulations and self-regulations have significant influences both on eco-process innovation and eco-product innovation, while industrial characteristics have no effects. The empirical results also show that the breadth of information sources has a positive effect on businesses in implementing eco-innovations. Our findings show that the Korean government should provide a good platform where firms can better understand the future trends of environmental policies, particularly policies on anticipated and self-regulations. At the same time, Korean firms should establish a voluntary system to control environmental activities so that they can improve eco-innovations through integrating external information.

Understanding the evolutionary role of environmentally-induced phenotypic variation (i.e., environmental plasticity) is an important issue in developmental evolution. One of the major physiological responses to environmental changes is cellular stress, which is counteracted by a generic stress reaction that detoxifies the cell, refolds proteins, and repairs DNA damage. In this paper, we elaborate on a previous finding suggesting that the cell differentiation cascade of human decidual stromal cells, a cell type critical for embryo implantation and the maintenance of pregnancy, evolved from a cellular stress reaction. We hypothesize that the stress reaction in these cells was elicited ancestrally through the inflammation caused by embryo attachment and invasion. We describe a model, Stress-Induced Evolutionary Innovation (SIEI), whereby ancestral stress reactions and their corresponding pathways can be transformed into novel structural components of body plans, such as new cell types. After reviewing similarities and differences between SIEI and the “plasticity first hypothesis” (PFH) of evolution, we argue that SIEI is a distinct form of plasticity-based evolutionary change because it leads to the origin of novel structures rather than the adaptive transformation of a pre-existing character.

The purpose of this paper is to evaluate the timing of innovative investment in technology product life cycles using a compound binomial option with management flexibility. Considering the business cycles changes in the macroeconomic will affect consumer purchasing power. The focus is how to evaluate the optimal investment strategy and the project value. It was applied to different product stages (three stages including production innovation, manufacture innovation, and operation innovation) and factored to different risks to build a technology innovation strategy model. An aim of this study is the options premium of the best strategy timing for each innovation stage. Its application of the compound binomial options for the manufacture innovation will only be considered after the execution of the production innovation. The same condition is applied to the operation innovation, which will only be considered after the execution of the manufacture innovation. Then, this paper constructs the dynamic investment sequential decision model, assesses the feasibility of an investment strategy, and makes a decision on the appropriate project value and options premium for each stage under the possible change of Gross Domestic Product (GDP). This paper investigates the product life cycle innovation investment topic by using the compound binomial options method and will provide a more flexible strategy decision compared with other trend forecast criteria.

The present context regarding development of the food products trade at European Union level presumes manifestation of some tendencies and challenges meant to claim at the highest level the adaptation capacity of economical agents - both producers and traders. Among these we can take into account their need to comply with organic product labeling standards as an integral part of food products safety policies at Union level. In order to be able to implement a proper label type, not only from the point of view of standards but especially from the perspective given by the consumers perception and motivation toward a healthy sustainable food consumption, producers have to constantly innovate, to find new design solutions for food products labels. This article propose an exploratory research in the form of a field survey that highlights the perceptions of Romanian and Serbian consumers, altogether from the urban environment in relation to organic food labeling and how they influence purchasing decision-making. A random number of 373 Serbian consumers’ questionnaires, respectively 1262 Romanian consumers’ questionnaires have been validated, the results showing interesting results from the point of view of national consumption profile differences due to different cultural, economic and social factors as well as different levels of integration within European economy for the both countries. Main conclusions of the research stress the fact that perceptions regarding organic food products labels are constructed around variables like: type of information to appear within the label, category of information that are missing from labels, degree of producers interest in proper labeling of organic food products, relevance of the information on the organic food labels as regards the decision to purchase the products etc. Conclusions propose some possible developments for innovative future characteristics for organic food products labels.

This study explores the properties and behavior of bi-close-to-convex functions, introducing new subclasses defined by their relationship with fractional differential operator and bi-univalent functions. Using the Faber polynomial technique, we derive upper bounds for the n^{th} coefficient of functions in these classes. We also investigate the erratic behavior of initial coefficients in bi-close-to-convex functions, as characterized by the (λ,q)-fractional differintegral operator. Furthermore, we address Fekete-Szegö problems and present notable findings from our investigation, contributing to the continued growth and refinement of geometric function theory, yielding new insights and practical uses.

Vienna Atomic Line Database (VALD) contains data on atomic and molecular energy levels and parameters of spectral lines required for stellar spectra analysis. Hundreds of millions lines for fine spectral synthesis and for opacity calculations are collected in present version of VALD (VALD3). Critical evaluation of the data and the diversity of extraction tools support high popularity of VALD among users. The data model of VALD3 incorporates obligatory links to the bibliography making our database more attractive as publishing platform for data producers. The VALD data quality and completeness are constantly improving allowing better reproduction of stellar spectra. To illustrate continuous evolution of the data content we present a comparative analysis of the recent experimental and theoretical atomic data for Fe-group elements, which will be included in the next VALD release. This release will also include a possibility for extracting the line data with full isotopic and hyperfine structures.

Integrating a grid-connected battery into a Renewable Energy Community boosts Collective-Self-Consumption of photovoltaic produced energy and allow to perform Energy Arbitrage in the day-ahead and intraday electricity market. However, is it a cost-effective investment? The proposed analysis relay on Net Present Value assessment. Ageing affects are integrated and sensitivity analyses are conducted: considering community customers number, electricity mar-ket prices, battery cost, size and the decision to engage in energy arbitrage. Each scenario under-goes a 20-year hourly simulation using an ageing aware rolling-horizon 24-hours-looking-ahead scheduling, optimized with Mixed-integer linear Programming. Forecast errors, provid-ing of ancillary services, real time control and grid constrains are not taken into account. Simulations conducted on the Italian market indicates that a battery dedicated solely to collec-tive self-consumption is not economically appealing. However, integrating Energy Arbitrage, despite impact on battery lifespan, halves the payback period and enhances the attractiveness of larger battery investments. The Net Present Value is contingent upon battery size, customer number and market prices. However, if battery cost does not exceed 200 €/kWh the investment become cost-effective across all scenarios.