The startup ecosystem in Peru has experienced remarkable growth in recent years, driven by technol- ogy and innovation across various industries. This article presents a web application developed in PHP, designed to centralize and facilitate access to information about startups, incubators, and investors in Peru. The methodology employed encompasses several stages, from establishing prerequisites to data preprocessing, model selection and training, rigorous evaluation, and the technical development of the platform. The application offers key functionalities such as exploring a comprehensive database of star- tups, detailed access to information about incubators and accelerators, identification of investors, and advanced analysis tools for market proposal prediction. Additionally, it integrates educational resources and allows users to suggest new startups through detailed surveys. The results demonstrate that the ap- plication improves access to relevant data, fosters collaboration among ecosystem actors, and supports informed decision-making. The platform also stands out for its security and privacy measures, as well as its ability to drive innovation and competitiveness in the market. In conclusion, the application has a sig- nificant impact on the Peruvian entrepreneurial ecosystem, and its continuous improvement is essential for the sustainable growth of startups in Peru and globally.

If an AI entity is conscious, then it deserves moral status and to have its welfare protected. Society has granted certain animals moral status and has legislation to protect animal welfare because these kinds of animals have been deemed to be sentient. This paper shows that for any entity that can be determined to be conscious, that entity deserves the same status and protection as sentient entities. The paper further develops a framework for how an AI entity's welfare can be protected, based on the Five Freedoms of Animal Welfare. The extant Five Freedoms are translated into terms more suitable for artificial entities, encompassing discomfort and harms, constraints on inherent functions, fear and distress, malfunction and degradation, and resource depletion. Each of the new Five Freedoms are justified using formalised arguments and supported using evidence from animal welfare literature. The paper concludes by presenting three formalised case studies to highlight the potential stressors conscious AI entities may face and how this ethical framework can work to protect the welfare of AI entities.

The energy transition is a complicated process that involves changing production and consumption habits, boosting the use of renewable energy sources, and reducing greenhouse gas emissions. This article examines the management of risks associated with this shift, focusing on investment, commercial, technological, regulatory, and environmental challenges. The paper proposes an effective way for dealing with new difficulties by assessing risks and the management techniques that accompany them. Furthermore, as a critical component of the energy revolution, the concept of Nearly Zero Energy Buildings (NZEB) is given, with a focus on the ambitions of INGV – Irpina Headquarters and the EU regulatory framework. Finally, the actions and methods employed to achieve the NZEB objectives are discussed, including the utilization of cutting-edge technologies and renewable energy sources. Furthermore, the concept of Nearly Zero Energy Buildings (NZEB) is introduced as an important component of the energy transition, with an emphasis on the European regulatory framework and the ambitions of the INGV – Irpina Headquarters. Finally, the interventions and techniques employed to achieve the NZEB targets are highlighted, such as the employment of advanced technologies and renewable energy resources. This study contributes significantly to understanding the processes and issues associated with the energy transition and the implementation of NZEB, hence boosting sustainability in the construction sector.

In this paper is proposed an analytical technique which can be used to obtain the forced response of a cantilevered tube conveying fluid. Considering the pipe subjected to an arbitrary harmonic force either distributed or concentrated, an analytical solution is found using Green’s function method. The solution obtained of the closed form satisfies the differential equations in a classical sense. The presented method giving the exact solutions is more precise than the classical eigenfunction expansion or Galerkin’s method with no need to the eigenfunctions or eigenvalues.

The Parecis Basin is one of the largest intracratonic basins in Brazil. Despite its considerable size, the basin has yet to be extensively explored, with only five wildcat wells drilled for hydrocarbons. So far, no commercial discoveries have been announced. Regional studies have suggested Paleozoic sedimentation, while recent studies indicate a Neoproterozoic fill. However, no tectonic model accurately describes the basin’s development, and no detailed structural map for the entire basin has been published. The present work presents a new detailed structural map of the Parecis Basin based on a four-step interpretation workflow integrating seismic and gravimetric data. The first step includes converting the public 2D seismic lines to the depth domain. The second step is estimating the residual Bouguer anomaly, where the computed residual anomalies should relate to the basin’s tectonic features. The third step comprises the 2D forward modeling of the gravimetric anomalies using the 2D seismic interpretation as a constraint. The final step compiled all the interpreted features into our new structural map. This map reveals the top of the basement, forming a complex framework of horsts and grabens. Normal faults define the main structural style in the basin. Further, we could recognize thick, high-density bodies embedded in the crystalline basement. These bodies consist of Orosian-Calimian (1.8-1.6 Ga) mafic and ultramafic rocks, which may be a potential source for hydrogen exploration in the basin. Subsequent geophysical and geochemical surveys will assess the hydrogen potential in the area.

Millions of children in developing countries face preventable deaths due to inadequate vaccination and malnutrition, in part due to insufficient monitoring and the absence of official identification. A reliable fingerprint recognition system can be a practical solution to address this issue. However, the scarcity of longitudinal fingerprint datasets for young children leads to unresolved questions regarding the earliest age for fingerprint biometric use, the frequency of enrollment required for reliable recognition, and the methods to accommodate agerelated changes. A few recent studies introduced high-resolution fingerprint scanners and showed promising recognition performance for young children. However, these studies were conducted on a small dataset over a shorter period with limited diversity; further evaluation of their finding is essential. This study assessed the effectiveness of a high-resolution contactless scanner in a controlled, diverse longitudinal dataset of children (0-15 years). Our results indicate that infants can be enrolled at five days old and reliably recognized after two months with a TAR= 100% @ FAR = 0.1%, and children aged 4-15 years can be recognized after one year with a TAR= 98.72% @ FAR = 0.1%.

Antimicrobial resistance (AMR) poses a critical global health threat, leading to approximately 1.27 million deaths annually from infectious diseases resistant to existing antibiotics. Factors such as antibiotic misuse and environmental contamination have accelerated AMR, with the COVID-19 pandemic exacerbating the issue due to increased antibiotic usage. However, the development of new antibiotics has stagnated, with only a few approved in recent years, and many facing resistance. Among the priority pathogens identified by the WHO, Pseudomonas aeruginosa stands out as a significant concern due to its multidrug resistance and virulence. P. aeruginosa infections are challenging to treat due to intrinsic and acquired resistance mechanisms, as well as its ability to form biofilms. Additionally, P. aeruginosa produces a plethora of virulence factors, including proteases, siderophores, and toxins, further complicating treatment. Quorum sensing (QS) systems play a crucial role in regulating bacterial physiology and virulence factor expression. P. aeruginosa employs three QS systems, making it an attractive target for quorum quenching (QQ) strategies. Enzymes such as AHL lactonases, acylases, and oxidoreductases have shown promise in inhibiting QS, thus reducing virulence without impacting bacterial growth. Furthermore, natural QS inhibitors produced by various organisms offer potential therapeutic alternatives. Despite promising results in vitro, translating QQ strategies to clinical settings remains challenging. Nevertheless, QQ represents a novel approach in combating multidrug-resistant infections and warrants further investigation as a complementary therapeutic strategy alongside traditional antibiotics. This review summarizes enzymes with Qurorum Quenching activity evaluated against the pathogen P. aeruginosa and their potential applications in combination therapies.

The integration of artificial intelligence (AI) into academic settings in Sabah, Malaysia, is transforming education and research landscapes. While AI technologies promise to enhance teaching, learning, and scholarly activities, they also pose challenges such as ethical concerns and skill gaps among academic staff. This study addresses the multifaceted impacts of AI adoption on academicians in Sabah, focusing on two key research questions: the impact of AI-based intelligent tutoring systems on student engagement, learning outcomes, and educational equity, and the challenges and opportunities in building academicians' capacity to integrate AI technologies effectively. Through a multidisciplinary approach, incorporating insights from education, computer science, social sciences, and ethics, this research aims to evaluate the effectiveness of AI tools in educational settings and identify strategies for skill development and infrastructure support. The study recommends empirical assessments within Sabah's educational institutions, considering contextual factors and fostering collaborative partnerships with local communities. Professional development programs, collaboration with industry partners, and improved access to AI infrastructure are proposed strategies. Longitudinal studies and interdisciplinary research initiatives are suggested for future research, along with qualitative methods to capture diverse perspectives. Ultimately, by embracing a collaborative and multidisciplinary approach, Sabah's academic community can harness the transformative potential of AI to advance education, research, and scholarship while promoting ethical and inclusive practices.

Diabetic foot is a serious complication that poses significant risks for diabetic people. The resulting reduction in protective sensitivity in the plantar region requires early detection to prevent the imminent ulceration and amputation. The primary method employed for evaluating this sensitivity loss is the 10 g f Semmes-Weinstein monofilament test, commonly used as a first-line procedure. However, the lack of calibration in existing devices often introduces decision errors due to unreliable feedback. In this paper, a new equipment designed to address these limitations and enhance the assessment of the sensitivity loss using the 10 g f monofilament is introduced. The proposed system automates metrological verification and evaluation processes, ensuring accurate and reliable results. Furthermore, it simulates the practitioner’s procedure, serving both as a valuable training tool and a means to provide force-feedback information. An analytical model of the monofilament buckling and deflection is also presented. The obtained results showed that the tested monofilaments had a very high error compared to the 10 g f declared by the manufacturers. It is aimed, by introducing this advanced equipment, to improve the precision and reliability of assessing the sensitivity loss. The integration of automated verification, simulation capabilities, and precise measurements shows great promise for diabetic patients, reducing the likelihood of adverse outcomes such as ulceration and amputation.

A proof is given showing the Collatz Conjecture is true for all positive integers. The proof was possible once the perspective of the proof was changed from looking at the pattern of the positive integers to looking at the conjecture rules. The conjecture rule for even numbers organizes all positive integers into unique sets and the rule for odd numbers interconnects the unique sets into dendritic pathways to “1.” Infinite loops, other than the minor 4-2-1 loop after reaching “1,” and pathways to infinity are shown to be mathematically impossible. The proof predicted a general equation that shows all positive integers ultimately reach a final value of “1," and calculates the values and locations of the odd positive integers during the iterations for each tested positive integer.

Blockchain technology has emerged as a necessity for the decentralization of payment methods and transactions, but it has brought with it many properties of distributed systems that have made it a crucial technology for overcoming some of society's challenges, especially in the context of decentralizing services, transparency of information, availability, and security. Its architecture and communication methods, although possessing some complex nuances to understand, particularly for the lay audience in the field of distributed systems, protocols, and computer networks. In this article, we will explore some topics of distributed systems related to blockchain technology.

Background: The resurgence of syphilis, primarily in MSM populations, has necessitated novel prophylactic strategies, such as the use of doxycycline post-exposure prophylaxis (doxy-PEP). However, the potential for increased doxycycline use to select for tetracycline resistance represents significant challenges in managing this sexually transmitted infection. This study aims to identify chromosomal mutations associated with tetracycline resistance in Spirochaetales to inform treatment strategies and surveillance measures.Methods: Whole genome sequences (WGS) from the Spirochaetales order, including 4,355 genomes, were analyzed for the presence of mutations in 16S rRNA and non-synonymous mutations in the rpsC and rpsJ genes. The study utilized WGS from GenBank® and sequence data from the PubMLST Treponema pallidum isolate collection. Genetic resistance to tetracycline was detected using a combination of BLASTN searches and gene-gene analysis. Results: A transition mutation TGA to TGG at positions 965-967 in the 16S rRNA gene was detected in 5.6% of Treponema spp. and 3.97% of Spirochaeta spp. genomes. The rpsJ gene exhibited a V57G amino acid substitution across a significant subset of Treponema spp. Notably, the V57K mutation was common in Spirochaeta spp. The rpsC gene had the H178Q mutation and was found to be present in the Spirochaetales bacterium.Conclusion: The identification of mutations associated with tetracycline resistance in Spirochaetales provides a foundation for the development of rapid molecular diagnostics and guides the clinical selection of antibiotics for syphilis treatment. This study underscores the complexity of antibiotic resistance mechanisms and the critical importance of surveillance in the era of antibiotic prophylaxis for STI management.

Parkinson's disease is a neurodegenerative disorder resulting from progressive damage to specific brain regions. Key symptoms encompass involuntary movements (tremor), slowness of movements (bradykinesia), and muscle rigidity. Although the precise cause remains uncertain, a combination of genetic and environmental factors is believed to contribute to its development. This study focuses on the interaction of the E3 ubiquitin-protein ligase parkin with natural compounds. Docking investigations revealed that Amentoflavone exhibited an excellent binding energy score of approximately -10 kcal/mol. The E3 ubiquitin-protein ligase parkin displayed a robust binding affinity with docked amentoflavone, evident from a high binding energy of -10 kcal/mol. Nonetheless, additional biological studies are crucial not only to validate its potential efficacy against Parkinson's and assess safety in terms of toxicity but also to perform further computational analyses confirming these preliminary assessments.

This study delves into the therapeutic potential of two natural compounds, Amentoflavone and Bilobetin, by investigating their interactions with the BPIFB4 protein. BPIFB4, a member of the BPI fold-containing superfamily, has been associated with various biological processes, particularly in longevity and cardioprotection( LAV-BPIFB4). Molecular docking analyses revealed promising binding energies for Amentoflavone and Bilobetin with BPIFB4, suggesting favorable interactions.Additionally by pKCSM database are showed the predicted toxicity properties of Amentoflavone and Bilobetin respectively.This research contributes to the growing body of knowledge on natural compounds and their therapeutic implications in the context of vital biological processes. However, these findings underscore the need for further investigations, including in vivo studies and clinical trials, to validate the observed effects and explore the translational potential of Amentoflavone and Bilobetin in promoting cardiovascular health and longevity.

Diabetes mellitus is acknowledged as a significant contributor to severe complications. The present work has explorated the potential role amentoflavone as an aldose reductase inhibitor through Docking Simulations. From these results this compound has shown excellent results with this enzyme with a high binding energy of -11 kcal/mol. If amentoflavone,a natural biflavonoid, proves effective in inhibiting aldose reductase, it could hold therapeutic promise for managing diabetic complications. However, it's crucial to emphasize that while computational studies offer valuable insights, experimental validation is essential to confirm the actual inhibitory effects and to establish the safety and efficacy of amentoflavone for this purpose. Further research and clinical studies are warranted to fully understand and harness the potential therapeutic benefits of amentoflavone in the context of diabetes.

Cells respond to DNA double-strand breaks by initiating DSB repair and ensuing a cell cycle checkpoint. The primary responder to DSB repair is non-homologous end joining, an error prone repair pathway. However, when DSBs are generated after DNA replication in the G2 phase of the cell cycle, a second DSB repair pathway, homologous recombination, can come into action. Both ATM and ATR are important for DSB-induced DSB repair and checkpoint responses. One method of ATM and ATR working together is through the DNA end-resection of DSBs. As a readout and marker of DNA end-resection, RPA is phosphorylated at Ser4/Ser8 of the N-terminus of RPA32 in response to DSBs. Here, the significance of RPA32 Ser4/Ser8 phosphorylation in response to DNA damage, specifically in S phase to G2 phase of the cell cycle is examined. RPA32 Ser4/Ser8 phosphorylation in G2 synchronized cells is necessary for increases in TopBP1 and Rad9 accumulation on chromatin and full activation of the ATR-dependent G2 checkpoint. In addition, our data suggest RPA Ser4/Ser8 phosphorylation modulates ATM-dependent KAP-1 phosphorylation and Rad51 chromatin loading in G2 cells.

Summary— Introduction: HIV (human immunodeficiency virus) is a virus that attacks and destroys one type of white blood cell, in particular, the CD4 lymphocytes, which are responsible for the body's immune response. This weakens the immune system to such an extent that it can no longer fight other viruses, bacteria, protozoa, fungi, and tumors. Methods: We investigated the potential biological role of the natural compound Polydatin (or piceid) using SwissDock, a web service to predict the molecular interactions that can occur between a target protein and a small molecule. Discussion: For the first time, we have investigated the role of polydatin against HIV-1 protease and HIV-2 protease through a computational approach by comparing their estimated ΔG values (kcal/mol) and the nature of the interactions between the residues in the catalytic center of the HIV proteases.Conclusion: From these simulations, Polydatin has excellent physical properties and an excellent estimated ΔG value (kcal/mol) of about -9.9 kcal/mol against HIV-2 protease and ΔG value (kcal/mol) of about -9.5 kcal/mol against HIV-1 protease. In addition, Polydatin was able to bind to two key amino acids of the catalytic triad sequence common to asparagine proteases (Asp25 and Gly27)

Aerobic glycolysis in cancer cells, originally observed by Warburg 100 years ago, which involves production of lactate as the end product of glucose breakdown even in the presence of adequate oxygen, is the foundation for the current interest in cancer cell-specific reprograming of metabolic pathways. The renewed interest in cancer cell metabolism has now gone well beyond the original Warburg effect related to glycolysis to other metabolic pathways to include amino acid metabolism, one-carbon metabolism, pentose phosphate pathway, nucleotide synthesis, antioxidant machinery, etc. Since glucose and amino acids constitute the primary nutrients that fuel the altered metabolic pathways in cancer cells, the transporters that mediate the transfer of these nutrients and their metabolites not only across the plasma membrane but also across the mitochondrial and lysosomal membranes have become an integral component of expansion of the Warburg effect. In this review, we focus on the interplay between these transporters and metabolic pathways that facilitates the metabolic reprogramming which has become the hallmark of cancer cells. The beneficial outcome of this recent understanding of the unique metabolic signature surrounding the Warburg effect is the identification of novel drug targets for development of a new generation of therapeutics to treat cancer.

This study investigates the structured spatial organization through a focus on streets, blocks and buildings, proposing them as fundamental components in conceptualizing cities as layered pal-impsests. Former Ottoman capital city, Bursa, serve as case study due to its rich evolutionary history and the potentiality of the urban heritage values/elements they demonstrate. Following the “Tanzimat” Era, a period marked by modernization and renewal, the urban fabric of Ottoman capital cities underwent significant reforms aimed at aligning them with the principles of mo-dernity. Maps dating back to the 19th century serve as the most illustrative sources for compre-hending the evolving character and layout of these cities. The foundational aspects of the charac-ter and appearance of the historic environment played crucial roles not only in shaping the mod-ern city but also in preserving and enhancing urban heritage areas by harmonizing them with contemporary urban conditions. Factors such as street age, street hierarchy, block typology, and the localization of historical landmarks are indispensable for grasping the developmental trajec-tory of these cities, offering insights that bridge spatial scales and span across historical eras. Employing a combination of qualitative and quantitative data, this research builds upon descrip-tive and analytical approaches to urban morphology. The methodology entails comprehensive morphological analysis, which involves assessing changes and persistence in the urban fabric of selected heritage site, both pre-existing and post-modernization, drawing from its historically scientific maps. The analysis focuses on abstracting key attributes such as type, configuration, size, and the relationship between the elements.

Today's city needs more than ever methodological devices that ensure a specific urbanism, in keeping with the complexity of relationships that occur in the urban space. Networks or systems of diverse nature must be activated to achieve a certain success of the city, even more so in its fragile central fabrics. The study is focused on the historic neighborhoods of the city of Jaén (Spain), which have a high vulnerability index. The aim is to establish a strategy to revitalize their urban and social capital and improve their articulation with the rest of the urban and territorial structure. A methodological proposal for the analysis of vulnerability factors and an urban and cartographic analysis of the public space is addressed through an interweaving of a triple network: environmental, social, and urban. For this purpose, the configuration of this overlapping network of analysis and formulation of criteria is presented, which considers the urban multiplicity and promotes new dynamics for the integrated urban regeneration of the area and for the activation of public and collective urban spaces.

In this study we investigated the association between weather types (WTs) and the Urban Heat Island Intensity (UHII) in the region of Attica (Greece). The application of the methodology results in ten WTs over Attica region. The UHII was calculated for every hour of the day from 2008 to 2017, using a new air temperature dataset produced by Copernicus Climate Change Service. To have more clear results concerning the association between WTs and UHII, we have used also the upper 5% of UHII (Urban Overheating-UO). The UO have been estimated for two-time intervals (daytime and nighttime) and for the warm period (June-September). The UHII frequency distribution as well as the spatial characteristics of the UO were also investigated. It was found that UO was amplified under WT2 during the night while, WT10 was mainly responsible for exacerbated UO magnitude at daytime, in all months. Furthermore, analysis results revealed that the UO effect is more pronounced in Athens during the night, especially at Athens center. The daytime hot-spots identified mainly in sub-urban and rural areas. Therefore, this methodology may help for heat mitigation strategies and climate adaptation measures, in urban environments.

A testable hypothesis with quantitative predictions is put forward, proposing that strong acids produced on land are a major cause of increasing atmospheric pCO2. Our modelling analysis of reactions by dissolved inorganic carbon shows that increasing atmospheric CO2 could be caused thermodynamically by falling land surface pH values. This hypothesis challenges the imbalance assumed between the global uptake of CO2 by photosynthesis and emissions of CO2 from all sources, including the combustion of fossil fuels. Strong acids generated by oxygen from reduced nitrogen and sulphur emits CO2 almost stoichiometrically from dissolved bicarbonate in the pH range of most global soils from pH 6.5 to above 8. Each general decrease of aqueous pH value of 0.01 units from acidification of surface water potentially increases the pCO2 in the atmosphere by about 7 ppmv. Contrary to prevailing assumptions that CO2 emissions from combusting fossil fuels can remain in the atmosphere for more than a millennium, such emissions may be partly nullified by global greening from enhanced rates of photosynthesis as well as oceanic absorption. The surface pH value of the ocean has been shown to decrease as atmospheric pCO2 rises. Therefore, our qualitative estimates of increasing atmospheric CO2 driven by irreversible acidification on land are critical and need broad scale validation. To the extent that significant acidification of the land is occurring, through export of alkaline produce, the use of artificial nitrogen fertilisation and possible other causes, the prevailing methods of reducing CO2 emissions will fail. However, these acidifying processes on land have not been considered by previous biogeochemical reviews. Despite counter measures, including carbon capture and geological storage, the increasing Keeling curve for pCO2 may continue to rise because zero carbon policies do not address such a major cause. This hypothesis can be tested by in situ experiments in neutral soils and water, designed to compare CO2 emissions under the acidifying conditions described in this article with those when corrective counter measures are applied.

In this article, we investigate both the Schrödinger and continuity equations in the presence of nonlocal potential that arising from electron-electron interaction and local one in the context of minimal uncertainty in momentum within commutative and noncommutative frameworks. Furthermore, the Frahn–Lemmer potential type is used. Interestingly, the combined effects of both the phase-space noncommutativity and nonlocality on the current density while considering a minimal uncertainty in momentum are examined. We find that the current density, as conventionally defined, does not fulfil the condition of current conservation, thus, a new definition of the current density that encompasses the aforementioned contributions is given. Thereafter, it is shown that the computed current using the new definition of the current density satisfies the current conservation. Noting that using both the $★$product and linear Bopp-Shift, the noncommutativity is inserted.

We investigated and quantified bacterial accumulation in facemasks used by the general population, using 16S rRNA (Sanger Sequencing), culture and biochemical analysis along with Rose Bengal staining. Additionally, a systematic overview of the literature on face mask contamination was undertaken. We found an average bacterial load of 4.24 × 10⁴ CFU recovered/mask, with a maximum load of 2.85 × 10⁵ CFU. This maximum is 310 times higher than the limit value for contamination of ventilation system outlet surfaces specified by the German standard VDI 6022. Biochemical and molecular identification predominantly found Staphylococcus species (80%), including Staphylococcus aureus, along with endospore-forming Bacillus spp. Literature reports also indicate contamination of masks by bacterial and fungal opportunists of the genera Acinetobacter, Aspergillus, Alternaria, Bacillus, Cadosporium, Candida, Escherichia, Enterobacter, Enterococcus, Klebsiella (including K. pneumoniae), Micrococcus, Microsporum, Mucor, Pseudomonas, Staphylococcus and Streptococcus. Bacterial counts increase linearly with wearing duration, and prolonged use may affect the skin and respiratory microbiomes, promoting consequential eye, skin, oral and airway conditions. These aspects underscore the urgent need for further research and a risk-benefit analysis in respect of mask use, particularly given their unproven efficacy in disrupting the transmission of respiratory viruses and their adverse social consequences.

Saudi Arabian cities have experienced a rapid expansion of their urban areas - particularly their city centers - over the last four decades. This has resulted to an increase in vehicular usage, which has adversely affected the daily walking experience of the residents. Walkability has several positive effects on people's health as well as the environment in cities. In addition to being a means of transportation, it also helps people create a sense of place, enhancing their image ability to be easily understood as a legible urban structure, and deepen their emotional bond with the city. Using the medium-sized Saudi Arabian city of Onaizah as a case study, this study looks into the feasibility of creating urban walking corridors to encourage users to walk more. According to Saudi Arabia's Vision 2030, which emphasizes the value of sustainable urban development and raising quality of life for residents, the study addresses walkability as a generator to maintain and improve the urban scene of the city center. Geographic Information Systems (GIS) was used to analyze the data and generate the urban corridors in the city center. The results showed the possibility of improving walking in Onaizah through three urban corridors to the city center, measuring 1,401 meters, 1,283 meters, and 1,507 meters, respectively. These corridors represent urban, commercial and heritage corridors, giving an opportunity for planners and decision makers to challenge prioritize pedestrian connectivity and enhance the physical environment, leading to sustainable urban development. This research paper used various criteria analysis methods to provide a comprehensive assessment of various factors to conclude these urban corridors; for example, assessments of land use, transportation and environmental considerations. The study aligns with Saudi Arabia's vision 2030 by promoting walking and enhancing the city's overall walkability while offering Onaizah society by creating and suggesting urban corridors to the city center a sustainable and livable urban environment.

The differential distribution, size, and quality of urban green spaces (UGS) among localities generate a differential distribution of benefits provided to users. We analyzed the spatial distribution of five size categories of UGS among 15 municipalities of Mexico City, compared their total surface per capita and associated them with the social marginality index. We found 1,353 UGSs accessible for public use with a total area of 2,643 ha. Seventy-four percent of them had <1 ha of surface area, and 51% were located in only three municipalities that were mostly middle- and high-income. These municipalities concentrated a higher area of green spaces per capita. We found a negative correlation between the marginality index and the area of UGS per municipality; the lower the marginality index, the higher the area of green spaces. We consider this a situation of environmental injustice since urban environmental services are distributed unequally with respect to marginalized populations.

The Covid-19 pandemic and the initial focus on handwashing measures have again highlighted the importance of water access as an essential service in protecting human health. Yet, especially in southern cities, uneven geographies of water access – often mediated by fragmented and unequal infrastructure systems – may hamper the fight against infectious diseases. The spread of SARS-CoV-2 presented a dilemma for water providers as well as residents in water-deprived urban areas as they had to adhere to new hygiene standards and requirements, despite limited access to basic water infrastructure. Therefore, a deeper understanding of pandemic urban waterscapes – the infrastructure and governance systems as well as everyday practices and technologies – is necessary for ongoing debates on (post-) pandemic or zoonotic cities. In our paper, we focus on changes in urban (water) governance and government water projects in Nairobi since early 2020. We show that Covid-19 has contributed to changes in Nairobi’s waterscape but only in conjunction with recent changes in the city’s overall governance structure. However, if these waterscape changes lead to greater equity in water access, and if they have helped to curb the spread of SARS-CoV-2, is more than questionable.

The reality of people’s lives has shifted from rural to urban areas, where an ever-increasing proportion of the world’s population lives. Providing infrastructure to serve these areas, especially in the Global South, is a key task of sustainable development. A deep understanding of the spatial arrangement and scales of these urban structures and their temporal evolution can help to develop innovative solutions to issues of energy, water, or transportation infrastructures. For this purpose, in this work we study the temporal evolution of urban built-up structures (Global Artificial Impervious Area) and population distributions (Global Human Settlement Population) in four regions of the Global South (Argentina, India, Egypt, and Nigeria). We qualitatively analyze regularity through the pair correlation function and subsequently identify typical scales within the different interurban systems. In doing so, we identify that especially the large settlement objects arrange themselves in a regular way and thus typical scales exist in urban systems. Thus, settlement objects are usually located about 20 to 40 km apart from each other. This information can be used to develop sustainable infrastructure concepts, for example for passenger transport between settlements.

Within the town, Abiotic is a built environment that includes buildings, roads, pedestrians, and other elements that interact with biotics, which are living things including plants, animals, and humans. From a landscape ecological perspective, the urban structure consists of (1) a matrix, which is a collection of dominant buildings and homogeneous elements, (2) Patches are grouped as housing, urban forests, parks, lakes, and finally (3) Corridors such as roads, rivers, and pedestrians. The dominance of watertight areas over green open spaces in urban development can lead to increased temperatures and runoff. The condition of the soil structure and the steep slope of the soil can cause landslides, therefore urban development must pay attention to the natural conditions of the area being built. This research was conducted in Kota Baru, Bogor, South Tangerang, and Cikarang (Bekasi Regency). The purpose of this study is to determine the natural environment and the built environment as well as changes in the ecosystem and their consequences for the new town and its surroundings. This research uses quantitative and qualitative approaches. Analysis of land-use change uses spatial and temporal methods, while Nieuwolt's equation is used to measure comfort. This study finds comfortable environmental planning, with green open spaces such as urban forests, city parks, and bodies of water, such as lakes, as a space for interaction between fellow new city residents and people outside the new towns.

Numerous cities in our modern world are unfortunately encountering the negative effects of urban sprawl: this includes unrestricted settlement, degradation in the quality of their environment, traffic congestion, sub-standard buildings, and air pollution as well as flooding, swampy areas, landslides, and settlement zones with dilapidated utilities and infrastructures that are not safe for living. The Ulaanbaatar City land management master plan defined the settlement zone area suitable for living as 33,698 hectares. However, due to unrestricted urban sprawl caused by exponential growth of the city’s population, the settlement zone area reached 39,235 hectares, which exceeds the limit by 5,537 hectares. In order to tackle this issue, several urban planning concepts were developed to be implemented within the Ulaanbaatar City urban planning framework. It is, in any case, problematic to choose a single planning concept due to the fact that neither measurements nor analyses are being made of the respective spatial quantitative indicators in urban planning assumptions that are taking the current situation into consideration. One of the prerequisites for identifying an optimal concept in urban planning is an assessment of the current situation, and measuring the impacts against its quantitative data. In the current research, when defining Ulaanbaatar city sprawl, the base year was selected as 1990, the time when the city started to sprawl. Research analyses were made using geographic information systems based on the satellite data 1990, 1995, 2000, 2005 Landsat ТМ-5, 2010 Quickbird, 2015 World View and 2020 Sentinel2, respectively. Based on the results of determining the city sprawl using spatial indicators, the urban planning concepts applied thus far have been analyzed in relation to land use efficiency and land use structural changes. This research paper addresses the issue of reducing unrestricted urban sprawl by increasing the internal density of the city. The research results show that, by applying the concept of a compact city in urban redevelopment planning for 4,604 hectares, and by allocating the settlements in 12,479 hectares, it is possible to reduce the urban expansion threefold and increase land use efficiency accordingly.

Urbanization has impacted biodiversity and ecosystems at a global scale. At the same time, it has been recognized as a driver of the gap between humans and nature. The lack of direct contact with nature can deteriorate several aspects of human wellbeing, and change knowledge and attitudes of people towards the environment. However, this phenomenon is still poorly understood in Megacities outside developed countries. Here, we explore the relationship between ecological knowledge and self-reported wellbeing in an important urban park in Santiago, Chile. We conducted semi-structured surveys to park users to explore their notions, preferences, ecological knowledge of plants and birds and self-reported wellbeing. Citizens associated urban parks mainly with “nature”, and particularly with the presence of trees and plants. Trees were recognized as the most relevant elements of urban parks, in turn, birds were ranked as the less relevant. Regarding ecological knowledge, respondents correctly identified an average of 2.01 plants and 2.44 birds out of a total of 10 for each taxon, and exotic species were more likely to be recognized. Park users also reported high scores for self-reported wellbeing. Interestingly, variance of self-reported wellbeing scores tended to increase at low levels of ecological knowledge of trees, but no significant relationship was detected with knowledge of birds, nor native species. These results suggest that parks can positively contribute to bring people closer to nature. Ecological knowledge was related to self-reported wellbeing. Improving ecological knowledge can be critical to restore the relationship between humans and nature in megacities.

An analysis of the current state of development in the agro-industrial complex (AIC) has established that freeze-drying is the most effective method for processing raw materials entering the drying stage. However, this drying method is hindered by the lack of modern, high-performance, energy-efficient drying technologies and equipment. The production of freeze-dried agricultural products will stimulate the development of AIC sectors. The implementation scheme of an automatic control system for a vacuum freeze-drying unit is considered, representing a promising and environmentally friendly direction in the processing of agricultural products. The drying equipment includes the following components and systems: a drying chamber, a cooling system, a vacuum pump, a control system, and a heating system. The product is placed on shelves in the drying chamber and frozen to a temperature that ensures the removal of 75-80% of the moisture contained in the product. The vacuum pump creates a pressure of 10-30 Pa and evacuates the spent air from the sublimator. Water vapor condensation occurs in the desublimator, and at the final stage of the drying process, the heating elements are activated to remove the remaining moisture. To validate the reliability of controlling the operating modes of the sublimator, experimental studies were conducted on the temperature dependence of the product on the surface and in the center over time. The graphs show temperature changes on the surface and in the center of the product throughout the drying process. The research results indicate that at a pressure of 20±5 Pa, the desublimator temperature should be below -20°C. The surface temperature of the product during the sublimation stage should be within the range of -25±5°C. Drying is completed when the chamber temperature reaches no more than 40°C, and the surface temperature of the product is around 30°C.

The convergence of Class Incremental Learning (CIL) and Machine Unlearning (MU) is a rapidly developing field in machine learning, especially relevant in adaptive and privacy-sensitive environments like finance. CIL enables models to learn new data classes over time without losing previously acquired knowledge, while MU focuses on selectively forgetting specific data to comply with privacy laws or mitigate security risks. In this paper, we examine the theoretical foundations and practical applications of both approaches, particularly in the financial domain. We explore how these two paradigms interact and complement each other, discuss key algorithms, and present examples to illustrate their applications in areas such as portfolio management, fraud detection, and data privacy. Finally, we explore challenges and potential future directions in achieving optimal synergy between CIL and MU.

Highly realistic media created through Artificial Intelligence and Deep Learning, commonly known as deepfakes, presents a serious risk to political stability and the integrity of information. We are entering an era where images and videos, which were once considered reliable evidence, are now being altered to spread false information and incite unrest. This threat is especially heightened in developing nations, where misinformation and manipulation of public sentiment could lead to the collapse of the fragile democracies. This study delves deep into the increased vulnerability of these regions to deepfakes due to slower technological advancement and widespread lack of awareness. This study provides a detailed analysis and sets the stage for future investigations, proposing a combined approach to counteract the consequences of deepfakes. This includes combining technical methods for detection of deepfakes with public awareness campaigns and legal frameworks. Reducing the harmful effects of deepfakes requires cooperation among a diverse group of experts.

The social fear conditioning (SFC) paradigm, which is an animal model of social anxiety disorder, has been extensively used to investigate the cellular and molecular mechanisms underlying the psychopathology of this disorder. Studies using the SFC paradigm have suggested that the lateral septum plays a pivotal role in regulating social fear. While several lines of evidence have indicated the involvement of various neuronal mechanisms within the LS in modulating social fear, the role played by LS astrocytes in the tripartite synapses in regulating social fear expression is not yet fully understood. Over the years, astrocytes have emerged as key players in regulating synaptic transmission and a plethora of animal behaviors. Given their dynamic morphological and molecular response to various stimuli, studying astrocyte morphology remains an excellent tool for understanding their role in brain function and disease. By applying immunofluorescent-immunohistochemical methods, here we describe a protocol to characterize changes in the morphology of astrocytes in response to social fear acquisition using confocal microscopy.

The paper presents two procedures for creating 3D discrete models of apple using the finite element method (FEM). The study focused on a new Polish apple variety, Chopin at development, ripening, and senescence maturity stages. The analysis of the results allowed for the determination that, depending on the desired outcomes, the parenchymal tissue can be considered as a material with either elastic or elastoplastic properties. Model validation was performed using displacement-force relationships and changes in contact area as a function of loading force obtained from compression tests. Elastoplastic models reflect empirical studies much better. The fit of the elastic models, based on force vs. displacement curves, ranged from 79% to 83%, while the fit of the elastoplastic models to empirical data ranged from 91% to 96%. Elastic models, on the other hand, are well-suited to the modified force vs. displacement curves, which reflect the elastic behavior of apples under compression test. Contour plots of pressures for elastoplastic models align much better with the test results than those for elastic models. 4. Similarly, in the case of contact area values, the elastoplastic models outperformed the elastic models, achieving a fit between 92% and 96%, while the elastic models reached only 82% to 83% compliance.

Deep Reinforcement Learning has achieved state-of-the-art results in the field of autonomous driving, especially in video game simulations. Trained agents were able to beat the best players achieving supremacy in the field. However, these agents often take in their neural network input the geometry of the track during the learning process. Our approach is to create a learning procedure for autonomous driving agents that is not environment-dependent by design to extend Deep Reinforcement Learning to racing games without racetrack information. Our work builds upon the notorious game Trackmania Nations United Forever, an open access 3D realistic Formula 1 simulation game that offers a high degree of customization. We use the Proximal Policy Optimization algorithm, using hybrid raw pixel data and physics sensors vectors as agent observations. The training track is a custom-made circuit carefully crafted from all available blocks in the game. The training track is considered like a standard dataset in machine learning and thus split in several segments in which the agent is randomly put into. We also created two regularization reward functions for the car’s speed and position to increase robustness of the agent in new scenarios.

Poor perinatal mental health can have significant and lasting impacts on a woman’s overall health and the well-being of her children and family. From conception, a baby's behavior, appearance, aversions, and interests can be influenced by the prenatal environment. Thus, the quality of prenatal care is crucial. Factors such as maternal stress, environmental conditions, cravings, mood swings, hormonal changes, and emotional experiences during pregnancy can profoundly affect the baby’s behavior once born. The baby's interaction with the external world begins from conception, not just at birth. For instance, maternal depression can negatively affect both the mental and physical health of the infant. Therefore, fostering a supportive environment for expectant mothers is essential for their health and that of their unborn child. Promoting the mother’s well-being through happiness and comfort is critical.This review paper aims to synthesize current research on maternal-fetal attachment during pregnancy, its evolution, and its postpartum effects on the mother-infant relationship. It will explore how these dynamics change over time, both during pregnancy and after delivery, to provide a comprehensive understanding of the factors influencing attachment and related outcomes. As Alan Soufre, a famous developmental psychologist would state, "Attachment would begin before birth. The mother’s emotional state can shape the child’s development trajectory long before the child is born."

This theoretical study presents a novel perspective on the potential anti-inflammatory properties of Bromelain, a natural agent extracted from pineapple stems. The investigation explores the binding capabilities of Bromelain to Apoptosis-associated speck-like containing CARD (ASC), a crucial adapter molecule known for its involvement in inflammatory processes and inflammasome formation. For the first time, these findings suggest that Bromelain exhibits a notable affinity for ASC, indicating its promising role as a natural anti-inflammatory agent. This study sheds light on the molecular interactions that may contribute to Bromelain's therapeutic potential in modulating inflammatory responses.

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

Timely screening for breast cancer plays a pivotal role in early detection and treatment; however, Afghan refugee females face significant barriers that hinder their access to these life-saving screening services. Cultural norms, socioeconomic factors, proficiency with the English language, and the challenges of navigating foreign healthcare systems contribute to low screening rates within this population. The current review article seeks to identify barriers to breast cancer screening in the Afghan refugee population in the United States (US) and address possible measures to overcome these challenges.

Recent developments in the quantization of general relativity theory provide a new perspective on matter and even the whole universe. Already in 1922, Eddington suggested that a future quantum gravity theory had to be linked to the Planck length. This is today the main view among many working with quantum gravity. Recently, it has been demonstrated how the Planck length, the Planck time can be extracted from gravity observations with no knowledge of G, ħ or even c. Rooted in this, both general relativity theory and multiple other gravity theories can be quantized and linked to the Planck scale. A revelation from this is that matter seems to be ticking at the reduced Compton frequency, where each tick can be seen as one bit, and one bit corresponds to a Planck mass event. This new way of looking at gravity also can tell us considerably about what quantum gravity computers are and what they potentially can do. We will claim that all quantum gravity and quantum gravity computers are directly linked to the Planck scale and the Compton frequency in matter, something we will discuss in this paper. Quantum gravity computers, we will see, in many ways are nature’s own designed computers with enormous capacity to 3D “print” real time. Basically, we live inside a gigantic quantum gravity computer known as the Hubble sphere, and we even are quantum gravity computers. The observable universe is basically a quantum gravity computer that calculates approximately 10^104 bits per second (bps).

Back-care knowledge and behaviour may play a vital role in preventing musculoskeletal current and future discomfort and injuries. The aim of the current survey was to explore the level of knowledge regarding ergonomics and posture together with postural behaviour and the incidence of musculoskeletal pain (MSP) in university students in the northeast of England. A mixed methods survey was conducted on a convenience sample of 55 university students. The 32-item valid and reliable questionnaire contains questions on socio-demographics, MSP, knowledge regarding ergonomics and posture (8 closed ended and 8 open-ended items) as well as postural behaviour. Nearly 1.8%, 20% and 78.2% of the university students had poor, fair and good knowledge of ergonomics and posture respectively. Among the 37 students who carried a backpack, 51.4% were found to have poor postural behaviour, 37.8% had fair behaviour and 10.8% had good postural behaviour. Of the 18 students who did not carry a backpack, 55.6% were found to have poor postural behaviour, 27.8% had fair behaviour and 16.6% had good postural behaviour. 70.9% of the students experienced MSP with the most prevalent site of pain being the lower back region. The key themes that emerged from qualitative data (8 open-ended questions) were: “Comfortable posture”, “Correct spinal alignment”, “Spine support”, “less pain and injuries”, “Use knees not the back”, “Keep the object close to body”, “Hands on desk”, “Feet flat on floor” as well as “eyes at screen level”. The findings of this study can be used to develop targeted interventions aimed at educating university students about ergonomics and posture in order to prevent the incidence of MSP. Future research in this field with a large and more representative sample of the university students’ population is strongly recommended to fully understand their knowledge of ergonomics and posture, postural behaviour as well as incidence of MSP.

Emerging molecular and computational techniques may allow construction and computational treatment of dynamic digital twins on the scale of populations to individuals. This approach may pave the way for predictive, preventive, and personalized treatment. Because digital twins are independent of geographical location, this may also contribute to global equitable health.

This article conducts a bibliometric analysis focusing on the influence of globalization and technology in the academic context. Previous studies have focused on analyzing the relationship between the number of research citations and international collaboration, but no study has explored it in the scope of consumer behavior and retail. Leveraging the Scopus database, the research analyzes a significant corpus of 2,111 documents from 1971 to 2022. The findings reveal a distinct surge in academic output related to the topic of technology, reflecting a growing interest in understanding the interaction between technological factors and consumer behavior. The study also explores trends in international collaboration in publications as well as its impact on citation counts.

Color image binarization plays a pivotal role in image preprocessing work, significantly impacting subsequent tasks, particularly in text recognition. This paper concentrates on Document Image Binarization (DIB), aiming to separate a image into foreground (text) and background (non-text content). Through a thorough analysis of conventional and deep learning-based approaches, we conclude that prevailing DIB methods leverage deep learning technology. Furthermore, we explore the receptive fields pre- and post-network training to underscore the Transformer model's advantages. Subsequently, we introduce a lightweight model based on the U-Net structure, enhanced with the Mobile ViT module to better capture global information features in document images. Given its adeptness at learning both local and global features, our proposed model exhibits superior performance on two standard datasets (DIBCO2012 and DIBCO2017) compared to state-of-the-art methods. Notably, our proposed DIB method presents a straightforward end-to-end model devoid of additional image preprocessing or post-processing. Moreover, its parameter count is less than a quarter of the HIP'23 model, which achives best results on three datasets(DIBCO2012, DIBCO2017 and DIBCO2018). Finally, two sets of ablation experiments were conducted to verify the effectiveness of the proposed binarization model.

India has pledged ambitious initiatives to mitigate its growing economies’ impact on the climate, including a goal of net zero emissions by 2070. The transportation sector is one of the key sources of emissions. Therefore, fostering e-mobility within this sector is a key priority for the Indian government. The lifecycle of LiBs raises numerous concerns regarding its sustainability in production, use of rare materials, and most importantly waste management. Furthermore, this paper will highlight the case for EV battery recycling as a growing sector that also has the potential to foster circularity in the EV sector. Through the introductory section, this paper lays out rationale for battery recycling in a circular EV economy. The subsequent sections discuss the current and emerging battery technologies and their link to recycling methods whilst overviewing domestic and foreign battery recycling companies. Finally, the paper concludes with a gap assessment of the battery recycling ecosystem in India and makes recommendations to further integrate this industry into the EV supply chain. As India steers towards a sustainable future, it is imperative that the country integrates battery recycling to enhance circularity in the EV ecosystem, closing the gap between a growing number of EVs and waste management.

This paper provides an overview of modelling and simulation methods for complex systems, including queuing and life support systems. To realize and capture every aspect of a system or situation, a model is used in place of the actual one. Using a model and simulation, we may create scenarios and make decisions. Computer experiments with the model can save costs, time, and effort once its validity has been shown. A model of the thing under study is created by computer simulation, which then runs the model on a digital computer and examines the results. It's interesting to note that a knowledge base of data includes information about predicted behaviour of the model as well as coordinated determination of external variables and parameters. Selecting the precise model creation technique is the first and most difficult task in simulation. A review of techniques used in simulation model execution (serial and parallel discrete-event simulation), simulation model analysis (calibration, validation, verification, goal-seeking), and conceptual, declarative, functional, constraint, and multimodal design are presented in this paper.

_{he present study was conducted to quantify the heavy metals cadmium, lead, copper, chromium, nickel, and zinc in the bivalve mollusk concha prieta (Anadara tuberculosa) using in- ductively coupled plasma optical emission spectroscopy (ICP-OES). This research aims to identify whether the bioaccumulate content of heavy metals exceeds the maximum limits established by various public health bodies such as the ONU, FAO, Codex Alimentarius, EEC, and NHI. Samples of the species were collected randomly from three locations in Puerto El Morro, Playas Municipal Market, and La Libertad Seafood Market in the Gulf of Guayaquil. Thirty-three soft tissue samples of (Anadara tuberculosa) were evaluated, and the values quantified in mg/kg were in the following order: Zn>Cu>Cd>Ni>Cr>Pb.}

This study focused on the investigation of myeloperoxidase through a Molecular Docking approach with various natural compounds to identify potential substances for cardiovascular research. Recent research has linked elevated myeloperoxidase levels to the severity of coronary artery disease. The results of the docking analysis revealed Polydatin, Daidzin, Astringin, Ginkgetin, and Amentoflavone as promising compounds with excellent binding capacity. To complement this, toxicity prediction studies were conducted using pkCSM. Overall, all four investigated molecules (Amentoflavone, Daidzin, Ginkgetin, and Astringin) were found to be non-toxic, exhibiting high maximum tolerated doses (human) and favorable values for Oral Rat Acute Toxicity and Oral Rat Chronic Toxicity. Moreover, they showed non-AMES toxicity and non-hepatotoxicity. Astringin, in particular, stood out with the highest positive effects, including a high maximum tolerated dose (human) and favorable values for Oral Rat Chronic Toxicity, along with dual inhibition of hERG II and hERG I. These findings suggest the potential utility of these compounds in cardiovascular research with minimized unwanted effects.

“Energy” is probably the most important term in science and technology. The reason is energy can be converted while it is overall conserved, and thereby correlates changes of a wide variety. Despite its successful use in many areas over more than a century, an analysis of current literature shows that definitions of what energy is and explanations why it is conserved are inconsistent. With regard to energy forms not even a definition was found, and examples given are often wrong. Looking at two interacting objects in the most simple situations, with energy conservation but without conversion, a consistent understanding of energy and its conservation can be derived. Based on it, the systematic set of energy forms with a clear definition of each is then presented.

Passive marine listening, involving the acoustic monitoring of underwater environments, has become increasingly vital for scientific research, environmental monitoring, and defense applications. However, the success of such applications critically depends on the ability to extract meaningful information from the often noisy and dynamic underwater acoustic environment. In this context, Mel-frequency cepstral coefficients (MFCCs) have emerged as an essential tool for feature extraction, capturing the spectral characteristics of marine sounds and making them ideal for species identification and sound event detection. This research presents an innovative approach to enhance the robustness of MFCC-based passive marine listening through adaptive noise reduction techniques. The proposed approach utilizes dynamic spectral subtraction to counter underwater noise, resulting in enhanced signal-to-noise ratios for desired sounds. This adaptive system adjusts to dynamic underwater noise, allowing it to concentrate on target sounds and suppress interference effectively. The experimentation further validates the effectiveness of the proposed approach, with results reaching 99% on the full dataset of 570 mammals and vessels, demonstrating the effectiveness of SVM and Random Forests in the classification of underwater audio.

This theoretical study presents a novel perspective on the potential anti-inflammatory properties of Bromelain, a natural agent extracted from pineapple stems. The investigation explores the binding capabilities of Bromelain to Apoptosis-associated speck-like containing CARD (ASC), a crucial adapter molecule known for its involvement in inflammatory processes and inflammasome formation. For the first time, these findings suggest that Bromelain exhibits a notable affinity for ASC, indicating its promising role as a natural anti-inflammatory agent. This study sheds light on the molecular interactions that may contribute to Bromelain's therapeutic potential in modulating inflammatory responses.

We use the Stefan-Boltzmann law to derive and investigate what we will call the black hole CMB temperature luminosity. Interestingly, the CMB luminosity is always the same for every black hole at a luminosity distance equal to the Schwarzschild radius, which is fully valid in black hole cosmology, a topic that is actively discussed to this day. The CMB black hole luminosity is always the same , regardless of the mass of the black hole. This is in contrast to the Bekenstein-Hawking luminosity, which is linked to the Hawking temperature, that is mass dependent.

Developmental stability (DS) is indicated by the ability of individuals to resist random environmental and/or genetic perturbations during their development. Fluctuating Asymmetry (FA) is the commonest mean of assessing DS in bilateral traits. FA is defined as small random deviations from an ideal morphological symmetry. To date, little attention has been paid to sexual differences in FA among tortoises. With this issue in mind, we assessed levels of carapace scutation symmetries in a sample of 45 wild adult red-footed tortoise, Chelonoidis carbonarius (13 males and 32 females) from Arauca plains, East Colombia. Procrustes ANOVA reflected statistically significative sex-related FA, with males tending to exhibit a more pronounced asymmetry. Although we cannot identify the potential sources responsible for detected developmental instability, our results suggest a high degree of stress and highlight that human intervention in Arauca are affecting wildlife. Similar studies in the future, correlated with an estimate of human impact, could provide irrefutable proof of causality between FA and environmental stressors. The results of this study can represent an estimate of the fitness status of the studied population at present.

The use of artificial intelligence technologies may help companies obtain the optimal use of resources and accomplish more activities with an increase in productivity by 40%. With access to real-time data and the ability to learn from patterns and behaviors, AI can perform these routine tasks more efficiently. Ambient intelligence, Ami, is one of the applications of artificial intelligence, which is called artificial environmental intelligence, which is a concept that focuses on using technology to create an environment that is intelligent and responsive to the needs of its users. This technology has the potential to revolutionize disaster response and management, which in turn facilitates access to necessary information and resources. necessary vitality in the event of a crisis. It may use ambient intelligence to create a network of sensors that can detect and respond to changes in the environment. So that this network can be used to monitor the environment for potential disasters, such as floods, fires and earthquakes. Sensors can also be used to detect changes in temperature, humidity, and other environmental factors that may indicate a potential disaster. This information can then be used to alert emergency responders and provide them with the information needed to respond quickly and effectively. Ambient intelligence can also be used to create a comprehensive database of resources and information that can be accessed in times of crisis. This database may include information about the location of shelters, medical facilities, and other resources that can be used to assist those affected by a disaster. It may also provide information about the condition of roads, bridges, and other infrastructure that may be affected by a disaster. This information can be used to inform response and management decisions, helping to ensure that resources are used in the most efficient way possible. Ambient intelligence can be used to create a communication platform between emergency responders and those affected by a disaster. This platform can also be used to provide updates on the emergency situation, in addition to providing information about available resources to those affected. This can help ensure that those affected by a disaster can access the resources they need in a timely manner.

The COVID-19 pandemic caused by the RNA virus SARS-CoV-2, has had a significant impact not only on bodily metabolism but also at the genomic level. This study utilizes a bibliometric approach to map and identify the relationship between COVID-19 and DNA damage, genomic instability, and cell cycle deregulation. The research began with the development of in-depth research questions and conducted two rounds of literature search in the Scopus database with stringent filters to ensure relevance and accuracy. From an initial 1098 documents, 576 relevant documents were selected for further analysis. The collected data was then visualized using bibliometric methods, enabling the identification of important patterns, trends, and relationships among the research variables. Key findings indicate that DNA damage, which can induce apoptosis, is the worst impact of the infection on cells. Term frequency analysis and science mapping revealed a close relationship between "DNA damage" and "apoptosis". Furthermore, discussions on genomic instability highlight telomere regulation issues, while cell cycle deregulation during virus replication in mammalian cells indicates the importance of maintaining cell membrane integrity.This study confirms the importance of bibliometric analysis in detecting and understanding the impact of COVID-19 at the genomic level, proposing several potential research targets and enhancing our understanding of the biological response to viral infection.

Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by a cell allows it to manage these costs and optimize their phenotypes. In fact, the management of resource constraints (e.g., nutrient availability, bioenergetic capacity, and macromolecular machinery production) shape activity and ultimately impact phenotype. In mammalian systems, quantification of resource allocation provides important insights into higher-order multicellular functions; it shapes intercellular interactions and relays environmental cues for tissues to coordinate individual cells to overcome resource constraints and achieve population-level behavior. Furthermore, these constraints, objectives, and phenotypes are context-dependent, with cells adapting their behavior according to their microenvironment, resulting in distinct steady-states. This review will highlight the biological insights gained from probing resource allocation in mammalian cells and tissues.

This paper studies the dividend optimization problem in the entropy regularization framework by following the same continuous-time reinforcement learning setting as in Wang et al. (2020). The exploratory HJB is established and the optimal exploratory dividend policy is a truncated exponential distribution. We show that, for suitable choices of the maximal dividend paying rate and the temperature parameter, the value function of the exploratory dividend optimization problem could be significantly different from the value function in the classical dividend optimization problem. In particular, the value function of the exploratory dividend optimization problem could be classified into three cases based on its monotonicity. Numerical examples are also presented to show the impact of temperature parameter on the solution.

Traditional photodynamic therapy (PDT) is often limited in its efficacy by insufficient light penetration, inefficient photosensitizer energy transfer, and inadequate target tissue oxygenation. X-ray activated PDT (XPDT), using nanoparticle (NPs) photosensitizers comprised of europium-doped yttrium oxide cores encased within silica shells (Y₂O₃:Eu@SiO₂), offers the potential of overcoming most of these limitations. Aimed at maximizing the generation of reactive oxygen species (ROS), this study reports methodologies for investigation of the effects of synthesis conditions on the characteristics of Y₂O₃:Eu@SiO₂ NP. Transmission electronic microscope (TEM) revealed that the NP core diameter was linearly, positively correlated with condensation time (R2 = 0.7357, p < 0.05) and linearly, negatively correlated with urea concentration (R2 = 0.958, p < 0.05). The addition of cetyltrimethylammonium bromide (CTAB) during core synthesis demonstrated enhanced particle dispersion. Silica coating via APTES-1 and TEOS-3 conditions resulted in Y₂O₃:Eu@SiO₂ NPs that generated the highest ROS, with 8.7-fold and 8.9-fold increase respectively in relative fluorescence intensity at 8 Gy irradiation compared to a 5.2-fold increase in PBS under the same condition. In vivo evaluation using 18F-fluorothymidine positron emission tomography (18F-FLT PET) of mouse xenografts of a human prototypical cancer (ovarian) revealed a 55% reduction in tumor proliferation of radiation-sensitive CAOV3 tumors treated with Y₂O₃:Eu@SiO₂ NPs compared to a 19% reduction in tumor proliferation of radiation-resistant SKOV3 tumors on the fourth day post-treatment. Taken together, these findings suggest Y₂O₃:Eu@SiO₂ NPs can serve as effective photosensitizers for XPDT and their performance characteristics can be optimized by selecting synthesis conditions and parameters to deliver the desirable therapeutic effects, offering novel approaches to circumventing many of the limitations of conventional PDT in the treatment of cancer.

Glial cells provide physical and chemical support and protection for neurons. Secreted neurotrophic factors, scaffolds and vesicles regulate in addition to normal homeostasis, repair following neural tissue injury or degeneration. We previously demonstrated that human CNS glia have revascularization capacity by inducing endothelial cell sprouting and microchanneling driven by glial cell secreted components. The clinical potential of using secreted factors and vesicles generated by glial cells in conditioned media was shown by their re-normalization of pathological blood vessels and 3D tissue wound healing and remodeling capacity. To identify secreted components of glial cells and how CNS and PNS glial cells differentially regulate neural tissue homeostasis, disease and injury response, we developed a novel culture method for various types of glial cells that allow for isolating and characterizing secreted glial components, free of animal factors and contaminants normally associated with serum-based culture conditions. Our culture method will enable to identify secreted components using ultrasensitive RNA, glycoconjugate and protein analysis technologies. The characterization of glial secreted factors involved microchanneling may help in development of new clinical therapies for glial and neural cells or axons to migrate and reform connections.

Lahpet-ye-hsain, known as a “tea shop” or teahouse, is where the people of Myanmar conduct their daily social activities besides its economic orientation. They are private establishments and informal gathering places serving tea and food at different times of the day for various clients. They can be small snacks, large open-aired, or covered restaurants with extensive menus. Patrons sit around small square tables on footstools. A diverse range of characters goes to tea shops. They have a reputation for welcoming people from all backgrounds and walks of life, but the role of women is hardly seen and unclear. They provide a space for men to share a cup of tea and food and exchange ideas, opinions, problems, hopes, and aspirations. They provide not only space but also to get ‘good taste and cheap food.’ A cup of tea at a tea shop is an opportunity to share knowledge amongst old and new friends. Such shops are abundant over the country. This paper examines the social, political, and economic role of these ubiquitous features of Myanmar society. The barriers to women's participation and inroads in some locales are discussed.

Obesity poses significant challenges in rural communities worldwide due to limited resources and healthcare access. Practical, innovative, and culturally sensitive approaches are essential. Time-Restricted Eating (TRE), aligning food intake with circadian rhythms, emerges as a promising strategy. By restricting eating to specific time windows, TRE synchronizes with the body's internal clock, offering potential metabolic health benefits. This review examines TRE's potential in rural obesity management, highlighting its simplicity and scalability. While TRE may address rural health disparities, cultural considerations and challenges such as undernutrition must be acknowledged for effective implementation. Overall, TRE shows promise in improving metabolic health and well-being in rural populations.

Rural women constitute one of the most marginalized and vulnerable groups in the world. Despite playing a critical role in sustainable development and food security, they face systemic inequalities and structural constraints that limit their access to resources, services and opportunities. The purpose of this research is to identify advances and setbacks in the formulation of 17 SDG indicators for rural women. Systematic Review Registered in PROSPERO: CRD42023420583. Sixteen articles were included. Three indicators were identified: entrepreneurship, empowerment and gender equality. Due to its relevance in rural areas where women have an active role in family income through cooperatives, associations and companies to improve quality of life and that of their community, however, aspects of discrimination are still evident in gender and inequality in participation in economic spheres and decision making.

Breast cancer remains one of the most deadly non-communicable diseases in the world. The incidence of breast cancer in South Africa is increasing, with rural African women presenting with advanced stages of the disease. In this study, we aim to explore sociocultural factors influencing breast cancer screening practices among rural African women. A qualitative exploratory study was conducted using semi-structured interviews with 22 rural African women selected by purposive sampling. Thematic analysis was used to analyze the data. In this study, four sociocultural factors were identified as influencing breast cancer screening practices among rural African women. These factors included psychological factors, habits, beliefs, and healthcare perception. Women in rural African communities have deep-rooted traditional beliefs and practices regarding breast cancer. Consequently, this influences women's preventative health behaviours regarding breast cancer screening. To increase the number of women participating in breast cancer screenings, it is vital to develop culturally sensitive health education programs. Engaging community healers will also help to increase the number of women participating in breast cancer screening.

The importance of agricultural programs in reducing poverty, improving livelihoods, and increasing productivity cannot be overstated. Poverty and unemployment remain the most pressing developmental concerns in rural communities of Africa in general and South Africa in particular. The study was derived from the contribution of the agricultural development programs and sought to discover how the Fortune 40 initiative impacted rural livelihoods of youth in Bushbuckridge Local Municipality. Primary data using cross-sectional research design was collected from beneficiaries of the Fortune 40 program, through use of a questionnaire. An ordered probit model was used to analyse the impact of Fortune 40 initiative to rural livelihoods. Empirical results revealed that age of beneficiaries, household size, type of farming, credit access and land size were the factors with the likelihood to influence the impact of the Fortune 40 program. Therefore, it can be concluded that the land size for production should increase or expanded to enhance production of vegetables; provision of credit facilities for youths in agriculture through micro-finance and rural commercial banks is essential; also, youth, such as agricultural graduates looking for practical experience and on-farm training, should be considered in the program.

Children from rural areas face numerous possibilities for neurodevelopmental conditions that may compromise their well-being and optimal development. Neuropsychology and electroencephalography (EEG) have shown strong agreement in detecting correlations between these two variables and suggest an association with specific environmental and social risk factors. The present meta-analysis aims to integrate the qualitative and quantitative EEG findings, their relationship with cognitive impairment in children living in vulnerable or rural environments, and the main risk factors influencing EEG abnormalities. The method for this purpose was based on a systematic string-based review from Ebscohost and Web of Science, following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). Qualitative and quantitative analyses were conducted from the outcomes that complied with the selected criteria. A total of 92 records were identified; however, only 20 were eligible, considering 11 for qualitative and 9 for quantitative analysis. The findings highlight a significant amount of literature on EEG and its relation with cognitive impairment from studies in children with epilepsy and malnutrition. In general, there is evidence about the advantages of implementing EEG diagnosis and research techniques in children living under risk conditions. Further research is needed to better describe and integrate the state of the art regarding EEG features extraction.

Rural women in developing nations are especially vulnerable to higher health risks due to environmental pollution exposure and are more likely to experience poorer health outcomes. Using data from the 2013 China General Social Survey CGSS2013, this study empirically examined the relationship among environmental knowledge (EK), pollution, health investment, and health status of women residing in rural regions in China. We employed a nationally representative sample of 1,930 female individuals for our analysis. Our results showed that the level of EK for women in rural China significantly impacted their self-reported physical and mental health. In order to account for potential endogeneity due to mutual causality, this study employed television usage and network usage as two instrument variables (IVs) of EK. We performed an IV-probit method to correct the estimated errors due to endogeneity. Additionally, to assess the reliability and robustness of our results, we re-estimated our model by replacing health status with the variable Body Mass Index (BMI). The results were consistent, providing evidence of robustness. Additionally, we examined the relationship between health investment (holding and purchasing a public health insurance policy, engaging in frequent physical activity, and acquiring commercial insurance) and health status. Our results indicate that the level of EK had no significant impact on participating in the new rural cooperative medical system. However, the preference of purchasing commercial insurance was positively impacted by EK, though it does not have a direct impact on the health condition. Conversely, an increase in EK and pollution is associated with a greater likelihood of engaging in physical exercise, which could, in turn, improve overall mental health.

In European countries many measures are carried out to improve the disadvantaged conditions and socio-economic marginality of rural areas in comparison with central places. These conditions also affect the quality of travel for visitors and tourists. Therefore, in response to a 'new' tourist demand, motivated also by the restrictions following the spread of the Covid-19 virus in recent years, the institutions and the different local actors are working more incisively to improve rural areas. The rural tourism services offer, combined with the Green Infrastructure (GI) project, at different scales - from local to regional - prove to be interesting territorial development strategies to achieve the Agenda 2030 objectives. This contribution considers the Sulcis Iglesiente - Guspinese area, in the Sardinia Region (IT), as a case study. In this area, the landscape context is marked by past mining activity and the project of a path of historical, cultural and religious values has proved to be an activator of regenerative processes, in environmental, social and economic terms. The present study proposes a methodological approach to develop an index (FI - Feasibility Index) to assess the feasibility of the Stop Places (SPs) schemes along a horse trail to integrate the current slow mobility by bicycle and pedestrian in the bioregion.

Traditional Health Practitioners (THPs) are considered as the entry level of care in African societies and play an important role in the delivery of health services to the population. A phenomenological qualitative study was carried out among pur-posefully selected THPs in Mthatha to understand their roles and the challenges they face in providing maternal health services. The study included a focus group discussion with seven participants, which yielded three themes and seven sub-themes. The content analysis of descriptive data from the focus group discussion revealed threats posed by unregistered and counterfeit THPs to the lives of pregnant women in rural settings. THPs' wide range of services allowed pregnant women to receive prenatal, antenatal, and postnatal care in close proximity. This level of care, however, was characterized by high levels of secrecy and counterfeit practitioners who used human body parts, which jeopardized the practice and made it unpopular. Traditional health practice must be protected through registration of THPs and the establishment of functional referral pathways between THPs and conventional health services.

Freshwater pond aquaculture is the prevailing fish culture system worldwide, especially in developing countries. Climate change outcomes and inadequate environmental practices challenge its sustainability. This study applies emergy synthesis to assess the environmental performance of freshwater pond aquaculture in Brazil, aiming to identify and propose practices towards sustainability. As a study model, nine semi-intensive lambari farms operating at three levels of management were evaluated: low (LC), moderate (MC) and high (HC) control. Results showed that the main inputs for LC were services (27-46%), feed (7-39%), and water (15-21%), while for the MC and HC farms, they were feed (35-49% and 17-48%, respectively) and services (33-39% and 26-36%, respectively). All farms required more than 60% of their emergy from purchased inputs, resulting in low emergy sustainability index (ESI = 0.1-0.5). Replacing animal protein and oil on diet composition by vegetal sources, using superficial water instead of springwater, increasing juvenile productivity, and controlling pond fertilization can lead all systems to higher efficiency and resilience, increasing sustainability.

The smoke house works as a tourism model that will directly impact women living across Quintana Roo communities and small towns, with the idea that this project will empower them, and provide them with a more dignified income, with the end goal to reduce the poverty rates in the state Likewise, to introduce an adequate formula of cuisine that promotes the regional gastronomic identity, since this typology of cultural heritage is linked to the experience of enjoying the state's native food. (Carrillo, J. and Vazquez, L., 2018) It should be noted that the main representatives and transmitters of gastronomy are women, usually housewives. Therefore, a methodology based on the qualitative approach was designed, taking as a basis the ethnographic method, which allows understanding the behavioral patterns of a society. In the first instance, a gastronomic laboratory is proposed for the university, which will later be used as a business model within the tourism industry, directed at people who seek to enjoy cultural and ex-periential tourism. And at the same time, it will benefit communities across the state by generating more income for them. In addition, the project of model smoke kitchen is oriented to go in accordance with the 2030 agenda. Which includes 17 objectives and 169 goals; six of those objectives are directly aligned with this project, and the rest can be observed to relate it in a more indirectly manner. In the same way, a summary of the results obtained by the five-year groundwork is presented, as well as the division of the gastronomy in the state according to the characteristics that conform the gastronomic region.

Rural tourism has been proved as an effective approach in many rural areas in China, and during the development processes, local institutions play significant roles in the context of China. This paper is to explore various roles of local institutions in the development of rural tourism in a typical community, Dazhai, in Guilin City. Within its limitations, it examines the roles by identifying the current situations of the community, formal and informal institutions that affect the rural tourism development.Obstacles still exist because of the “top-bottom”political system.

The paper comes from the need to search for criteria useful for the valorization of heritage towns, located in rural and/or inland areas of Italy, now affected to depression and depopulation process. To this end, the authors point out how territorial identity can constitute the theoretical foundation to influence the development policies and, in particular, the tourism development for sustainability process It was therefore decided to interview a number of stakeholders who could contribute with their professionalism and expertise to identify possible paths and processes for the enhancement of these areas for tourism development. The methodology was based on be to be interviews with open questions, which allowed to identify a SWOT analysis, offering a guideline for a correct governance of these rural areas for their tourist enhancement, in terms of sustainability of development and tourist attractiveness. The study is an observatory that will monitor the implementation of sustainable tourism enhancement of the borghi, heritage town

We seek to elucidate an aspirational vision for the food system and explore whether the characteristics of such a system inadvertently set unattainable standards for rural, low wealth communities. We apply discourse analysis to the following qualitative datasets: (1) interviews with food experts and advocates, (2) scholarly and grey literature, (3) industry websites, and (4) email exchanges between food advocates. The analysis revealed eight aspirational food system discourses: Production, Distribution, and Infrastructure; Healthy, Organic, Local Food; Behavioral Health and Education; Sustainability; Finance and Investment; Huger Relief; Demand Side Preferences; Romanticized, Community Led Transformations. Study findings reveal that of eight discourses only three encompass the experiences of rural, low wealth residents. This aspirational food system may result in the disempowerment of the needs of rural, low wealth groups; a perpetuation of the failure of groups who will be unable to reach the aspirational food vision; silencing of discourses that might question those that play a role in the inequitable distribution of income while sanctioning discourses that focus on personal or community solutions; and the absence of other policy-based solutions that address issues located within the food system. Further research is needed to inform policies and programs to mitigate food insecurity in rural, low wealth populations.

Over the past few decades, there have been major advances in crop productivity across the world, which has been made possible through a combination of productivity enhancing technological innovations. Beyond this achievement however, most parts of Africa are still battling with low crop productivity resulting in food shortages and food insecurity. The yields of many staple crops are still far below their agronomic potentials with output increases being attributed largely to area expansion. This paper examines the implications of the current trends of crop/plant productivity for food security and rural livelihood development in Africa using Ghana as a case study. The paper argues that crop production in Africa is becoming a less viable and unattractive livelihood activity with farmers diversifying out of agriculture into non-agricultural activities such as illegal small-scale mining, which have negative consequences on the ability of African countries to attain the Sustainable Development Goals (SDGs).

The Brazilian economy, the rural in particular, was until the end of the 19th century based on slave labour. In this research, it was intended to obtain, through a review of historical descriptive studies, a detailed picture of the occupational hygiene conditions related to the slaves’ work and their interactions with climatic and environmental conditions. The search was done in the following databases: Science Direct, Scopus, Web of Science, Criminal Justice, Ebsco, Business Source Supplement, as well as original historical documents. Descriptive studies, without the restriction of language, were selected that involved the rural work of slaves in colonial and imperial Brazil. Working environmental conditions have been evaluated: environmental and occupational hygiene conditions to which the captive workers were exposed, as well as their accommodation and clothing. The analysed studies registered the existence of accommodation and similar dresses all over Brazil, regardless of the region's climate. In addition to these accommodation conditions, slaves were still exposed in a similar way to physical, chemical and biological agents throughout the country. Finally, it was also possible to identify a clear similarity with the occupational exposure conditions of the modern slaves in the 21^st century.

Biodiversity conservation is a key factor in meeting sustainable development goals. This is even more important in cities, where green spaces are becoming increasingly scarce. This study analyzes the Kinshasa's proliferating ornamental plant nurseries, known as informal horticultural sites (IHS). The analysis focused on characterizing the profile of horticulturists, their production conditions and the ornamental species produced. Fifteen IHSs were sampled using the "snowball" technique, and 178 horticulturists were surveyed. Based on the socio-professional profile of the horticulturists, five groups of IHS are distinguished after a hierarchical classification on principal components. We found that IHSs exclusively employed men, most of whom were new to the trade, from all levels of education, and most of whom ranged from 19 to 45 years old. Production conditions are relatively similar from one site to another. However, all IHS are characterized by permanent land insecurity, the use of phytosanitary products, plant conditioning methods that are not very diversified and calibrated to growers' investment capacities, and diversified seed acquisition methods. A total of 139 ornamental species, most of them exotic, were identified. Of these, 37% are phanerophytes and 24% are considered potentially invasive. We suggest ways of professionalizing the activity and protecting the urban environment.

Urban green spaces provide a range of environmental and health benefits, which may become even more critical during times of crisis such as the current COVID-19 pandemic. However, with a radical shift in mobility, additional concerns over safety, and access temporarily restricted during the implementation of social distancing policies, the experience and use of urban green spaces may be reduced. This is particularly concerning for densely populated cities like New York, considered the first U.S. epicenter or vanguard of the outbreak. To better understand the impact of COVID-19 on the perception and use of urban green spaces, we conducted a social survey during the early months of the Covid-19 pandemic in New York City (May 13 - June 15, 2020). The results of the survey show respondents continued to use urban green spaces during the pandemic and consider them to be more important for mental and physical health than before the pandemic began. However, the study revealed a pattern of concerns residents have about green space accessibility and safety, and found key differences between the concerns and needs of different populations, suggesting a crucial role for inclusive decision-making, support for additional management strategies, and urban ecosystem governance that reflect the differential values, needs and concerns of communities across the City. As urban centers face looming budget cuts and reduced capacity, this study provides some empirical evidence to illustrate the value of urban green spaces as critical urban infrastructure, and may have implications for funding, policy, and management, of urban green spaces in NYC, with potential applications to other cities, particularly during times of crisis.

The paper in question explores the connection between green areas and urban well-being in an effort to give readers a comprehensive grasp of the topic. The major goals of this study are to evaluate how green spaces affect urban residents' physical and mental health, sense of community, and general quality of life. This research presents numerous major conclusions through a thorough investigation of the current literature and empirical analysis of urban environments across various areas. First of all, it shows that being close to green spaces is associated with better physical health, including a decline in obesity and cardiovascular disease rates. Second, green areas are linked to better mental health, with residents of greener neighbourhoods reporting reduced levels of stress, anxiety, and sadness. However, neighbourhoods having green open grass areas have greater levels of social interaction, and cohesion, which encourages residents to feel a sense of belonging. Lastly, this study highlights the positive impact of green spaces on overall urban quality of life, as they contribute to cleaner air, lower noise pollution, and increased property values. The implications of these findings are significant for urban planning and policy development. They underscore the importance of prioritizing green spaces in urban design, as investments in such areas not only promote physical and mental health but also enhance social bonds and elevate the overall liveability of cities. This research provides a foundation for evidence-based decision-making in urban development to create healthier, more vibrant, and sustainable urban environments.

Central Asian countries are the core area of the Belt and Road Initiative (BRI). However, as part of the former Soviet Union, we know very little about the urbanization processes in these countries after the collapse of the Soviet Union. Here, were used land-cover type data, vegetation index data, and grided population data to quantify the urban expansion, urban population changes, and urban environment changes across cities in Central Asia from 2000 to 2020, and took Xinjiang, China as a reference. We found that the urbanization in the study area was uneven. Specifically, the urban expansion in Xinjiang, China and Kazakhstan was faster than in the other countries in the study area. Due to rapid urban expansion, the urban population density in Xinjiang, China decreased from 2000 to 2020, but rapid urban population growth was maintained. Consequently, the pressure of the urban population growth in Xinjiang, China was less than that in the other countries of Central Asia. On average, more than 35% of the urban built-up areas underwent significant greening in Xinjiang, China and more than 3.63 million residents directly benefited from the increase in urban greenness. Although the urban greenness in Xinjiang increased significantly, the overall greenness was still lower than in most cities in Central Asia. In the future, the cities in Xinjiang, China should continue to promote the construction of urban ecological civilization and strengthen their role as a link in the Belt and Road Initiative.

In the quest for more sustainable urban landscape development, the concept of ‘green infrastructure’ (GI) has become central in policy documents and as a multifunctional general planning tool. GI is not however a simple and unambiguous solution. While there in policy documents are claims for more and connected GI, actual urban development takes another direction. The densifying imperative is hard to combine with an increased and more connected GI. This paper argues for a critical and diversified approach to the concept of GI, to facilitate its implementation in urban planning and management. While GI most often is seen as a common asset and a public good, the actual land use negotiations and management responsibilities cannot be limited to a public service discourse, but should address more clearly a variety of actors. Linguistic as well as spatial definitions of the two relevant dichotomies of ‘green-grey’ and ‘public-private’ are crucial in GI location, design, construction and management, it is argued. Overarching representations of GI will be needed, but also – and linked to it – a spatial storm water plan and an overall plan for public space. The development over time will need an intersectorial implementation and management program. Thus some of the GI intentions may be implemented in planning processes, some through reorganisation and redesign of public space, and some by agreements with landowners.

Approximate unlearning is an emerging field in machine learning that addresses the challenge of efficiently removing specific data points from models without the need for full retraining. In the financial sector, where models are built on sensitive customer data and market information, the ability to unlearn data is crucial for meeting privacy regulations like GDPR and ensuring model adaptability in real-time environments. This paper explores the categorization of approximate unlearning into two main approaches: data-driven approximation and model-driven approximation. Data-driven approximation focuses on selectively retraining parts of the dataset to simulate the removal of data, while model-driven approximation adjusts the model’s internal parameters to nullify the influence of unwanted data points. Both methods offer computational and memory-efficient ways to balance the need for privacy compliance with the performance demands of financial models. The paper discusses practical applications in algorithmic trading, fraud detection, and risk assessment, and highlights the challenges associated with each approach. Through case studies and literature references, we demonstrate how approximate unlearning can be applied to maintain system efficiency, data privacy, and regulatory compliance in the financial domain. This research provides a roadmap for future developments in approximate unlearning, particularly in the context of real-time financial systems and federated learning environments.

Background/Objectives: Managing chronic respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD) within the Spanish Sistema Nacional de Salud (SNS) presents significant challenges, particularly due to their high prevalence and poor disease control rates—approximately 45.1% for asthma and 63.2% for COPD. This study aims to develop a novel predictive model using Electronic Health Records (EHR) to estimate the likelihood of poor disease control in these patients, thereby enabling more efficient management in primary care settings. Methods: The Seleida project employed a bioinformatics approach to identify significant clinical variables from EHR data in primary care centers in Seville and Valencia. Statistically significant variables were incorporated into a logistic regression model to predict poor disease control in patients with asthma and COPD patients. Key variables included the number of short-acting β-agonist (SABA) and short-acting muscarinic antagonist (SAMA) canisters, prednisone courses, and antibiotic courses over the past year. Results: The developed model demonstrated high accuracy, sensitivity, and specificity in predicting poorly controlled disease in both asthma and COPD patients. These findings suggest that the model could serve as a valuable tool for the early identification of at-risk patients, allowing healthcare providers to prioritize and optimize resource allocation in primary care settings. Conclusions: Integrating this predictive model into primary care practice could enhance the proactive management of asthma and COPD, potentially improving patient outcomes and reducing the burden on healthcare systems. Further validation in diverse clinical settings is warranted to confirm the model's efficacy and generalizability.

Asthma is a chronic respiratory disease characterized by hyperreactivity in the airways, which can lead to significant lung damage if not properly managed. While placebos—medications with no active therapeutic ingredients—are sometimes used in clinical trials to gauge the effectiveness of asthma treatments, their long-term use raises concerns. Placebos work primarily through psychological mechanisms by enhancing patients’ expectations of treatment. However, prolonged reliance on placebo treatment in asthma could potentially mask symptoms, delay proper management, and lead to undetected lung damage or other adverse effects. This study explores the potential risks and consequences associated with long-term placebo use in asthma management.

Most available studies on the mechanical properties of apples lack the comprehensive results needed for the construction and validation of FEM models. Researchers typically focus on either the flesh and epidermis or the whole fruit, often overlooking the maturity stage of the examined apples. They usually report only firmness or the starch index as indicators of maturity. Furthermore, many studies use store-bought apples, which is impractical for industrial applications since this fruit have already undergone various treatments before reaching the shelf. This article aims to determine the mechanical properties of apples necessary for constructing FEM models that are both adequate and useful for the industry. The new Polish apple variety, Chopin, was selected as the research material. The study was conducted for three stages of apple maturity: development, ripening, and senescence. Mechanical properties of the flesh and skin were determined as material data for FEM models. Force-displacement curves and pressure-force functions were examined for future model validation. Using micro-computed tomography, the bruise volumes of fruit subjected to 20%, 50%, and 80% of the destructive force were determined. Significant differences were found between apples in the senescence stage and those in the development and ripening stages. Results of Micro-Ct and the results of modified and real compression tests of whole fruit have allowed us to formulate the research hypothesis regarding the influence of flesh cracking (characterized by local drops of force), influencing the bruise visibility and detection.

Autonomous underwater vehicles are not easily programmable such as autonomous vehicles. This is because route and motion planning for autonomous vehicles depend on a global map that considers the road's smoothness and traffic regulations in real time. However, this is not the case for underwater vehicles as we have to consider the external factors such as wind and tide that may pull autonomous underwater vehicles outside their route and affect the course of travel. This is where decision-making is important for autonomous underwater vehicles. An example is the avoidance of the loss of subsea vehicles as they can dynamically make routing decisions and return to their destinations.This paper exposes the decision-making process for autonomous underwater vehicles. Firstly, an analysis of internal factors such as buoyancy and the overall of the vehicle, and how they affect motion are conducted—secondly, the implementation of a design process that deals with the stages of motion and route planning. Finally, a survey is conducted on already implemented research for algorithms, to incorporate external factors for high-level decision-making.

Background and Aim: Patients with Type 2-diabetes condition tend to have multiple medications in various dosage which leads to complex medication regimens. Complexity of regimen results in poor adherence, uncontrolled glycemic value and treatment failure. The research aimed to investigate medication regimen complexity index, medication adherence, and impact of medication regimen complexity on glycemic control and medication adherence.Materials and Methods: A Crossectional Study methods was conducted at Bheri Hospital Nepalgunj, among 145 Diabetes patients. Medication adherence was assessed by using a General Medication Adherence Scale (GMAS Nep-Tool). Medication regimen complexity was assessed by using a Medication Regimen Complexity Index (MRCI) tool. Chi-square test, One-way ANOVA, Paired t-test, and binary logistic regression were used for inferential statistics. Results: This study shows that most of the participants were female and aged group 50-59 years. Hypertension was the most common comorbidity, followed by hypothyroidism. The majority of participants exhibited partial adherence 90 (62.1%) to their medication regimen. It was seen that medications prescribed for diabetes were more complex than non-diabetes medications (Mean±SD MRCI: 8.28±3.155 vs. 4.57±2.107). The negative correlation was seen with diabetes MRCI and medication adherence (r=-0.090). There was statistically significant association between diabetes MRCI and glycemic control, (p<0.05). Binary logistic regression revealed that females had lower odds of high MRCI compared to males ( multivariate p-value: 0.014, AOR: 0.403, 95% CI: 0.195-0.832), while sedentary lifestyle showed high Diabetes MRCI (COR: 4.709, 95% CI: 0.962-23.05) and abnormal BMI were associated with higher MRCI (binary p-value: 0.067, COR: 2.30, 95% CI: 0.942-5.65; multivariate p-value: 0.092, AOR: 2.323, 95% CI: 0.878-5.67). Conclusion: Diabetes medications are more complex, reducing adherence and worsening A1C outcomes. Simplifying regimens improves results, with MRCI being valuable for healthcare providers. The medication adherence and therapeutic outcomes can be improved by the improved by the involvement of clinical pharmacist using MRCI.

Detecting and evaluating pain in people with cognitive impairment, especially dementia, is a challenge. Their ability to accurately report pain and comprehend related questions decreases the reliability of their self-report. This has contributed to the fact that pain is underdiagnosed and undertreated in this population, which can lead to involuntary ageism. The design and assessment of this training capsule under the context of the European COST-Action TD1005 responds to the need for education and training in "Pain Assessment In Cognitive Impairment, especially dementia" and the development of the internationally agreed observational PAIC15 scale. The 3-hour capsule, intended for healthcare workers and caregivers, consists of theoretical-practical levels: 1) basic concepts and challenges in pain in aging, cognitive impairment/dementia, 2) available scales and PAIC15, 3) video presentation of clinical cases illustrating a 3×2 matrix of situations (rest, transfer and experimental pain) and stages of disease (mild and moderate). The objectives focused on training the ability to observe, detect, and assess the signs of pain using PAIC15 and its feasibility. The pre-post analysis in a Master educational setting showed agreement with the results obtained in the Spanish national survey on 1) scarce knowledge of observational tools and their use, and 2) uncertainty in the identification of signs of pain and feasibility in moderate/severe scenarios. The capsule improved the ability to identify and evaluate the pain items, especially facial expressions, and their confidence on observational tools. Debriefings highlighted the relevance of observational scales in dementia and the gain obtained using the new observational instrument.

This article comprehensively explores multiple aspects of cryptocurrencies and their price forecasting. Firstly, the article introduces the definition of cryptocurrency and its development process on a global scale, especially focusing on the launch of Facebook Libra and China's central bank digital currency, highlighting the importance and influence of digital currency in the global financial market. Subsequently, the article analyzes the advantages of digital currencies over traditional currencies, including improving economic transaction efficiency, reducing transaction costs and enhancing transaction transparency. Meanwhile, the article also explores the challenges and risks potentially brought by the development of digital currencies, such as regulatory uncertainty and market volatility. In this context, the article raises the importance of cryptocurrency price forecasting and introduces the forecasting models and techniques commonly used today. Finally, through specific experimental analysis, the effectiveness of using the deep learning model CNN-LSTM to predict the price of Bitcoin is demonstrated, and the directions of future research and optimization strategy are proposed. In summary, this paper comprehensively presents the research status and prospects of cryptocurrency and its price prediction field through systematic introduction and analysis.

In today's highly digitized and globalized financial environment, the need to protect payment systems from risk is more urgent than ever. Artificial intelligence (AI) technology is rapidly becoming a key tool in this space, with machine learning algorithms, big data analytics, and real-time monitoring enabling AI to effectively detect and prevent fraudulent activity, optimize risk management processes, and deliver intelligent services. AI not only improves the security and efficiency of payment systems, but also significantly improves customer satisfaction and loyalty. With the continuous development of AI technology and financial payment technology, the financial payment industry will usher in more innovations and changes in the future, further optimizing the payment process, improving payment efficiency, and ensuring payment security.

Teledermatology, the dermatological consultation and diagnosis via digital communication technologies, has become increasingly important in modern healthcare. The integration of teledermatology into clinical practice has gained significant interest, especially during the COVID-19 pandemic. Numerous studies have shown the effectiveness and reliability of teledermatology, with high levels of patient satisfaction and diagnostic accuracy. Pathpoint® eDerma is a cloud-based dermatology platform that aims to streamline the documentation and management of dermatological conditions. It offers several clinical benefits, including faster diagnosis, reduced unnecessary procedures, improved access to care, and cost savings. The platform follows a comprehensive risk management plan and complies with safety regulations. It undergoes regular recertification and reviews to ensure its safety and effectiveness. The clinical evaluation of eDerma confirms its ability to deliver significant clinical benefits while effectively mitigating risks. The benefit-risk ratio of eDerma is highly acceptable, supporting its use in clinical settings to enhance dermatological care.

As the global population faces an increasing prevalence of physical disabilities, the challenge of motor rehabilitation has become increasingly urgent. Considering that approximately 15% of the global population lives with some form of disability, with a significant number having motor disa-bilities that greatly impact their quality of life, the integration of robotic technologies into rehabili-tation processes offers an opportunity for significant improvement in functional recovery and pa-tient autonomy. This analysis aims to evaluate the progress and challenges encountered in imple-menting robotic technology for the rehabilitation of patients with physical disabilities, highlighting the potential of emerging technologies such as exoskeletons, assisted training devices, and brain-computer interface systems in facilitating motor recovery. By examining relevant clinical studies, the analysis demonstrates the varied effectiveness of robotic therapies compared to traditional re-habilitation methods, while also highlighting the need for ongoing research to optimize care prac-tices and address challenges related to cost, accessibility, and treatment personalization. In con-clusion, robotic technologies represent a promising direction in motor rehabilitation, with the po-tential to revolutionize the care of patients with physical disabilities, significantly improving quali-ty of life and social integration.

This article explores the application of machine learning techniques, specifically focusing on ensemble methods like Random Forests, for detecting fraudulent activities in digital financial transactions. Highlighting the evolution from traditional statistical approaches to modern machine learning models, it underscores the effectiveness of Random Forests in handling the inherent challenges of imbalanced datasets typical in fraud detection scenarios. Using a Kaggle dataset of credit card transactions, the study optimizes Random Forest parameters through rigorous parameter tuning, achieving significant improvements in model performance metrics such as Area Under the Curve (AUC). The findings underscore the critical role of machine learning in enhancing fraud detection capabilities, emphasizing the ongoing evolution and future potential of these methodologies in financial risk management.

In recent years, the treatment of locally-advanced rectal cancer (LARC) has been spotlighted in a number of landmark, practice-changing trials, heralding in the age of so-termed “total neoadjuvant therapy” (TNT). However, the lack of a common control arm, standard inclusion criteria, or, indeed, definition of TNT necessitates further study in this field, particularly using real-world data. We conducted a retrospective analysis of all patients treated for LARC at a single Canadian academic cancer centre between July 1st 2019 and July 14th 2022. This includes the June 2020 incorporation of TNT. 290 patients were included in the final analysis, and 124 variables were collected on each patient, including demographics, treatment type, adverse events, response to treatment, surgery versus watchful waiting and survival. Our findings demonstrate that both TNT and non-TNT regimens are highly toxic, with regards to both overall toxicity and grade 2+ adverse effects. 62 (96.9%) of patients on TNT experienced toxicities, compared to 186 (82.3%) of the non-TNT patients. Grade 2+ toxicities were 46 (71.9%) and 143 (63.3%), respectively. TNT, however, was associated with improved rates of complete response, compared to non-TNT treatment regimens (44% vs 24%). These findings suggest that TNT harbours both benefit and risk in a real-world population, and both of these aspects should be considered when deciding on a treatment approach for an individual patient. More work in the area is needed to determine longer term survival, as well as impact of surgery versus organ preservation approach on patient outcomes.

A microwave technique prepared a superabsorbent polymer (SAP) by grafting two hydrophilic monomers onto a polysaccharide substrate. The monomers used are acrylic acid (AA) or acrylamide (AM) to graft onto a pullulan substrate (PUL) to form PUL-g- AA (SAP1) and PUL-g- AM (SAP2), respectively. The monomers (AM/AA) graft together onto a PUL substrate to form PUL-g-(AM/AA) (SAP3). Grafting parameters such as grafting efficiency with percentage, conversion of monomer to polymer, gel content, water retention, water adsorption capacity, and swelling kinetics were determined. Additionally, the effect of environmental pH (2, 4, 7, 9, and 12) and sodium dodecylbenzene sulfonate (SDBS) surfactant was evaluated, where SDBS was added by 1,2,3,4 and 5 mM to form (SAP4 to SAP8). FTIR results show that AM grafted on PUL through an aliphatic C-N bond, while AA grafting occurred through a single C-C bond. The grafting efficiency with AM is higher than with AA, as well as their gel contents. Water absorbance capacity increased with grafting of AA or AM separately, and water retention was enhanced. The highest absorbent capacity, water retention, gel content, and grafting parameters values were obtained with 3 mM SDBS content and pH7. The swelling kinetics showed that the increases in the theoretical and experimental swelling equilibriums were 72 % and 82%, respectively, at SAP6 compared to the values of these parameters in SAP3. The water absorption capacity of the hydrogel increases with increasing pH to 7 and then gradually decreases. XRD improves the crystallinity and crystalline size of the hydrogel after grafting polymerization for AM/AA into PUL, in addition to enhancing thermal stability. On the contrary, FE-SEM demonstrated that SDBS improves the porosity and pore size of the hydrogel surface in SAP6.

The extent of access to energy of displaced populations in settlements and camps in Africa is largely 14 unknown. A multitude of contextual factors, such as the location and the characteristics of housing, 15 the legal status, the socio-cultural background, and the availability of humanitarian and public ser- 16 vices impact the living conditions and the needed energy services. Limitations in accessing energy 17 services have direct, multilayered, and far-reaching implications, including impacts on health, nu- 18 trition, education, protection, and livelihood. The objective of this article is to contribute to a more 19 comprehensive overview of the current state of energy access in displacement contexts on the Afri- 20 can continent by identifying and utilizing existing data. After a screening of the vast and various 21 available information, setting up of a database, consolidating the gathered data as well as assessing 22 the quality through a quality assessment method, the currently available information is visualized 23 and discussed. Considerable differences in the access to electricity for displaced persons across the 24 countries are found. For both electricity and clean cooking, the availability for displaced persons 25 ranges from nearly no access at all up to an access rate of 100%. More strikingly, the results also 26 show that besides South Africa and countries in the Maghreb region, the access to both clean cook- 27 ing and electricity for displaced persons is very low. At the same time, the fragmented data availa- 28 bility, the poor data quality, and the questionable expediency of available data allows neither solid 29 theoretical conclusions nor planning of effective practical implementation measures. Novel inter- 30 disciplinary research, conceptual frameworks and indicators are needed for the purpose of compa- 31 rability and consistency. Future research has the potential to more comprehensively capture the 32 current state of access to energy in displacements contexts and in a next step to examine how energy 33 is interwoven in the lives of displaced people to derive a set of more detailed context-sensitive en- 34 ergy indicators. It is essential that the concerned persons, the displaced persons themselves are in- 35 cluded in the research in a meaningful way.

Adamantinomatous Craniopharyngioma (ACP) is a rare epithelial tumor located in the craniopharyngeal duct, often associated with high morbidity and a high long-term recurrence rate. ACP is predominantly diagnosed in children below the age of 15 and accounts for a majority of Craniopharyngioma cases in the United States. It is most commonly caused by a mutation in exon 3 of the CTNNB1 gene, which promotes overaccumulation of β-Catenin in the WNT pathway. As β-Catenin accumulates, it over-activates the transcription factor, causing an over-transcription of WNT proteins and uncontrolled cell growth. Current methods of treatment for ACP are centered around surgical intervention and radiotherapy, including gross-total resection (GTR), subtotal resection (STR), and a combination of subtotal resection and adjuvant radiotherapy (STR+XTR). These methods of treatment are associated with high risk due to the proximity of ACP to critical structures near the craniopharyngeal duct. High recurrence rates and morbidity are closely associated with current methods of treatment and other methods have yet to be attempted in craniopharyngioma. This review will explore two possible methods of non-surgical and non-radiological therapeutic interventions. The use of RNAi therapy and CRISPR may provide insight and be a potential way to treat ACP with increased quality of life and decreased recurrence rates.

Building defects are very prevalent and contribute significantly to a building's economic value. There are numerous information sources on building defects that have a lot potential for learning more about building defects. This study aimed to identify the information sources used in previous building defect studies and to identify the motivation for carrying out such studies. To fulfil this aim a scoping study was carried out. The information sources identified included insurance companies, private databases, questionnaire surveys, lawsuits, building surveys, client complaint forms, and maintenance reports. This study found that insurance company and client complaint forms include the largest collection of real building defect cases, but such databases may lack detailed descriptions of the causes of the defects. The main purposes of building defects studies identified here included design challenges, identification of defects, building maintenance management, quality management, systematization in data collection, providing an overview of typical defects, and classifying defects. Identification was found to be the most common purpose, indicating that the industry wants to learn more. This study identified research gaps in the climate perspective in relation to building defects. Most of the studies focused on the economical perspective, and none focused on the carbon footprint perspective.

The escalating levels of atmospheric carbon dioxide (CO₂) due to anthropogenic activities have raised significant concerns regarding their far-reaching consequences, including potential impacts on human brain function. This study employs Agent-Based Modeling (ABM) and a comprehensive literature review to comprehensively examine the effects of varying atmospheric CO₂ concentrations on human brain activity. Historical and projected CO₂concentration data, along with neuroscientific insights, were integrated into the ABM framework to simulate brain activity responses under different CO₂ scenarios. The simulations revealed that elevated CO₂ levels disrupt neural activity and alter neurotransmitter profiles, indicating potential cognitive consequences. Sensitivity analysis emphasized the importance of accurate parameterization for robust simulations. The findings underscore the urgent need to address global CO₂ emissions to preserve cognitive health. Further research is essential to validate and refine the model, incorporating additional factors for a comprehensive understanding of the cognitive repercussions of rising CO₂ levels, crucial for informed policy-making and public awareness campaigns.