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%.

Nitrogen is one of the most important macronutrients for crops, and in conjunction with artificial intelligence algorithms, it is possible to estimate it with the aid of vegetation indices through remote sensing. Various indices were calculated and those with a correlation ≥ 0.7 were selected for subsequent use in Random Forest, Gradient Boosting, and Artificial Neural Networks to determine their relationship with nitrogen levels measured in the laboratory. Random Forest showed no relationship, yielding an R2 of zero, whereas Artificial Neural Networks yielded the best results with an R2 of 0.93. Thus, it is reliable to estimate nitrogen levels using this algorithm by feeding it with data from TCARI, MCARI, TCARI/OSAVI, and MCARI/OSAVI, assisted by technological tools.

This work focuses on short-term forecasting of PV output power. The multilayer perception (MLP), convolutional neural networks (CNN), and k-nearest neighbour (kNN) neural networks have been used singly or in a hybrid (with other algorithms) to forecast solar PV power or global solar irradiance with good success. Their performances in forecasting PV power have been compared with other algorithms but not with themselves. The study aims to compare performance of a number of neural network algorithms in solar PV energy yield forecasting under different weather conditions. The performance of MLPNN, CNN and kNN are being compared using solar PV (hourly) energy yield data for Grahamstown, Eastern Cape, South Africa. The choice of location is part of the study parameters to provide insight into renewable energy power integration in specific areas in south Africa that may be prone to extreme weather conditions. The kNN algorithm was found to have RMSE value of 4.95% and MAE value of 2.74% at its worst performance, and RMSE value of 1.49% and MAE value of 0.85% at its best performance. It outperformed the others by a good margin and kNN could serve as a fast, easy, and accurate tool to forecast solar PV output power.

In recent years, there has been an intensification of weather variability worldwide as a result of climate change. Some regions have been affected by drought, while others have experienced more intense rainfall. The incidence and severity of mouldy grain and mycotoxin contamination during the growing and harvesting seasons have increased as a result of these weather conditions. Addi-tionally, torrential rains and wet conditions may cause delays in grain drying, leading to mold growth in the field. In July 2023, a wheat field in Lecco (Lombardy, Italy) was affected by torren-tial rains that led to the development of the Claviceps fungi. In the field, dark sclerotia were identi-fied on some ears. Wheat ears, kernels and sclerotia were collected and analyzed by LC-MS/MS at IZSLER, Food Chemical Department, in Bologna. The wheat ears, kernels and sclerotia were ana-lyzed for 12 ergot alkaloids (EAs) according to (EU) Regulation 2023/915 (er-gocornine/ergocorninine; ergocristine/ergocristinine; ergocryptine/ergocryptinine; ergome-trine/ergometrinine; ergosine/ergosinine; ergotamine/ergotaminine), after QuEChERS (Z-Sep/C18) purification. The analyzed sclerotia showed significant differences in total alkaloids content that varies between 0.01-0.5% (w/w), according to the results of 2017 EFSA scientific report. EAs de-tected in sclerotia were up to 4951 mg/kg, in wheat ears up to 33 mg/kg, and in kernels were 1 mg/kg. Additional mycotoxins including ochratoxin A, deoxynivalenol, zearalenone, fumonisins, T2-HT2 toxins, and aflatoxins were investigated in wheat kernels, after purification with immu-noaffinity columns (IAC). The analysis revealed the presence of deoxynivalenol in wheat kernels at a concentration of 2251 µg/kg. It is expected that climate change will increase the frequency of extreme weather events. In order to mitigate the potential risks associated with mycotox-in-producing fungi and to ensure the protection of human health, it is suggested to implement of-ficial controls in the field.

Invasive species are non-native organisms that are introduced to a particular environment with a potential to spread from the place of introduction and cause biodiversity loss. This research was done in Gullele Botanical Garden with the objective of advancing management strategies for invasive and potentially invasive species by examining their abundance, distribution, impacts. Proportional number of plots with a size of 10m by 10m was laid at each land use types to collect vegetation and environmental data. The impact rank was analysed as a data frame using the R-statics packages, which shows the lower and higher impact rate ranges for the sampled land use types. ArcGIS was used to map the spatial distributions of each species. A total of 2550 individuals from 12 families comprising 16 invasive and potentially invasive species have been recorded in 40 sample plots across all sampled land use types. The highest species abundance appeared near the roadside among the sampled plots. Acacia decurrens, Cyathula uncinulata, and Acacia melanoxylon were the three most predominant species, had a substantial contribution to the high impact on the native species. Either intentionally by planting for their advantageous qualities or unintentionally associated with other seeds or other vectors, invasive and potentially invasive species were introduced into the garden. Although there are various techniques to control invasive species, mechanical controlling mechanisms like hand-weeding, uprooting, cutting, and rehabilitation with native species, along with regular monitoring, are highly recommended for the current challenge in the garden.

Epidemiological studies point cholesterol as a possible key factor for both prostate cancer incidence and progression. So, it could represent a targetable metabolite as the most aggressive tumors also appear to be sensitive to therapies designed to decrease hypercholesterolemia, such as statins. However, whether and how cholesterol, through its dietary uptake and its metabolism, could be important for early tumorigenesis, remains unknown. Oncogene clonal induction in Drosophila melanogaster accessory gland allows to reproduce tumorigenesis from initiation to early progression, where tumour cells undergo basal extrusion to form extra-epithelial tumors. Here we show that these tumors accumulate lipids, and especially esterified cholesterol, as in human late carcinogenesis. Interestingly, high cholesterol diet displays limited effect on accessory gland tumorigenesis. On the contrary, cell-specific downregulation of cholesterol uptake, intracellular transport or metabolic response, impairs the formation of such tumors. Furthermore, in this context, high cholesterol diet suppresses this impairment. Taken together, these results reveal that during early tumorigenesis, tumour cells strongly increase their uptake and use of dietary cholesterol to specifically promote the step of basal extrusion. Interestingly, expression data from primary prostate cancer tissues indicate an early signature of redirection from cholesterol de novo synthesis to uptake. Altogether, these results suggest by which mechanism reduction of dietary cholesterol could lower the risk and slow down the progression of prostate cancer.

This article touched upon various issues regarding vulnerability, disparities amongst community settings, and the effect of air pollution on the populace (low-income communities). Furthermore, the paper emphasized environmental ethics approaches like anthropocentric, nature-centric, and deep-ecological approaches. More so, it addresses the importance of handling these disparities, particularly from the geopolitical dimension, and recommends cross-border cooperation and accountability in promoting environmental justice in India.

Vaccine refusal and hesitancy pose a critical challenge to public health, leading to delays in vaccination and compromising herd immunity. To address this issue, we conducted a comprehensive observational study on the adult Spanish population in 2021. Through an online questionnaire, we explored the sociodemographic and sociocultural factors, beliefs, and opinions of those refusing or holding hesitancy about vaccines, and their vaccination behaviours by vaccine type and sex. Our findings revealed that vaccine refusal rates were relatively low (16.8%), and mainly associated with influenza vaccination (10.3%). Greater refusal of vaccination was observed in over 60 years old, in those expressing hesitancy due to vaccine components and opposing free and compulsory vaccination, unaware that vaccination protects the community and being against consuming cow’s milk and the use of infant formulas for breastfeeding. Vaccine hesitancy was greatest in individuals under 31 years old, women, parents of children under 15 years old, against compulsory vaccination, unaware that vaccination protects the community, with hesitancy due to vaccine costs, and in favour of alternative and complementary treatments. These insights underscore the need for strategies to improve education about vaccination and dispel misconceptions are crucial for effectively reducing vaccine refusal and hesitancy across the population.

Reducing the carbon footprint of energy production is one of the most pressing challenges facing humanity today. Lignocellulosic biomass residues from fruit production industries show promise as a viable energy source. This paper presents a study of the Italian context concerning the utilization of orchard lignocellulosic residues for energy production as electricity or bioethanol. The potential of various orchard residues was assessed through chemical and physical analysis, and an equivalent electrical energy of about 6441.62 GWh or an amount of 0.48 Mt/y of bioethanol was obtained based on the average annual dry residue mass availability of about 3.04 Mt/y. These data represent the 9.30% of the national electrical energy production from renewable sources, as well as the 6.21% of the Italian demand for gasoline in 2022. Electricity generation from these residues shown its potential as a reliable and sustainable baseload power source, as well as source of renewable transportation fuel. The studied process could be a valuable reference to expand these concepts on global scale to achieve a greener and more sustainable energy future.

Aim/Purpose: This study aims to assess the influence of integrating ChatGPT on enhancing the academic writing performance and engagement of English as a Foreign Language (EFL) undergraduate students at Delhi, India, who are enrolled in Academic Writing during the first semester of the academic year 2024/2025. Given the unique challenges within the Indian undergraduate education system, innovative technological interventions are essential to improve writing skills and increase engagement among EFL learners.

Thermodynamics of protein-ligand interactions seems to be associated to a narrow range of Gibbs Free Energy. As a consequence, a linear enthalpy-entropy relationship showing an apparent Enthalpy-Entropy compensation (EEC) is frequently observed associated to the study of protein-ligand interactions. This EEC affects negatively the design and discovery of new and more efficient drugs capable of binding protein-targets with a higher affinity. Originally attributed to experimental errors, compensation between H and TS values is a real observable fact, although its molecular origin has remained obscure and controversial. Herein we show the results of a data search of G values of 2558 protein-ligand interactions and 3025 “in vivo” ligand concentrations from the Protein Data Bank bind Database and the Metabolome Data Base (2020). These results, together with the mechano-statistical interpretation of the thermodynamic properties leads to the conclusion that the EEC has no basis in statistical thermodynamics. It can be plausibly explained as a consequence of the narrow range of G associated to protein-ligand interactions. The Gaussian distribution of the G values matches very well with that of ligands. These results suggest the hypothesis that the set of G values for the protein-ligand interactions is the result of the evolution of proteins. The conformation versatility of present proteins and the exchange of thousands (even millions) of minute amounts of energy with the environment may have functioned as a homeostatic mechanism to make G of proteins adaptive to changes in availability of ligands, and therefore achieve the maximum regulatory capacity of the protein function. Finally, a plausible strategy to avoid the EEC is suggested.

This paper investigates the importance of enhancing the safety of research reactors, especially in newcomer countries where experience may be limited. The focus is on the role of Independent Assessment (IA) and assessors in addition to using Best Estimate plus Uncertainty (BEPU) approach in enhancing safety measures. By using the best estimate codes to perform uncertainty calculations, the BEPU technique logically connects nuclear thermal hydraulics and nuclear reactor safety. BEPU is based on an understanding of the phenomena related to the reactor state. Reactor circumstances, such as those related to operations or accidents, could be identified in this way. The IA process, involves experts supporting design, installation, safety analysis, decommissioning, and modification. In order to shape the use of IA process in this study feedback from nuclear professionals was collected through questionnaires, revealing a consensus on the necessity of qualified regulatory bodies in newcomer countries. Additionally, the questionnaires highlighted the potential benefits of IA, such as minimizing accident risks and providing valuable insights for future analyses. The results indicate a global anticipation of increased research reactor construction, particularly in newcomer countries. The study discusses the propagation of input uncertainties, emphasizing the importance of considering various factors and parameters in safety assessments. The BEPU method was applied by using the COBRA-TF code by modeling onset of nucleate boiling (ONB) conditions for VVR-K research reactor. For uncertain parameters; ±1% inlet/initial pressure, ±1% inlet temperature, and ±1% linear heat rate, the ONB temperature in the axial region with the average cladding temperature was calculated to be 114.44℃. Table 2 (our references) provided a value of 114.6℃. The close agreement between the reference value and the COBRA-TF result shows that the model used in the calculation of the reference value and the Chen relation used by COBRA-TF are compatible.

Gastric cancer is the 5th most common disease in the world and the 4th most common cause of death. It is diagnosed through esophagogastroduodenoscopy with biopsy, however there are limitations in finding lesions in the early stages. Recently, research has been actively conducted to use liquid biopsy to diagnose various cancers, including gastric cancer. Various substances derived from cancer are reflected in the blood. By analyzing these substances, it was expected that not only the presence or absence of cancer but also the type of cancer can be diagnosed. However, the amount of these substances is extremely small, and even these have various variables depending on the characteristics of the individual or the characteristics of the cancer. To overcome these, we collected methylated DNA fragments using MeDIP and compared them with normal plasma to characterize gastric cancer tissue or patient’s plasma. And we attempted to diagnose gastric cancer using the characteristics of cancer reflected in the blood through the cancer tissue and patient’s plasma. As a result, we confirmed that the consistency of common methylated fragments between tissue and plasma was approximately 41.2%, and found the possibility of diagnosing and characterizing cancer using the characteristics of the fragments through SFR and 5'end-motif analysis.

In the dynamic landscape of Sabah's socio-economic development, the integration of AI technologies holds both promise and challenge. While AI has the potential to drive economic growth, enhance productivity, and elevate quality of life, it also brings forth concerns regarding job displacement, skill gaps, and unequal distribution of benefits. The latest research problem in the realm of AI and employment in Sabah revolves around ensuring inclusive and sustainable development amidst this technological disruption. This encompasses two key dimensions: skill development and education, and labor market dynamics. Addressing the research questions necessitates a multifaceted approach. Firstly, in the realm of skill development and education, there is a critical need to assess the adequacy of existing programs in equipping the workforce with AI-driven skills. Strategies such as promoting STEM education, fostering digital literacy, and facilitating lifelong learning initiatives, particularly among marginalized communities, are essential. Additionally, fostering collaboration between stakeholders and implementing curriculum reforms are pivotal steps in enhancing the alignment between educational curricula and the demands of an AI-driven economy.

The microstructure evolution during the cold rolling and subsequent annealing of Alloy 800H was investigated. Two distinct rolling methods, unidirectional rolling and cross-rolling, were intro-duced. Results show that better ductility was observed in the unidirectional rolling than in cross-rolling, whilst a higher volume fraction of large deformed grains was observed in the cross-rolled plates than in the unidirectionally rolled plates. Recrystallization occurred faster in plates from unidirectional rolling than from cross-rolling.

This review explores the unique structural and functional characteristics of natural products featuring highly oxygenated cyclobutane rings, with a specific focus on oxetane and 1,2-dioxetane motifs. It presents the structures and biological activities of compounds containing these rings, highlighting their contribution to molecular stability and pharmacological potency. Through detailed case studies and recent research findings, it has been demonstrated that these oxygen-rich rings enhance the molecular diversity and biological efficacy of natural products, potentially offering new avenues for drug development. Notably, these compounds are predominantly synthesized by microorganisms and can also be found in extracts from fungi, plants, and certain marine invertebrates. Compounds with oxetane and 1,2-dioxetane rings are primarily noted for their strong antineoplastic properties, among other biological activities. In contrast, most 1,2-dioxetanes exhibit potent antiprotozoal effects. It is important to note that 1,2-dioxetanes often serve as intermediate products in oxidation reactions, characterized by their instability and propensity to decompose into new compounds.

Abrasive Water Jet Machining (AWJM) is a non-conventional machining process that, unlike other methods, is deemed superior because of its applicability, versatility, and no heat-affected zones in the target material. The main objective of this paper was to develop a cheap, practical model for a low-pressure water jet cutting machine and provide some empirical test data for cutting delicate materials. Proper design calculations were performed and are included for both the water jet machine and the two-axis numerical control. Finite Element Analysis results validate the structural integrity of beams and columns in AWJM. Computational Fluid Dynamic analysis of the nozzle shows good agreement with the theoretical calculations regarding the pressure and velocity of the water-abrasive mixture exiting the nozzle. Modal analysis in ANSYS was done to mitigate potential failure due to resonance induced by vibrations. Limited testing on various thicknesses of polystyrene foam ranging from 1-5 mm thickness and rubber sheet of 1 mm thickness showed that even low pressure of 25-30 bar was sufficient to produce a kerf without any burr. However, extensive testing to report optimized parameters like nozzle transverse speed, standoff distance, abrasive flow rate, etc for working at low-pressure ranges is still a consideration for future investigation.

Coastal cliffs erode in response to short- and long-term environmental changes but predicting these changes continues to be a challenge. In addition to a chronic lack of data on the cliff face, vegetation presence and growth can bias our erosion measurements and limit our ability to detect geomorphic erosion by obscuring the cliff face. This paper builds on past research segmenting vegetation in 3-band red, green, blue (RGB) imagery and presents two approaches to segmenting and filtering vegetation from the bare cliff face in dense point clouds constructed from RGB images and structure-from-motion (SfM) software. Vegetation indices were computed from previously published research and their utility in segmenting vegetation from bare cliff face were compared against machine learning (ML) models for point cloud segmentation. Results demonstrate that, while existing vegetation indices and ML models are both capable of segmenting vegetation and bare cliff face sediments, ML models can be more efficient and robust across different growing seasons. ML model accuracy quickly reached an asymptote with only two layers and RGB images only (i.e., no vegetation indices), suggesting that these more parsimonious models may be more robust to a range of environmental conditions than existing vegetation indices which vary substantially from one growing season to another with changes in vegetation phenology.

Papillary thyroid carcinoma (PTC) presents a significant health concern, particularly among Hispanic women in the United States, who exhibit a disproportionately higher chance of developing an advanced disease when compared to the non-Hispanic population. Emerging evidence suggests coagulation factor X, encoded by F10 gene, has a potential role in inhibiting cancer cell migration. However, comprehensive investigations into the differential expression patterns of F10 in Hispanic versus non-Hispanic females remain limited. RNA-sequencing data was acquired from the TCGA database for white female patients, 166 non-Hispanic and 25 Hispanic. A statistically significant (p < 0.05) 2.06-fold increase in F10 expression levels was detected in disease-free tumors compared to recurrent PTC tumors. Furthermore, an increase in F10 gene expression levels was also observed corresponding to approximately a 1.74-fold increase in non-Hispanic patients compared to Hispanic patients. The probability of tumor recurrence was 1.82 times higher in the cohort with low expression of F10 compared to the high expression cohort, correlating with the lower disease-free rates observed in Hispanic patients’ cohort when compared to non-Hispanics. This finding underscores the relevance of ethnic disparities in molecular profiles for understanding cancer susceptibility. Identifying F10 as a potential prognostic biomarker highlights avenues for targeted interventions and contributes to improving diagnostic and treatment strategies for diverse patient populations.

In this paper, the entire downhole fluid sucker rod pump system is replaced with a viscoelastic vibration model, namely a third-order differential equation with an inhomogeneous forcing term. Both Kelvin and Maxwell viscoelastic models can be implemented along with the dynamic behaviors of a mass point attached to the viscoelastic model. By employing the time-dependent polished rod force measured with a dynamometer as the input to the viscoelastic dynamic model, we have obtained the displacement responses, which match closely with the experimental measurements in actual operations, through an iterative process. The key discovery of this work is the feasibility of the so-called inverse optimization procedure which can be utilized to identify the equivalent scaling factor and viscoelastic system parameters. The proposed Newton-Raphson iterative method with some terms in the Jacobian matrix expressed with averaged rates of changes based on perturbations of up to two independent parameters provides a feasible tool for optimization issues related to complex engineering problems with mere information of input and output data from either experiments or comprehensive simulations. The same inverse optimization procedure is also implemented to model the entire fluid delivery system of a very viscous non-Newtonian polymer modeled as a first-order ordinary differential system similar to the transient entrance developing flow. The convergent parameter reproduces transient solutions which match very well with those from full-fledged computational fluid dynamics models with the required inlet volume flow rate and the outlet pressure conditions.

The research is devoted to the study of geotectonic and geodynamics of the Shu-Ile belt and petrographic composition and intrusive complexes geochemical features analysis. The Shu-Ile suture is an important geological structure of Kazakhstan. It is characterized by the presence of various intrusive formations and deep faults. The material composition of these intrusions is of interest for understanding the geological and metallogenic processes in this region. The research used modern scientific methods, including petrographic and geochemical studies of various compositions intrusion samples. Based on the results of material composition studies of intrusive complexes, their possible connections with other geological structures of Kazakhstan and the metallogeny of the region have been established. Based on the data obtained, a conclusion was made about the intrusive complexes origin and evolution of the Shu-Ile belt, which may be important for further geological research and forecasting of mineral resources in the region.

Nowadays, one of the greatest challenges in Data Meshes revolves around detecting and creating Data Domains and Data Products for providing the ability to adapt easily and quickly to changing business needs. This requires a disciplined approach to identify, differentiate and prioritize distinct data sources according to their content and diversity. The current paper tackles this highly com-plicated issue and suggests a standardized approach that integrates the concept of Data Blueprints with Data Meshes. In essence, a novel standardization framework is proposed that creates Data Products using a metadata semantic enrichment mechanism, the latter also offering Data Domain readiness and alignment. The approach is demonstrated using real-world data produced by mul-tiple sources in a poultry meat production factory. A set of functional attributes is used to compare qualitatively the proposed approach against existing data structures utilized in storage architectures with quite promising results. Finally, experimentation with different scenarios varying in data product complexity and granularity suggests successful performance.

Time series forecasting has been a challenging area in the field of Artificial Intel-ligence. Various approaches such as linear Neural Networks, Recurrent Linear Neural Networks, Convolutional Neural Networks and recently Transformers have been attempted for the time series forecasting domain. Although, Trans-former-based architectures have been outstanding in the Natural Language Pro-cessing domain, especially in autoregressive language modeling, the initial at-tempts to use transformers in the time series arena have met with mixed success. One of the recent papers demonstrated that modeling the multi-variate time se-ries problem as independent channels on a transformer architecture produced lower mean square and mean absolute errors on benchmarks, however, another recent paper claimed that a simple linear neural network out-performs previous approaches including transformer-based designs. We investigate this paradox in detail comparing the linear Neural Network and Transformer based designs, provide insights to why a certain approach may be better for a particular type of problem. We also improve upon the recently proposed simple linear Neural Network based architecture by using dual pipelines with batch normalization and reversible instance normalization. Our enhanced architecture outperforms all existing architectures for time series forecasting on majority of the popular benchmarks.

This critical study examines the social consequences of neoliberal urbanism, with a focus on housing policies by implementing qualitative approach. The main goal of the study is to identify downsides of the neoliberalism in residential areas and shed light on the potential social challenges caused by this. After reviewing the existing literature in this field and introducing some cases, the findings highlight that the prioritization of market mechanisms in urban development, which is the key characteristic of neoliberalism, has led to unaffordable housing, gentrification, and displacement of marginalized communities, exacerbating socio-economic inequalities. The commodification of housing under neoliberal urbanism has transformed homes into financial assets, and instead of addressing the structural roots of housing insecurity, strategies such as implementing public-private partnerships (PPPs), urban mega projects and deregulation, have perpetuated housing crises in urban areas. The results suggest that alternative methods such as inclusionary zones for having a mix of market-rate and affordable housing in new developments, as well as strengthening tenant protections through rent control, and tenant rights advocacy programs, can remarkably help address systemic inequalities. By prioritizing the needs of vulnerable populations, policymakers can work towards mitigating the detrimental social effects of neoliberal urbanism and fostering more just and inclusive urban environments. Finally, critical engagement with social justice issues is essential to creating diverse and inclusive urban communities.

China's economic development has shifted from high speed to high quality. This study constructs an evaluation index for China’s high-quality development utilizing a new development concept. The entropy method and cluster analysis were used to assess the level of high-quality development in China between 2015 and 2021. Kernel density estimation method was employed to explore spatiotemporal dynamics. The results reveal significant differences in the level of economic development among provinces in China; the eastern region is significantly better than the central, northeastern, and western regions. From the perspective of the sub-item evaluation, challenges with uneven, uncoordinated, and insufficient economic development exist in various Chinese provinces.

Taxonomic studies of dreams that continue to influence the dreamer’s thoughts and feelings after awakening have distinguished three types of impactful dreams: nightmares, existential dreams, and transcendent dreams. Of these, existential dreams and transcendent dreams are characterized by recurrent metacognitive appraisal of the epistemic tension between complementary (a) metaphoric (A “is” B) assertions and (b) literal (A “is not” B) assertions. Metacognitive appraisal of such complementary metaphoric and literal assertions is detectible as the felt sense of inexpressible realizations. The poesy of such inexpressible realizations depends upon the juxtaposition of a metaphoric topic and vehicle that are both “semantically dense” but at an abstract level “distant” from each other. The result is the “emergence” of attributes of the metaphoric vehicle that are sufficiently abstract to be attributes also of the metaphoric topic. The cumulative effect of successive metaphoric/literal categorical transformations produces a higher-level form of metacognition that is consistent with a neo-Kantian account of sublime feeling. Sublime feeling occurs as either sublime disquietude (existential dreams) or as sublime enthrallment (transcendent dreams). The aftereffects of these two dream types are thematically iterative “living metaphors” that have existential (but not totalizing) abstract ontological import.

Measuring reference evapotranspiration (ETo) is a difficult and costly process. Several parameters are needed to calculate it from meteorological parameters with the aid of some developed equations. There may be variable microclimates in some regions and these are often quite far from the climate stations. Therefore, for ETo, it is better to prefer local measurements rather than relying on regional values. ETo is of great importance for all water-related sectors. It is the primary factor designating the amount of irrigation water to be applied to the plant rootzone in agricultural activities. The amount of irrigation water to be applied is determined by correcting ETo value with the plant coefficient (kc) and irrigation efficiency. There have been many developments in measurement/calculation of ETo in recent years and it is expected that there will be more in the future. Within the scope of this study, ETo values measured with ETgage equipment were compared with the monthly ETo values calculated with the use of Thornthwaite, Blaney-Criddle, Cropwat (FAO Penman Monteith), Jensen-Haise and ASCE standardized Penman Monteith (ASCE SZ PM) methods. In terms of total ETo value, Thornthwaite (17%) and Jensen-Haise (14%) methods yielded lower values than ETgage readings. On the other hand, Blaney-Criddle (15%), Cropwat FAO PM (10%) and ASCE SZ PM (30%) methods yielded greater values than ETgage readings. Among the calculation methods, in Cropwat software, FAO PM equation yielded the closest value to ETgage readings. It was concluded based on present findings that ETgage equipment could reliably be used in determination of ETo.

Financing frameworks for Public Private Partnerships (PPPs) are lacking in developing countries. This study develops and recommends a financing framework for water and sanitation PPP infrastructure projects in Zimbabwe. The framework model integrates the Public Private Partnership models, sources of finance for water and sanitation PPPs, and the drivers of water and sanitation PPP finance. Both the public and private sources of finance are instrumental for financing water and sanitation PPP projects. Tobit econometric models are applied on data collected from both international and domestic data banks. The time frame for the analysis is a 25-year period running from 1996 ending 2021. Capital market variables, bank market development and economic affluence drive the financing of water and sanitation Public Private Partnership infrastructure projects in Zimbabwe. The study recommends the application of the developed framework in the water and sanitation Public Private Partnership infrastructure financing policy, for developing countries.

Pediatric psychology action in the pediatric clinical-surgical high complexity unit has become increasingly necessary. It allows for the possibility of integrating complex pediatric clinical-surgical operations by reducing painful effects on the emotional world of children and adolescents. The pediatric psychologist in a pediatric unit continuously oversees children and adolescents (C/A) throughout the entire therapeutic process, extending activity to parents and healthcare personnel. In ill children and adolescents, physical pain and psychological suffering follow, with minimal temporary variations, the same clinical path with continuous changes which put a strain on the ability of children, adolescents, parents and healthcare staff to cope with stress.

Today, there are commercially available high-performance electric wheelchairs, capa-ble of responding to strong limitations. However, despite these advancements, there is a significant portion of the population with severe disabilities who cannot access this mobility solution due to safety reasons. Indeed, either due to motor issues preventing reliable control of the wheelchair's commands, or associated visual or cognitive pathologies, the use of an electric wheelchair by these individuals would put them at risk and could also constitute a danger to those around them. This is why our research team is working on the development of augmented wheelchairs that allow a greater autonomy. We are mainly developing a system compatible with all electric wheel-chairs on the market, capable of making them anti-collision and anti-fall on uneven ground (sidewalks, stairs, etc.). In this article, we present our solution regarding the anti-collision function, in particular the sensors used to do this, as well as the strategy. We will focus on the shortcomings and weaknesses of various types of sensors and demonstrate how, by combining them in a certain way, we can develop a collision avoidance device capable of managing the diversity of everyday life situations. The two types of sensors that will be combined here are an in-house developed special near infrared sensor from the laboratory and a commercially available ultrasonic sensor. We will present the internal operation of the sensors, their limitations, experimental tests involving integration with the wheelchair, and the structure of the complete device.

COVID-19 pandemic disproportionately affected seven South Asian countries because of rampaging virus and weak health system response. Vaccination commenced in all countries during early 2021, once the vaccines became available in the international market. Vaccines were donated by international development partners, friendly countries and procured utilizing domestic resources and financial support from various agencies. All countries opted for a phasing of the vaccination by prioritizing high risk populations which included health care personnel, front line workers and elderly with comorbidities. Seven vaccines that had WHO emergency authorization usage were utilized in South Asia. India produced more than 2.4 billion doses of AstraZeneca vaccine and has indigenously developed five COVID-19 vaccines. Vaccine inequity was obvious and characterized by fewer people in South Asia vaccinated with single dose vis a vis the developed countries. Vaccine hesitancy was another obstacle that kept the vaccination rates low. Difficult to reach areas in Afghanistan, Bhutan, Maldives, Nepal could not fully access vaccines. South Asian countries need to strengthen their health system for efficient deployment of vaccines in future health emergencies. At the same time the global agencies and developed countries must address the issue of vaccine access to low-income countries to mitigate the impact of pandemic all over the world.

Artery of Percheron Infarct (AOP) is a rare congenital anatomical vascular variant supplying the paramedian thalamus and the rostral midbrain. It arises from either proximal segment of the posterior cerebral artery (P1). The symptoms of an AOP infarction might vary, although they typically manifest as memory loss, altered mental status, and supranuclear vertical gaze palsy. Most of the time, the initial CT scan fails to diagnose the AOP infarct. Most of these diagnoses are made when ischemic stroke patients are not eligible for thrombolytic therapy. We report a case of a 40-year-old female with a history of well-managed hypertension, who presented in the ER with chief complaints of altered behavior, altered gaze palsy, and drowsiness. Initially, the CT scan did not show pathological changes. The diagnosis was made the next hospital day by MRI. Our case presents an unusual presentation and the lack of evidence of AOP infarction on a CT scan does not exclude its diagnosis. An infarcted Percheron artery requires a thorough clinical and radiological examination.

As part of the Fabaceae project of northeastern Mexico, today we present the compendium of legumes of the subfamilies Caesalpinioideae, Cercidoideae and Detarioideae from this region. As in our previous work on the Mimosoideae Clade, new nomenclatural changes and retypification of genera of the subfamily Caesalpinioideae are included. Also, based on new scientific information published, the taxonomic changes in new genera, recently segregated from the genus Caesalpinia (Conzattia, Coulteria, Denisophytum, Erythrostemon, Guilandina, Hoffmannseggia, and Pomaria) are included. Based on field work, collection of botanical samples over the past 37 years, and reviewing botanical materials in national and international herbaria, the diversity of legumes of the subfamilies Caesalpinioideae, Cercidoideae, and Detarioideae in northeastern Mexico has been recorded. The subfamily Caesalpinioideae includes two tribes, the tribe Caesalpinieae with 12 genera (Caesalpinia, Ceratonia, Coulteria, Delonix, Denisophytum, Erythrostemon, Gleditsia, Guilandina, Hoffmannseggia, Haematoxylum, Parkinsonia, and Pomaria), and 26 species and the tribe Cassieae, which includes three genera (Cassia, Chamaecrita, and Senna) and 28 species. The subfamily Cercidoideae include two genera (Bauhinia and Cercis), and eight species and the subfamily Detarioideae, includes only one genus and one species (Tamarindus indicus). The total flora of these three subfamilies comprize 18 genera and 63 species, it includes 56 native species and seven exotic ones: Bauhinia variegata, Cassia fistula, Ceratonia siliqua, Delonix regia, Erythrostemon gilliesii, Senna alata, and, Tamarindus indicus. The endemism of both subfamilies includes a total of 20 species and 10 infraspecific categories.

We demonstrate a new quantitative method to the sieve of Eratosthenes, which is an alternative to the sieve of Legendre. In this method, every element of a given set is sifted out once only, and therefore, this method is free of the Mobius function and of the parity barrier. Using this method, we prove that every sufficiently large even number is the sum of two primes, and that every even number is the difference of two primes in infinitely many ways.

Polyphenols are ubiquitous plant metabolites that demonstrate biological activities essential to the plant-environment interactions. They are of interest to plant food consumers, as well as to the food, pharmaceutical and cosmetic industry. The class of the plant metabolites comprises both widespread (chlorogenic acids, luteolin, quercetin) and unique compounds of diverse chemical structures but of the common biosynthetic origin. Polyphenols, next to sesquiterpenoids are regarded as the major class of the Inuleae-Inulinae metabolites responsible for the pharmacological activity of medicinal plants from the subtribe (Blumea spp., Dittrichia spp., Inula spp., Pulicaria spp. and others). Recent decades have brought a rapid development of molecular and analytical techniques which resulted in better understanding of the taxonomic relationships within the Inuleae tribe and in a plethora of data concerning the chemical constituents of the Inuleae-Inulinae. The current taxonomical classification has introduced changes in the well-established botanical names and rearranged the genera based on molecular plant genetic studies. The newly created chemical data together with the earlier phytochemical studies may provide some complementary information on biochemical relationships within the subtribe. Moreover, they may at least partly explain pharmacological activities of the plant preparations traditionally used in therapy. The current review aimed to systematize the knowledge on the polyphenols of the Inulae-Inulinae.

Osteoporosis is a bone condition where bones become weaker, leading to fractures, especially in older adults and postmenopausal women. Bioceramics for bone regeneration have indeed emerged as a promising solution for conditions like osteoporosis. Choosing the right bioceramic depends on how quickly it dissolves, how strong it is, and whether the body will react to it. Studies show that bioceramics can help bones grow back by activating (bone morphogenetic protein) BMP, (mitogen-activated protein kinase) MAPK, and Wingless/integrated (Wnt)/β-catenin pathways in the body when combined with stem cells, drugs, and supports. However, bioceramics have some problems like not being flexible enough and being prone to breaking, as well as difficulties in growing stem cells and finding the right supports for different bone types. While there has been progress in improving bioceramics for bone healing, we need to keep looking for new ideas from other areas of medicine to keep improving them. This review aims to add to the expanding field of scientific research by offering a detailed look at how bioceramics and growth factors contribute to bone regeneration. Ultimately, this knowledge will help in creating new types of bioceramics that can improve bone regrowth, providing new treatment options for people with bone diseases.

Dietary intake and alcohol consumption might be influenced by genetic variations in taste receptor genes. The objectives of this study were to examine the relationship between polymorphisms in bitter taste receptor genes TAS2R13 (rs1015443) and TAS2R38 (rs1726866, rs10246939, and rs713598) as well as alcohol consumption and body fat percentage in college students. Four hundred and two students with a mean age of 20.2 years participated in this study. An NIH Diet History Questionnaire (DHQ II) was used to collect data on their dietary intake, while AUDIT survey was used to determine their level of alcohol consumption. Bitter taste receptor gene polymorphisms were assessed by TaqMan allelic discrimination assays. Despite significant associations between TAS2R13 (rs101544) and certain aspects of alcohol consumption, including the frequency of alcohol intake, no indeed significant associations were found between TAS2R13 (rs1015443) and alcohol consumption after accounting for confounding variables in the regression model. Neither association was found regarding percent of body fat. In contrast, ethnicity and gender significantly influenced percent of body fat (p < 0.001), while no significant association was observed between TAS2R13 (rs1015443) and percent of body fat. Likewise, TAS2R38 (rs1726866, rs10246939 and rs713598) demonstrated no significant association with alcohol consumption and percent of body fat. These results were controlled for confounding factors, such as ethnicity and gender. Body fat percentage and alcohol consumption may be influenced by ethnicity, gender and age rather than SNPs of TAS2R13 and TAS2R38 genes. Assessing the taste genes’ interactions with diet and body composition might be useful in identifying human disease risk.

Earth’s climate cannot be ignored any longer. Policies are vital in order to mitigate the negative effects of climate change. The energy crisis created by the Russo-Ukrainian war and pandemic affected the EU and its member states. The focus is more than ever on its energy policies and independence. The EU revised the energy strategy in response to Russia’s blackmail, and it sped up all the processes for energetic independence from Russia. This benefited the climate change policies the most, as all the measures involved reducing energy consumption and increasing renewables, thus contributing to reducing greenhouse gas emissions. As a member state of the EU, Romania is committed to complying with EU regulations. With a high degree of energy independence compared with the other EU members, Romania plans to become a regional energy provider and modernize the energy infrastructure internally as a response to Russia’s unprovoked aggression. The measures that the EU and Romania implemented after the war started in 2022 have come to fruition, and the effects are becoming visible a year later. This study aims to study the energy strategy of Romania in correlation with the EU strategy in the turbulent period of pandemics and war between 2019 and 2023, with the latest available data.

The mechanism of immune activation and de-activation is very important. Host should trigger effective immunity against pathogen infection. And, host cannot trigger immunity against self-antigens that will lead to detrimental autoimmune disorders. Spleen and liver have opposite roles in mediating immune responses. Spleen is the organ involving in immune activation, and liver is the organ involving in immune de-activation. Sympathetic nerve system and parasympathetic nerve system have opposite roles in mediating immune responses. Sympathetic nerve system is involving in pro-inflammatory, and parasympathetic nerve system is involving in anti-inflammatory. ACTH and glucocorticosteroid have opposite roles in mediating immune responses. ACTH is involving in activating adaptive immunity with inhibiting innate immunity, and glucocorticosteroid is involving in activating innate immunity with inhibiting adaptive immunity. The molecular chaperons, heat shock proteins, which are induced by fever, have the vital roles in immune activation. On the contrary, IgD B cells and gamma-delta T cells are causing immune de-activation via the mechanism of clonal anergy. These mechanism can help us the know the work of immunological pathways better for better control of infectious diseases and autoimmune disorders.

Purpose: To evaluate the relationship between corneal nerve structure and function in a veteran population. Methods: 83 veterans (mean age: 55 ± 5 years) seen at the Miami Veterans Affairs (VA) eye clinic were included in the study. Each individual filled out questionnaires to evaluate ocular symptoms (5-Item Dry Eye Questionnaire, DEQ5, Ocular Surface Disease Index, OSDI) and ocular pain (Numerical Rating Scale, NRS, Neuropathic Pain Symptom Inventory modified for the Eye, NPSI-Eye). Individuals also underwent an ocular surface examination that captured functional nerve tests including corneal sensation, corneal staining, and Schirmer test for tear production. Corneal sub-basal nerve analysis was conducted using in vivo confocal microscopy (IVCM) images with corneal nerve density, length, area, width, and fractal dimension captured. IVCM and functional corneal metrics from the right eye were examined using correlational and linear regression analysis. Results: Most corneal structural metrics were not related to functional metrics, except for weak correlations between various IVCM metrics and tear production. In addition, corneal nerve fiber area was positively related to corneal sensation (r = 0.3, p = 0.01). On linear regression analyses, only corneal fractal dimension remained significantly related to tear production (β = -0.26, p = 0.02) and only corneal nerve fiber area remained significantly related to corneal sensation (β = 0.3, p = 0.01). Conclusions: Most corneal nerve structural metrics did not relate to functional metrics in our veteran population, apart from a few weak correlations between structural metrics and tear production. This highlights caution in using corneal nerve anatomy to predict corneal function.

In this paper, we dive into the exciting world of wireless communication, focusing on how millimeter-wave technology and Multiple-Input Multiple-Output phased array antennas are shaping the future of 5G and the upcoming 6G technologies. We cover the latest advancements in millimeter-wave and beam-forming technologies, emphasizing their role in enhancing network security and efficiency in automotive vehicles through dual radar communication. Our discussion spans the benefits, applications, challenges, and solutions of these technologies individually from millimeter-wave to beam-forming technology and joint radar communications, alongside a look at their theoretical and practical implementations. We emphasize the integration of beam-forming technology in joint radar communications for future automotive vehicles and its impact on automotive systems, smart cities, and the Internet of Things (IoT). Looking ahead, we discuss the potential of these technologies to transform future tech landscapes, while also addressing the security implications of merging communication and radar capabilities. This paper aims to provide a clear view of the advancements and prospects of millimeter-wave, beam-forming, and dual radar communication technologies.

Histone deacetylases inhibitors (HDACi) have shown promising therapeutic outcomes in haematological malignancies such as leu-kaemia, multiple myeloma and lymphoma, with dis-appointing results in solid tumours when used as monotherapy. As a result, combination therapies either with radiation or other deoxyribonucleic acid (DNA) damaging agents have been suggested as ideal strategy to improve their efficacy in solid tumours. Numerous in vitro and in vivo studies have demonstrated that HDACi can sensitise malignant cells to both electromagnetic and particle types of radiation by inhibiting DNA damage repair. Although the radiosensitising ability of HDACi has been reported as early as 1990s, the mechanisms of radiosensitisation are yet to be fully understood. This review brings forth the various protocols used to sequence the administration of radiation and HDACi treatments in the different studies. The possible contribution of these various protocols on the ambiguity that surrounds the mechanisms of radiosensitisation is also highlighted.

As a widely used plastic, the aging and degradation of polyethylene (PE) are inevitable problems, whether the goal is to prolong the life of PE products or address the issue of white pollution. Molecular simulation is a vital scientific tool in elucidating the mechanisms and processes of chemical reactions. To obtain the distribution and evolution process of PE's thermal oxidation products, this work employs the self-consistent charge density functional tight binding (SCC-DFTB) method to perform molecular simulations of the thermal oxidation of PE with different crystallinity and branched structures. We discovered that crystallinity does not affect the thermal oxidation mechanism of PE, but higher crystallinity makes PE more susceptible to cross-linking and carbon chain growth, reducing the degree of PE carbon chain breakage. The branched structure of PE results in differences in pore size between the carbon chains, with larger pores leading to a concentrated distribution of O2 and free radicals subsequently formed. The breakdown of PE is slowed down when free radicals are localized in low-density regions of the carbon chain. The specifics and mechanism of PE's thermal oxidation are clearly revealed in this paper, which is essential for understanding the process in-depth and for the development of anti-aging PE products.

The term `motor control´ encompasses a wide range of mechanisms thought to be implicated in the organization of movements. Their study, like that of any other scientific field, must use specific notions to get to grips with them. This review is therefore organized along a series of notions that are frequently used in motor control, and we will discuss them with particular emphasis on neurological conditions, which may disrupt normal motor functioning. We will start with a short description of the roles of space and time, in which movements take place. Subsequently we will deal with kinematics and kinetics (dynamics) of movements. Then, we will list the inputs to motoneurons (MNs), which, in different forms, convey signals from the central nervous system (CNS) to skeletal muscles and muscle spindles, including central pattern generators (CPGs), sensory inputs and supraspinal descending fiber systems. Some helpers in movement organization will be introduced, such as internal models and neuronal network models. A relatively brief section on sensory-motor learning will follow because learning abilities are required to endow the sensory-motor system with flexibility and adaptability. The major emphasis is placed on neurological processes, which result from genetic modifications, autoimmune diseases, neurodegenerative diseases, infections in the nervous system as well as vascular and traumatic lesions. These neurological diseases lead to a variety of impairments and symptoms, particularly movement derangements including cerebellar ataxia, spasticity, and (other) movement disorders such as Parkinson’s syndromes. The conclusion is that there is no unique top controller that controls ´motor control`.

This study aimed to develop multifunctional nanoplatforms for both cancer imaging and therapy using superparamagnetic iron oxide nanoparticles (SPIONs). Two distinct synthetic methods, reduction-precipitation (MR/P) and co-precipitation at controlled pH (MpH), were explored, including the assessment of coating’s influence, namely dextran and gold, on their magnetic properties. These SPIONs were further functionalized with gadolinium to act as dual T1/T2 contrast agents for magnetic resonance imaging (MRI). Parameters such as size, stability, morphology, and magnetic behavior were evaluated by a detailed characterization analysis. To assess their efficacy in imaging and therapy, relaxivity and hyperthermia experiments were performed, respectively. The results revealed that both synthetic methods lead to SPIONs with similar average, 9 nm. Mössbauer spectroscopy indicated that samples obtained from MR/P consist of approximately 11-13% of Fe present in magnetite, while samples obtained from MpH have higher content, of 33%-45%. Despite coating and functionalization, all samples exhibited superparamagnetic behavior at room temperature. Hyperthermia experiments showed increased SAR values with higher magnetic field intensity and frequency. Moreover, the relaxivity studies suggested potential dual T1/T2 contrast agent capabilities for the coated SPpH-Dx-Au-Gd sample, thus demonstrating its potential in cancer diagnosis.

A common problem in education has always been to get students to achieve an adequate level of motivation and engagement. Many evidences show that gamification has the potential to make learning more engaging, motivating and effective. However, it is essential to design gamified experiences thoughtfully, ensuring that they align with educational objectives and promote meaningful learning outcomes, and so the lack of established design methodologies can lead to unintended consequences.

In the realm of smart transportation and mobility, delivery organizations are continuously refining their strategies, harnessing resources and advanced analytical techniques to streamline operations, aiming to achieve optimal solutions in terms of both efficiency and cost-effectiveness. However, a persistent challenge faced by these delivery companies revolves around the effective assignment of delivery personnel to customer orders, often grappling with suboptimal assignments that lead to inefficiencies and delays. To address this issue, we propose an architecture that uses the Munkres algorithm to optimize the task assignment problem for delivery personnel with pending orders, employing different cost functions obtained with deterministic and machine learning techniques. We compared the performance of linear and polynomial regression methods to construct different cost functions represented by matrices with orders and delivery people information. Subsequently, we applied the Munkres optimization algorithm to solve the assignment problem, which optimally assigns delivery people and orders. The results demonstrate that linear regression, used to estimate distance information, can reduce estimation errors by up to 568.52 km (1.51%) for our dataset compared to other methods. Conversely, polynomial regression proves effective in constructing a superior cost function based on time information, reducing estimation errors by up to 17,143.41 minutes (11.59%) compared to alternative methods. The proposed approach aims to enhance delivery personnel allocation within the delivery sector, optimizing the efficiency of this process.

Hepatitis C virus (HCV) is a major medical health burden and leading cause of chronic liver disease and cancer worldwide. More than 58 million people are chronically infected with HCV, with 1.5 million new infections occurring each year. An effective HCV vaccine is a major public health and medical need as recognized by the World Health Organization. However, due to the high variability of the virus and its ability to escape the immune response, HCV rapidly accumulates mutations making a vaccine a formidable challenge. An effective vaccine must elicit broadly neutralizing antibodies (bnAbs) in a consistent fashion. After decades of studies from basic research through clinical development, the antigen of choice is considered to be the E1E2 envelope glycoprotein due to conserved, broadly neutralizing antigenic domains located in the constituent subunits of E1, E2, and the E1E2 heterodimeric complex itself. The challenge has been elicitation of robust humoral and cellular responses leading to broad virus neutralization due to the relatively low immunogenicity of this antigen. In view of this challenge, structure-based vaccine design approaches to stabilize key antigenic domains have been hampered due to the lack of E1E2 atomic-level resolution structures to guide them. Another challenge has been development of a delivery platform in which a multivalent form of the antigen can be presented in order to elicit a more robust anti-HCV immune response. Recent nanoparticle vaccines are gaining prominence in the field due to their ability to facilitate a controlled multivalent presentation and trafficking to lymph nodes, where they can interact with both the cellular and humoral components of the immune system. This review focuses on recent advances in understanding the E1E2 heterodimeric structure to facilitate a rational design approach and the potential for development of a multivalent nanoparticle-based HCV E1E2 vaccine. Both aspects are considered important in the development of an effective HCV vaccine that can effectively address viral diversity and escape.

Many medicinal plants and their essential oils are used to treat or prevent diseases without the risk of mutagenicity, carcinogenicity, or teratogenicity. Eucalyptus essential oils are commonly used as preservatives, flavoring agents, and in various consumer goods. Eucalyptus leaves are being widely studied due to their volatile essential oils, including 1,8-cineole, p-cymene, α and β-pinene, limonene, citronellal, citral, eudesmol, terpinen-4-ol, terpineol, α–phellanderene, and 9β-sitosterol. Among these compounds, 1,8-cineole is the most abundant. Eucalyptus leaves are rich in flavonoids and phenolic compounds and are thus a great source of antioxidants. 2,2-diphenyl-1-picrylhydrazyl (DPPH), Ferric Reducing Antioxidant Power (FRAP), and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assays are used to measure antioxidant capacity. The antioxidant activity of Eucalyptus essential oil is stronger than that of standard antibiotics like Erythromycin, Cefixime, and Gentamicin due to the presence of significant terpenoids in addition to phenolic chemicals and flavonoids. The lower the IC₅₀ value, the higher the antioxidant potential. Phenolic compounds and flavonoids are often associated with beneficial health outcomes, including anti-inflammatory and antioxidant effects, anti-cancer properties, reduced risk of cardiovascular diseases, prevention of age-related neurodegenerative diseases, and prevention of Alzheimer’s disease. Flavonoids also play an essential role in plants, including protecting against reduction, fertility, reproduction, and infection. Due to their anti-inflammatory, anti-oxidative, and immune-modulatory properties, flavonoids are crucial for pharmacological, medical, and nutraceutical applications.

Deep learning is widely used in image segmentation, effectively identifying crops and weeds and contributing to the reduction of herbicide use. Traditional methods of applying pesticides over large areas are inefficient in dealing with weeds as needed, leading to massive waste of pesticides, high-cost production, and serious environmental pollution. This affects crop yield and quality. Although weed recognition using conventional deep learning methods has evolved over time, there are still challenges in weed extraction, detection, and segmentation. Accurate recognition and detection of weeds are essential prerequisites for implementing variable spraying. This paper proposes a semantic segmentation method based on UNet++ for complex environments where accurate identification of plants and weeds is challenging, targeting weeds in sugar beets, peas, and rice. An attention module is integrated into the upsampling process of UNet++, and UNet++ is used as a backbone network to effectively integrate multi-scale information, efficiently suppressing external noise interference. The UNet++ model with an integrated attention mechanism module achieves higher IOU than the general UNet++ model used in medical image analysis. This method effectively detects crops and weeds in complex backgrounds, providing reference material for the accurate application of robotic herbicides.

Metformin, a widely used anti-diabetic drug, has garnered attention for its potential in cancer management, particularly in breast and colorectal cancer. It is established that metformin reduces mitochondrial respiration, but its specific molecular targets within mitochondria vary. Proposed mechanisms include inhibiting mitochondrial respiratory chain Complex I and/or Complex IV, and mitochondrial glycerophosphate dehydrogenase, among others. These actions lead to cellular energy deficits, redox state changes, and several molecular changes that reduce hyperglycemia in type 2 diabetic patients. Clinical evidence supports metformin’s role in cancer prevention in type 2 diabetes mellitus patients. Moreover, in these patients with breast and colorectal cancer, metformin consumption leads to an improvement of survival outcomes and prognosis. The synergistic effects of metformin with chemotherapy and immunotherapy highlights its potential as an adjunctive therapy for breast and colorectal cancer. However, nuanced findings underscore the need for further research and stratification by molecular subtype, particularly for breast cancer. This comprehensive review integrates metformin-related findings from epidemiological, clinical, and preclinical studies in breast and colorectal cancer. Here, we discuss current research addressed to define metformin's bioavailability and efficacy, exploring novel metformin-based compounds and drug delivery systems, including derivatives targeting mitochondria, combination therapies, and novel nanoformulations, showing enhanced anticancer effects.

This study delves into the extraction and compositional analysis of soybean meal protein isolates (SMPI) compared to soy protein isolates (SPI), focusing on their functional and structural properties, digestibility, amino acid composition, and the impact of various proteases on antinutritional factors. By leveraging alkaline (0.25 % of NH4OH) extraction and isoelectric precipitation, SMPI was efficiently obtained. Compositional characteristics revealed that SMPI has high moisture, protein, and ash, but lower fat, and carbohydrate content compared to SPI. Alcalase, Neutrase and Pepsin hydrolysis indicated lower digestibility of SMPI than SPI. Fourier-transform infrared spectroscopy and sodium dodecyl sulfate-polyacrylamide gel electrophoresis provided similar molecular structure and protein molecular weight distribution. This comprehensive analysis underscores the valorization of soybean meal, promoting its use beyond conventional animal feed towards nutritional supplements and bio-based products, thereby contributing to environmental sustainability and the enhancement of global food systems.

A Infectious diseases account for about 3 million deaths per year. The advent of molecular techniques has led to an enormous improvement in their diagnosis, both in terms of sensitivity and specificity and in terms of the speed with which a clinically useful result can be obtained. Digital PCR, or 3rd generation PCR, is based on a series of technical modifications that result in more sensitive techniques, more resistant to the action of inhibitors and capable of direct quantification, without the need for standard curves.This review presents the main applications that have been developed for the diagnosis of viral, bacterial and parasitic infections, and the potential prospects for the clinical use of this technology.

Glioblastoma (GBM) is the most aggressive brain cancer. To model GBM in research, orthotopic brain tumor models, including syngeneic models like GL261 and genetically engineered mouse models like TRP, are used. In longitudinal studies, tumor growth and treatment response are typ-ically tracked with in vivo imaging, including bioluminescence imaging (BLI), which is quick, cost-effective, and easily quantifiable. However, BLI requires luciferase-tagged cells, and recent studies indicate that the luciferase gene can elicit an immune response, leading to tumor rejection and experimental variation. We sought to optimize the engraftment of two luciferase-expressing GBM models, GL261 Red-FLuc and TRP-mCherry-FLuc, showing differences in tumor take, with GL261 Red-FLuc cells requiring immunocompromised mice for 100% engraftment. Immuno-histochemistry and MRI revealed distinct tumor characteristics: GL261 Red-FLuc tumors were well-demarcated with densely packed cells, high mitotic activity, and vascularization. In con-trast, TRP-mCherry-FLuc tumors were large, invasive, and necrotic, with perivascular invasion. Quantifying tumor volume using the HALO® AI analysis platform yielded results comparable to manual measurements, providing a standardized and efficient approach for reliable high-throughput analysis of luciferase-expressing tumors. Our study highlights the importance of considering tumor engraftment when using luciferase-expressing GBM models, providing in-sights for preclinical research design.

Spatial planners are nowadays strongly interested in the benefits of greenspace for the health of urban residents. However, concrete and context-specific guidance on effective greening strategies is still lacking. We present a novel, model-based approach to support the development of such strategies. The approach is quantitative and spatially-explicit, and accounts for multiple health benefits as well as burdens. In this study, we applied the approach to the city of Maastricht (The Netherlands), and conducted an integrated, city-scale assessment of the health benefits and burdens of four urban greenspace designs. These included: ‘No greenspace’, ‘Current greenspace’, ‘Green parking lots and squares’, and ‘Optimized greenspace locations’. For each greenspace design, indicator values were calculated for five health determinants: heat stress, air pollution, perceived unsafety, unattractive views, and tick-bite risk. To assess the health contribution of urban greenspace in a given design, these indicator values were compared with the values in the ‘No greenspace’ design. The study produced clear, quantitative conclusions about the health benefits and burdens of the urban greenspace designs for the case of Maastricht, but also generated novel, more general insights relevant to planning of urban greenspace for health. These insights concern the importance of translating health policy objectives into specific target values or thresholds, and the importance of ‘smart’ choices in greenspace type and location that can effectively reduce trade-offs between health benefits and burdens. Priorities for future research, addressing limitations of the presented approach, concern a further expansion of the range of health benefits and burdens covered by the model, and the development of a common metric for the entire range of health benefits and burdens allowing optimization of greenspace design to maximize its overall net health benefit.

The ordinary 3D wave equation for nondissipative, homogeneous, isotropic media admits solutions where the point sources are permitted to move, but it does not admit solutions where the receiver is allowed to move. To overcome this limitation, the new wave equation is derived, permitting both the receiver and the source to move. This new wave equation is a generalization of the standard wave equation, and it reduces to the standard wave equation when the receiver is at rest. To derive this new wave equation, we first mathematically define a diverging spherical wave caused by the stationary point source. From this purely mathematical definition, the wave equation for the stationary source and the moving receiver is derived together with the corresponding free-space Green's function. Utilizing the derived Green's function, it was shown that this new wave equation also permits the solutions where both the receiver and the source are permitted to move. In conclusion, this paper demonstrates that, instead of an ordinary wave equation, the wave equation for the moving source and the moving receiver governs the waves emitted by the moving point sources and received by the moving receivers.

The adoption of technology and digital tools across various user groups has brought about a heightened risk of cyber-attacks targeting devices and shared data. These elevated levels of cybercrime necessitate thorough investigations to address victims’ inquiries about the nature, causes, affected data, and impacted resources of the attack. Digital forensics serves as a crucial means to answer these queries. Additionally, it enables the formulation of strategies and delineation of roles essential for fortifying future defenses against such attacks. Within digital forensics, digital evidence holds pivotal importance in the investigative process as it serves as a cornerstone in legal proceedings to identify perpetrators. Numerous research endeavors focus on devising solutions to safeguard evidence, including centralized storage centers or cloud computing. These efforts aim to create frameworks integrating diverse security levels for sharing and preserving evidence effectively. In this paper, a new framework is proposed that seeks to amalgamate novel technologies with forensic practices to address challenges in the preservation phase of digital forensics. Strategies include segmenting evidence into smaller components, leveraging steganography to support preservation, and employing blockchain technology to ensure the integrity of collected evidence.

This study develops a progressive optimal fault-tolerant control method based on insufficient fault information. By combining passive and active fault-tolerant control manners during the process of fault diagnosis, insufficient fault information is fully used, and optimal fault-tolerant control effect is achieved. In addition, the fault-tolerant control method based on guaranteed robust cost control is introduced. The proposed progressive optimal fault-tolerant control method considers two aspects. First, as the amount of fault information continually increases, the performance index of the progressive optimal fault-tolerant controller improves. Second, at each moment, based on the corresponding insufficient fault information and prior knowledge, optimal fault-tolerant control is achieved according to current fault information. The process of progressive optimal fault-tolerant control converges to active fault-tolerant control when the fault is completely identified and the optimal fault-tolerant controller is no longer reconfigured until no more useful fault information can be provided. Furthermore, a progressive optimal fault-tolerant control algorithm based on the grid segmentation in the parameter uncertainty domain and the selection of different auxiliary center points is introduced. The simulation results verify the feasibility of the proposed algorithm and the validity of the proposed theory.

The independence of commercial law and the independence of commercial trial are the key issues in the development of China's market economy, which is of great significance for maintaining the market order and protecting the rights and interests of consumers. With the development of China's market economy, the independence of commercial law and commercial trial has gradually become the focus of social attention. On the one hand, the independence of commercial law refers to the effective distinction between commercial law as a normative system and other laws, which has an independent social and economic basis and a unique role. On the other hand, the independence of commercial trial means that commercial trial has relatively independent space and procedures, which can effectively guarantee the fair settlement of commercial disputes.The independence of commercial law is reflected in many aspects, including commercial law ontology, normative structure and content, external relations and so on. Commercial law has the independent social and economic foundation and the unique role, and is the foundation of the development of market economy. The basic principles, adjustment objects, and system design of commercial law are independent, which makes commercial law play its unique role in social life. There are differences between commercial laws and other laws, such as civil law and economic law, in essence and in expression form, which makes commercial law irreplaceable.

With the use of linear regression modeling, this study sought to forecast and analyze rainfall patterns in Ethiopia. The dataset included historical rainfall data as well as pertinent independent variables. The R-squared score and mean squared error (MSE) were used to assess the effectiveness of the linear regression model. The results showed that the model's ability to forecast and analyze rainfall patterns was not very good. Only around 5.3% of the variance in rainfall could be explained by the chosen independent variables, according to the R-squared score of 0.053. This low number indicated that there was little correlation between the selected variables and rainfall, and that a sizable percentage of the variation in the dependent variable was not captured by the model. The model's accuracy in forecasting rainfall was shown to be quite low by the MSE error, with significant squared discrepancies between the expected and actual amounts. These results support the notion that the linear regression model as it is now designed is not appropriate for studying or forecasting Ethiopia's rainfall patterns. Alternative modeling approaches, the inclusion of other pertinent factors, and the assurance of the availability of high-quality data that faithfully captures the intricate dynamics of rainfall in the area all require more investigation.

Classically the walk in biped robotics was obtained controlling balance during the whole step, i.e. guaranteeing that the pressure point under the soles always stayed in the polygon of the supporting feet. However, this assumed that the feet were able to transfer torque to the ground during the whole gait cycle. In spite of the fact that the amount of transferrable torque in the feet-ground contact is limited, it is possible only during some phases of the step, and the overall process is energetically inefficient. On the other side, starting from the passive motion of the rimless wheel falling on an inclined surface, and ending to the inverted pendulum with a compass, balance in the whole was proven in spite of dynamical instability inside each step. Along this line results of Foot Placement Estimation (FPE) in 2-D and 3-D showed how energy efficient walk was possible, emulating the human walk with a free fall on the swing foot and energy restitution at the foot collision with the ground for the next step. This model assumes pointy feet, so without torque transfer to the ground. In the realm of FPE, in previous papers the present author adopted the 3-D inverted pendulum in polar coordinates (Spherical Inverted Pendulum - SIP) to introduce omnidirectional walks with arbitrarily changing characteristics. No torque control was used during the step, i.e the pendulum was always in free fall at each step, the only control actions were at the beginning of the next step. These actions are: the change of angular velocities at the start of a new step, with respect to those given after the collision (emulating the torque action in the brief double stance period), to recover for the losses, and the preparation of the position in the frontal and sagittal planes of the swing foot for the next collision. The present paper improves this paradigm, proposing a general model to account for all characteristics of the biped and of the gait, with adding a minimum of dynamical complexity with respect to the SIP. This model allows, not only to walk omnidirectionally on a flat surface, but also to go up and down staircases.

Soybean a pulse of considerable nutritional value due to its high protein, fibers and polyunsaturated fatty acid (PUFA) contents, also contains phytoestrogenic compounds that definitely hinder its recommendation for general consumption. Contrarily to ancient times when soybeans were boiled, modern commercial soy-foods can contain up to 150 mg/100g of estrogenic isoflavones. Interestingly, current estimations of isoflavone intake in the literature do not distinguish between the origins of soy-food i.e. home-made or commercial. As a result, the isoflavone exposure in Asian countries may well be over-estimated. This study aims to demonstrate, based on step-by-step monitoring of isoflavones, that traditional and domestic treatments, leveraging isoflavones water-solubility, can indeed significantly reduce their content in soy-foods. Indeed, when compared to commercial foods, the isoflavone contents was found to be 20, 2.6, 4.5 and 9.8 times lower in “home-made” soy-juice, tofu, tempeh and miso, respectively. Additionally, water soaking was found to reduce the isoflavones levels in soy-textured-proteins by more than 70%. Hence, this simple process has the potential to help drastically reduce overall xenoestrogens exposure. This study could serve as a basis for establishing the isoflavones Reference Dose and issuing food safety guidelines.

Additive manufacturing (AM) has revolutionized the field of biopolymers by providing a range of opportunities to create complex and intricate structures. Here we provide an overview of developments in biopolymer AM, first in the context of how natural systems have impacted the synthetic processes of AM, and secondly in the context of how synthetically derived structures can be used for biomedical applications. In particular, we explore the range of biopolymers developed for AM, AM techniques for biopolymers, and potential biocompatible medical applications with a focus on four categories of tissue in the human body: skin, bone, heart, and nerve. Despite the current challenges of the technology, exciting results in tissue regeneration, synthetic replacements for natural grafts, and complex dynamic organoids have already come to pass - with many more possible in the future.

The current paper provides a cutting-edge information data length- theoretic approach to human emotions. This is a revolutionary breakthrough that unifies information data length and the dynamics of emotions. The significant impact of both time and its mean value associate on both the upper and lower bounds of the obtained information data length is observed and noted. The paper concludes with some challenging open problems, combined with concluding remarks and future research pathways.

it still undergoes corrosion when exposed to corrosive environments. This paper proposes an evaluation method for assessing the corrosion level of SPCC steel specimens using traditional eddy current testing (ECT), along with two different machine learning approaches. The objective is to classify the corroded state of the specimens into two states: a less corroded state (state-1) and a highly corroded state (state-2). Generative and discriminative models were implemented for classification. The generative classifier was based on the Gaussian mixture model (GMM), while the discriminative model was based on the logistic regression model. The models used features based on the absolute maximum of the perturbation magnetic field components at two different frequencies. The performance of the classifiers was evaluated using metrics such as absolute error, accuracy, precision, recall, and F1 score. The results indicate that high classification accuracy can be achieved based on both methods using traditional eddy current testing.

The structural, elastic, and electronic properties of orthorhombic Cd2SiO4 and Hg2GeO4 were examined under varying pressure conditions using first-principles calculations based on densi-ty-functional theory employing the projector augmented wave method. The obtained cell pa-rameters at 0 GPa were found to align well with existing experimental data. We delved into the pressure-dependence of normalized lattice parameters and elastic constants. In Cd2SiO4, all lat-tice constants decreased as pressure increased, whereas in Hg2GeO4, parameters a and b de-creased while parameter c increased under pressure. Employing the Hill average method, we calculated the elastic moduli and Poisson’s ratio up to 10 GPa, noting an increase with pressure. Evaluation of ductility/brittleness under pressure indicated both compounds remained ductile throughout. We also estimated elastic anisotropy and Debye temperature under varying pres-sures. Cd2SiO4 and Hg2GeO4 were identified as indirect band gap insulators, with estimated band gaps of 3.34 eV and 2.09 eV, respectively. Interestingly, Cd2SiO4 exhibited a significant increase in band gap with increasing pressure, whereas the band gap of Hg2GeO4 decreased under pres-sure, revealing distinct structural and electronic responses despite their similar structures.

Lactic acid production from lactose by Lactiplantibacillus plantarum AC 11S was studied. The influence of initial substrate concentration was investigated, and optimal pH and temperature were determined. An unstructured mathematical model was developed comprising equations for bacterial growth, substrate consumption, and product formation. The model was solved with different terms for specific growth rates considering substrate and/or product inhibition. The best bacterial growth and lactic acid production were achieved at pH = 6.5 and 30 oC. Production of lactic acid was mainly growth-associated and at substrate concentration over 15 g/L a considerable product inhibition was observed. The parameters of different models were determined and compared. While the modified Gompertz equation gave the best fit for biomass growth, a variant of the logistic equation including a term for product inhibition described in the best way the entire set of equations comprising bacterial growth, substrate consumption, and product formation at different initial substrate concentrations.

This comprehensive review traces the transformative journey of genomic mapping, ushering in the era of "Genomic Atlas 2.0," characterized by advanced strategies and cutting-edge technologies. Beginning with a historical overview, it highlights the evolution from early linkage analysis to the current landscape shaped by high-throughput sequencing. Key breakthroughs are emphasized, showcasing the pivotal role of platforms such as Illumina and Oxford Nanopore in accelerating the identification of genetic variations. Long-read sequencing technologies, including PacBio and Oxford Nanopore, are explored as transformative elements overcoming limitations associated with short-read sequencing. The review delves into spatial genomics and chromatin conformation capture techniques, revealing the three-dimensional intricacies of the genome, with a particular focus on the revolutionary impact of Hi-C in understanding chromatin interactions. CRISPR technologies emerge as indispensable tools in Genomic Atlas 2.0, enabling targeted genome editing and the generation of precise genetic models. Functional genomics screens, utilizing RNA interference and CRISPR-based techniques, are discussed for their scalable precision in deciphering genome functions. Navigating challenges, the review addresses complexities in data integration and ethical considerations, offering strategies to ensure the robustness and ethical conduct of genetic mapping. Looking optimistically towards the future, it explores opportunities such as improved sequencing accuracy and novel applications of CRISPR technologies. Envisioning the expansion of genomics into personalized medicine, agriculture, and conservation biology, the review serves as a guiding resource for researchers, scientists, and students navigating the intricate terrain of Genomic Atlas 2.0.

The as-received commercial Inconel 718 material was solid solution heat treated (ST), cold rolled (CR), and precipitation hardened (PH) to investigate the effects of deformation on tensile properties, hardness, and texture. Three sets of specimens (0%, 20% and 50% CR) were STed at 1100 C/1h, CR and aged (720 °C/8 h + 650 °C/8 h) for the analysis. Ultimate tensile strength (UTS), 0.2% yield strength (YS) and elongation of 50% deformed condition were 1645 MPa, 1512 MPa, and 3.8 %, respectively. The 20 % deformation resulted in a balanced UTS (1348 MPa), YS (1202 MPa) and elongation (11%). Contributions of precipitation hardening to the strength was decreasing, while contribution of CR increases with increasing percentage of deformation. Correspondingly, the size and quantities of  decreased with increasing deformation level. In CR specimens, a high density of nano/micro twins were generated with the twin planes oriented perpendicular to the RD-ND surface. The preferred rotation of the crystals generated the gradient of orientation and internal features of the large austenitic grains. The cross-slip of screw dislocations induced a complete β-fibre, consisting of {110}, {112}, and{123}, with doubled intensity at higher deformation. In addition, the specimens tended to be highly susceptible to the twinning-induced orientation emerged by a predominant ⫽ND. An incomplete but intense α-fibre clustered between {110} and {110} was characterized in the as-deformed condition. Besides achieving highest strength, the current work demonstrates the effects of CR on the material strength without the complex influences of  precipitate.

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

This study provides a comprehensive investigation of lactic acid bacteria (LAB) isolated from Argentinean Capsicum annum L. The research covers important aspects, including genotypic characterization, bacterial stress tolerance, adhesion ability, safety evaluation, and functional and technological properties. The predominant isolates were identified as Lactilactobacillus curvatus and Lactiplantibacillus plantarum. Rep-PCR analysis grouped the isolates into 11 clonal groups. Lp. plantarum LVP 40 and LV 46; Levilactobacillus brevis LVP 41, Pediococcus pentosaseus LV P43, and Lt. curvatus LVP44, displayed both safety and resilience against adverse conditions such a slow pH, bile, and simulated gastric and intestinal juices. Moreover, the LAB strains exhibited high hydrophobicity and auto-aggregation percentages, NaCl tolerance, and substantial acidifying capacity. LAB supernatants demonstrated promising surfactant and emulsifying properties. Likewise, they differentially inhibited Staphylococcus aureus and Pseudomonas aeruginosa biofilms, showcasing their potential as antipathogenic agents. Noteworthy some strains displayed considerable co-aggregation with these pathogens, and several isolates showed an effective antimutagenic and detoxifying power, further emphasizing their multifaceted capabilities. Five pepper bacterial strains showcased probiotic properties, suggesting their potential for gut health enhancement. In summary, these LAB strains hold promise as vegetable fermentation starters, contributing to food safety and versatile applications in food science.

The retinal pigment epithelium (RPE), which ensures the normal functioning of the neural retina, is a pigmented single-cell layer that separates the retina from the Bruch's membrane and the choroid. There are three main types of pigment granules in the RPE cells of the human eye: lipofuscin granules (LG) containing the fluorescent “age pigment” lipofuscin, melanoprotein granules (melanosomes, melanolysosomes) containing the screening pigment melanin and complex melanolipofuscin granules (MLG) containing simultaneously both types of pigments - melanin and lipofuscin. This review examines the functional role of pigment granules in the aging process and in the development of oxidative stress and associated pathologies in RPE cells. The focus is on the process of light-induced oxidative degradation of pigment granules caused by reactive oxygen species. The reasons leading to increased oxidative stress in RPE cells as a result of oxidative degradation of pigment granules are considered. A mechanism has been proposed to explain the phenomenon of age-related decline in melanin content in RPE cells. The essence of the mechanism is that when the lipofuscin part of the melanolipofuscin granule is exposed to light, reactive oxygen species are formed, which destroy its melanin part. As more melanolipofuscin granules are formed with age and the development of degenerative diseases, the melanin in pigmented epithelial cells ultimately disappears.

This article examines the diagnosis of the Agricultural Innovation System (SIA) in the department of Tolima, Colombia, as part of a project led by the Colombian Ministry of Agriculture and Rural Development and the Technological University of Pereira (TUP), which also evaluated the National Agricultural Innovation System (NAIS) in regions such as Chocó, Bolívar, and Meta. A methodology was used that involved a survey with 58 questions on a Likert scale to 300 participants, evaluated with congruence and relevance indexes, identifying key variables in the operation of the Agricultural Innovation System (AIS). A survey was also applied to actors of the National Innovation System for Higher Education in Agriculture, A survey was also applied to map the participating actors in the regional agricultural innovation systems of Tolima to identify gaps in extension, innovation, development, sustainability, ICT, education and training. Among the conclusions, it stands out that the associativity subsystem presents the lowest lag and is close to a score of two on the scale of gaps, evaluation carried out among the five subsystems including extension, ICT, environmental aspects, and pub-lic policy. The department of Tolima shows low performance in innovation and ICT, while the extension is less lagging. In Chaparral there is a general lag, with innovation being the worst evaluated subsystem. Rovira obtains high scores in most subsystems, although innovation and ICT have lower scores. At the national and regional levels, innovation is low, and articulation among NARS actors is insufficient, which highlights the need to promote good practices, strategies, and projects.

Tinnitus is a symptom often associated with hearing loss (HL) and is in many cases more burdening to the individual than the HL itself. Many approaches have been made to explain the development and chronification of the phantom percept as well as different treatment strategies to lower the tinnitus related burden. In many studies, the variance of the HL data is high and therefore the interpretation of specific data might be difficult. With this retrospective study, we attempt to explain a part of this variance by investigating specifically the effects of non-auditory comorbidity categories on pure-tone audiometric data in a tinnitus patient collective that was homogeneous with respect to auditory comorbidities. We found age dependent as well as number of non-auditory comorbidity (e.g. diabetes mellitus) dependent differences in the mean HL of the tinnitus patients as well as differences in the peak HL frequency relative to the tinnitus frequency. The analysis of the age dependent HL within the different non-auditory comorbidities revealed specific – partially opposed – effects of endocrine, circulatory, muscle-skeletal and digestive disease categories on the hearing thresholds of tinnitus patients. Taken together we argue that in future tinnitus (and non-tinnitus) patient studies also non-auditory comorbidities should be taken into account as possible covariables that might explain the variance found in the auditory threshold development of these patients.

Dry periods and drought are inherent natural occurrences. However, due to the increasing pressures of global warming and climate change, these events become more frequent and severe on a global scale. These phenomena can be traced with various indicators and related indices proposed by various scholars. In general, drought risk assessment is done by modelling these indicators and determining the drought occurrence probabilities. The proposed adaptation introduces the "Kaplan-Meier Estimator," a non-parametric statistic traditionally used in medical contexts to estimate survival functions from lifetime data. The study aims to repurpose this methodology to assess drought risk by treating past droughts as "events" and evaluating the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) and map these results for a better understanding of the drought risks within larger spatial scales such as a river basin. The adapted method provides the probability of non-occurrence, with inverted results indicating the likelihood of drought occurrence. As a case study, the method is applied to SPI and SPEI values at different time steps (3, 6, and 12 months) across 27 meteorological stations in the Gediz River Basin, located in Western Turkey—a region anticipated to be profoundly affected by global climate change. The results are represented as the generated drought risk maps and curves, which indicate that (i) drought risks increase as the considered period extends, (ii) drought risks decrease as the utilized indicator timescales increase, (iii) locally plotted drought curves indicate higher drought risks as their initial slope get steeper. The method used enables the generation of historical evidence based spatially distributed drought risk maps which expose more vulnerable areas within the river basin.

The rapid advancements and the merging of hybrid quantum-classical computing, artificial intelligence (AI), machine learning (ML), and deep learning (DL) pose a potentially unseen and significant threat to encryption that may impact Post-Quantum Cryptography (PQC) transition timelines. There is a direct hybrid quantum-classical computing threat on cryptography, and there is also a direct threat AI/ML on cryptography. However, the synergistic combination of these technologies presents known and unknown threats that need attention, focus action, and research. This paper reviews Grover's Adaptive Search (GAS), which combines Grover's Algorithm with adaptive techniques to optimize search further, potentially making it even more efficient for attacking encryption. This work also examines the quantum-accelerated Harrow-Hassidim-Lloyd (HHL) Algorithm, designed to solve systems of linear equations exponentially faster than classical algorithms in certain conditions. The HHL algorithm can solve some lattice-based problems, which have implications for lattice-based encryption. This technological confluence and its potential impact on cryptography and encryption necessitate a proactive and coordinated approach to developing and implementing quantum-resistant AI/ML cryptographic solutions. This paper reviews the technological confluence and its potential implications for classical cryptography and PQC transition timelines and calls for further research.

XPS and ARXPS characterization of surface layers resulting from the functionalization of polymers such as PVC modified with MPTMS and APTES is challenging due to the signals overlap, deriving both from the substrate and the functionalized layers. In this work, a freshly cleaved, ideally flat gold surface was used as carbon-free model substrate functionalized with MPTMS and subsequently grafted with APTES. Avoiding the overlap of signals from carbon atoms present in the substrate, the signals in the C1s, O1s, Si2p, S2p and N1s high-resolution spectra could be assigned to the MPTMS / APTES functionalized layer only and the curve fitting parameters could be determined. Quantitative analysis was in very good agreement with the expected stoichiometry of the functionalized layer, confirming the adopted curve fitting procedure. In addition, it was found that one molecule of APTES grafted two MPTMS via silane groups. ARXPS allowed determining the thickness of the functionalized layers: MPTMS thickness was found to be 0.5 (0.2) nm, MPTMS + APTES thickness 1.0 (0.2) nm in good agreement with Avogadro model calculations. This approach can be considered a powerful tool for characterising functionalized surfaces of more complex systems by XPS.

Human endogenous retroviruses (HERV) are remnants of ancient retroviral infections that, over millions of years, became integrated into the human genome. While normally inactive, environmental stimuli such as infections have contributed to the transcriptional reactivation of HERV promoting pathological conditions including the development of autoimmunity, neurodegenerative disease and cancer. What infections then trigger HERV activation? Mycobacterium avium subspecies paratuberculosis (MAP) is a pluripotent driver of human disease. Aside from granulomatous diseases Crohn’s, sarcoidosis and Blau syndrome, MAP is associated with autoimmune disease: type one diabetes (T1D), multiple sclerosis (MS), rheumatoid arthritis and autoimmune thyroiditis. MAP is also associated with Parkinson’s disease. Autoimmune diabetes, multiple sclerosis and rheumatoid arthritis are the diseases with the strongest MAP/HERV association. There are several other diseases associated with HERV activation including diseases whose epidemiology and/or pathology would prompt speculation for a causal role of MAP. These include non-solar uveal melanoma, colon cancer, glioblastoma and amyotrophic lateral sclerosis (ALS). This article further points to MAP infection as a contributor to autoimmunity, neurodegenerative disease and cancer via unsilencing of HERV. We examine the link between the ever-increasing number of MAP- associated diseases, the MAP/HERV intersection with these diverse medical conditions and propose treatment opportunities based upon this association.

Robotic odor source localization (OSL) is a technology that enables mobile robots or autonomous vehicles to find an odor source in unknown environments. An effective navigation algorithm that guides the robot to approach the odor source is the key to successfully locating the odor source. While traditional OSL approaches primarily utilize an Olfaction-only strategy, guiding robots to find the odor source by tracing emitted odor plumes, our work introduces a fusion navigation algorithm that combines both vision and olfaction-based techniques. This hybrid approach addresses challenges such as turbulent airflow, which disrupts olfaction sensing, and physical obstacles inside the search area, which may impede vision detection. In this work, we propose a hierarchical control mechanism that dynamically shifts the robot’s search behavior among four strategies: crosswind maneuver, Obstacle-avoid Navigation, Vision-based Navigation, and Olfaction-based Navigation. Our methodology includes a custom-trained deep-learning model for visual target detection and a moth-inspired algorithm for Olfaction-based navigation. To assess the effectiveness of our approach, we implemented the proposed algorithm on a mobile robot in a search environment with obstacles. Experimental results demonstrate that our Vision and Olfaction Fusion algorithm significantly outperforms Vision-only and Olfaction-only methods, reducing average search time by 54% and 30%, respectively.

In recent years, an interest in multimedia services has grown expeditiously where the main part is comprised of video. Firms as well as subscribers require higher resolutions, framerates and sampling precision which results to higher amount of data need for processing, storing and transmitting. Therefore, a big challenge arises for researchers to develop new compression standards which should reduce the huge amount of data and keep quality at the same level. This paper examines compression performance of the latest and currently most used video codecs, namely H.266/VVC, AV1, H265/HEVC and H.264/AVC. The test set consists of seven sequences with various content at 8K, Ultra HD and Full HD resolution and encoded to bitrates from 1 to 15 Mbps for Full HD and Ultra HD resolutions and from 5 to 50 Mbps for 8K resolution, respectively. Codec performance was measured using PSNR, SSIM and VMAF objective quality metrics. In terms of the Bjøntegaard-Delta (BD) model, the results showed that H.266/VVC outperforms all other codecs, namely H.264/AVC,H.265/HEVC and AV1, respectively. Averaged bitrate savings were approximately 78\% for H.266/VVC, 63\% for AV1 and 53\% for H.265/HEVC relative to H.264/AVC, 59\% for H.266/VVC, 22\% for AV1 compared to H.264/AVC and 46\% for H.266/VVC relative to AV1, all for 8K resolution. The results also showed that the performance varies depending on resolution – with higher resolution, the efficiency of newly developed codecs such as H.266/VVC and AV1 is greater, which confirmed the fact that the H.266/VVC and AV1 codecs have been primarily developed for videos at high resolutions as 8K and/or UHD.

Abstract: Community forests are being promoted in Togo as an alternative to the degradation of protected areas and as a means of restoring forest landscapes. The present study is carried out within Kouampante Community Forest (KCF) in Ogaro (Togo, West Africa). It intends to contribute to the sustainable management of KCF. Specially, it aims at: (i) mapping forest ecosystems and analysing their dynamic and (ii) characterising the floristic diversity of the KCF. Forest ecosytems are mapped and their dynamic evaluated based on Google Earth images of 2010 and 2020. The floristic and silvicultural analyses are based on inventories carried out in 13 plots of 1,000 m² each. The KCF is made up mainly by tree/shrub savannahs (58.73%) and croplands/fallow (41.27%) in 2010. These two land use types have undergone changes over the period. In 2020, the KCF had two land use types: tree/shrub savannahs (84.30%) and croplands/fallows (15.70%). The flora census consisted of 59 species grouped in 6 families. The most important plant species are Detarium microcarpum and Vitellaria paradoxa. The Fabaceae were the most abundant and diversified families, followed by the Combretaceae. The demographic structure showed a high abundance of individuals with small diameter and height. This indicates the possibility of a rapid restoration of the native vegetation. Protecting the forest from anthropogenic threats could be crucial for achieving the desired objective.

Leptospira, which are known to be important disease-causing agents transmitted between animals and humans, results in significant illness and, in some cases, significant death in human populations. This study aims to examine the genomic structure of Leptospira interrogans serovar Copenhageni strain FDAARGOS_203 to identify the specific genetic factors that contribute to antimicrobial resistance (AMR) and defense against phages. The genome, consisting of two contigs totaling 4,630,574 base pairs, underwent thorough examination for protein-coding sequences, transfer RNA genes, and ribosomal RNA genes. A total of twenty-two antibiotic resistance genes that specifically target essential cellular processes such as cell wall synthesis, DNA replication, and protein synthesis have been identified. Significant among these were gidB, GdpD, and PgsA, each involved in separate aspects of antibiotic resistance. In addition, the investigation explored the defense mechanisms of bacteriophages, revealing the presence of defense islands that contain a range of anti-phage systems, including RM_Type_IV, PrrC, Borvo, CAS_Class1-Subtype-IC, and CAS_Class1-Subtype-IB. This comprehensive genomic analysis enhances our understanding of the molecular mechanisms that determine Leptospira's ability to adapt to various environments. The identified genetic factors linked to AMR and defense against phages not only enhance our scientific comprehension but also provide a basis for focused interventions to reduce the impact of leptospirosis.

Studies have established the crucial role of sleep among the students which plays a significant role in their mood. This study aimed to examine the mood disorders and sleep quality among undergraduate students at the University of Georgia (UG) and comparison between students’ nationality.This cross-sectional study was a self-reported questionnaire comprised of demographics including age, gender, year of study, current location, lifestyle data (Exercise and smoking), the Depression, Anxiety, and Stress Scale (DAS21) and the Pittsburgh Sleep Quality Index (PSQI). We performed a descriptive analysis, and the Chi-square was statistically significant at p<0.05. The prevalence was at a 95% confidence interval (95% CI) as multivariate analysis examined the multicollinearity. The female students were most of the respondents, below the age of 20 years. The student's mean age was 20.20 (SD± 3.0). DAS report presented 72.7% of students with depressive symptoms, 77.8% with anxiety symptoms, and 62.2% had stress. Georgian students were more at risk of having depressive complaints (95% Cl[1.567-3.788]), anxiety (95% Cl[1.612-4.285]), and stress symptoms (95% Cl[1.743-3.831]). There was a strong relationship between the students who experienced poor sleeping patterns and depressive complaints (aOR 0.10). The students who were smokers (aOR 0.39) were more likely to report anxiety symptoms than the students that do not exercise (aOR 1.68). It was observed that students with depressive symptoms, anxiety, and complaints of stress had a significantly high risk of poor sleep quality. Further studies are recommended to curb psychological symptoms of mood changes in association with sleep disorders among students.

Risk management for technological hazards mainly focuses on the consequences on human lives. Although technological risk analysis evaluates environmental vulnerability, it does not reflect the consequences on environmentally exposed elements, such as rivers, water springs, flora, and fauna. This paper's objective was to propose a conceptual framework and create a multidisciplinary evaluation model for environmental risk analysis in the oil and gas industry. Initially, the problem was approached from a global perspective to justify the necessity of a holistic environmental risk analysis methodology in the oil industry, using environmental risk factors as well as underlying factors, such as environmental fragility and lack of resilience. The holistic assessment was carried out based on probabilistic risk analysis methodologies to obtain a holistic environmental risk index, HERI. This methodology was applied to an oil and gas industry company in Colombia. This allowed greater disaggregation of the results to establish priorities for risk reduction actions and identify the company's weaknesses.

The spread of high-performance personal computers, frequently equipped with powerful Graphic Processing Units (GPU), raised the interest on a set of techniques able to extract models of electromagnetic phenomena (and devices) directly from available examples of the desired behavior. Such approaches are collectively referred to as Machine Learning (ML). A typical representative ML approach is the so called “Neural Network” (NN). Using such data-driven models allows evaluating the output in a much shorter time when a theoretical model is available, or allows predicting the behavior of the systems and devices when no theoretical model is available. With reference to a simple yet representative benchmark electromagnetic problem, some of the possibilities and the pitfalls of the use of NN for the interpretation of measurements (inverse problem) or to obtain the required measurements (optimal design problem) are discussed. The investigated aspects include the choice of the NN model; the generation of the dataset(s); the selection of hyperparameters (hidden layers, training paradigm). Finally, the capabilities in the handling of ill-posed problems are critically revised.

Urinary infections are very prevalent in pregnant women and are a cause for great concern con-sidering the negative impacts they can have on both, the mother and the baby. The objectives were characterize urinary infections associated with pregnant women, study the most prevalent strains in urinary infections in pregnant women and analyze the antibiogram of the most prevalent strains in infections in pregnant women. A retrospective observational study was carried out on all posi-tive urine cultures from pregnant women between January 2018 and December 2022 at a Hospital Center in the Center of Portugal, totaling 201 samples. Data were collected with computer support, including age, origin, previous antibiotic therapy, catheterization, isolated bacteria and tested an-tibiotic therapy. The majority of pregnant women were in the third trimester of pregnancy and came from the External Consultation. The most identified bacteria was Escherichia coli, followed by Streptococcus agalactiae. Regarding the interaction with antibiotics, Escherichia coli showed total sensitivity to one antibiotic, while Streptococcus agalactiae showed sensitivity to four anti-biotics in 2022. This work contributes to the knowledge of urinary infections in pregnant women in the center of the country, being a contribution to the continued improvement of the care provided

Additive Friction Extrusion Deposition (AFED) is a recently developed additive manufacturing technique that promises high deposition rates at low forces. Due to the novelty of the process, the underlying phenomena and their interactions are not fully understood, and in particular the processing strategy and tool design are still in their infancy. This work contributes to the state of the art of AFED through a comprehensive analysis of its working principles and an experimental program including a representative sample component. The working principle and process mechanics of AFED are broken down into their individual components. Forces, their origins and effects on the process are described, and measures of process efficiency and theoretical minimum energy consumption are derived. Three geometrical features of the extrusion die are identified as most relevant to the active material flow, process forces and deposition quality: the topography of the inner and outer circular surfaces and the geometry of its extrusion channels. Based on this, the experimental program investigates seven different tool designs in terms of efficiency, force reduction and throughput. The experiments using AA 6061-T6 as feedstock show that AFED is capable of both high material throughput (close to 550 mm³/s) and reduced substrate forces: For example, the forces for a run at 100 mm³/s remained continuously below 500 N, and for a run at 400 mm³/s below 3500 N. Material flow and microstructure of the AFED are assessed from the macrosections. Significant differences are found between the advancing and retracting sides for both process effects and material flow. Banded structures show strong similarities to other solid state processes. The fabrication of the sample components demonstrates that AFED is already capable of producing industrial grade components. In mechanical testing, interlayer bonding defects result in a more brittle failure behavior in the direction of the structure, in the microstructure show strong similarities to other solid-state processes. The manufacturing of the sample components demonstrates that AFED is already capable of producing industrial grade components. In mechanical tests, interlayer bonding defects result in a more brittle failure behavior in the direction of the structure, while in the horizontal direction of the structure mechanical properties corresponding to a T4 temper have been achieved.

In the past few decades, the transmission of data over an unsecure channel resulted in an increased rate of hacking. Therefore, the requirement to make multimedia data more secure is increasing day by day. Numerous algorithms are developed to improve efficiency and robustness. In this article, a novel and secure image encryption algorithm is presented. It is based on a modified chaotic logistic map (CLM) that provides the advantage of having less computational time to encrypt an input image. The encryption algorithm is based on Shannon’s idea of using substitution-permutation and one-time-pad network to achieve ideal secrecy. The CLM is used for substitution and permutation to improve randomness and increase dependency on the encryption key. Various statistical tests are conducted, such as Key Space Analysis, Complexity Analysis, Sensitivity Analysis, Strict Avalanche Criteria (SAC), Histogram Analysis, Entropy Analysis, Mean of Absolute Deviation (MAD) Analysis, Correlation Analysis, Contrast Analysis, and Homogeneity to give a comparative analysis of the proposed algorithm and verify its security. As a result of various statistical tests, it is evident that the proposed algorithm is more efficient and robust as compared to previous ones.

Background: Nursing home residents (NHRs) have special needs and may experience reduced functionality, higher sedentary behavior time (SBT) and decreased physical activity (PA). This study aimed to characterize NHRs based on SBT, PA, and functional performance (FP), and to identify associations between these factors. Methods: Cross-sectional study with 65 NHRs aged ≥60, evaluated by accelerometer (SBT, PA) and the following tests: Timed Up and Go (TUG), Short Physical Performance Battery (SPPB), Barthel Index (BI), and Mini-Mental State Examina-tion (MMSE). Health-related variables and anthropometry were assessed. The FP (TUG, SPPB, BI), SBT, PA intensities were used for K-means clustering analysis. Results: The cluster analysis identified: C1 – better FP, shorter SBT, and longer time in PA intensities; C2 - lower FP, longer SBT, and shorter time in PA. In addition, C2 were older, with lower MMSE, lower body mass index, and walking aids use. The SBT showed a negative weak correlation with BI. The moderate PA (MPA) was moderately correlated with the SPPB and strongly correlated with the TUG and BI. Conclusions: MPA is strongly associated with better FP and independence. NHRs have dif-ferent physical and cognitive profiles, which indicates the need for personalized strategies to prevent disability and increase PA.

Numerous scientific fields employ entropy, the Shannonian measure of disorder and inaccessible information. Current paper examines educational uses of entropy. The major objectives of this survey are to create a coherent perspective of the applicability of classical entropies and to provide a concise detailed explanation that blends technical pertinence with conceptual extraction from the most recent literature. What's more intriguing are the closing thoughts mixed with a few unsolved issues and the creation of a future work schedule in these areas.

The dimethylaminophenyl-substituted silver phthalocyanine [dmaphPcAg] can be used as a UV-vis photoinitiator for in situ preparation of a silver/polymer nanocomposite. To verify early steps of the supposed mechanism of radical polymerization, we performed quantum chemical calculations of m[dmaphPcAg]q complexes with charges q = +1 to -2 in the two lowest spin states m, of a free ligand and its dehydrogenated/deprotonated products m[dmaphPcHn]q, n = 2 to 0, q= 0, -1 or -2, in the lowest spin states m. The calculated electronic structures and electron transitions of all the optimized structures in CHCl3 solutions are compared with experimental EPR and UV-vis spectra, respectively. The unstable 3[dmaphPcAg]+ species deduced only from previous EPR spin trap experiments was identified. In addition to 2[dmaphPcAg]0, our results suggest the coexistence of both reaction intermediates 1[dmaphPcAg]- and 3[dmaphPcAg]- in reaction solutions. Silver nanoparticle formation is a weak point of the supposed reaction mechanism from the energetic, stereochemistry, and electronic structure points of view.

Nereis as a mudflat organism has a variety of uses, in the history of China as a Chinese herbal record, because of its body contains rich amino acids, fatty acids and other nutrients, it can be used for therapeutic treatment and treatment can also be used as health care products. acids, fatty acids and other nutrients, it can be used for therapeutic treatment and treatment can also be used as health care products. In modern times, more and more researchers have studied the protease extract of Nereis as a mudflat organism. In modern times, more and more researchers have studied the protease extracted from the body of nereis and found that there are a variety of functional proteins in nereis, including superoxide dismutase, superoxide dismutase, superoxide dismutase and superoxide dismutase. More and more researchers have studied the proteases extracted from the body of nereis and found that there are a variety of functional proteins in nereis, including superoxide dismutase, adenylate cyclase, glycosidase, and plasminase. In this paper, the functional proteases in the extracts of nereis were summarized, and the functions and characteristics of proteases in nereis were discussed from the perspective of molecular structure.

In recent years, there has been a surge of proposals for innovative approaches to public planning. It has become apparent that the traditional emphasis on "economic development" as the predominant objective of public policy is no longer adequate to promote a thriving society. Common Agricultural Policy in Europe faces challenges to adopt and implement the dynamic of culture. However, culture as a pillar of sustainable development is not a new topic. This concept has been incorporated into economic studies with increasing tension. The present study aims to measure scientific interest through published scientific studies and papers related to the contribution of culture in the context of European development programs and strategies. A total of (n=902) published documents during the period 1990-2023 from the Scopus database were explored to identify (n=27) appropriate publications for research analysis based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach and flow diagram. Bibliometric analyses using Vos Viewer (Center for Science and Technology Studies, Leiden University, Leiden, The Netherlands) and constructed term co-occurrence network plots based on bibliometric evidence were performed. The results show that there was no scientific interest. The systematic review and bibliometric analysis of the present paper could provide a valuable and seminal reference for the researchers of rural development and the relevant policymakers.

Large-scale crowd phenomena are complex to model because the behaviour of pedestrians needs to be described at both strategic, tactical, and operational levels and is impacted by the density of the crowd. Microscopic models manage to mimic the dynamics at low densities, whereas mesoscopic models achieve better performances in dense situations. This paper proposes and evaluates a novel agent-based architecture to enable agents to dynamically change their operational model based on local density. The ability to combine microscopic and mesoscopic models for multi-scale simulation is studied through a use case of pedestrians at the Festival of Lights, Lyon, France. Pedestrian outflow data is extracted from video recordings of exiting crowds at the festival. The hybrid model is calibrated and validated using a genetic algorithm that optimizes the match between simulated and observed outflow data. Additionally, a local sensitivity analysis is then conducted to identify the most sensitive parameters in the model. Finally, the performance of the hybrid model is compared to different models in terms of density map and computation time. The results demonstrate that the hybrid model has the capacity to effectively simulate pedestrians across varied density scenarios while optimizing computational performance compared to other models.

Sensory processing is a crucial function of the nervous system that significantly affects a large portion of the population, particularly older individuals who may be dealing with different forms of dementia. The global population of people aged 65 or older has reached a substantial count of around 703 million, representing approximately 9% of the total global population. Within this demographic, an estimated 5-8% of those aged 60, highlighting the growing need to address sensory modulation challenges for healthy aging. Sensory diet, derived from sensory integration theory, provide a tailored approach to modulating sensory experiences and triggering neuroplastic changes in the brain. Recent neuroimaging studies have revealed intricate structural and functional alterations in the brain associated with the implementation of sensory diets. Furthermore, the integration of the Metaverse, augmented reality, and virtual reality has opened up personalized experiences, fostering cognitive stimulation and emotional well-being for individuals during aging. This article offers a comprehensive exploration of the effectiveness of sensory diets in enhancing attentional control, self-regulation, and alleviating sensory-related distress among the healthy aging and dementia population. By employing precise quantitative evaluations such as sensory processing scales and advanced neuroimaging methodologies, it presents solid evidence of the tangible impact of these interventions. Emphasizing the importance of interdisciplinary cooperation and leveraging technological advancements, the article underscores the crucial need for customized sensory diets to optimize sensory processing and improve the overall well-being of older individuals contending with sensory modulation challenges and dementia.

In archaea, the interaction of HerA helicase and NurA nuclease is required for 3' end resection during DNA double-stranded break repair, and its disruption results in unfaithful DNA repair. Interactions transpire by the four conserved domains, including the N-terminal HAS domain (HerA-ATP synthase), which serves as a binding site for the exonuclease NurA. As a HerA hexamer between its two subunits, the conserved C-terminal brace extension functions as an adjacent brace. DBD serves as a location for DNA binding, which causes the DNA strands to be propelled into the HerA pocket to begin unwinding. The putative pore entrance is made up of four helix coils, which provide a suitable charged surface for guiding DNA into the pore. The crystal structure of the complex HerA-NurA allows for the identification of key residues for protein-protein interaction. This allows us to predict that most archaeal HerA orthologs will be able to interact with one another. Archaeal HerA is a homo-hexameric assembly featuring a DNA-binding domain that is conserved. It also features distinctive ATP and NurA binding domains. Following the structure and sequence conservation criteria, we find one HerA ortholog in Pyrobaculum calidifontis and multiple HerA paralogs, but the role of none is established yet.Interestingly, orthologous HerA is part of an Mre11-Rad50 gene neighborhood while paralogous HerA is not, which could be misleading. As a result, it sought to describe the criteria that may be used as a possible fingerprint for identifying orthologous genes, as well as the cloning procedures and tactics that would aid in the confirmation of the HerA helicase in P. calidifontis. Their confirmation is based on PCR cloning and characterization following HerA construct creation.

Residual sugars (RS) in wine are the sugars that remain in a wine after fermentation is complete. In some wine styles, such as semi-dry wines, the accurate measurement of the RS concentration is critical for both qualitative and legislative reasons. Brix, measured by a simple refractometer, can give a good estimation of the RS concentration in the must, but during fermentation, the presence of alcohol leads to inaccurate sugar measurements. In order to measure the RS accurately, other more precise techniques are used, most of which are expensive or require professional skills. Therefore, novel approaches for rapid, easy, and practical measurements for estimating the sugar content were suggested over the years. However, most of these methods do not supply an actual measurement of RS but rather give brix values, and those that measure RS involve special equipment, which is less relevant for small wineries. This study suggests a novel model for predicting and controlling the wine's residual sugar. The data the model uses is the initial brix of the must before fermentation and its density during fermentation. The model was created by measuring actual residual sugars during the fermentation of natural and synthetic musts, with various degrees of initial brix levels, while simultaneously measuring their densities and correlating the two measurements. Linear regression between the residual sugar of the wine and its density was obtained for all treatments and repetitions (i.e., different values of must initial brix) with R² values above 0.97. Using the model, one can calculate (before commencing the fermentation) the density values at which the fermentation will reach a particular desired residual sugar value for a specific initial brix level; the model is applicable for the fermentation conditions used in this work, i.e., brix levels of 18-27˚Bx, Saccharomyces cerevisiae strains (fx-33 and fx-10) in common conditions of fermentation regarding temperature and aeration.

(1) Background: Interparental conflict is a phenomenon that poses a serious threat not only to the quality of life for the couple but also to the father-child relationship, mother-child relationship, and well-being of adolescents. This study examined the influence of marital conflict on father-child and mother-child attachment and the psychosocial adjustment (2) Methods: 67 adolescents involved in Child Welfare Services (CWS) in disadvantaged neighbourhoods in southern Spain were examined. The sample was split into two groups according to the exposure to marital conflict. Subsequently, differences between groups were analysed on father attachment, mother attachment, aggression, antisocial behaviour, and emotional intelligence. (3) Results: Primarily, the data showed significantly worse attachment with the father among conflict-exposed versus non-conflict-exposed adolescents. These results were not found for the attachment with the mother. Additionally, greater anger and worse stress management were found in conflict-exposed adolescents. (4) Conclusions: The results partially confirmed the spillover and compensatory hypothesis. Practical implications point out that developing preventive interventions that protect the father-adolescent attachment in situations of family conflict is recommended.

Fruit cracking or splitting, a severe physiological disease that highly affects appearance and quality, compromise the commodity value of fruit and also causes huge economical losses to the producers of several fleshy fruit crops. The growth-promoting phytohormone gibberellic acid (GA) and growth-inhibiting phytohormone abscisic acid (ABA) antagonistically regulate numerous developmental processes throughout the plant life cycle. Homeostasis of endogenous GA and ABA play a significant role in the normal growth of fruits, and its imbalance may lead to the occurrence of cracking or splitting during the process of fruit growth, development, ripening and postharvest storage. The pathways of GA and ABA metabolism and signaling have been studied widely, and the major components were well characterized, which including the genes encoding major biosynthesis and catabolism enzymes and the key signaling components. Nevertheless, our knowledge of the mechanisms of GA and ABA governing fruit cracking is not comprehensive enough. In this review, we not only focus on the scenarios of effects of endogenous GA and ABA contents in the fruit and exogenous plant growth regulators GA and ABA treatments, but also endeavor to provide some genetic cues on the function of GA and ABA responsible for fruit cracking modulation. Information from this review aims to strengthen the understanding of potential molecular bases underlying GA and ABA in fruit cracking control and provide guidance in breeding of fruit cultivars with cracking-resistant ideotypes, and also make great theoretical significance in guiding the establishment of integrated prevention and control measures to fruit cracking or splitting.

Background: Takayasu’s arteritis is a rare type of vasculitis, with severe complications like stroke, ischemic heart disease, pulmonary hypertension, secondary hypertension, aneurysms. Diagnosis is conducted by clinical and angiographic criteria. Treatment is medical and surgical, but unfortunately, the outcome is reserved. Case presentation: A 34- year- old Caucasian women had an ischemic stroke (2009). She was diagnosed with Takayasu’s arteritis and she received treatment with methotrexate, prednisolone, antiplatelet agents, with a mild improvement of clinical state. After 5 years (2014) she associated ascending aorta aneurysm, pulmonary hypertension, mild aortic regurgitation. The surgical treatment solved both ascending aorta aneurysm and left carotid artery stenosis (ultrasound in 2009 and computed tomography angiogram in 2014). Morphopathology revealed typical appearance for Takayasu’s arteritis. Tumor necrosis factor inhibitors (TNF-inhibitors) were associated to methotrexate. At 48 years (2023) she developed coronary heart disease (angina, electrocardiogram); echocardiography revealed severe pulmonary hypertension; angiography described normal coronary arteries, abdominal aorta pseudoaneurysm and arterial-venous fistula, with origin in right coronary artery and drainage on medium pulmonary artery. The patient refused surgical/ interventional treatment; she received again TNF- inhibitors, methotrexate, antiplatelet agents, statins. Conclusions: This case report presents us a severe form of Takayasu’s arteritis. We consider that morphopathology had a great importance in revealing to clinicians the typical appearance and the stadialization of inflammatory arterial process: acute or chronic. The verdict of morphopathologist was chronic phase, with acute relapses, so we decided that immunosuppressive treatment was still necessary.