Similarly to his special theory of relativity, Einstein's special principle of relativity extends beyond the limits currently known to it. Up to now, the principle has not been suspected to have the potential to translate laws. However, the principle holds an inherent capacity to translate physical laws and, in so doing, speeds up our understanding and control of physical reality. Such a translation of laws leads to the faster discovery of other laws, such as the Laws of Electronic Motion, characterizing the motion of electrons around the atomic nucleus, and the Third Law of Biological Resistance, facilitating the successful control of drug resistance in medicine. The ability of the special principle of relativity to translate laws shines forth once the said principle is duly interpreted. This interpretation exposes a parallelism between experimental frames of reference and justifies the applicability of the laws of one frame of reference in other parallel frames of reference. This process opens the door to our faster discovery of the laws governing a multiplicity of frames parallel to a frame we already know the laws of. In practice, the interpretation of Einstein's special principle of relativity speeds up our understanding of the workings of physical reality and strengthens our capacity to subdue matter.

Mangoes have a unique nutrient profile (carotenoids, polyphenols, sugars, vitamins) that we hypothesized would mitigate post-exercise inflammation. This study examined the effects of mango ingestion in moderating exercise-induced inflammation in a randomized crossover trial with 22 cyclists. In random order with trials separated by a 2-week washout period, the cyclists ingested 330 g/day mangoes with 0.5 liters water or 0.5 liters water alone for 2 weeks, followed by a 2.25-h cycling bout challenge. Blood and urine samples were collected pre- and post-2 weeks supplementation, with additional blood samples collected immediately post-exercise, and then 1.5-h, 3-h, and 24-h post-exercise. Urine samples were analyzed for targeted mango-related metabolites. The blood samples were analyzed for 67 oxylipins that are upstream regulators of inflammation and other physiological processes. After 2-weeks mango ingestion, three targeted urine mango-related phenolic metabolites were significantly elevated compared to water alone (interaction effects, p≤0.003). Significant post-exercise increases were measured for 49 oxylipins, but various subgroup analyses showed no differences in the pattern of change between trials (all interaction effects, p>0.150). The 2.25-h cycling bouts induced significant inflammation but no countermeasure effect was found after 2-weeks mango ingestion despite the elevation of mango gut-derived phenolic metabolites.

This paper presents an approach to enhancing the clarity and intelligibility of speech in digital communications compromised by various background noises. Utilizing deep learning techniques, specifically a Variational Autoencoder (VAE) with 2D convolutional filters, we aim to suppress background noise in audio signals. Our method focuses on four simulated environmental noise scenarios: storms, wind, traffic, and aircraft. Training dataset has been obtained from public sources (TED-LIUM 3 dataset, which includes audio recordings from the popular TED-TALK series) combining with these background noises. The audio signals were transformed into 2D power spectrograms, upon which our VAE model was trained to filter out the noise and reconstruct clean audio. Our results demonstrate that the model outperforms existing state-of-the-art solutions in noise sup-pression. Although differences in noise types were observed, it was challenging to definitively conclude which background noise most adversely affects speech quality. Results have been assessed with objective methods (mathematical metrics) and subjective (listening to a set of audios by humans). Notably, wind noise showed the smallest deviation between the noisy and cleaned audio, perceived subjectively as the most improved scenario. Future work involves refining the phase calculation of the cleaned audio and creating a more balanced dataset to minimize differences in audio quality across scenarios. Additionally, practical ap-plications of the model in real-time streaming audio are envisaged. This research contributes significantly to the field of audio signal processing by offering a deep learning solution tailored to various noise conditions, enhancing digital communication quality.

The twelve cranial nerves play a crucial role in nervous system, orchestrating a myriad of functions vital for our everyday life. These nerves are each specialized for particular tasks. Cranial Nerve I, known as the olfactory nerve, is responsible for our sense of smell, allowing us to perceive and distinguish various scents. Cranial Nerve II, or the optic nerve, is dedicated to vision, transmitting visual information from the eyes to the brain. Eye movements are governed by Cranial Nerves III, IV, and VI, ensuring our ability to track objects and focus. Cranial Nerve V controls facial sensation and jaw movement, while Cranial Nerve VII, the facial nerve, facilitates facial expressions and taste perception. Cranial Nerve VIII, or the vestibulocochlear nerve, plays a critical role in hearing and balance. Cranial Nerve IX, the glossopharyngeal nerve, affects throat sensation and taste perception. Cranial Nerve X, the vagus nerve, is a far-reaching nerve, influencing numerous internal organs such as the heart, lungs, and digestive system. Cranial Nerve XI, the accessory nerve, is responsible for neck muscle control, contributing to head movement. Finally, Cranial Nerve XII, the hypoglossal nerve, manages tongue movement, essential for speaking, swallowing, and breathing. Understanding these cranial nerves is fundamental in comprehending the intricate workings of our nervous system and the functions that sustain our daily lives.

The integration of deep neural networks into sparse Synthetic Aperture Radar (SAR) imaging has been explored to enhance SAR imaging performance and reduce the system’s sampling rate. However, the scarcity of training samples and mismatches between the training data and the SAR system pose significant challenges to the method’s further development. In this paper, we propose a novel SAR imaging approach based on Deep Image Prior Powered by RED (DeepRED), enabling unsupervised SAR imaging without the need for additional training data. Initially, DeepRED is introduced as the regularization technique within the sparse SAR imaging model. Subsequently, variable splitting and the Alternating Direction Method of Multipliers (ADMM) are employed to solve the imaging model, alternately updating the magnitude and phase of the SAR image. Additionally, the SAR echo simulation operator is utilized as an observation model to enhance computational efficiency. Through simulations and real data experiments, we demonstrate that our method maintains imaging quality and system downsampling rate on par with deep neural network-based sparse SAR imaging, but without the requirement for training data.

In recent decades, given the important role of gamma-aminobutyric acid (GABA) in human health, scientists have paid great attention to the enrichment of this chemical compound in food using various methods, including microbial fermentation. Moreover, GABA or GABA-rich products have been successfully commercialized as food additives or functional dietary supplements. Several microorganisms can produce GABA, including bacteria, fungi, and yeasts. Among GABA-producing bacteria, lactic acid bacteria (LAB) are commonly used in the production of many fermented foods. Lactiplantibacillus plantarum (previously Lactobacillus plantarum) has a long history of natural occurrence and safe use in a variety of food products. This LAB species provides functional properties to various fermented foods by producing a variety of bioactive compounds, including GABA. The present review aims, after a preliminary excursus on the function and biosynthesis of GABA, to provide an overview on the current uses of microorganisms and in particular of L. plantarum in the production of GABA, with a detailed focus on fermented foods.

Chiral semiconductor nanostructures and nanoparticles are promising materials for applications in biological sensing, enantioselective separation, photonics, and spin-polarized devices. Here, we have studied the induction of chirality in atomically thin only 2 monolayers thick CdSe nanoplatelets (NPLs) grown by a colloidal method and exchanged with L-alanine and L-phenylalanine as model thiol-free chiral ligands. We have developed a novel two-step approach to completely exchange the native oleic acid ligands for chiral amino acids at the basal planes of NPLs. We performed an analysis of the optical and chiroptical properties of the chiral CdSe nanoplatelets with amino acids, which was supplemented by an analysis of the composition and coordination of ligands. After the exchange, the nanoplatelets retain HH, LH and SO exciton absorbance and bright HH exciton luminescence. Capping with thiol-free enantiomer amino acid ligands induce pronounced chirality of excitons in the nanoplatelets, as proven by circular dichroism spectroscopy, with high dissymmetry g-factor up to 3.4 × 10−3 achieved for HH excitons in the case of L-phenylalanine.

Growing mushrooms is meeting challenges while aiming for sustainability and circularity. Wherever the producer is located, commercial strains are the same originating from several producers. Following the harvest, enormous quantities of spent mushroom substrate containing spores are disposed presenting a type of foreign material pressure on the ecosystem in the form of the loss of genetic diversity in wild mushroom populations. This challenge can be mitigated by bioprospecting local strains and using them to generate commercial inoculum. Accordingly, the mycoceutical potential of five polypore mushroom species from Serbia was evaluated: secondary metabolite composition, oxidative damage prevention, anti-tyrosinase, and anti-angiotensin converting enzyme (ACE) properties. The phenolic pattern was comparable in all samples, but the amounts of specific chemicals varied. Hydroxybenzoic acids were the primary components. All samples had varying quantities of ascorbic acid, carotene, and lycopene, and showed a pronounced inhibition of lipid peroxidation (LPx) and ability to scavenge HO•. Extracts were more potent tyrosinase inhibitors but unsuccessful when faced with ACE. Fomitopsis pinicola had the strongest anti-tumor efficacy while Ganoderma lucidum demonstrated strong selectivity in anti-tumor effect in comparison to healthy cells. The evaluated species provided a solid foundation for commercial development while keeping the local ecology in mind.

A series of ZnO doped nitrogen-carbon materials (xZnO-N-C) with ZnO content of 5-40% are prepared by vacuum curing-carbonization strategy using polyamide-imide as N-C source and zinc nitrate as metal source for propane dehydrogenation (PDH). 20ZnO-N-C exhibits outstanding initial activity (propane conversion of 35.2% and propene yield of 24.6%) and relatively low deactivation rate (0.071 h-1) at 600 ◦C. The detailed characterization results show that small ZnO nanoparticles (5.5 nm) with high dispersion on the catalyst could be obtained by adjusting ZnO loading. Moreover, much more nitrogen-based species especially ZnNx species are formed on 20ZnO-N-C by comparison with 20ZnO-N-C-air prepared by curing-carbonization without vacuum, which may contribute for the higher product selectivity and catalytic stability of 20ZnO-N-C. The probable active sites for PDH reaction on the catalyst system are proposed to be C=O species and Zn2+ species. Moreover, the aggregation of ZnO nanoparticles is the primary reason for the activity loss on this catalyst system. The present finding not only provides the feasible construction strategy for the metal oxide doped nitrogen-carbon materials but also valuable guidance for the design of efficient catalyst in dehydrogenation of light alkane.

The insufficient toughness of concrete can lead to the occurrence of crack expansion, ultimately resulting in a decline in the physical and mechanical properties such as bearing capacity and deformation characteristics of structural components. In severe cases, this may lead to brittle failure, where the entire structure and system fail suddenly without significant deformation after being stressed. Additionally, during the process of shear and bending failure of reinforced concrete beams, the cracks generated on the side of the beam are mostly I-II composite cracks. Considering the material nonlinearity and geometric irregularity of reinforced concrete, it is of great significance to study the dynamic evolution law of crack expansion in reinforced concrete members. Based on experimental data, this paper aims to utilize the nonlinear finite element simulation software Abaqus to conduct finite element simulations of crack expansion in simple supported reinforced concrete beams. By accurately controlling the constitutive curves of concrete and reinforcement materials, the design of seismic performance of structural members can be enhanced, thereby making essential contributions to the preliminary analysis of actual crack control engineering. The nonlinear finite element results indicate that the joint cracks of the frame with the floor slab primarily manifest as flexural cracks, with the concrete damage degree of the floor slab being higher than that of the beam. This finding underscores the importance of considering the behavior of concrete and reinforcement materials in designing for seismic performance and crack control in actual engineering applications.

Gastroesophageal (GE) junction adenocarcinoma is an aggressive malignancy of growing incidence and is associated with public health issues such as obesity and GERD. Management has evolved over the last 2 decades to incorporate a multidisciplinary approach including endoscopic intervention, and neoadjuvant chemotherapy/ chemoradiation and minimally invasive or more limited surgical approaches. Surgical approaches include esophagectomy, total gastrectomy, and more recently proximal gastrectomy. This review analyzes the evidence for and applicability of these varied approaches in management as well areas of continued controversy and investigation.

BACE1 is involved in the production of beta-amyloid peptides, and inhibiting its activity is a potential therapeutic strategy for managing Alzheimer's disease, as excessive beta-amyloid accumulation is a characteristic feature of the disease.Computational results suggest that hypericin has the potential to act as an inhibitor of BACE1. The Molecular Docking results indicate a high binding affinity between hypericin and BACE1, with a notable binding energy score of -10.3 kcal/mol. Additionally, the formation of various chemical bonds, including hydrogen bonds and hydrophobic bonds, further supports the idea that hypericin may effectively interact with the active site of BACE1. It's important to note that while the in silico Molecular Docking results are promising, further in vitro and in vivo studies would be necessary to validate and better understand the inhibitory potential of hypericin against BACE1. Additionally, the practical application of hypericin as a BACE1 inhibitor in a therapeutic context would require careful consideration of factors such as bioavailability, safety, and efficacy.

Recently considered modifications to public policy and trends in technology transfer practices have underscored the need for validated instruments to assess the maturity of technologies. This paper details a study that aimed to develop and present a generalized technology readiness level (GTRL) scale that a variety of professionals and researchers could use to assess the maturity of technologies in a range of contexts. Of particular interest is developing and validating an instrument that technology transfer professionals in federal laboratories, universities, and the private sector in the United States of America can use to assess the maturity of technologies to facilitate their technology transfer efforts. The primary goal of the research study was to highlight the need for validated measurement instruments for assessing the maturity of technologies in these contexts, test methods for validating the GTRL scale and other readiness level scales, and fill the knowledge gap regarding methods for properly validating such instruments. This included producing insights to inform future efforts to validate the GTRL scale as well as efforts to develop and validate other instruments to measure technology maturity. The study provides specific recommendations relevant to determining the face validity, content validity, inter-rater reliability, and intra-rater reliability of the GTRL scale and other such instruments for assessing technology maturity.

Prediabetes, a pivotal phase in glucose metabolism between normalcy and diabetes, exerts a profound influence on the aging process and the risk of age-related diseases. This comprehensive review delves into the intricate web of blood-based biomarkers that collectively expedite senescence, marking the transition from a state of health to age-related complications. Key findings underscore the significance of diverse biomarkers, such as telomere length, p16INK4a, senescence-associated secretory phenotype (SASP) factors, DNA methylation clocks, advanced glycation end products (AGEs), inflammatory and oxidative stress markers, circulating hormones, and additional factors like folate, B12, osteocalcin, and more. Not only do these biomarkers serve as indicators of senescence, but they actively fuel chronic inflammation, oxidative stress, and metabolic dysregulation, all of which contribute to accelerated aging. The implications of this understanding are profound, as prediabetes emerges as a critical period in an individual's life, influencing various physiological systems, including the vascular and neural systems, metabolic functions, hormonal regulation, and bone health. Recognizing the profound influence of prediabetes on senescence provides a foundation for personalized intervention strategies to mitigate age-related complications and promote healthy aging. Future research directions call for a more diverse array of biomarkers, in-depth exploration of their roles, and the development of tailored precision medicine strategies to ensure a holistic understanding and effective management of prediabetes-induced senescence and its implications for aging. This knowledge has far-reaching implications for public health and clinical practice, emphasizing the need for early detection and intervention in prediabetic individuals to enhance the quality of life in an aging population with diverse needs.

Trio-based exome sequencing and high-resolution HLA typing were employed to analyze three patients with autoimmune adrenal insufficiency (AAI), including those with autoimmune polyglandular syndrome (APS) type 2, as well as their parents. Benign or likely benign variants of the AIRE gene were identified in all participants of the study. These variants, coupled with clinical data and the results of antibody studies to type I interferons, helped to exclude APS-1. Patients with APS-2, in contrast to patient with AAI, inherited distinct variants of unknown significance in the CLEC16A gene, which is associated with autoimmune diseases including AAI. Various risk alleles in other genes associated with autoimmunity were identified in all patients. HLA typing of second class loci revealed alleles related to APS types 2, 3, and 4. Nevertheless, the frequencies of the haplotypes identified are substantial in the healthy Russian population, precluding from regarding these alleles as genetic determinants linked to APS development. Immunological examination can detect antibody carriers and predict the risk of autoimmune disease development. In the future, to identify genetic predictors of autoimmune endocrinopathies, it is recommended to analyze the whole genome of patients and their relatives, examining clinically relevant variants in non-coding regions.

Sesame (Sesamum indicum), a highly valued oilseed, faces challenges in cultivation, especially in regions susceptible to environmental stressors. This study investigates the interactive effects of salinity and temperature on sesame seed germination. Two cultivars, Darab 1 and Oltan, were subjected to various salinity levels (-3 to -12 bars) and temperatures (15°C, 20°C, and 25°C). Results revealed that at 15°C, salinity levels beyond -3 bars significantly reduced germination, while at 25°C, 40% and 62% germination rates were recorded even at -12 bars for Darab 1 and Oltan, respectively. The study highlights the importance of temperature in mitigating the inhibitory effects of salinity on germination. Germination speed exhibited a decline with increasing salinity, particularly at lower temperatures. Shoot and root lengths and dry weights decreased with rising salinity, but Oltan demonstrated greater tolerance than Darab 1. The research emphasises the species-specific nature of temperature-salinity interactions and the intraspecific variability among sesame cultivars. Notably, Oltan, adapted to arid regions with elevated temperatures, displayed increased tolerance to salinity stress. The findings contribute to understanding sesame's resilience to environmental stressors, aiding in developing resilient cultivars for challenging agricultural landscapes. Overall, temperature is pivotal in influencing sesame seed germination and early seedling growth under salinity stress, offering insights for optimised cultivation practices.

At the Rio Conference in 1992, the sustainable development agenda promised a new era for natural resource management, where the well-being of human society would be enhanced through the sustainable use of natural capital. Several decades on, economic growth continues unabated at the expense of natural capital, as evidenced by biodiversity loss, climate change and further environmental issues. Why is this happening and what can be done about it? In this research, we present three Agent-Based Models that explore the social, economic and governance factors driving (un)sustainability in complex social-ecological systems. Our modelling results reinforce the idea that the current economic system does not protect the natural capital on which it depends. This is due to a disjunction between the economic and environmental elements upon which the sustainable development paradigm is founded. Additionally, various factors appear to enhance social-ecological system unsustainability: the role of financial entities and monetary debt; economic speculation; technological development and efficiency; lack of long-term views and late government interventions; inefficient tipping point management; and the absence of strong top-down and bottom-up conservation forces. Interestingly, alternative scenarios showed that these same factors could be redirected to enhance sustainable development. The current economic system may, therefore, not be inherently unsustainable, but rather specific economic mechanisms, agents’ decision-making, and the kinds of links between economic and natural systems could be at the root of the problem. We argue that short- and medium-term sustainability can be enhanced by implementing mechanisms that shift capitalist forces to support environmental conservation. Long-term sustainability, however, requires further paradigm change: where the economy integrates, and fully accounts for, externalities and recognises the actual value of natural capital.

The authors of the article analyze the existing methods and models of technological preparation of machine-building industries. The structure of a three-level simulation model with network-centric control, the structures of individual elements of the simulation model and the process of simulation modeling are described. The criteria for choosing a rational option for the processing technological route have been determined. During the research, a simulation program was implemented in C++. It allows you to select the optimal scenario for the operation of a production site based on two criteria: time and cost. The volume of implementation is about 2x103 lines of code. A diagram of the modeling algorithm for the implemented program, a description of the classes and their interactions are given in the article. The developed simulation model was tested at a machine-building enterprise using the example of the “Pusher” part, manufactured under single-unit production condi-tions. The technological equipment used for the manufacture of this part was formed in the form of input data of the simulation model. The results of simulation modeling for the selected part are described. For each variant of the technological processing route, the values of variable costs and the duration of the production cycle were determined.

Underground storage of natural gas has the characteristics of clean and low-carbon, and has the ability to provide sustainable and stable supply. It is a very high-quality green energy that can increase the storage efficiency of gas storage through fracturing, achieving the sustainable development goal of "Carbon Peaking and Carbon Neutrality". The accurate evaluation of the fracability of a reservoir is an important prerequisite for reservoir fracturing design and post fracturing productivity evaluation. At present, research on fracability is mainly based on qualitative characterization or quantitative evaluation based on rock mechanics and fracturing construction parameters, which cannot fully reflect the rock composition and structure of each stage. Firstly, based on logging data, this paper analyzes the evolution laws of strain energy such as elastic properties, pre-peak dissipation energy, and post-peak fracture energy during the transition of rock materials from plastic deformation to brittle fracture in an energy perspective, and determines the key energy that affects the brittle characteristics of rocks. Secondly, a brittleness index evaluation approach has been established that can comprehensively reflect the mechanical properties of rocks during pre-peak deformation and post-peak damage stages. In addition, this article focuses on the impact of reservoir stratigraphic environment by combining the influence of geo-stresses with the rock brittleness index, and proposes a new method for evaluating reservoir fracability. Finally, this paper conducts a study on the fracability evaluation of three wells in a gas storage facility in eastern China. The results indicate that low modulus and fracability coefficient are beneficial for fracturing, thereby improving the gas production and peak shaving ability of gas storage.

1,3 Dipolar cycloaddition of imidazolidine derivatives containing exocyclic double bonds is a convenient method of creating spiro-conjugated molecules with the promising anticancer active. In this work, the derivatives of parabanic acid (2-thioxoimidazolidine-4,5-diones and 5-aryliminoimidazolidine-2,4-diones) were firstly investigated as dipolarophiles in the reactions with nitrile imines. The generation of nitrile imines was carried out either by the addition of tertiary amine to hydrazonoyl chlorides «drop by drop» or using recently proposed diffusion mixing technique, which led to ~5-15% increasing of target compounds yields. It was found that the addition of nitrile imines to C=S or C=N exocyclic double bonds led to 1,2,4-thiazolines or triazolines and occurred regioselectively in accordance to the ratio of FMO coefficients of reactants. The yield of the resulting spiro-compound depended on the presence of alkyl substituents in nitrile imine structure and was significantly decreases at the reactions with imines with strong electron donor or electron-withdrawing groups. Some of the obtained compounds showed reasonable in vitro cytotoxicity. IC50 values were calculated for HCT116 (colon cancer) cells using the MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) test.

In recent years, ozone (O3) pollution has been rapidly spreading, restricting further improvement of air quality in China. Investigating the interaction of O3 concentration and identifying their driven cities are important for the prevention and control of O3 pollution in China. However, the complex interaction between O3 pollution between the cities and their driven cities has not yet been revealed. In this study, we address this gap based on complex network methods. Specifically, an ozone relational network is constructed using an association calculation method. The driven nodes and spatial clusters were analyzed based on the maximum matching algorithm and the Louvain algorithm. The findings of the study reveal an aggregation phenomenon in the ozone network concerning distance. Furthermore, as the threshold Tc varies, the proportion of driven nodes exhibits a positive correlation. Moreover, a closer threshold value corresponds to a higher coincidence ratio of the driven nodes. The results provide scientific guidance for national O3 pollution prevention and regional synergy formatting. Furthermore, the introduced network-based approaches offer a mythological framework for the study of air pollution in key cities and clusters.

The interaction between O2 and reduced ceria nanocubes was mainly investigated by FTIR spectroscopy. Nanorods and nanoparticles were also studied for comparison. Adsorption of O2 at 100 K on unreduced ceria produces only O2 molecularly adsorbed on Ce4+ sites. The Ce3+ cations in H2-reduced ceria were monitored by the 2F5/2 → 2F7/2 electronic transition band at 2133-2095 cm-1. This band possesses a fine structure well resolved at 100 K. The positions of the individual components depend on the Ce3+ environment, including the presence of nearby species such as OH groups. Even at 100 K, the interaction of O2 with reduced ceria leads to fast oxidation of about half of the Ce3+ cations, including all Ce3+ sites bound to OH groups and carbonates, and the simultaneous formation of superoxo (O2) and peroxo (O22) species. The remaining fraction of Ce3+ sites disappears upon heating up to 348 K. At higher temperatures, the peroxo species decompose directly, yielding lattice oxygen. Superoxides are converted to hydroperoxides, which then decompose to terminal OH groups. Reduced samples evacuated at T < 773 K contain sorbed H2. Part of this hydrogen is also fast oxidized to H2O even at 100 K.

Machine learning, including deep learning, reinforcement learning, and generative artificial intelligence are revolutionising every area of our lives when data is made available. With the help of these methods, we can decipher information from larger datasets while addressing the complex nature of biological systems in a more efficient way. Although machine learning methods have been introduced to human genetic epidemiological research as early as 2004, those were never used to their full capacity. In this review, we outline some of the main applications of machine learning to assigning human genetic loci to health outcomes. We summarise widely used methods and discuss their advantages and challenges. We also identify several tools, such as Combi, GenNet and GMSTool, specifically designed to integrate these methods for hypothesis-free analysis of genetic variation data. We elaborate on the additional value and limitations of these tools from a geneticist’s perspective. Finally, we discuss the fast-moving field of foundation models and large multi-modal omics biobank initiatives.

The groundbreaking Advanced Forest-Based Tagging Framework (AFTF) represents a paradigm shift in the domain of information extraction from medical texts. AFTF introduces a novel dual-binary tree structure that redefines how entity-relation triples are extracted. This innovative approach directly tackles the limitations of traditional linear and graph-based methods, effectively addressing challenges related to overlapping triples and computational efficiency. The AFTF model stands as a beacon of excellence, surpassing established baselines by significant margins in comprehensive evaluations on two pivotal medical datasets. Notably, AFTF achieves remarkable improvements in F1 scores, showcasing its prowess in accurate information extraction from complex medical narratives. Beyond its exceptional performance in the medical domain, AFTF exhibits remarkable versatility. This adaptability is vividly demonstrated through its robust performance across three diverse public datasets, further affirming its position as a versatile and reliable solution for information extraction tasks. This paper provides a comprehensive exposition of the AFTF architecture, shedding light on its innovative design principles and its efficient handling of intricate medical texts. AFTF represents a groundbreaking step forward in the realm of information extraction, promising enhanced accuracy, efficiency, and adaptability for a wide range of applications.

In the context of circular economy that recommends the most efficient use of waste, algae wastes have a huge potential for valorisation. In this study, algae wastes obtained after alkaline extraction of active compounds from two types of marine algae (green algae – Ulva sp. and red algae – Callithamnion sp.), were used as biosorbents to remove metal ions from aqueous effluents. Their efficiency in the biosorption processes was tested for Zn(II), Cu(II) and Co(II) ions, considered technologically valuable metal ions. The batch mono-component experiments performed under optimal conditions (pH = 5.0; 4.0 g biosorbent/L; 22 ± 1C), showed that more than 75 % of the metal ions are removed when their initial concentration is less than 1.25 mmol/L. The very good fit of the experimental data with the pseudo-second order kinetic model and Langmuir isotherm model, and the high values obtained for the maximum biosorption capacity (qmax: Cu(II) (0.52 mmol/g) > Zn(II) (0.41 mmol/g) > Co(II) (0.39 mmol/g) for G-AWB, and qmax: Cu(II) (1.78 mmol/g) > Zn(II) (1.72 mmol/g) > Co(II) (1.66 mmol/g) for R-AWB) highlights the potential use of these biosorbents to remove such technologically valuable metal ions from industrial wastewater. This possibility was tested using industrial wastewater samples obtained from the metal coating industry. Quantitative removal (> 91 %) of Zn(II), Cu(II) and Co(II) ions was obtained when their initial concentration was adjusted to 50 mg/L. Also, the rapid and efficient desorption of these metal ions from loaded-biosorbents, by simple treatment with small volumes of HNO3 (10-1 mol/L), further emphasizes the possibility of their recovery and reuse in the technological circuit. The results included in this study indicate that algae wastes have the potential to be used in industrial effluents decontamination processes and opens new perspectives for the implementation of circular economy principles.

The structure characterization of two new polysaccharides from Agrocybe aegerita (AA-P) and Hygrophorus olivaceoalbus (HO-P) by HPGPC, GC-MS, NMR and FT-IR indicated that AA-P was composed of Galactose, Glucose and Arabinose, in the ratio of 3:2:1. Its skeleton structure was consisted of (1→4)-Arap, (1→4,6)-Glup and (1→6)-Galp with one branched chain. The HO-P was consisted of mannose, galactose and glucose in a ratio of 1:1:2. Its skeleton structure was consisted of (1→6)-Galactose residues, (→1)-glucose residues, (1→4)-glucose residues and (1→4,6)-D-mannose residues. There were two branched chains connected to the main chain. AA-P and HO-P had the best stimulation effect on B cells and RAW264.7 cells, respectively, and could both mainly by impacting and reducing G0/G1 phase which lead to a significant proliferation of B cells, T cells and RAW264.7 cells. In addition, AA-P and HO-P could significantly promote the secretion of TNF-α from T cells, the secretion of IgA, IgD, IgE, IgG and IgM from B cells, and the secretion of TNF-α from RAW264.7 cells, but neither of them could impact the secretion of IL-1β from RAW264.7 cells.

“Blue carbon”, apart from marine humus, includes the carbon (C) stock of coastal ecosystems such as mangroves, marshes, and seagrass meadows, which have been overlooked until recently. Information about the role of coastal wetlands in C sequestration and providing other ecosystem services is still insufficient. In the present study, we assessed the C reserves of soils and vegetation biomass in two complex coastal landscapes (tombolos) located on the coasts of the White and Baltic seas. The soil and plant C stocks were slightly higher at the plot at the Baltic Sea (93.4 ± 46.7 Mg C·ha-1 and 5.22 ± 2.51 Mg C·ha-1, respectively) than at the plot on the White Sea (71.4 ± 38.2 Mg C·ha-1 and 3.95 ± 2.42 Mg C·ha-1, respectively). We attributed the higher values of the C reserved to a warmer climate and less saline water at the plot on the Baltic Sea. Both soil and plant C showed high heterogeneity due to geomorphological complexity and differences in vegetative communities. The Phragmites australis community showed the highest plant biomass and, in some places, high soil C reserves. Allochthonous C contributed to the soil C stock at the site on the White Sea. Though P. australis sequestered more C than other communities, its effect on ecosystem services was mostly negative because the invasion of reeds reduced the biological diversity of the marshes.

Fish processing by-products such as frames, trimmings, and viscera of commercial fish species are rich in proteins. Thus, they have the potential to be an economical source of proteins that may be used to obtain bioactive peptides and functional protein hydrolysates for the food and nutraceutical industries. The structure, composition, and biological activities of peptides and hydrolysates depend on the freshness and the actual composition of the material. Peptides isolated from fisheries by-products showed antioxidant activity. Changes of hydrolysis parameters changed the sequence and properties of the peptides, and determined their physiological functions. Optimization of the value of such peptides and the production costs must be considered for each particular source of marine by-products and for their specific food applications. This review will discuss the functional properties of fisheries by-products prepared using hydrolysis and their potential food applications. It also reviews the structure-activity relationships of the antioxidant activity of peptides as well as challenges to the use of fisheries by-products for protein hydrolysates production.

Ultralight power generation equipment has high requirements for the power density, continuous operation, and transient stability of the whole machine, and there is a direct conflict between high power density design and substantial stability control in the power unit design. In order to meet the power density requirements of ultra-light power stations, three main problems need to be solved, namely engine speed oscillation and flameout in the process of load power mutation, matching of the generator and engine torque, and stabilizing the voltage waveform of the AC output end. In this paper, we proposed an exquisite control strategy for ultralight power generation systems in engines, generators, and inverters. The effectiveness and practicability of the proposed strategy are verified by both simulation and experiment. The results show that the proposed control strategy can effectively solve the instability problem of the ultralights generator set and improve the stability of the system, where the response recovery can be achieved within 0.9 seconds under the condition of total load increase or decrease, and the mismatching degree of the generator following the engine is reduced by 90%. The strategy could also guarantee long-term stable operation with high-quality electrical energy output.

The severe volumetric expansion of silicon nanoparticles (~400 %) limits their practical application as an anode material for next-generation lithium–ion battery (LIB). Here, we describe the fabrication and characterization of conformal polydopamine carbon shell encapsulating rattle-type silica@silicon nanoparticles (PDA−PEI@PVP−SiO2@Si) with tunable void structure prepared following a dual SiO2 template using (3–aminopropyl)triethoxysilane (APTES) as a self-catalytic, structure-directing agent to tetraethyl orthosilicate (TEOS) pretreated with polyvinylpyrrolidone (PVP K30) via modified Stöber process. Polyethylene imine (PEI) crosslinking facilitated the construction of interconnected three-dimensional bubble wrap-like carbon matrix structure through hydrothermal treatment, pyrolysis, and subsequent surface-protected etching. The composite anode material delivered 539 mAh·g−1 capacity after 100 cycles at 0.1 A·g−1, and 453 mAh·g−1 rate performance at 5 A·g−1. The satisfactory electrochemical performance of the PDA−PEI@PVP−SiO2@Si was attributed to the following: the rattle-type structure providing void space for Si volume expansion, PVP K30-pretreated APTES/TEOS SiO2 seeds via catalyst-free, hydrothermal-assisted Stöber protecting Si/C spheres upon etching, carbon coating strategy increasing Si conductivity while stabilizing the solid electrolyte interface (SEI), and PEI carbon crosslinks providing continuous conductive pathways across the electrode structure. The present work realizes a promising strategy to synthesize the tunable yolk–shell C@void@Si composite anode materials for high power/energy-density LIB applications.

We introduce quantum spatio-temporal dynamics (QSD) as modeled by the Nexus Paradigm (NP) of quantum gravity to resolve the problem of energy- momentum localization in a gravitational field. Currently, the gravitational field as described using the language of geometry modeled under General Relativity (GR) fails to provide a generally accepted definition of energy-momentum. Attempts at resolving this problem using geometric methods have resulted in various energy-momentum complexes whose physical meaning remain dubious since the resulting complexes are non-tensorial under a general coordinate transformation. In QSD, the tangential manifold is the affine connection field in which energy-momentum localization is readily defined. We also discover that the positive mass condition is a natural consequence of quantization and that dark energy is a Higgs like field with negative energy density everywhere. Finally, energy-momentum localization in quantum gravity shows that a free falling object will experience large vacuum fluctuations (uncertainties in location) in strong gravity than in weak gravity and that the amplitudes of these oscillations defines the energy of the free falling object.

This paper shows the development of a numerical analysis model, which enables the calculation of the cargo transport capacity of a vehicle that circulates through a vacuum tube at high speed, whose effectiveness in transport is analyzed. The simulated transportation system is based on vehicles moving in vacuum tubes at high speed, a concept commonly known as Hyperloop, but assuming the vehicles for cargo containers. For the specific vehicle proposed, which does not include a compressor and levitates on magnets, the system formed by the vehicle and the vacuum tube has been conceptually developed, establishing the corresponding mathematical relationships that define its behavior. To properly model the performance of this transport system, it has been necessary to establish the relationships between the design variables and the associated constraints, such as the Kantrowitz limit, aerodynamics, transport, energy consumption, etc. Once the model was built and validated, it was used to analyze the effects of the variation of the number of containers, the operating speed and the tube length, considering the total and specific consumption of energy. Once the most efficient configuration was found regarding energy consumption and transport effectiveness, the complete system was calculated. The results obtained constitute a first approximation for the pre-design of this transport system and the built model allows different alternatives to be compared according to the design variables.

The phenomenon of droplet impact on moving surfaces is widely observed in fields such as transportation, rotating machinery, and inkjet printing. Droplets exhibit non-axisymmetric behavior due to the motion of solid surfaces which significantly determines core parameters such as contact time, maximum spreading radius, and bounding velocity, thereby affecting the efficiency of related applications. In this study, we focus on kinetics and morphology of the non-axisymmetric bouncing behaviors for droplets impacting on a moving superhydrophobic surface (SHPS) within the normal (Wen) and tangential (Wet) Weber numbers. Considering the influences of moving surface on the contact area and contact time, the previous scaling formula for the horizontal velocity of droplets has been improved. Based on the velocity superposition hypothesis, we establish a theoretical model for the ratio of the maximum spreading radius at both ends depending on Wen and Wet. This research provides both experimental and theoretical evidence for understanding and controlling the non-axisymmetric behavior of droplets impacting on moving surfaces.

Active-case finding (ACF) using chest X-ray is an essential method of finding and diagnosing TB cases that may be missed in Indonesia's routine TB case finding. This study compares active and passive TB case-finding strategies. A retrospective study of TB case notification was conducted. Data between January 1 and December 31, 2021, was used. The population in this study were TB cases notified from Kulon Progo District health facilities, including those found through routine activities or active-case finding. A total of 255 TB cases were diagnosed in Kulon Progo in 2021, and 106 (41.6%) were bacteriologically confirmed. The TB patients' mean age was 46.3 (SD 21.4, range 0-85 years). The majority of cases were male (58.8%) and mostly among people aged 16-60 years old (63.5%). ACF diagnosed 91 TB cases (35.7% total cases, 91/255). The proportion of clinical TB cases (n=68, 74.7%) among those found through ACF was higher than found through passive-case finding. Use of chest X-ray in ACF likely contributed to the detection of a higher proportion of clinical TB than bacteriologically confirmed.

The incidence of human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC) is rising in the West, but little is known in Asia. This study elucidated changes in the incidence and HPV-positive portion of OPSCC in Hong Kong. Data from population-based cancer registry were used to analyze the incidence of OPSCC in associate with other head and neck cancers. Archived tumour tissues were tested for HPV. From 1986 to 2020, there was a marked decrease in the incidence of nasopharyngeal and laryngeal cancers, but a persistent increase in OPSCC from 36 cases in 1986 to 116 cases in 2020. The average positive rate for high-risk HPV was 36.1% (112/310) among OPSCC diagnosed in 2010-2020. The HPV positive rate in recent years was significantly higher than earlier cases (tonsil SCC: 64.7% (55/85) in 2016-2020 vs. 40.4% (19/47) in 2010-2015, P = 0.007). Patients with HPV-positive tonsil cancers were significantly younger than those negative (mean [SD]: 58.9 [9.9] vs. 64.3 [13.3] years, P = 0.006), but no significant difference between genders. A persistent increase in the incidence of oropharyngeal cancer over the last few decades was observed in Hong Kong, which can be explained by the remarkable increase in HPV-positive tonsil cancers.

Sr4Al6O12SO4 samples were obtained from the compound mixture formed by a solid–state reaction of Al2O3, SrSO4, and SrCO3. Samples were compacted at 100MPa to form pellets of 1 and 4cm in diameter and were sintered at 1400°C for 4 hours. The compound was analyzed by X–ray diffraction. Static immersion and wettability tests were performed to evaluate corrosion resistance in contact with Al–Si. Corrosion tests were carried out by immersion at 800, 900, and 1000°C for 24, 50, and 100 hours, while wettability was carried out at 900, 1000, and 1100°C for 2 hours. Subsequently, the samples were prepared metallographically. Samples were analyzed by optical microscopy, scanning electron microscopy, and image analysis. In general, reaction products consisting of alumina, spinel, oxides, and sulfates were found. The contact angles obtained were 124° to 135°. It is concluded that ceramic substrate Sr4Al6O12SO4 is resistant to corrosion by Al–Si alloy, since the slight thickness of the reaction products found in the samples (100μm) considering the severe conditions of the experiment: 1000°C and 100 hours of isothermal temperature. Furthermore, it can be said that Sr4Al6O12SO4 is not wettable by Al–Si alloys.

The contamination of aquatic environments by pharmaceutical products consistently takes the attention of researchers due to the compounds' toxicity even at low concentrations. In response, we have developed an ecologically sustainable biosurfactant derived from a microorganism and incorporated into the bacterial cellulose. This bioproduct, along with the bacterial cellulose itself, was employed as a sorbent for pharmaceuticals (hormones and paracetamol) present in water. Bacterial cellulose membranes were generated through the cultivation of Gluconacetobacter xylinus ATCC 53582. The biosurfactant was produced by pre-inoculating Bacillus subtilis in a synthetic medium, followed by immersing the bacterial cellulose membranes in the biosurfactant solution, for incorporation. Tests were conducted using water experimentally contaminated with parace-tamol and 17α-ethinylestradiol (EE2), evaluating the biosurfactant's effect on bacterial cellulose sorption. Paracetamol levels were analyzed using spectrophotometry, and EE2 levels were as-sessed using high-performance liquid chromatography. In summary, bacterial cellulose exhibited superior adsorption for EE2 compared to paracetamol. The incorporation of biosurfactant onto bacterial cellulose reduced hormone adsorption but enhanced paracetamol sorption. Our findings indicated that adsorption is more effective with bacterial cellulose in its original and freeze-dried forms, without the incorporation of biosurfactant. Notably, we achieved more promising results in remediating the hormone EE2 compared to the paracetamol.

Culture signifies the customs, language, ceremonies, Indigenous Medical Knowledge (IMK) and other material objects of a tribe. These and many other features are a representation of identity for many Zambian communities. IMK practices are skills inherent by certain individuals in a tribal grouping who are chosen by the spirits (gods) or trained by those who practice. This intrinsic skill is in danger of diminishing as a result of modern medication. This article attempts to understand the role of traditional healers (also known as asing’anga in local language) in preservation of IMK in Chibombo District of Zambia. In so doing, the paper examined methods of preservation used by asing’anga and the challenges faced. Using hermeneutic phenomenology and linear snowball sampling, findings revealed that preservation was done through training. The study found unwillingness, expiration, and spirituality as challenges in the process of preserving IMK. The study recommended that the Lenje Cultural Association consider documenting and disseminating information to the local people by showcasing what is available in the Mukuni Culture Village Museum and Library. This was seen as a way through which many youths would be encouraged to appreciate the indigenous values in their culture.

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

: Organic poultry need high-quality proteins in their diet. The EU’s organic regulation forbids synthetic amino acids; therefore, soybean, with its balanced essential amino acid content, has become the most used protein source, though much of it is imported from non-EU countries. Soybean, however, has some important problems related to sustainability and crop competition; therefore, it must be substituted with a high-protein-value alternative such as insect meal. In this study, 900 Aviagen Savanna broilers were reared using three different organic diets. The diets used the following as protein feed material: soybean only (S100), 50% black soldier fly larvae meal (BSL) and 50% soybean (BSL50), and 100% BSL only (BSL100). Broiler performance, welfare, and fatty acids (FA) in the thigh and breast were analyzed. BSL50 and BSL100 negatively affected growth performance, while BSL100 worsened all of the market-related measures of performance. Meat quality was worse in BSL50 and BSL100, with a significant increase in saturated FA (SFA) and a corresponding decrease in polyunsaturated FA (PUFA). Among SFA, lauric acid (C12:0) more notably increased. The increase in SFA represents a negative aspect of BSL meal inclusion, namely the production of lauric acid; however, this trend could have a beneficial effect, which will be more deeply explored with regard to its impact on animal and human health.

Proxy re-encryption (PRE) is a momentous and widely used cryptographic technique. It enables a proxy to forward ciphertext without the need of decryption. PRE has received significant interest in applications like cloud computing, blockchain, and the Internet of Things. Despite its wide range of uses, PRE has also been subject to new security and privacy regulations. In PKC’19, Cohen $et~al.$~first drew attention to the weakness in PRE's security against chosen-plaintext attacks (CPA) and put up a more stringent security concept known as security against honest re-encryption attacks (HRA). Notably, Cohen provides a beneficial conclusion as well. It is proveded that PRE schemes with re-encryption simulatability property can be elevated from CPA to HRA security. It is also proved that CPA-secure PRE schemes with re-encryption simulatability property can be directly elevated to those satisfying HRA security. However, those PRE schemes with re-encryption simulatability are almost always based on pairings. In this study, to the best of our knowledge, we directly construct HRA-secure PRE with re-encryption simulatability for the first time based on the learning with errors (LWE) assumption, which was widely believed to be quantum-resistant. Based on the re-encryption key generation algorithm and the re-encryption algorithm construction method of the above scheme, we can modify attribute-based conditional proxy re-encryption (AB-CPRE) as well as the corresponding attribute-based proxy re-encryption (AB-PRE) algorithm to make them have re-encryption simulatability properties. Finally, by using this property, We boost the security of AB-CPRE scheme of ESORICS'21 from CPA to HRA and simplify the HRA-security proof for the AB-PRE of ESORICS'21.

Gelephu, located in the Himalayan region, has experienced one of the strongest development activities due to the suitable topography and geographic location, which has led to rapid urbanization. The main objective of the study is to perform land use land cover (LULC) mapping for Gelephu for 2016 and 2023 by a Random Forest (RF) classifier, using the Semi-automatic Classification Plugin (SCP) in QGIS and identify LULC changes. Furthermore, the study assessed the vegetation change dynamics within the study area by analysing the Normalized Difference Vegetation Index (NDVI) for 2016 and 2023. Additionally, the study characterized the resulting LULC change for Gelephu Thromde, a sub-administrative municipal entity, as a result of the notable intensity of the infrastructure development activities. The current study used a framework to collect Sentiniel-2 satellite data, which was then used for pre- and post-processing to create LULC and NDVI maps. The classification model achieved high accuracy, with an area under the curve (AUC) of up to 0.89. The corresponding LULC and NDVI statistics were analysed to determine the current status of the LULC and vegetation indices, respectively. The LULC change analysis reveals urban growth of 5.65% and 15.05% for Gelephu and Gelephu Thromde, respectively. The NDVI assessment shows significant deterioration in vegetation health with a 75.11% loss of healthy vegetation in Gelephu between 2016 and 2023. This research provides the first version of LULC and NDVI maps of Gelephu. The analysis results indicate possible future implications on sustainable development management in Gelephu Bhutan.

Measuring Marginal Reflex Distance-1 (MRD-1) is a crucial clinical tool used to evaluate the position of the eyelid margin in relation to the cornea. Traditionally, this assessment has been conducted manually by plastic surgeons, ophthalmologists, or trained technicians. However, with the advancements in Artificial Intelligence (AI) technology, there is a growing interest in the development of automated systems capable of accurately measuring MRD-1.In this context, we introduce novel MRD-1 measurement methods based on deep learning algorithms that can simultaneously capture images and compute the results. This prospective observational study involved 154 eyes of 77 patients aged over 18 years who visited Chungnam National University Hospital between September 1, 2023, and July 29, 2023. We collected four different MRD1 da-tasets from patients using three distinct measurement methods, each tailored to the individual patient. The mean MRD1 values, measured through the manual method using a penlight, the deep learning method, ImageJ analysis from RGB eye images, and ImageJ analysis from IR eye images in 56 eyes of 28 patients, were 2.64 ± 1.04 mm, 2.85 ± 1.07 mm, 2.78 ± 1.08 mm, and 3.07 ± 0.95 mm, respectively. Notably, the strongest agreement was observed between MRD1_deep learning (DL) and MRD1_IR (0.822, p < 0.01). In the Bland-Altman plot, the smallest difference was observed between MRD1_DL and MRD1_IR ImageJ, with a mean difference of 0.0611 and △LOA (limits of agreement) of 2.5162, which is the smallest among the other groups. In conclusion, this novel MRD1 measurement method, based on an IR camera and deep learning, demon-strates statistical significance and can be readily applied in clinical settings.

Studies of mast cell biology is dependent on relevant and validated in vitro models. We here present detailed information concerning the phenotype of both freshly isolated human skin mast cells (MCs), and of in vitro cultures of these cells that was obtained by analyzing their total transcriptome. Transcript levels of MC-related granule proteins and transcription factors were found to be remarkably stable over a 3-week culture period. Relatively modest changes were also seen for important cell surface receptors including the high affinity receptor for IgE, FCER1A, the low affinity receptor for IgG, FCGR2A, and the receptor for stem cell factor, KIT. FCGR2A was the only Fc receptor for IgG expressed by these cells. Comparisons of the present transcriptome against previously reported transcriptomes of mouse peritoneal MCs and mouse bone marrow derived MCs (BMMCs) revealed both similarities and major differences. Strikingly, cathepsin G was the most highly expressed granule protease in human skin MCs, in contrast to the almost total absent of this protease in both mouse MCs. Transcript levels for the majority of cell surface receptors were also very low compared to the granule proteases in both mouse and human MCs, with a difference of almost two orders of magnitude. An almost total absence of T cell granzymes was observed in human skin MCs, indicating that granzymes have no or only a minor role in human MC biology. Ex vivo skin MCs expressed high levels of selective immediate early genes and transcripts of heat-shock proteins. In validation experiments, we determined that this expression was an inherent property of the cells and not the result of the isolation process. Three to four weeks in culture results in an induction of cell growth related genes accompanying their expansion by 6-10-fold, which increases the number of cells for in vitro experiments. Collectively, we show that cultured human skin MCs resemble their ex vivo equivalents in many respects and are a more relevant in vitro model compared to mouse BMMCs for studies of MC biology, in particular human MC biology.

Since China’s economic reform launched in the late 1970s, rural industrial parks (RIPs) have played a crucial role in the rise of the manufacturing industry in the Pearl River Delta (PRD), transforming the former agricultural land into a location of world-famous factories. However, as China has put forward higher requirements for economic development and stricter control measures for environmental pollution, RIPs with low-end industries and low efficiency present an urgent need for renovation and upgrade. By analyzing the spatial and socioeconomic cross-sectional dataset of rural industrial parks in Nanhai District of Foshan City, this paper attempts to classify the existing industrial parks into groups and propose corresponding redevelopment strategies. The results of the spatial analysis show that the spatial distribution of rural industrial parks is closely related to their location and transportation conditions. Failure of the market has resulted in large tracts of advantageous land being taken up by inefficient industrial parks. Cluster analysis and overlay analysis are used evaluate the difficulty of redevelopment and divide the industrial parks into three clusters: retained RIPs, medium-term-removed RIPs, and near-term-removed RIPs. It is shown that some of the industrial parks are still in good form while the majority need substantial reconstruction. Taking economic and institutional factors into consideration, the authors put forward that different strategies should be adopted for the future renovation of medium-term-removed and near-term-removed RIPs.

We addressed whether arbitrary top–down regulation based on self-referential thinking could be valid for sensorimotor synchronization. We hypothesized that the dorsal anterior cingulate cortex (dACC) could regulate sensorimotor synchronization in accordance with internal models generated by self-referential processing. To illustrate the validity of the hypothesis, we conducted a missing oddball task with musical students. Utilizing the event-related deep-brain activity (ER-DBA) method cooperatively with the event-related potential (ERP) method, we found that dACC activation promotes repetitive tapping supported by modal completion, whereas dACC deactivation promotes precise tapping under avoiding erroneous responses for the missing pulses. Endogenous ERP components including P150 as a marker of modal completion and N200 as a marker of response inhibition supported this claim. Furthermore, combining the ER-DBA and ERP results, it was suggested that the brain creates a coherent story to promote repetitive tapping by mediating sensory evidence via modal completion. The free energy measurements theoretically support these findings, thereby confirming the validity of our hypothesis.

The meaning of a good social outcome in land use transport policy/planning has been relatively underdeveloped, compared to economic and environmental sustainability goals, but this is now changing. Cities are increasingly prioritizing reducing social exclusion, with the allied intent of providing all residents with equitable access to the benefits of their city. However, in jurisdictions that use cost-benefit analysis to guide government decision-making, this poses a challenge: monetization of the benefits of reducing social exclusion is poorly developed. An evaluation gap thus confronts benefit-cost based assessment of initiatives intended to reduce social exclusion, compared to initiatives directed towards societal economic and environmental goals. This is a particular problem for public transport services that primarily enable people at risk of mobility-related social exclusion to access more opportunities in their society (social transit). The benefits of reducing social exclusion associated with these services have not been monetized, so social transit initiatives are poorly placed to argue their merits against competing initiatives where benefit monetization is more advanced (e.g., mass public transport and roads). The paper summarizes Australian research that has developed monetized measures for the value of increased trip making, bridging/bonding social capital, sense of community and several conceptions of wellbeing, and of reducing neighbourhood disadvantage, as these contribute to reducing social exclusion. New Singaporean research on the value of trip making to support reduced exclusion is also presented, affirming the Australian trip values. Trip values are then used in case study examples to show they can make a material difference to the societal worth of initiatives intended to reduce exclusion. Using these trip values, and other pathway values linked to reducing social exclusion, closes or at least substantially reduces the evaluation gap confronting social goal achievement in land use transport policy and planning, strengthening the case for reducing exclusion. These values will assist jurisdictions that are seeking to provide their residents with more equitable access to the benefits of their city.

Histone deacetylase 6 (HDAC6) regulates many physiological processes that are involved in cancer development and progression such as cell proliferation, apoptosis, motility, epithelial to mesenchymal transition, by deacetylation of multiple substrates and association with interacting proteins. Due to its the ability to remove misfolded proteins, induce autophagy, and regulate unfolded protein response, HDAC6 plays a protective role in responses to stress and enables tumor cells survival. HDAC6 is often overexpressed in tumors, including colorectal cancer (CRC) and is correlated with poor disease prognosis. However, it has been shown in animal models that HDAC6 is not essential for normal mammalian development. Therefore, it represents a good target for the development of novel cancer therapeutics. Selective inhibition of HDAC6 impairs growth and progression of many tumors without inducing major adverse events in experimental animals. In CRC, HDAC6 inhibitors have shown potential to reduce tumor progression and to enhance the therapeutic effect of other drugs. As HDAC6 is involved in regulation of immune responses, HDAC6 inhibitors have shown potential to improve antitumor immunity by increasing immunogenicity of tumor cells, augmenting immune cell activity and alleviating immunosuppression in tumor microenvironment. Therefore, HDAC6 inhibitors may represent promising candidates to improve the effect and to overcome resistance to immunotherapy.

The biological conservation measures factor (B) in the Chinese Soil loss Equation (CSLE) model is one of the main components in evaluating soil erosion, and the accurate calculation of B factor at the regional scale is fundamental in predicting regional soil erosion and the dynamic changes. In this study, we developed an optimal computational procedure for estimating and mapping the B factor in the Google Earth Engine (GEE) cloud computing environment using multiple data sources through data suitability assessment and image fusion. Taking the Yanhe River Basin in the Loess Plateau of China as an example, we evaluated the availability of daily precipitation data (CHIRPS, ERA5, and PERSIANN-CDR data) against the data at national meteorological stations. We estimated the B factor from Sentinel-2 data and proposed a new method, namely trend migration method, to patch the missing values in Sentinel-2 data using three other remote sensing data (MOD09GA, Landsat-7, Landsat-8). We then calculated and mapped the B-factor in Yanhe River Basin based on rainfall erosivity, vegetation coverage, and land use types. The results show that the ERA5 precipitation dataset outperforms the CHIRPS and PERSIANN-CDR data in estimating rainfall erosivity and rainfall, and it can be utilized as an alternative data source for meteorological stations in soil erosion modeling. Compared to the harmonic analysis of time series (HANTS), the trend migration method proposed in this study is more suitable for patching the missing parts of Sentinel-2 data. The restored high-resolution Sentinel-2 data fit nicely with the 10-m resolution land use data, enhancing the B factor calculation accuracy from the region to the spot level. The B factor computation procedure developed in this study is applicable to various river basin and regional scales for regional soil erosion monitoring.

During the progression of cancer cells, the degree of genome instability increases leading to genome chaos in populations of malignant cells. While normally chaos is associated with er-godicity, i.e., the state when the time averages of relevant parameters is equal to their phase space averages, the situation with cancer propagation is more complex. Chromothripsis, a catastrophic massive genomic rearrangement, is observed in many types of cancer leading to increased mu-tation rates. We present an entropic model of genome chaos and ergodicity and experimental evidence that increasing the degree of chaos beyond the non-ergodic threshold may lead to the self-destruction of the tumor cells. We study time and population averages of chromothripsis frequency in cloned rhabdomyosarcoma from rat stem cells. Clones with frequency above 10% result in cell apoptosis possibly due to mutations in the BCL2 gene. Potentially this can be used for suppressing cancer cells by shifting them into a non-ergodic proliferation regime.

The issue of optimising the initial stand density (ISD) of tree plantations has high practical importance. The objective of this study was to nondestructively evaluate the influence of the initial stand density of Scots pine plantations located in the European part of the Russian Federation on wood basic density (BD), moisture content (MC), ultrasound velocity (UV), latewood content, and drilling resistance (DR). 45-year-old trees with stand densities of 500, 1000, 3000, 5000, and 10000 trees/ha were tested by a 5-cm-long core sample for gravimetric MCGM and BD, by PULSAR-2.2 for UV along the height (UVH) and through the tree trunk diameter (UVD), by the IML-RESI PD-400 tool for DR, and by GANN HT 85T for MC based on the electrical resistance method (MCERM). A significant influence of ISD was found on DBH, UVD, MCGM, and MCERM. ISD had no significant impact on BD, UVH, and DR. The wood BD ranged from 356 to 578 kg/m-3, with a mean value of 434±3.3 kg/m-3, and was restricted by the soil and environmental factors. DBH and 70% MCERM were good indicators of tree vitality. Linear correlations between DBH and MCERM (R2=0.67), DBH and MCGM (R2=0.74), DR and BD (R2=0.71), and the two-factor model MCGM=f(DBH, BD), (R2=0.76) were found.

Tyrosyl-DNA phosphodiesterase 1 (Tdp1) is an important DNA repair enzyme and one of the causes of tumor resistance to topoisomerase 1 inhibitors such as topotecan. Inhibitors of this Tdp1 in combination with topotecan may improve the effectiveness of therapy. In this work, we synthesized usnic acid derivatives, which are hybrids of its known derivatives - tumor sensitizers to topotecan. New compounds inhibit Tdp1 in the micromolar and submicromolar concentration range; some of them enhance the effect of topotecan on the metabolic activity of cells of various lines according to the MTT test. One of the new compounds (compound 7) not only sensitizes Krebs-2 and Lewis carcinomas of mice to the action of topotecan, but also normalizes the state of the peripheral blood of mice, which is disturbed in the presence of a tumor. Thus, the synthesized substances may be the prototype of a new class of additional therapy for cancer.

The phytonutraceutical Ormona® is a product composed of: purified oil of Bixa orellana Linné; dry extract of Myrciaria dubia McVaugh; dry extract of Trifolium pratense L. and dry extract of Euterpe oleracea Mart. obtained using Evolve® technology. This study evaluated the effects of Ormona® on Wistar rats affected by ovariectomy-induced osteoporosis. Pre-treatment was conducted for 15 days before surgery and continued for a further 45 days after the surgical procedure. The experimental design consisted of 5 groups (n=5): OVW: treated with distilled water (1 mL/ kg, p.o); ADS: alendronate sodium (4 mg/ kg p.o); EST: conjugated estrogen (2 ug/ kg, p.o); ORM: Ormona® (20 mg/kg, p.o); ORM + EST: Ormona® (20 mg/kg + conjugated estrogen 2 ug/ kg, p.o. Biochemical and hormonal parameters, along with bone histopathology and trabecular and femoral diaphysis size, were evaluated through Scanning Electron Microscopy (SEM) and bone calcium quantification by atomic absorption spectrophotometry. The results show that ovariectomy caused bone alterations such as loss of femoral microarchitecture, decreased bone homeostasis parameters, and changes in the lipid profile. Estrogen supplementation reduced parameters such as cholesterol, LDL, and Ca2+ concentration. However, Ormona® showed higher serum estradiol levels (p&lt; 0.01), effects on the lipid profile, including parameters that estrogen replacement and alendronate sodium did not affect, with an increase in HDL, and positive modulation of bone metabolism, increasing osteocytes and the presence of osteoblasts. Ormona®, therefore, produced better results than the groups treated with estrogen and alendronate sodium.

In this paper, we present a groundbreaking methodology in the realm of aspect-level sentiment analysis, which capitalizes on the advanced capabilities of graph-based neural networks. Our approach, distinguished as the Aspect Correlation Graph Network (ACGN), represents a significant departure from conventional models. These traditional models often analyze aspects in isolation, failing to capture the intricate web of sentiment relationships that may exist within a single sentence. ACGN, however, is designed to address this gap by employing a sophisticated bidirectional attention mechanism, integrated with positional encoding. This unique combination not only enhances the model's ability to focus on relevant parts of the sentence but also aids in constructing detailed, aspect-focused representations. These representations are particularly crucial for understanding the nuanced interplay of sentiments associated with different aspects. Central to our model's architecture is the incorporation of a graph convolutional network. This network serves as a pivotal component in mapping and analyzing the complex network of sentiment correlations that can exist among various aspects within sentences. Through this integration, ACGN is able to unearth and interpret the subtle and often overlooked sentiment dynamics that traditional models might miss. Our comprehensive evaluations of the Aspect Correlation Graph Network, conducted using the SemEval 2014 datasets, have yielded promising results. These findings demonstrate a clear and significant advancement over the capabilities of existing models. Particularly, the results underscore the critical importance and utility of recognizing and understanding the connections between sentiments of different aspects in text analysis. This insight opens new avenues in the field of sentiment analysis, suggesting a broader application potential of ACGN in various contexts where understanding nuanced sentiment relationships is key. Overall, our study not only introduces a novel approach in aspect-level sentiment analysis but also sets a new standard for future research in this area. By highlighting the integral role of inter-aspect sentiment connections, ACGN paves the way for more sophisticated and accurate sentiment analysis tools, capable of handling the complexities of natural language with greater finesse and precision.

Improving performance and promoting sustainability in women's handball are key objectives to maximize the potential of female players and ensure the long-term viability of the sport. In this context, training with Olympic movements and their derivatives improves the development of strength, power, and speed, which are determinants of performance in team sports. The aim of this study was to determine if training with Olympic movements produces significant improvements in jumping, throwing, sprinting, and change of direction performance in women handball players. Twenty-one female handball players participated in the study (10 for the control group and 11 for the intervention group). Age ranged from 15 to 17 years. All participants performed four assessment tests (Abalakov Test, throw test, 20-meter Sprint and V-Cut Test) to determine jump height, throwing speed, running speed, and change of direction ability. Measurements were carried out before and after the intervention. For six weeks, the control group performed the strength work established by the club twice a week while the intervention group additionally performed training with Olympic movements. Significant differences (p &lt;0.05) were found between the pre and post measurement of the control group and the intervention group in jump height, throwing speed and running speed, being higher in the intervention group. For the change of direction, no significant differences were found. Between groups, significant differences were observed at the end of the intervention for jump height and running speed. The conclusion of this study was that, by training with Olympic movements, in addition to regular training, could produce greater improvements in jumping performance, throwing speed and running speed in female handball players.

Chilean jack mackerel (Trachurus murphyi) is recognized as one of the most valuable pelagic resources across the southeast Pacific Ocean. Despite its nutritious properties it is an underused resource due to its rapid spoilage. The use of high hydrostatic pressure (HHP) for the processing of aquatic products could be an efficient alternative to cold storage since HHP might inactivate microbial pathogens and slow down spoilage microorganisms, therefore extending the product’s shelf life. The aim of the study was to compare the effect of HHP at 450 and 550 MPa for 3 min on the physicochemical properties of jack mackerel muscle undergoing pre- and post-rigor mortis stage and further storage for 26 days at 4°C. pH, total volatile basic nitrogen, trimethylamine, color, water-holding capacity, and texture were assessed. The proximate composition, pH, total volatile basic nitrogen, trimethylamine, color, water holding capacity, and texture, showed significant changes between untreated and treated samples, while the water holding capacity was virtually unaffected. Overall results showed an acceptable and long-lasting edible quality of Trachurus murphyi stored at 4°C when preserved through HHP. These findings suggest that the HHP might be able to industrially scale the production of highly physicochemical superior and minimally processed fish products.

Enzymes are biological molecules produced by living entities for carrying out biological processes. The application of enzymes for waste treatment has been gaining pace commercially to solve concerns related to agricultural residues, wastewater, replacement of synthetic processes with natural ones, etc. The application of enzymes for waste management has been an environmentally reliable and sustainable process. Treatment of waste with enzymes such as xylanase, proteases, hydrolases, cellulose, peroxidases, chitinases, laccases, etc. has been studied to be effective. These enzymes act upon the waste products and transform them into biodegradable forms that can be recycled, reused and converted to value-added products. They have wide applications and utility as it has been an effective approach, economically cheaper and sustainable techniques. Application of such enzymes for waste management would be beneficial for reducing the quantity of waste, diminishing the negative effects of waste and pollution on the environment, and would be beneficial in bio-converting the waste products into alternate sources of energy. The current chapter focuses on different types of enzymes, their applications for waste management, and their limitations. This chapter also emphasizes the usage of some prominent microorganisms, their secreted enzymes and their proposed mechanisms of action involved with the degradation of the waste products.

Drought monitoring and early detection have improved greatly in recent decades through the development and refinement of numerous indices and indicators. However, a lack of guidance, based on user experience, exists as to which drought monitoring tools are most appropriate in a given location. This review paper summarizes the results of targeted user engagement and the published literature to improve the understanding of drought across North America, and to enhance the utility of drought monitoring tools. Workshops and surveys were used to assess and make general conclusions about the perceived performance of drought indicators, indices and impacts information used for monitoring drought in the five main Köppen climate types (Tropical, Temperate, Continental, Polar Tundra, Dry) found across Canada, Mexico, and the United States. In Tropical, humid Temperate, and southerly Continental climates, droughts are perceived to be more short-term (less than 6 months) in duration rather than long-term (more than 6 months). In Polar Tundra climates, Dry climates, Temperate climates with dry warm seasons, and northerly Continental climates, droughts are perceived to be more long-term than short-term. In general, agricultural and hydrological droughts were considered to be the most important drought types. Drought impacts related to agriculture, water supply, ecosystem, and human health were rated to be of greatest importance. Users identified the most effective indices and indicators for monitoring drought across North America to be the U.S. Drought Monitor (USDM) and Standardized Precipitation Index (SPI) (or another measure of precipitation anomaly), followed by the Normalized Difference Vegetation Index (NDVI) (or another satellite-observed vegetation index), temperature anomalies, crop status, soil moisture, streamflow, reservoir storage, water use (demand), and reported drought impacts. Users also noted the importance of indices that measure evapotranspiration, evaporative demand, and snow water content. Drought indices and indicators were generally thought to perform equally well across seasons in Tropical and the colder Continental climates, but their performance was perceived to vary seasonally in Dry, Temperate, Polar Tundra, and the warmer Continental climates, with improved performance during warm and wet times of the year. The drought indices and indicators, in general, were not perceived to perform equally well across geographies. This review paper provides guidance on when (time of year) and where (climate zone) the more popular drought indices and indicators should be used. The paper concludes by noting the importance of understanding how drought, its impacts, and indicators are changing over time as the climate warms, and by recommending ways to strengthen the use of indices and indicators in drought decision-making.

A paddle wheel aerator is developed in this research, which includes a wireless sensor network for measuring the water quality in the aquaculture of marine shrimp ponds. It can also move to the desired position to fill oxygen and measure water quality. A basic requirement is good standard water quality to prevent shrimp from epidemics and improve production. The water quality paddle wheel aerator applies a microcontroller and sensors to measure eight parameters of water quality. These water quality parameters are observed on the web application via an IoT module. The movement system of the water-quality paddle wheel aerator consists of a LiDAR, GPS, and remote RF signal. Each item of data is recorded immediately on the cloud server while the water-quality paddle wheel moves in the marine shrimp farm. The controlled paddle wheel aerator is harnessed automatically to enhance precisely the spatial monitoring resolution of the measurement system installed, which is needless for a multiple measurement system with high cost of investment. Also, farmers can access real data through the Line application. Hence, they are able to plan and control a good environment for aquaculture, preventing the occurrence of various epidemics and decomposing organic matter in the pond.

Background. This is a retrospective analysis of the results of treatment for varicose veins using the sandwich technique with cyanoacrylate glue and foam sclerotherapy. This novel method al-lows for substantial reduction of amount of glue needed for the vein closure, and minimizes the risk of granuloma formation and allergic reaction related to the epifascial administration of cy-anoacrylate. Methods: This technique was used in 60 patients, 77 intrafascial veins were managed. Vein closures were performed with Venex cyanoacrylate glue and 1-3% polidocanol foam. All proce-dures were done under ultrasonographic control, though direct percutaneous punctures of target veins. Follow-up were scheduled 1-3 week after the procedure. If revealed, unclosed segments of the target veins were obliterated at these follow-up visits, with glue and/or sclerotherapy. Results. There were no serious adverse events intra- or postprocedurally. The technical success rate was 100%. The primary success rate at 1-3 week follow-up was 84.4%. The primary assisted success rate, after additional closures, was 100%. Conclusions. We demonstrated that the treatment for varicose veins, using sandwich tech-nique, which combines cyanoacrylate glue and foam sclerotherapy, can be safe and efficient.

This study examines the impact of chainsaw chain type and tree species on the concen-tration of inhalable wood dust generated during motor-manual harvesting in forested areas. The chainsaw chain is a critical component, contributing not only to productivity but also to the oper-ator's health and safety. Wood dust creation during harvesting operations poses significant risks and necessitates careful attention due to its potential health effects. We investigated the effects by conducting real-world measurements of inhalable dust within the operator's breathing zone during forestry work. Two different chain types were evaluated: the commonly used 3/8" pitch chain (conventional chain) and the 0.325" pitch chain. Additionally, measurements were taken for three tree species: beech, oak, and pine (including both live and standing dead trees after a fire). Results showed that, overall, using the conventional 3/8" chain type yielded the highest concentration of wood dust for all three tree species. Notably, the highest wood dust concentration was observed in the burned Pinus brutia cluster, also with the 3/8" chain pitch. These findings emphasize the im-portance of understanding how chain type and tree species contribute to wood dust levels and provide valuable insights for enhancing operator health and safety during motor-manual har-vesting operations

In high-traffic harbor waters, marine radar frequently encounters signal interference stemming from various obstructive elements, thereby presenting formidable obstacles in the precise identification of ships. To achieve precise pixel-level ship identification in the complex environments, a customized neural network-based ship segmentation algorithm named MrisNet is proposed. MrisNet employs a lightweight and efficient FasterYOLO network to extract features from radar images at different levels, capturing fine-grained edge information and deep semantic features of ship pixels. To address the limitation of deep features in the backbone network lacking detailed shape and structured information, an adaptive attention mechanism is introduced after the FasterYOLO network to enhance crucial ship features. To fully utilize the multi-dimensional feature outputs, MrisNet incorporates a Transformer structure to reconstruct the PANet feature fusion network, allowing for the fusion of contextual information and capturing more essential ship information and semantic correlations. In the prediction stage, MrisNet optimizes the target position loss using the EIoU function, enabling the algorithm to adapt to ship position deviations and size variations, thereby improving segmentation accuracy and convergence speed. Experimental results demonstrate that MrisNet achieves high recall and precision rates of 94.8% and 95.2%, respectively, in ship instance segmentation, outperforming various YOLO and other single-stage algorithms. Moreover, MrisNet has a model parameter size of 13.8M and real-time computational cost of 23.5G, demonstrating notable advantages in terms of convolutional efficiency. In conclusion, MrisNet accurately segments ships with different spot features and under diverse environmental conditions in marine radar images. It exhibits outstanding performance, particularly in extreme scenarios and challenging interference conditions, showcasing robustness and applicability.

Nowadays, the combination of fingerprinting methodology with friendly environmental and economical analytical instrumentation are becoming increasingly relevant in the food sector. In this study, a highly versatile portable analyser based on Spatially Offset Raman Spectroscopy (SORS) to obtain the edible vegetable oils (sunflower and olive oils) fingerprints was used to evaluate the capability of such fingerprints, obtained quickly, reliable and without any sample treatment, to discriminate/classify the analysed samples. After data treatment, not only HCA and PCA as unsupervised pattern recognition techniques but also SVM, kNN and SIMCA as supervised pattern recognition techniques, showed that the main effect over the discrimination/classification was associated to those regions of RAMAN fingerprint related to the free fatty acids content, especially oleic and linoleic acid. These facts allowed the discrimination attending to the original raw material used in the oil's elaboration. In all the model established, reliable qualimetric parameters were obtained.

The study aimed to investigate the effect of climate change exposure on affect and pro-environmental behavioural intentions in a randomised controlled trial. An online survey was completed by 100 adult participants and included measures of affect and pro-environmental behavioural intentions pre- and post-exposure. Participants were randomly allocated to a group that saw a climate change video (n=55) or a group that saw a non-climate change video (n=45). The findings showed were that participants in the climate change group showed a significant increase in negative affect and pro-environmental behavioural intention scores post-video exposure compared to the non-climate change video group. This suggests that climate change video exposure negatively influences affect but also potentially increases the intention to act pro-environmentally. These findings have the potential to support policies and societal change, however further investigation into the type of contents, actual behaviour change, and impacts on diverse populations (e.g., minority groups) is needed that influences pro-environmental behaviours is required. Furthermore, to achieve a greater impact, future research should be conducted measuring actual pro-environmental behaviour change, including with those from diverse populations.

Equipping autonomous agents for dynamic interaction and navigation is a significant challenge in intelligent transportation systems. This study aims to address this by implementing a brain-inspired model for decision-making in autonomous vehicles. We employ active inference, a Bayesian approach that models decision-making processes similar to the human brain, focusing on the agent's preferences and the principle of free energy. This approach is combined with imitation learning to enhance the vehicle's ability to adapt to new observations and make human-like decisions. The research involved developing a multi-modal self-awareness architecture for autonomous driving systems and testing this model in driving scenarios, including abnormal observations. The results demonstrated the model's effectiveness in enabling the vehicle to make safe decisions, particularly in unobserved or dynamic environments. The study concludes that the integration of active inference with imitation learning significantly improves the performance of autonomous vehicles, offering a promising direction for future developments in intelligent transportation systems.

A simple method is presented for the continuous generation of carbon nanotube forests stably anchored on stainless-steel surfaces using a reactive-roll-to-roll (RR2R) configuration. No addition of catalyst nanoparticles is required for the CNT-forest generation, the stainless-steel substrate itself being tuned to generate the catalytic growth sites. The process enables very larges surfaces covered with CNT forests having individual CNT roots anchored to the metallic ground through primary bonds. Fog water harvesting is demonstrated and tested as one potential application using long CNT-covered wires. The RR2R is performed in the gas phase, no solution processing of CNT suspensions is used contrary to usual R2R CNT-based technologies. Full or partial CNT-forest coverage provides tuning of the ratio and shape of hydrophobic and hydrophilic zones on the surface. This enables optimization of fog water harvesters for droplet capture through the hydrophobic CNT forest, and water removal from the hydrophilic SS surface. Water recovery tests using small harp-type harvesters with CNT-forest generate water capture of up to 2.2 g/cm2h under ultrasound-generated fog flow. The strong CNT root anchoring on the stainless steel surfaces provides opportunities for (i) robustness and easy transport of the composite structure, (ii) chemical functionalization and/or nanoparticle decoration of the structures, and opens the road for a series of applications on large scale surfaces, including fog harvesting.

Dravet syndrome (DS), also known as severe myoclonic epilepsy of infancy, is a rare and drug-resistant form of developmental and epileptic encephalopathies, which is both debilitating and challenging to manage, typically arising during the first year of life, with seizures often triggered by fever, infections, or vaccinations. It is characterized by frequent and prolonged seizures, developmental delays, and various other neurological and behavioral impairments. Most cases result from pathogenic mutations in the sodium voltage-gated channel alpha subunit 1 (SCN1A) gene, which encodes a critical voltage-gated sodium channel subunit involved in neuronal excitability. Precision medicine offers significant potential for improving DS diagnosis and treatment. Early genetic testing enables timely and accurate diagnosis. Advances in our understanding of DS's underlying genetic mechanisms and neurobiology have enabled the development of targeted therapies, such as gene therapy, offering more effective and less invasive treatment options for patients with DS. Targeted and gene therapies provide hope for more effective and personalized treatments. However, research into novel approaches remains in its early stages, and their clinical application remains to be seen. This review addresses the current understanding of clinical DS features, genetic involvement in DS development, and outcomes of novel DS therapies.

This comprehensive review delves into the multifaceted aspects of ERK signaling and the intricate mechanisms underlying distinct cellular fates. ERK1 and ERK2 (ERK) govern proliferation, transformation, epithelial-mesenchymal transition, differentiation, senescence, or cell death, con-tingent upon activation strength, duration, and context. The biochemical mechanisms underlying these outcomes are inadequately understood, shaped by signaling feedback and the spatial localization of ERK activation. Generally, ERK activation aligns with the Goldilocks principle in cell fate determination. Excessive or insufficient ERK activity inhibits growth, whereas moderated activation supports proliferation and survival. Unraveling the intricacies of how the degree of ERK activation dictates cell fate requires deciphering mechanisms encompassing protein stability, transcription factors downstream of ERK, and the chromatin landscape.

Guava (Psidium guajava L.) is a species is widely distributed in Córdoba, despite this, there are few studies that have been carried out to understand its genetic diversity. For this reason, the objective of this research was to evaluate the genetic diversity and variability of guava (Psidium guajava L) using microsatellite markers in Montería, Córdoba-Colombia. Forty-five accessions were evaluated. For DNA extraction, the CTAB 2x extraction protocol was used with modifications. The extracted DNA was amplified by the PCR technique using seven microsatellite markers. A total of 46 alleles were found with an average of 6.5 alleles per locus. A total of 28 private alleles were identified in the populations, possibly fixed by different evolutionary forces. The evaluated population presented an average expected heterozygosity of 0.572 and the observed heterozygosity was lower (0.058). The fixation index presented a total average of 0.906, indicating that in Montería there is an excess of homozygotes. The PIC values allowed us to determine that the markers mPgCIR9, mPgCIR11, mPgCIR13, mPgCIR16, mPgCIR19 and mPgCIR22 are highly informative, while mPgCIR23 is moderately informative. The guava population in Montería presented a low genetic diversity within the subpopulations, which could be related to inbreeding events such as self-pollination..

This article focuses on the variation of how the U.S. Circuit Court of Appeals uses the language of trauma in gender-based asylum claims. Gender-based asylum claims include female genital mu-tilation (FGM), domestic violence, forced marriage, coercive population control (CPC) in the form of forced abortions and forced sterilizations, and rape. The Circuit Courts have reviewed appeals from petitioners with asylum claims since 1946, yet the language of trauma did not appear in the Court’s decisions until 1983. From 1983-2023 only 385, 3.85% or less, of the over 10,000 asylum cases before the Circuit Courts used the language of trauma in its legal interpretation of persecution. I have identified 101 gender-based asylum cases that were reviewed by one of the eleven U.S. Circuit Court of Appeals that apply the language of trauma in its legal interpretation of persecution for this analysis. This study found that U.S. Circuit Courts use the language of trauma in four ways: precedent cases, psychological trauma, physical trauma, and policies and reports when reviewing gender-based asylum claims.

To ensure sustainable production and consumption in the agricultural sector, it is necessary to assess the contribution of each element of the nexus in the agricultural production chain. The aim of this study is to make a quantitative and qualitative analysis of the contributions of each element of the energy, water, waste and land nexus to agricultural products. A composite method approach combining aspects based on input-output model, Location Quotient (LQ) as well as competitive position is adopted. A database of nexus elements over a period from 2009 to 2018 is used for Cameroon, with ten regions considered. The results show proportions of around 0.42% energy, 67.88% water withdrawal, 11.91% harvested area, 97.81% waste for agricultural products. The geolocation of harvested areas shows that the largest portion is in the far north (1,373,829 ha) and the smallest in Adamawa (224,038 ha). Maximum production is in the central region (4,334,095 tons) and minimum in the Adamawa region (915,841 tons). The central, littoral and west regions are more representative of agricultural products. The analysis of the competitive position of agricultural products contributes to a better orientation of national strategies for agricultural sustainability according to existing potentials.

While Neural Radiance Fields (NeRF) are gaining increasing interest in various domains as innovative methods for novel view synthesis and image-based reconstruction, their potential application in the realm of Cultural Heritage remains unexplored. Purpose of this paper is to assess the effectiveness of applying NeRF to sets of images of digital heritage objects and sites. The study’s findings demonstrate that NeRF could be valuable when used in combination with or as a comparison to other well-established techniques such as photogrammetry, to expand the possibilities of preserving and presenting heritage assets with enhanced visual fidelity and accuracy. Particularly, NeRF show promising results in improving the rendering of translucent and reflective surfaces, objects with homogeneous textures, and elements with intricate details. In addition, we demonstrate that, when considering the same set of input images (with known camera poses), reducing the image quality or the number of images results in significantly less information loss with NeRF compared to photogrammetry. This suggests that NeRF is preferentially suited for scenarios involving sparse information or low-quality photos or videos, which could be especially valuable in risky or challenging situations.

Smelting used to be less efficient in the past, so wastes obtained from historical processing at smelter plants usually contain certain quantities of valuable metals. A case study was conducted, which included an investigation of the physicochemical, mineralogical, and microstructural properties of raw material found at the historic slag pond near the Topilnica Veles smelter in North Macedonia. The Pb-Zn slag was sampled using traditional geophysical methods such as drill holes and pitholes. The mineralogical and microstructural analysis revealed that the Pb-Zn slag is a very complex and inhomogeneous alternative raw material with utilizable levels of metals, specifically Pb (2.24 wt%), Zn (7.10 wt%), and Ag (27.53 ppm). Amorphous phase, lead alloys, zinc alloys, wurtzite, sphalerite, galena, cerussite, elemental silver, elemental copper, elemental iron, magnetite, spinel, rutile, hematite, and troilite were also identified through qualitative mineralogical analysis. The glassy matrix composed of spinel, silicates, and mixed spinel-silicate is the most abundant constituent in slag composition. The various potential applications of the slag are possible based on its mineralogical and geochemical properties. Because the extraction of Pb, Zn, and Ag has certain economic potential, the next step, which will include gravity concentration and magnetic separation procedures, will be to form metal concentrates into their collective concentrate, from which the maximum amount of silver can be extracted. Slag's amorphous spinel, silicate, and mixed spinel-silicate phases, which contain high concentrations of SiO2, Al2O3, CaO, and Fe2O3, are suitable for use in building materials such as cement clinker, filler, or aggregate for concrete or mortar. The goal of this research is to close the circle of slag's reutilization potential in terms of Net Zero and Zero Waste principles, so it is critical to thoroughly investigate the material and establish methods and preparation processes, as well as ways of concentrating useful components into commercial products.

E-waste is considered the fastest-growing global waste stream and has become an emerging environmental challenge. The widespread usage of digital devices has generated a large amount of e-waste. According to the Ministry of Commerce, India annually generates ~14.5 lakh metric tons of e-waste and recycles only ~5 % of e-waste. Annually, the global production of e-waste has been expected to increase by 4–5 %. Advancements in IT and communication divisions have improved the usage of electronic equipment. Heavy metals such as (Pb), mercury (Hg), arsenic (As), tin (Sn), and organic chemicals such as polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs), polybrominated biphenyls (PBBs), polybrominated dibenzo-p-dioxins (PBDDs), polybrominated diphenyl ethers (PBDEs) are subsequently released from e-wastes and contaminates soil and water sources. These toxic compounds are hazardous to human health and the environment. They are capable of entering various biological systems and causing alterations in respiratory functions of the lungs, DNA damage, impaired functioning of the thyroid, and increased risk of chronic diseases such as cancer and cardiovascular ailments. Such concerns raise the quintessential need to manage e-waste to prevent future hazards. This manuscript critically reviews the sources, health and environmental impact, disposal techniques, recycling, and regulation of e-waste.

The COVID-19 outbreak demonstrated the viability of various remote working solutions, telepresence robots (TPRs) being one of them. High-quality video transmission is one of the cornerstones of using such solutions, as most of the information about the environment is acquired through vision. This study aims to compare the camera capabilities of four models of popular telepresence robots using compact reduced LogMAR and Snellen optometry charts as well as text displayed on the projector screen. The symbols from the images are extracted using OCR (Optical Character Recognition) software and the results of the recognition are compared with the symbols on the charts. Double 3 TPR provides the best quality images of optometric charts, but the OCR results of measurements of the image on the projector do not show the clear advantage of one single model over the others. The results demonstrated by Temi 2 and Double 3 TPRs are generally better than the others, suggesting that these TPRs are more feasible to be used in teaching and learning scenarios.

Abstract: Important variables that affect the quality and functionality of sperm and may affect male reproductive health and fertility include telomere length, mitochondrial content, and the ratio of mitochondrial DNA (mtDNA) to nuclear DNA (nDNA). The purpose of this study was to look at the connections between these three sperm characteristics and how they might affect a woman's ability to conceive. Methods: Data were collected from 82 men who underwent IVF/ICSI at the University Hospital of Ioannina's IVF Unit in the Obstetrics and Gynecology Department. Evaluations included sperm morphology, sperm count, sperm motility, and participant history. To address this, males of reproductive age who were categorized into three body mass index (ΒΜΙ) groups—normal, overweight, and obese—had their sperm samples tested. Results: Our findings indicate a negative correlation between relative telomere length and ΒΜΙ for both the normal and overweight groups. Conversely, a positive correlation was observed for the obese group, indicating a possible relationship between mitochondrial health and telomere maintenance. The results were statistically significant only for the obese group. Furthermore, a negative correlation was observed between telomere length and mitochondrial content in both the normal and overweight groups, indicating that a lower mitochondrial content may be linked to longer telomeres. Nonetheless, there was a positive correlation for the group that was obese. For all three groups, the data did not reach statistical significance. Given that mitochondrial con-centration and telomere length are both markers of cellular integrity and health, these correla-tions may have an impact on the quality of sperm. Furthermore, the relative telomere length of the normal and overweight groups had a negative correlation with the ratio of mtDNA to nDNA, though the obese group showed a positive correlation. The findings were not statistical-ly significant in any of the groups under investigation. According to this, male fertility may be negatively impacted by an imbalance in the copy number of the mitochondrial genome com-pared to the nuclear DNA in sperm. Conclusions: Our research, in essence, emphasizes the interaction among human sperm telo-mere length, mitochondrial concentration, and the mtDNA to nDNA ratio. Gaining knowledge of these correlations could help explain the reasons behind male infertility and open up new treatment options for reproductive health problems. The functional importance of these correla-tions and possible uses in therapeutic contexts require more investigation.

Micro and small wood-processing enterprises represent the heart of the European forest-based industries, being among the key drivers of economic growth in rural, mountainous, and poor regions. Their economic efficiency is of fundamental importance for their existence and the pro-vision of income for the local population in rural areas. Data Envelopment Analysis (DEA) is nonparametric, linear-programming-based approach, commonly used to analyse the efficiency of organizational units. This method allows estimating the economic efficiency of a certain eco-nomic system without assumptions about the functional form between resources and products. Furthermore, DEA determines the efficiency frontier and gives results of whether an enterprise, i.e., a Decision Making Unit (DMU) is efficient or not. The main objective of this study was to investigate and evaluate the economic efficiency of micro and small wood-processing enterpris-es in the EU countries and reveal the hidden inputs that facilitate efficiency generation. The eco-nomic efficiency evaluation was carried out on the basis of the official statistical data for the mi-cro and small wood-processing companies in the EU member states for the period 2015-2020 by performing a two-stage DEA analysis. The data used were standardized by value per employee. In addition to the first stage of DEA, fractional regression probit and logit models with four contextual variables were used to reveal the influence of the hidden inputs in the model. The results showed that the micro and small wood-processing enterprises can be regarded as more scale-efficient than technically-efficient entities. The only contextual variable affecting the eco-nomic efficiency was Investments per Person Employed, improving the efficiency by 2% per 1% increase of the investments.

A question of physical importance is whether finite-energy spatiotemporally localized (i.e., pulsed) generalizations of monochromatic accelerating Airy beams are feasible. For luminal solutions, this question has been answered affirmatively by Saari, Valdmann, Piksarv, Valta-Lukner and Saari, and Kaganovsky and Heyman within the framework of the paraxial geometry. The time-diffraction technique introduced by Porras recently has been motivated by Besieris and Shaarawi in terms of the Lorentz invariance of the equation governing the narrow angular spectrum and narrowband temporal spectrum paraxial approximation and has been used to derive finite-energy spatiotemporally confined subluminal, luminal, and superluminal Airy wave packets. The goal in this article is to provide exact finite-energy broadband spatiotemporally localized Airy solutions (a) to the scalar wave equation in free space; (b) in a dielectric medium moving at its phase velocity; (c) in a lossless second order temporally dispersive medium.

Background: Inflammasomes recognize cytosolic danger signals, including pathogens, and subsequently induce the secretion of pro-inflammatory cytokines, such as interleukin (IL)-1β. Studying inflammasomes in the red fox (Vulpes vulpes) is crucial from a wildlife veterinary and public health perspective, as it can be used to help control and prevent the transmission of zoonotic pathogens. The understanding of how diversity in inflammasomes across species affects pathogen carriage in the red fox is still limited. Methods: We investigated the activation and intracellular mechanisms of three inflammasomes (NLRP3, AIM2, and NLRC4) in fox peripheral blood mononuclear cells (PBMCs), using established triggers and inhibitors derived from humans and mice. Results: Fox PBMCs exhibited normal activation and induction of IL-1β secretion in response to representative inflammasome triggers (ATP and nigericin for NLRP3, dsDNA for AIM2, flagellin for NLRC4). However, in inhibitor studies, MCC950, a selective NLRP3 inhibitor, suppressed IL-1β secretion mediated by the fox AIM2 and NLRC4 inflammasomes. Conclusions: These findings suggest that NLRP3 may have a common role in dsDNA- and flagellin-mediated inflammasome activation in the red fox. In conclusion, this fox inflammasome biology can be applied to the control of zoonotic infections and the treatment of inflammasome-mediated diseases in the red fox.

A key component for the proper functioning, availability, and reliability of power grids is the power trans- former. Although these are very reliable assets, the early detection of incipient degradation mechanisms are very important to prevent failures that may shorten their lifetime. In this work a review and comparative analysis, of classical Machine Learning algorithms (such as single and ensemble classification algorithms) and two automatic machine learning classifiers, are presented for the fault diagnosis of power transformers. The goal is to determine whether fully automated ML approaches are worse or better than traditional ML frameworks that require a human in the loop (such as a data scientist) to identify transformer faults from oil-dissolved gases data. The methodology uses a DB compiled from published and proprietary transformer fault samples. Faults data is obtained from the literature, the Duval pentagon method, and user-expert knowledge. The parameters from, either single or ensemble classifiers, were optimized through standard machine learning procedures. The results showed that the best performing algorithm is a robust automatic machine learning classifiers model followed by classical algorithms such as neural networks and stacking ensembles. These results highlight the ability of a robust automatic machine learning model for, handling imbalanced power transformers faults datasets with high accuracy, using the minimum tuning effort by the electrical experts. By providing the most probable transformer fault condition will reduce the time required to find and solve the fault.

Anion doping of tungsten trioxide by nitrogen is used to obtain electrochrome cathode material, the spectral transmittance of which can be controlled by the doping level. A series of samples was synthesized by reactive magnetron sputtering of a metal tungsten target in a mixture of argon, nitrogen and oxygen gases. Warm-colored tungsten oxynitride films were prepared at higher doping levels and characterized using scanning electron microscopy, X-ray diffraction and X-ray photoelectron spectroscopy techniques. Optical properties were measured making use of transmission spectrophotometry and spectroscopic ellipsometry. These extensive experimental studies revealed an increase in absorption towards shorter wavelengths with increasing the doping level. At the same time, it was found that with increasing the doping level, the fraction of non-stoichiometric oxygen also steadily increases to half the total oxygen content. The imperfection of the doped material can stimulate its intercalation with electrolyte ions, accelerating the coloring/bleaching process and increasing the dynamical range between the dark and clear states, thus improving the consumer qualities of electrochemical materials and devices.

Plasmonic nanomaterials have garnered considerable attention in the scientific community due to their applicability in light-mediated technologies, owing to tunability, large light absorption cross-sections, transparency, and potential scalability. While single morphology plasmonic nanoparticles exhibit substantial absorption cross-sections, their effectiveness is limited to a narrow energy window, especially under polychromatic illumination like sunlight. Integrating plasmonics with a Fabry-Pérot nanocavity is a promising approach to broaden the absorption energy range of the photosystem. Traditionally, the fabrication of these nanocavities involves clean room processes, posing scalability challenges. This study presents a novel approach, demonstrating the successful enhancement of light absorption in a plasmonic photoelectrode system through a Fabry-Pérot nanocavity created using bottom-up solution methods. This innovative technique not only overcomes the scalability issues associated with clean room processes but also enables the production of scalable photosystems that can be rendered entirely opaque or semitransparent. Such versatility opens up a multitude of application possibilities for these photosystems.

The Semantic-Enhanced Tree-LSTM (SeT-LSTM) network, a novel advancement in the realm of linguistic modeling, marks a significant step forward from traditional Tree-based Long Short Term Memory (LSTM) networks. By intricately weaving in the nuances of typed grammatical dependencies, SeT-LSTMs offer a more nuanced understanding of language semantics. Traditional models often overlook the semantic shift caused by variations in word or phrase roles, a gap this paper aims to fill by focusing on the types of grammatical connections, or typed dependencies, within sentences. Our proposed architecture, dubbed the Semantic Relationship-Guided LSTM (SRG-LSTM), leverages a control mechanism to model the interplay between sequence elements. Additionally, we present a novel Tree-LSTM variant, the Semantic Dependency Tree-LSTM (SDT-LSTM), which integrates dependency parse structures with dependency types for more robust sentence embedding. The SDT-LSTM demonstrates superior performance in Semantic Relatedness Scoring and Sentiment Analysis compared to its predecessors. Qualitatively, it shows resilience to changes in sentence voice and heightened sensitivity to nominal alterations, aligning well with human intuition. This research underlines the pivotal role of grammatical relationships in sentence understanding and paves the way for further exploration in this domain.

Contemporary diagnostic practice in psychiatry relies on the tick-box approach of diagnostic manuals. In light of the obvious limitations of diagnostic systems, narrative formulations, whether in the form of biological, psychodynamic or behavioural cognitive ones, have been proposed. Their approach, which can be caricatured as one of drawing arrows, enriches our clinical tools and practice but in their explicitly theoretical orientation, as well as expanding the field of discovery, they also constrain it. In two previous papers I summarized the resulting limitations, with specific reference to the patient’s experience and proposed further enriching clinical perspicacity by attending to images and parataxis. The specific intent of attending to the patient’s experiences through a process that explicitly eschews narrativization, but allows clinical phenomena to “hang loose”, is to facilitate a process of clinical discovery and healing through practices of co-production between patient and clinician. In the present paper, I expand the range of phenomena that may assist in this co-production through adding attention to dreams to that of images and parataxis. In particular, I turn to the work of the Italian novelist Guido Morselli. Morselli agrues that the self is created through bundling experiences together through acts of “will” in order to establish our personal narrative. In doing so, however, the “will” forbids access to phenomena that do not fit the dominant narrative. Experience is therefore impoverished. Dream consciousness is a type of consciousness not harnessed by the constraints of narrativity. It allows a slipping of the narrative vigilance which bundles phenomena together to create a coherent narrative and thus offers a richer menu of potential experiences, including “bizarre” images that can serve to challenge our usual self-narrative and offer a new perspective on ourselves.

Understanding aspects of maritime/underwater cultural heritage (MUCH) and the associated cultural values and integrating them into maritime spatial planning (MSP) endeavors, is a new global challenge, alongside the rapid increase of human activities at sea and climate change impacts on the seas and the oceans. The article highlights the significance of cultural values in shaping human interactions with the marine environments, and how MSP can address the cultural dimensions of marine resources management. To this end, a systematic literature review was carried out to address the research question on how maritime/underwater cultural heritage is incorporated into MSP and map relevant academic literature. Following, a methodology that entailed an academic database search and the application of exclusion criteria, 346 articles resulted from Scopus. These articles were classified using science mapping techniques (i.e the VOSviewer Software ) and several categories (clusters) were created. The research showed a diversity of literature addressing the relationship between MUCH and MSP with a strong focus on sustainability, the significance of cultural ecosystem services (CES) and cultural values, the role of indigenous and local communities, but also of local stakeholders, the transfer of traditional knowledge to MSP and the participatory approaches and tools. The article concludes that for MSPlans to be innovative and acceptable by local communities, the “missing layer”of socio-cultural values and data is indispensable. In the MSP process, MUCH should be understood within this broader framework of socio-cultural considerations and values.

This research deals with risk assessment for human life, man-made infrastructure, and agriculture in a landslide-prone area using GIS-based spatial methods. The study area landslide inventory map was prepared based on previous landslide information, aerial photograph analysis, and several field observations. A total of 550 landslides have been included with 182 debris flow and 368 soil slides. All included landslides were classified into two groups by random selection; half were used for model calibration and the rest were used for cross-validation. In the analysis, fourteen causative factors were vastly used, such as aspect, slope, curvature, elevation, topographic wetness index, forest timber diameter, forest type, forest crown density, forest age, land-use, geology, soil drainage, soil depth, and soil texture. Moreover, to identify the interaction between occurred landslides and causative factors, the affected pixels were divided into different sub-classes using a frequency ratio method. Based on the total dataset, three landslide susceptibility maps were constructed using Bayesian prediction, likelihood ratio, and fuzzy set method. By evaluating cross-validation and success rate curve, model susceptibility results were plotted with a receiver operating characteristic (ROC) curve and the area under the curve (AUC) was estimated. In addition, for risk assessment, each social data layer such as agriculture, house, industry, business, road, river, population intensity, monetary value, and vulnerability level was added based on the local standard and incident time and was converted into US dollars. During the analysis, each method hazard map was used with a specific group of thematic data layers. Subsequently, for preparing the probability table, study area total pixels and predictive landslide affected pixels were considered. Matching with the affected pixels, a standard of 5000 pixels was selected to run the final evaluation. Based on the results, the agricultural field showed the highest vulnerability and estimated risk of US $ 16.3 million. Further, the man-made infrastructure map showed a risk of US $ 31.3 million. The total estimated population casualties were 6.77, which was relatively similar to the published data.

Omentin is an adipokine mainly produced by visceral fat tissue, and it has two isoforms: omentin-1 and omentin-2. Omentin-1 is predominantly secreted by visceral adipose tissue, deriving specially from the stromal vascular fraction cells of white adipose tissue (WAT). Levels of omentin-1 are also expressed in other WAT depots, like epicardial adipose tissue. Omentin-1 exerts several beneficial effects in glucose homeostasis in obesity and diabetes. In addition, research has suggested that omentin may have atheroprotective (protective against the development of atherosclerosis) and anti-inflammatory effects, potentially contributing to cardiovascular health. This review highlights the potential therapeutic targets of omentin-1 in metabolic-related disorders.

This rapid review aims to present a comprehensive overview of barriers and facilitators or factors, and, effective interventions that promote immunisation uptake by older people in the Asia-Pacific region. Rapid review methodology was applied using two databases (PubMed, Embase). Articles were included if studies were conduced in Australia, Singapore, Indonesia and the Philippines, included human population ≥50 years old, used original data, adopted quantitative, qualitative, and mixed-method designs, and published from 2016 to August 2022. The study selection yielded 1424 articles. A total 23 papers met the inclusion criteria, of which 19 reported on barriers and facilitators, while, 4 articles reported on effective interventions to promote vaccination uptake. Among the 19 studies that identified barriers and facilitators to vaccination uptake, the more common factors were social influences (n=8/19), perceived benefits of vaccine (n=7/19), and perceived vaccine safety (n=6/19). Strategies that focussed on supporting clinicians were found to be effective in leading them to recommend vaccinations among older adults such as creating awareness on the low baseline vaccination rates among older adults, provision of structured health assessment, and nurse reminders. More studies are needed ascertain the factors, and effective interventions influencing vaccine uptake among older people in the Asia-Pacific region.

Jacobian-free Newton Krylov (JFNK) is an attractive method to solve nonlinear equations in nuclear engineering systems, and has been successfully applied to steady-state neutron diffusion (k-eigenvalue) problems and multi-physics coupling problems. Preconditioning technique plays an important role in JFNK algorithm, significantly affecting computational efficiency. The key point is how to automatically construct a high-quality preconditioning matrix that can improve the convergence rate, and perform the preconditioning matrix factorization efficiently. An efficient reordering-based ILU(k) preconditioner is proposed to achieve the above objectives. In detail, the finite difference technique combined with the coloring algorithm is utilized to construct an efficient preconditioning matrix with low computational cost automatically. Furthermore, the reordering algorithm is employed for the ILU(k) to reduce the additional non-zero elements and pursue robust computational performance. A two-dimensional LRA neutron steady-state benchmark problem is used to evaluate the performance of the proposed preconditioning technique, and steady-state neutron diffusion problem with thermal-hydraulic feedback is also utilized as a supplement. The results show that coloring algorithms can efficiently and automatically construct the preconditioning matrix. The reordering-based ILU(k) preconditioner shows excellent robustness, avoiding the effect of fill-in levels k choice in incomplete LU factorization.

This study assessed the impacts of genotypes, environments, and their interaction on the performance of elite cowpea lines for key adaptive, grain yield, and associated traits across different locations. A total of 42 elite genotypes were evaluated in five Nigerian environments, representing various savanna ecologies during the 2021 growing season. The experimental design employed was an alpha lattice arrangement, replicating each genotype three times. The results revealed significant differences among genotypes, environments, and genotype-by-environment interaction for most traits, including days to maturity, 100 seed weight, and grain yield. GGE biplot showed G21 (IT14K-2111-2) and G25 (IT15K-2386-1) as the most stable genotypes across the five environments, G41(IT1K-61-82) was best adapted to Ibadan and Shika, G5 (245-1) was best adapted to Bagauda and Gumel while G30 (IT16K-2365-1) was best adapted to Bauchi. G21 and G25 could be recommended across the five test environments while G41, G30 and G5 are specific to the adapted environments.

The lack of a generalizable machine learning model for predicting the safety of food for 1 human consumption is a significant challenge for policymakers and responsible authorities. This 2 study provides a step-by-step guide to predict the results of seafood product import inspections, 3 focusing on identifying and understanding the critical factors that influence these results. By compar- 4 ing the performances of an ensemble of machine learning models, this study combines the strengths 5 of multiple algorithms to improve the predictive accuracy and gain insights into the key factors 6 impacting them. The ensemble model based on the soft voting technique achieves superior perfor- 7 mance to that based on the hard voting technique in terms of the recall and area under the curve 8 (AUC) scores. The study discovered that various characteristics, such as the exporting country ratio, 9 major product category, overseas manufacturer ratio, importer ratio, and seasonal variation, had a 10 substantial influence on the models’ decisions. This research guide for predicting seafood product 11 import inspection results could pave the path for other items to follow.

Mindful Eating (ME) is an increasingly popular dietary practice that may mediate the sympto-matology of Eating Disorders (EDs). Orthorexia Nervosa (ON) is a recently proposed eating dis-order characterized by excessive concern for healthy eating and calorie control. The purpose of this study is to investigate the relationship between ME and Psychological Distress (PD) with EDs and ON. In a cross-sectional study involving 407 adults, this research explored the interplay between ME, PD, and EDs, notably ON. Utilizing validated scales for ME (MES-16), EDs (EDE-QS), ON (ORTO-R), and PD, subcategorized in depression, anxiety, and stress (DASS-21), alongside inquiries into Instagram usage, significant correlations emerged. ME demonstrated a robust negative asso-ciation with both EDE-QS (r=-0.501, p<0.001) and ORTO-R (r=-0.519, p<0.001), while EDE-Q and ORTO-R showed significant correlations with depression, anxiety, and stress (p<0.001). Variations in ORTO-R mean scores were notably distinct across different ME categories (p<0.001), emphasizing the relationship between ME and ON. Additionally, participants with extensive daily Instagram use displayed significantly higher ON scores compared to minimal users (p<0.05). These findings sug-gest a negative link between ME with EDs and ON, highlighting ME's potential role in reducing ON tendencies. Furthermore, Instagram use seems associated with PD and elevated ON levels.

In the context of globalization One Health enables and concurs to the achievement of Global Health. One Health approach involves wide knowledge and understanding of its critical factors, next to an adequate implementation, also in farm animal sector. Moreover, animal farming and breeding shows particularities depending on country. Therefore, well-defined and specific strategies are still needed to be developed and adapted to the current conditions found in various countries for ensuring a well implementation, thus driving to better and healthier global outcomes and security. This paper will explore the One Health status in Romania, highlighting the current progress registered until now and the future perspectives based on its potential, in the context of the livestock farming framework and challenges. Our findings may help to disclose the challenges of putting in practice One Health in Romania, alongside to the pathways showing potential to enhance sustainability in livestock farming.

Abstract: The centrepiece of this analytical review is the metabolism of hydroxyapatite in its natural, bone, and synthetic forms, where the mitochondria-mediated mechanism may serve as the leading mechanism. The possibility that osteoblast mitochondria play an important role in the initial stages of bone mineralisation is discussed. Furthermore, the paper highlights the key role of mitochondria in the metabolism of synthetic hydroxyapatite.Differences between the results of in vivo and in vitro studies using synthetic hydroxyapatite of different morphologies are also detailed. It is noted that long-term infiltration with immune cells and in vivo studies are necessary to adequately evaluate hydroxyapatite as a bone-plastic material.Particular attention is given to the interaction of hydroxyapatite with immune cells and its ability to affect the ribosomes and mitochondria of cells. Due to its mechanical properties, scalability and potential use for the treatment of extensive bone defects of tumor origin, hydroxyapatite is a promising material.This study also highlights the importance of further development of in vitro research methods in the context of their biomimeticity. Overall, this work offers a theoretical direction for future studies of hydroxyapatite as a bone grafting material and emphasises the value of in vivo studies.

In this work, we propose a Fog-enabled UAV-as-a-Service (FU-Serve) architecture to address the issues of data transmission delay for serving time-critical Internet of Things (IoT) applications. Traditionally, in a UAV-as-a-Service (UaaS) platform, different UAVs host heterogeneous sensors, which sense the physical phenomenon and transmit the sensed data to a centralized entity. Transmission of data from the sensors to the centralized entity and making any decision for an application consumes a significant amount of time. Consequently, the traditional UaaS architecture is unsuitable for serving time-critical IoT applications such as transportation, healthcare, and industries. To address these issues of service latency for time-critical IoT applications, we present the FU-Serve architecture by introducing the concept of fog computing in the UaaS platform. We discuss all the components of FU-Serve elaborately in this paper. Additionally, we architect optimal and dynamic fog node selection mechanisms for FU-Serve, which reduce the transmission delay in the networks. The simulation results show that the FU-Serve outperforms by $75\%$ compared to the traditional UaaS platform.

The number of new financing options has increased quickly, including alumni crowdfunding and strategic investments. The antecedents and consequence of these funding mechanisms have not been thoroughly studied in research yet. In this study, the efficacy of leveraging alumni crowdfunding and strategic investments to overcome the perennial funding challenges in French language education was rigorously examined. The study examined the funding challenges plaguing French language education, casting a spotlight on the urgency of creative financial solutions and the strategic provisions of alumni engagements. The study further covered the various roles of strategic investments, synergy of alumni crowdfunding and investments. The analysis proffers a balanced perspective, delving into challenges and concerns that can potentially hinder the smooth operation of these innovative funding channels. Practical recommendations for successful alumni crowdfunding and effective strategic investments were provided. A synthesis of the key findings reveals profound implications for the future of French language education. It was concluded that effective fundraising for French language education relies on well-structured policy and institutional guidance. With these policies in place, educational institutions can navigate the complexities of funding French language programs and secure their future.

The 2-Acetyl-1-pyrroline (2-AP) is the most important volatile in determining the aroma of fragrant rice, however, the transcriptional regulation mechanism of 2-AP biosynthesis in fragrant rice is still unclear. In this study, the Osp5cs1 knockout mutant lines and OsP5CS1 over-expression lines were constructed by genetic transformation of indica rice cultivar i.e., ‘Zhonghua11’, which was knocked out OsBADH2 to produce fragrance in aromatic rice. The OsP5CS1 gene was also identified as a key gene in the 2-AP biosynthesis pathway of aromatic rice. The OsP5CS1 promoter was used as bait, and the transcription factor OsbZIP60-like was screened by yeast one-hybrid assays. The transcription factor OsbZIP60-like specifically bound to the OsP5CS1 gene. The dual luciferase reporting system found that OsbZIP60-like transcription factor promoted the transcriptional activation of OsP5CS1. Compared with the wild type, the OsP5CS1 gene expression was significantly down-regulated in Osbzip60-like mutant, and resulted in substantial reduction in 2-AP biosynthesis. Moreover, the OsP5CS1 gene expression was significantly up-regulated in OsbZIP60-like over-expressed plants, and the 2-AP concentrations were also increased whereas the Osbzip60-like mutants were found to be sensitive to Zn deficiency. Overall, the OsbZIP60-like transcription factor promoted the 2-AP accumulation. This study provides a theoretical basis for the transcriptional regulation mechanism of 2-AP biosynthesis and explores the function of OsbZIP transcription factor in fragrant rice.

Tocilizumab against interleukin-6 receptor (IL-6R) has been demonstrated to inhibit the progression of diverse cancers in vitro and in vivo. Nonetheless, evidence regarding the anti-tumor effects of Tocilizumab on human colorectal carcinoma (CRC) corresponding to IL-6R expression levels re-mains scarce. To investigate the influence of IL-6R expression, SW480 and HT-29 cells inoculated subcutaneously into NU/NU mice were used as our human CRC xenograft models with anti-IL-6R antibody (Tocilizumab) therapy. IL-6R expression levels, the histology of CRC growth/ invasiveness and tumor growth-related signaling pathway were estimated by H&E and immunohistochemical staining. SW480 tumor cells with higher IL-6R expression levels exerted better responsiveness in Tocilizumab therapy than the treated HT-29 group. Likewise, therapeutic effects of Tocilizumab on the proliferative ability with mitotic index and Ki-67 expressions, the invasiveness with MMP-9 proteinase expressions, ERK 1/2 and STAT3 signaling transduction in SW480 treatment group were superior to HT-29 treatment group. In light of our results, IL-6R is the key indicator for the efficacy of Tocilizumab treatment in CRC xenografts. From the perspective of precision medicine, tumor response to anti-IL-6R antibody therapy could be predicted on the basis of IL-6R expression levels. In this manner, Tocilizumab may serve as a targeted and promising anti-CRC therapy.

Construction safety is especially important because the construction industry is so important to a country's development. Significant research and practice have been conducted to mitigate potential risks during construction and improve worker efficiency. With the rapid advancement of cognitive neuroscience and the incorporation of medical technology in recent years, various wearable monitoring devices have been widely used in the construction field for real-time monitoring of workers' physical and mental status. Among these, the use of EEG (Electroencephalogram) in construction environment research allows researchers to gain insight into the physical and mental states of construction workers while performing construction tasks. This review introduces EEG technology and portable EEG devices, followed by an overview of their use in both monitoring workers' adverse reactions and identifying hazards on construction sites, providing an effective guide for EEG research in the construction field and on-site safety management.

Hybrid organic/inorganic conducting and magnetic composites of core–shell type have been prepared by in-situ coating of nickel microparticles with polypyrrole. Three series of syntheses have been made. In the first, pyrrole was oxidized with ammonium peroxydisulfate in water in the presence of various amounts of nickel and the composites contained up to 83 wt% of this metal. The similar syntheses in 0.1 M sulfuric acid followed. Finally, the composites with polypyrrole nanotubes were prepared in water in the presence of structure-guiding methyl orange dye. FTIR and Raman spectroscopies confirmed the formation of polypyrrole. The resistivity of composite powders of the order of tens to hundreds Ω cm was monitored as a function of pressure up to 10 MPa. The resistivity of composites slightly increased with increasing content of conducting nickel. This apparent paradox is explained by the coating of nickel particles, which prevents their contacts and generation of metallic conducting pathways. Electrical properties were practically independent of the way of composite preparation or nickel fraction and were controlled by polypyrrole phase. On the contrary, magnetic properties were determined exclusively by nickel content. The composites were used as a solid phase to prepare a magnetorheological fluid. The test showed better performance when compared with a different nickel system.