Achieving glycemic control and sustaining functional pancreatic β-cell activity remains an unmet medical need in the treatment of type 2 diabetes mellitus (T2DM). Glucokinase activators (GKAs) constitute a class of anti-diabetic drugs designed to regulate blood sugar levels and enhance β-cell function in patients with diabetes. A significant progression in GKA development is underway to address the limitations of earlier generations. Dorzagliatin, a dual-acting GKA, targets both the liver and pancreas and has successfully completed two Phase III trials, demonstrating favorable results in diabetes treatment. The hepato-selective GKA—TTP399— emerges as a strong contender, displaying clinically noteworthy outcomes with minimal adverse effects. This paper seeks to review the current literature, delve into the mechanisms of action of these new-generation GKAs, and assess their efficacy and safety in treating T2DM based on published pre-clinical studies and clinical trials.

Breast Angiosarcoma is a rare malignancy, accounting less than 1% of all soft tissue. It comprises primitive and secondary subtypes, such as radiogenic breast angiosarcoma (RAS). Despite the multimodal treatment, angiosarcomas represent an incurable disease for many patients and represent a cause of substantial deterioration of their quality of life. Surgery represents the cornerstone in the management, but high recurrence rates are reported. Electrochemotherapy (ECT) is practicable locoregional treatment in patients with advanced angiosarcoma, in a multimodal therapeutic strategy. ECT palliative benefit includes optimal patient compliance, good local hemostasis control, and local responses. Considering that only 22 cases are described in literature, we reported a rare case of RAS treated with ECT, after a multidisciplinary approach including Next Generation Sequencing (NGS). A literature review about the feasibility of ECT in RAS management was also performed.

As the international community attaches importance to environmental and climate issues, carbon dioxide emissions in various countries have been subject to constraints and limits. Carbon trading market, as a market tool to reduce greenhouse gas emissions, has gone through a development process from a pilot carbon market to a national carbon market in China. At present, the industries included in the national carbon market are mainly the electric power industry, and the carbon emissions of the electric power industry account for about 40% of the national carbon emissions. According to the construction history of foreign carbon markets, China's future carbon quota allocation will gradually transition from free allocation to auction allocation,the auction mechanism will bring a heavy economic burden to the electric power industry, especially the thermal power generation industry. Therefore, this study takes Guangdong Province as an example to optimize the power generation mix with the objective of minimizing the total economic cost after the innovative introduction of the carbon quota auction mechanism and constructs an optimization model of the power generation mix based on the auction ratio by comprehensively applying the system dynamics model and the multi-objective linear programming model and systematically researches the power generation structure under different auction ratios with the time scale of months and quantitatively evaluates the economic inputs needed to reduce the greenhouse gas emissions.The results of the study show that after comprehensively comparing the total economic cost, renewable energy development and carbon emissions, it is the most scientific and reasonable to set the auction ratio of carbon allowances at 20%, which achieves the best level of economic and environmental benefits.

To investigate the structural behavior of simply supported concrete beams with steel and polypropylene fiber under low velocity impact loading. In all twenty-four beams (150X200X1800 mm) with simply supported boundary condition were modeled and analyzed using ABAQUS software. Steel and polypropylene fibers of aspect ratio of 60 and 231 respectively are used. The total volumes of fibers are maintained at 1% by volume of specimen. A 100 kg hammer with tip diameter 16 mm (hemispherical contact area = 201 mm2) with four different velocities (3.13 m/s, 4.42 m/s, 5.43 m/s and 6.11 m/s) were used in the analysis. It is observed that with the addition of hybrid fibers the deflection in beams was reduced. The beams with 1% PP and 0% steel fiber shows the maximum deflection values due to low modulus of elasticity. Beams with 0.9% steel and 0.1% polypropylene fibers was less affected in terms of deflection as compared to all other beams, it is due to presence of high tensile strength fibers.

Depression and cognitive impairment are recognized complications of COVID-19. This study aimed to assess cognitive performance in clinically diagnosed post-COVID depression (PCD) patients using neuropsychological testing. The study involved 71 post-COVID patients, with matched control groups: recovered COVID-19 individuals without complications (n=18) and individuals without prior COVID-19 history (n=19). A post-COVID depression group (PCD, n=25) was identified based on psychiatric diagnosis, a comparison group (noPCD, n=46) included participants with neurological COVID-19 complications, excluding clinical depression. The PCD patients showed significantly less scores in the MoCA test, decreased immediate memory recall in the Word Memory Test, decreased processing speed and higher accuracy in the Trail Making Test, and near to significant worse executive control and processing speed in the Stroop task compared to controls and the noPCD patients. The number of post-COVID symptoms negatively correlated with immediate word memory recall and processing speed among all post-COVID patients. In PCD patients, negative correlations between number of post-COVID symptoms and delayed recall, between time after recovery and immediate recall, and positive correlation between the number of acute symptoms and processing speed in the incongruent condition of the Stroop task were found. No differences between groups in Sniffin’s stick olfactory test was found. Overall, our study revealed cognitive impairment in PCD patients similar to those in major depressive disorder.

Skin cancer is a global health concern with increasing prevalence, necessitating effective early detection and classification systems. Transfer learning has emerged as a powerful tool in this domain, enhancing diagnostic accuracy. Attention mechanisms, which selectively focus on pertinent image features, play a pivotal role in transfer learning. While previous studies have highlighted their effectiveness, their applicability across different models and datasets remains understudied. This empirical study explores the impact of various attention mechanisms on the performance of transfer learning models for skin cancer detection and classification. Using five transfer learning models (DenseNet121, InceptionV3, MobileNet, VGG16, and Xception) and six attention mechanisms (Channel Attention, Global Context Attention, Guided Attention, Nonlocal Attention, Positional Attention, and Spatial Attention), we conducted 105 experiments across three datasets. Traditional metrics (accuracy, precision, recall, and f1-score) were employed for empirical validation. The results reveal a nuanced relationship between attention mechanisms, transfer learning models, and datasets. Overall, attention mechanisms exhibit the potential to enhance skin cancer classification. Spatial and channel attention mechanisms consistently outperform others, offering simplicity and effectiveness. Model-specific selection of attention mechanisms is crucial, with a trade-off between model complexity and performance evident. This study provides insights into developing efficient skin cancer classification models utilizing attention mechanisms.

In this paper, we present a general version of polygonal fitting problem called Unconstrained Polygonal Fitting (UPF). Our goal is to represent a given 2D shape S with an N-vertex polygonal curve P with a known number of vertices, so that the Intersection over Union (IoU) metric between S and P is maximized without any assumption or prior knowledge of the object structure and the location of the N-vertices of P that can be placed anywhere in the 2D space. The search space of the UPF problem is a superset of the classical polygonal approximation (PA) problem, where the vertices are constrained to belong in the boundary of the given 2D shape. Therefore, the resulting solutions of the UPF may better approximate the given curve than the solutions of the PA problem. For a given number of vertices N, a Particle Swarm Optimization (PSO) method is used to maximize the IoU metric, which yields almost optimal solutions. Furthermore, the proposed method has also been implemented under the equal area principle so that the total area covered by P is equal to the area of the original 2D shape to measure how this constraint affects IoU metric. The quantitative results obtained on more than 2,800 2D shapes included in two standard datasets quantify the performance of the proposed methods and illustrate that their solutions outperform baselines from the literature.

The two-stage direct thermal contact (2sDTC) process is a rapid dewatering approach for fluid fine tailings (FFT) that is integrated into an oil sands bitumen extraction plant to reduce tailings pond storage and freshwater usage. In the first stage, combustion gas directly contacts atomized FFT, vaporizing water and yielding dry solids and steam-rich hot gas. The second stage involves pond effluent water directly contacting the steam-rich hot gas, recovering heat and condensing moisture. Case studies confirm the technical feasibility of the integration. Benefits include producing a dry discharge, reducing tailings water discharge and conserving an equivalent to 0.2 barrels of freshwater per barrel of oil produced. Most importantly, these benefits incur no additional energy cost to the plant as the integration eliminates the energy penalty and CO2 emissions associated with FFT dewatering. Further capacity enhancement can be achieved by using centrifuge-concentrated FFT. The study reveals that FFT concentrated to ~50 wt% solids could still maintain its pump-ability and be accommodated by the 2sDTC process, leading to an integration which could dewater more FFT annually and conserve more freshwater ( 0.58 barrels per barrel of oil produced), with the sole energy requirement being the power to drive the centrifuge machinery.

Background: Fermented milks are a source of bioactive peptides with different potential benefits on human health (mainly antioxidant and antihypertensive effects) and may be considered as functional foods. Furthermore, those made with sheep milk have higher nutritional value and higher concentrations of proteins, fats, minerals, and vitamins, if compared to milk of other species. Objectives: Aim of this study was to perform a biochemical characterization and a comparison between sheep fermented milk (SFM) made with commercial starter cultures and sheep milk YoAlp®, a fermented milk obtained using local strains of lactic acid bacteria (LABs) (Streptococcus thermophilus and Lactobacillus delbrueckii) which have been isolated during years in Aosta Valley mountain dairy cattle farm. Methods: Sheep milk and fermented milk (Sarda and Lacaune breeds) have been collected and immediately analyzed. Biochemical characterization, by a proteomic approach, GC/MS and microtiter plate assay methods, have been conducted to evaluate their peptide, fatty acid and aromatic profile, and to assess potential health promoting effects. Results: The comparison between SFM and YoAlp® peptide profile shows a higher number of peptides using autochthonous starter cultures (52) than commercial starter cultures (35). Among these peptides 20,78% and 29,87%, respectively, are supposed to be potentially bioactive (DPP - dipeptidyl peptidase-IV - inhibitor, ACE - angiotensin converting enzyme – inhibitor and antioxidant). In both products, the fatty acids profile was similar to that of origin sheep milk; concerning aromatic profile, YoAlp® shows yogurt typical aromatic assets, similar to the commercial one. As far as bioactivity is concerned, ACE inhibitor activity is high for both samples. Similar values, as expected by peptide profile analysis, have been obtained using commercial and autochthonous starters. Even in the case of antioxidant capacity, peptide profile bioactivity prediction has been confirmed by the assay showing a DPPH inhibition higher for SFM than for YoAlp®, but this difference is not statistically significative. Conclusions: Local strains of lactic acid bacteria from Aosta Valley seems to work as well as the commercial, preserving biodiversity and typicality. However, further analyses are needed to identify peptides generated by autochthonous LABs in order to understand microbial proteolytic activities and to investigate gastric digestion resistance of bioactive peptides which can have positive effects on human health.

Public health is an important aspect of community activities, making research on health necessary because it is a crucial field in maintaining and improving the quality of life in society as a whole. Research in public health allows for a deeper understanding of the health problems faced by a population, including disease prevalence, risk factors and other determinants of health. This work aims to explore the potential of hospital patient data analysis as a valuable tool for understanding community implications and deriving insights for effective community health interventions. The study recognises the significance of harnessing the vast amount of data generated within hospital settings to inform population-level health strategies. The methodology employed in this study involves the collection and analysis of deidentified patient data from a representative sample of a hospital in Indonesia. Various data analysis techniques, such as statistical modelling, data mining and machine learning algorithms, are utilised to identify patterns, trends and associations within the data. A program written in Python is used to analyse patient data in a hospital for five years from 2018 to 2022. These findings are then interpreted within the context of public health implications, considering factors such as disease prevalence, socioeconomic determinants and healthcare utilisation patterns. The results of the data analysis provide valuable insights into the public health implications of hospital patient data. The research also covers prediction for the patient data to the hospital based on disease, age and geographical residence. The research prediction shows that in 2023, the number of patients was not considerably affected, but in in March to April 2024, the number significantly increased to 10,000 patients. These recommendations encompass targeted prevention strategies, improved healthcare delivery models and community engagement initiatives. The research emphasises the importance of collaboration between healthcare providers, policymakers and community stakeholders in implementing and evaluating these interventions.

Degenerative mitral valve disease (DMVD) consists of progressive degeneration of the mitral valve that can occur either in isolation or in association with the tricuspid valve, leading to incomplete coaptation of its leaflets and subsequent valve regurgitation. It's the most common cardiac condition in small animals, accounting for about 75% of cases of heart disease in dogs, mainly affecting elderly small-breed dogs. Breeds with a genetic predisposition such as Cavalier King Charles Spaniels and Bull Terriers tend to develop the disease early. It can be classified into 4 stages: A, B, C, and D, with B having subdivisions (B1 and B2). Animals in stages A, B1, and B2 are asymptomatic, showing clinical signs only from stage C onwards. The report details the case of a 13-year-old Fox Terrier diagnosed at stage B2 of the disease, progressing to stage C within two years. A cardiologist conducted annual monitoring.

This study investigated the capability of vocal-identity-cloning Artificial Intelligence (AI) to encode human-specific confident, doubtful, and neutral-intending emotive states. Linear mixed-effects models and machine learning classification with eXtreme Gradient Boosting were employed to examine the underlying acoustic signatures from 2,700 audio clips, comprising of sentences spoken by human speakers and two sets of equivalences (AI-Geography/AI-Trivia, based on the trained text) generated by voice-cloning models designed to clone human speakers’ identities. Compared with neutral-intending voice, human speakers lengthened their vocal tract, raised the fundamental frequency, and increased Chroma constant-Q transform when they intended to be confident; An opposite pattern was shown when they intended to be doubtful. The two sets of AI sounds displayed a similar pattern to human speech, suggesting a shared mechanism for encoding vocal expression across sources. The 1,000 times training-testing classification models reported an in-group advantage for AI sources. The algorithms, trained on AI-Geography/AI-Trivia, resulted in higher accuracies when tested within these AI sources than when tested on human audio. All between-source classifications reported above-chance-level (1/3) accuracies. These findings highlighted that voice-cloning AI, the widely used conversational agent, can learn and generate human-specific vocally-expressed confidence.

Keywords: Ecosystem services; Cultural Ecosystem Services; marine/maritime spatial planning; mapping, assessment, tools, methods, PPGIS

The current study aims to develop a methodology for obtaining topology-optimal structures made of short fiber-reinforced polymers, which include the fluid-structure interaction. Accounting for the molding process during the internal iterations of topology optimization makes it possible to enhance the weight efficiency of structures—a crucial aspect, especially in aerospace. Anisotropy is considered through the fiber orientation tensor, which is modeled by solving the plastic molding equations for non-Newtonian fluids, and then introduced as a variable of the stiffness matrix during the structural analysis. The materials used were non-linearly modeled using an exponential-and-linear hardening law. The evaluation of weight efficiency in structures composed of short-reinforced composite materials using a dimensionless criterion is addressed. Experimental verification was performed to confirm the validity of the developed methodology. The evidence illustrates that considering anisotropy leads to stiffer structures and structural elements should be oriented in the direction of maximal stiffness. The load-carrying factor can be expressed in terms of failure criteria. The presented multidisciplinary methodology can be used to improve the quality of the design of structures made of short fiber-reinforced composites (SFRC) where high stiffness, high strength, and minimum mass are the primary required structural characteristics.

Background: To investigate the experiences and perspectives of rural physical therapists in relation to various telehealth strategies in physical therapy; Methods: A qualitative field study was conducted in [n=4,344] remote regions of [n=6] (Mexico). Using telehealth technology, 16 physical therapists from 6 clinics expanded their reach and provided physical therapy care to patients located in nonmetropolitan sites. The outcomes measured were the sociodemographic characteristics, telemedicine modalities employed, and the types of treatments administered. These assessments were conducted pre, post-intervention, and during the follow-up period; Results: This study included 4,344 participants, averaging 44.5 ±20.7 years old. Most visits (80.1%) were initial, while 19.9% were follow-ups, with an average of 12.4 ±4.7 sessions. "Puebla sur" had the highest case frequency (29.3%), followed by "Tlalnepantla" (27.5%), "CAPU" (17.4%), "Tlalpan" (15.5%), and "Guadalajara" and "Guatemala" clinics with lower frequencies (8.8% and 1.5%, respectively); Conclusions: This study highlights the potential of telemedicine to surmount barriers such as limited access to healthcare facilities, physical impediments faced by patients in rural areas, and financial burdens on families. The findings contribute to the optimization of telehealth strategies, specifically tailored to the unique challenges of rehabilitation care in underserved rural communities.

The jet-slit milk homogenizer is one of the most energy-efficient among all types of homogenizers in the dairy industry. The principle of its operation is based on the creation of a maximum speed difference between the fat globules of cream and the flow of skimmed milk. Reducing the specific energy consumption and finding the optimal parameters of the homogenizer were based on the results of both theoretical and experimental studies. The optimization criteria (decreasing specific energy consumption while maintaining high homogenization quality) were chosen to achieve a dispersion of 0.8 μm with minimal energy consumption. The parameters of the width of the ring gap, the fat content and the speed of the cream have been optimized. It is possible to reduce the specific energy intensity of the process to values of 0.88–0.92 kWh/t when using cream with a fat content of 33–43%, which should be fed through an annular gap with a width of 0.6–0.8 mm. Optimum values of the cream feed speed had been found, which should be equal to 7–11 m/s. The research results are of high practical value for the further development of the energy-efficient industrial model of a jet-slit homogenizer.

Iron (Fe), the main component of non-exhaust particulates, is known to have variable health effects that depend on the chemical species of iron. This study characterized the possible contribution of iron oxides and hydroxides to airborne brake-wear particles under realistic vehicle driving and braking conditions with different brake-pad friction materials. We found significant differences in wear coefficients and PM₁₀ emissions between non-asbestos organics (NAO) and European performance (ECE) brake pads. Iron was the dominant contributor to PM₁₀ and PM_2.5 brake-wear particles for both NAO and ECE. The iron concentration ratio in the particle mass were comparable to the disc to pads ratio measured by wear mass. The fact that magnetite, which is of interest with respect to health effects, was less abundant in NAO than in ECE suggested that tribo-oxidations occurred in NAO. Metallic iron is generated not only from abrasive wear but also from tribo-chemical reduction with magnetite as the starting material. We found differences not only in PM emissions between brake friction materials but also that the phase transformations of iron differed between friction materials. These differences were apparent in the distribution of iron oxides and hydroxides. Heat, tribo-oxidation, and tribo-reduction are intricately involved in these reactions.

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a frequent, debilitating and still enigmatic disease. There is a broad overlap in the symptomatology of ME/CFS and the Post-COVID Syndrome (PCS). A fraction of the PCS patients develops the full clinical picture of ME/CFS. New observations in microvessels and blood from patients suffering from PCS have appeared and include microclots and malformed pathological blood cells. Capillary blood flow is impaired not only by pathological blood components but also by prothrombotic changes in the vascular wall, endothelial dysfunction, and expression of adhesion molecules in the capillaries. These disturbances can finally cause a low capillary flow and even capillary stasis. A low cardiac stroke volume due to hypovolemia and the inability of the capacitance vessels to adequately constrict to deliver the necessary cardiac preload generate an unfavorable low precapillary perfusion pressure. Furthermore, a predominance of vasoconstrictor over vasodilator influences exists, in which sympathetic hyperactivity and endothelial dysfunction play a strong role, causing constriction of resistance vessels and of precapillary sphincters which leads to a fall in capillary pressure behind the sphincters. The interaction of these two precapillary cardiovascular mechanisms causing a low capillary perfusion pressure is hemodynamically highly unfavorable in the presence of a primary capillary stasis already caused by the pathological blood components and their interaction with the capillary wall, to severely impair organ perfusion. The detrimental coincidence of the microcirculatory with the precapillary cardiovascular disturbances may constitute the key disturbance of the Post-COVID-19 syndrome and finally lead to ME/CFS in pre-disposed patients because the interaction causes a particular kind of perfusion disturbance - capillary ischemia-reperfusion - which has a high potential of causing mitochondrial dysfunction by inducing sodium- and calcium-overload in skeletal muscles. The latter in turns worsens the vascular situation by the generation of reactive oxygen species to close a vicious cycle from which the patient can hardly escape.

Structural systems in housing projects contribute to the energy consumption of buildings during and after construction, and the climate plays a significant role in this energy consumption. Housing projects in harsh environments such in the United Arab Emirates (UAE) directly contribute to energy performance, specifically in low-density residential areas. By selecting the most efficient structural system, prior construction can enhance energy performance in such housing projects. The present study investigates the energy performance of three different structural systems used in UAE national housing: precast concrete, reinforced concrete, and light gauge steel (LGS). The case studies used for this study were constructed in Abu Dhabi, the capital of the UAE, specifically in Alain city. Second, through qualitative analysis and average annual billing of each housing project, the study identifies the thermal defects and determines the electricity consumptions of each system. The results indicate that the LGS system provides high thermal conductivity through its structural elements whereas reinforced concrete leads to the highest annual energy consumption in kW h/m². Finally, precast concrete has few thermal defects in its junctions and structural elements. The results indicate that LGS and reinforced concrete should be further studied, especially with regard to insulation and improvement, prior to implementation in housing systems.

Lipid nanoparticles (LNPs) have attracted extensive attention in tumor immunotherapy in recent years. The strategy of targeting immune cells in cancer therapy has become a research area of great interest. mRNA vaccines are a potential choice for tumor immunotherapy due to their ability to directly encode antigen proteins and stimulate a strong immune response. However, the mode of delivery and lack of stability of mRNA are key issues limiting its application. LNPs are an excellent mRNA delivery vector, and their structural stability and biocompatibility make them an effective means to deliver mRNA to specific targets. This study summarizes the research progress in LNP delivery vector-assisted targeted controlled release mRNA vaccines in tumor immunity. The role of LNPs in improving mRNA stability, immunogenicity and targeting is discussed. In addition, combined with the cutting-edge research results, the potential mechanisms and application prospects of LNP-mRNA vaccines in tumor immunotherapy were further analyzed. This review aims to systematically summarize the latest research progress in LNP delivery carrier-assisted targeted controlled-release mRNA vaccines in tumor immunity to provide new ideas and strategies for tumor immunotherapy and provide more effective treatment plans for patients.

Cold atmospheric plasma (CAP) has emerged as a promising therapeutic technology, distinguished by its safety, efficiency, and minimal side effects. With increasing applications in dermatology, CAP demonstrates antimicrobial efficacy against bacteria, viruses, and fungi, supports tissue proliferation and wound healing, and hinders the growth and migration of tumor cells. This review encompasses the concept, physical characteristics, and current research applications of CAP in dermatology. CAP, a gas cloud produced by ionizing gases, operates at room temperature, ensuring safety and efficacy in dermatological use. Its effects are mediated through active components like reactive oxygen and nitrogen species (RONS) and ultraviolet radiation. The extensive research covered in this paper explores CAP's applications in skin infections, immune-related diseases, and tumor diseases. As a biologically suitable technology, cold atmospheric pressure plasma finds widespread use in medicine, including medical device sterilization, dentistry, oncology, and dermatology. The direct and indirect forms of CAP applications, including plasma-activated liquids, complement each other. CAP holds promise as a dermatological treatment technique, but further exploration and research are needed. This article briefly explores CAP's diverse applications and potential utility within dermatology. The objective is to enhance the progress of plasma medicine by furnishing a concise overview of the applications of this groundbreaking technology in dermatological contexts.

As yin and yang, cancer and diabetes are metabolic disorders characterized by deregulated, yet opposing, metabolic alterations. These metabolic shifts reflect a complex network of defective underlying signaling pathways, which ultimately orchestrate both disease pathogenesis and progression. The Warburg effect portrays the chief metabolic phenotype in cancer and is reflected by the dominance of aerobic glycolysis over minimal-to-no viable oxidative phosphorylation in cancer. Conversely, during the pathogenesis of type 2 diabetes (T2D), oxidative phosphorylation is constantly heightened. In advanced insulin resistance and T2D, the metabolic landscape becomes more complex, with exacerbating metabolic alterations affecting oxidative phosphorylation in a tissue-specific manner. Promising nutritional adjuvants, such as alpha-lipoic acid and flavonoids, can reprogram metabolism and exert antitumor and antidiabetic effects. Other pharmacological agents, such as metformin, have therapeutic effects on cancer and T2D. Herein, we discuss the molecular mechanisms and signaling pathways involved in the metabolic shifts in cancer and T2D, and explore the therapeutic strategies under investigation that aim to reverse the metabolic shift in both disease scenarios.

This paper introduces an innovative approach to lipreading, leveraging a web application designed to generate subtitles for videos where the speaker's mouth is visible and a comprehensive literature review that precedes the discussion, encompassing a thorough examination of various lipreading methods employed over the past decade. Our method employs a powerful deep learning model, featuring a 3D-convolution network and bidirectional LSTM, enabling accurate sentence-level predictions based solely on visual lip movements. With an impressive accuracy of 97%, our model is trained using pre-segmented lips regions, transformed into animated GIFs for effective pre-training. This work stands as a significant contribution to the evolving landscape of lipreading research, offering a practical and accurate solution for real-world applications.

Franklinite-Zincochromite-Gahnite solid solutions have been prepared by ceramic or coprecipitation method and its pigmenting capacity as cool ceramic pigments in different glazes (double and single firing frits and porcelain frit) was studied. XRD, UV-Vis-NIR diffuse reflectance, CIEL*a*b* colour analysis, bandgap measurement and the photocatalytic activity over the Orange II azoic dye were carried out for the characterization of samples. Following criteria of high red colouring capacity and high NIR reflectance at minimum Cr amount, Zn(Fe1.8Cr0.2), Zn(Al1.5Cr0.5) and Zn(Al1.3Cr0.5Fe0.2)O4 turn out to be the optimal compositions for an intense reddish cool pigment. All powders show a direct semiconductor behaviour with bandgap around 2 eV, falling in the visible range (620 nm), and according to literature, the associated photocatalytic activity over Orange II with visible light irradiation is moderate in all cases, but the Franklinite-Zincochromite Zn(Fe1.8Cr0.2) stands out.

The problem of intensification of melt crystal growth process has been analyzed using CdTe as an actual material. Numerical simulation of 100 mm diameter CdTe crystal growth by VGF technique has been carried out. The heat-mass transfer was controlled by introducing of low-frequency oscillating baffle into the melt, so called axial vibrational control (AVC) technique. The baffle configuration has been optimized to destroy solid «tails», which were formed near the crucible walls at high cooling rates due to the low thermoconductivity and the corresponding latent heat. Analysis of CdTe homogeneity range showed that during fast crystal cooling Te micro precipitations were formed resulting from decay of oversaturated Cd-riched nonstoichiometric solid solution at Bridgman crystal growth technique. A VGF grown CdTe crystal after full crystallization stays inside the phase field of the high temperature wurtzite polymorph. This makes it possible to go through the polymorph transition without Te micro-precipitating using the advantages of VGF specific feature of very slow cooling.

Tigrai region is one of the potential beekeeping areas in Ethiopia, which is endowed with diversified honeybee plant species. However, its honeybee plants are deforested and degraded due to natural and anthropogenic pressures. Area exclosures (AEs) has been practicing for the last three decades restore degraded habitats of the plant species in Ethiopia. Empirical data on the effectiveness of AE is still limited for restoration of honey bee plant species; this study was conducted to assess the roles of AE for species composition, density, and diversity and regeneration status of honeybee floras. Sixty quadrats were installed, 36 in AE and 24 in CGL (communal grazing lands) using a systematic sampling method. The study showed that a total of 42 honey bee plant species belonging to 23 families in AE and 33 species belonging to 17 families in CGL were recorded. The study also indicated a significant increase in the abundance, diversity, regeneration and the structure of the honey bee plant species was found in the AEs. The list presented herein provides a guide to stakeholders in establishing of AE for the foraging resource of honeybee in order to enhance the abundance, diversity and regeneration and structure. Thus, AE has made a significant contribution to solving the shortage of honeybee forages in the beekeeping industry. Therefore, the development of beekeeping is integrated with conservation of natural resources.

Carbonate rocks occupy about 6490 km2 in Albania (23% of the country) and the total exploitable karst water resources are estimated in 2.84*109 m3/year (about 65% of the total exploitable groundwater resources in the country, and about 70% of those used for water supply). In addition, karst massifs are very rich in thermal waters, related to the ascending fluids which are essential for the development of hypogenic karstification in the outer Albanides. This type of karst facilitates the circulation regime of deep fluids, which are revealed at the surface through both numerous phenomena of hypogene karst and hot springs. The relatively small Kruja Tectonic Zone is characterized by the presence of SE-NW oriented carbonate structures, rich in thermal sources, and contains more than the 80% of Albania thermal springs. One of its most interesting carbonate structures, for the presence of both cold and thermal waters, is the small karst structure of Makaresh, with a surface of 22 km2. The purpose of this article is to describe the characteristics and factors that affect the quantitative and qualitative formation of cold and thermal groundwater in this massif. Based on the physico-chemical characteristics, groundwaters of the study area are classified in cold and thermal waters. The former are mainly of HCO3-Ca or HCO3-Ca-Mg type (Electrical Conductivity 580-650 μS/cm, Temperature 13.9-16.6° C). Thermal waters are mainly of the Cl-Na-Ca type (EC 7200-7800 μS/cm, T 18.5-22.5° C); further, they are characterized by high hydrogen sulphide concentration, up to about 350 mg/l. The presence of two groundwater types in the Makaresh massif is connected to the presence of two groundwater circulation systems. The main factors of the groundwater physic-chemical quality are the solution of rocks and minerals therein contained, the presence of hypogenic speleogenesis, and the mixing of the groundwater of the two systems. The hydrogeological studies proved that karst rocks contain considerable fresh water resources; the capacity of water wells used for the drinking water supply reaches up to about 50 l/s. Thermal waters are not currently exploited due to their temperature, but they are potentially suitable for thermal uses, by drilling boreholes at depth of about 1000 m.

High-methoxyl apple pectin (AP) derived from apple was employed as the main ingredient facilitating rheological modification features for developing dysphagia-friendly fluidized alimentary matrices. Xanthan gum (XG) was also included as a composite counterpart to modify the viscoelastic properties of the thickened system under different thermal processes. The results indicate that AP is extremely sensitive to thermal processing, and the viscosity is greatly depleted under a neutral pH level. Moreover, the inclusion of calcium ions echoed a modification effect on the rheological properties of AP, and both the elastic property and viscosity value are promoted after thermal processing. The modification effect of viscoelastic properties (Gʹ and Gʹʹ) is observed while XG is incorporated into the composite formula. By promoting the XG ratio from 7: 3 to 6: 4 (AP: XG), it triggers the rheological transformation from a liquid-like form to a solid-like state, and the viscosity value shows that the AP-XG composite system exhibits better thermal stability after thermal processing. The ambient modifiers of pH (pH < 4) and calcium chloride concentration (7.5%) with an optimal AP-XG ratio of 7:3 lead to weak-gel-like behavior (Gʹʹ < Gʹ), helping to maintain the texture properties of dysphagia-friendly features similar to those prior to the thermal processing.

Angiogenesis is a critical process in various physiological and pathological conditions, and snake venom disintegrins (SVDs) have been shown to be important regulators of this process. In this review, we explore the dual roles of SVD in angiogenesis, both as antiangiogenic agents by inhibiting integrin binding and interfering with vascular endothelial growth factors and as proangiogenic agents by enhancing integrin binding, stimulating cell migration and proliferation, and inducing neoangiogenesis. Studies in vitro and in animal models have demonstrated these effects and offer significant therapeutic opportunities. The potential applications of SVD in diseases related to angiogenesis, such as cancer, ocular diseases, tissue regeneration, wound healing, and cardiovascular diseases, are also discussed. Overall, SVDs are promising potential therapeutics, and further advances in this field could lead to innovative treatments for diseases related to angiogenesis.

We present the case of a 28-year-old male with a history of alcohol dependency and smoking, who presented with chest pain, shortness of breath, and altered sensorium. He exhibited severe metabolic acidosis, low platelet count, and acute kidney injury. Alcoholic ketoacidosis (AKA) was suspected due to ketonuria, metabolic acidosis, and ketonemia, compounded by electrolyte abnormalities and radiographic findings of pneumonia.Prompt intervention included electrolyte correction, thiamine supplementation, broad-spectrum antibiotics, and diuretics. Thiamine played a pivotal role in the patient's recovery, with significant improvement in consciousness observed within a day. After six days, the patient was discharged in stable condition, showing normal renal and hepatic function during follow-up.This case emphasizes the need for early recognition and comprehensive management in AKA, highlighting thiamine's crucial role in treatment success.

The enzyme-linked immunosorbent assay (ELISA) coupled with surface-enhanced Raman spectroscopy (SERS) detection is a growing area of analytical chemistry emerged as a solution to a problem of sensitivity improvement. SERS-based ELISA with horseradish peroxidase as an enzymatic label, o-phenylenediamine (oPD) substrate, and 2,3-diaminophenazine (DAP) enzymatic product was one of the first examples of such systems. Surprisingly, the full potential of this long-known approach has not been revealed yet. The current study addresses a previously neglected problem of SERS detection stage performance. Using silver nanoparticles and model mixtures of oPD and DAP, the effects of pH, concentration of aggregating agent, and particle surface chloride stabilizer were extensively evaluated. At optimal mildly acidic pH of 3, 0.93 to 1 M citrate buffer, and AgNPs stabilized with 20 mM chloride, at least two orders of magnitude advantages in the detection limits of SERS over colorimetry both for DAP and HRP were demonstrated. We suppose that this improved detection system could become a useful tool for the development of SERS-based ELISA protocols.

Online artificial intelligence (AI) tools have recently gained in popularity. So-called “generative AI” chatbots unlock new opportunities to access vast realms of knowledge when being prompted by users. Here, we test the capabilities of two such AIs in order to determine the benefits for plastic surgery while also assessing potential risks. Future developments are outlined. We used the online portals of OpenAI’s ChatGPT(version 3.5) and Google’s Bard to ask a set of questions and give specific commands. Results provided by the two tools were compared and analyzed by a committee. For professional plastic surgeons, we found that ChatGPT and Bard can be of help when it comes to conducting scientific reviews and helping with scientific writing but are of limited use due to the superficiality of their answers in specific domains. For medical students, in addition to the above, they provide useful educational material with respect to surgical methods and exam preparation. For patients, they can help when it comes to preparing for an intervention, weighing in risks and benefits, while providing guidance on optimal post-operative care. ChatGPT and Bard open widely accessible data to every internet user. While they might create a sense of “magic” due to their chatbot interfaces, they nonetheless can help to increase productivity. For professional surgeons, they produce superficial answers - for now - albeit providing help with scientific writing and literature reviews. For medical students, they are great tools to deepen their knowledge about specific topics such as surgical methods and exam preparation. For patients, they can help in translating complicated medical jargon into understandable lingo and provide support for pre-operative as well as post-operative care. Such AI tools should be used cautiously as answers are not always precise nor accurate and should always be used in combination with expert medical guidance.

A milk drink flavored with dates syrup produced at a lab scale level was evaluated. The production process of date syrup involves a sequence of essential unit operations, commencing with the extraction, filtration, and concentration processes from two cultivars: Sukkary and Khlass. Date syrup was then mixed with cow’s and camel’s milk at four percentages to form a nutritious, natural, sweet, and energy milk drink. Sensory, physical, and chemical characteristics of the milk drinks flavored with date syrup were examined. The objective of this work was to measure physiochemical properties of dates fruits and milk drinks flavored with dates syrup, then to evaluate the physical properties of milk drinks utilizing a non-destructive NIR spectra. The study assessed the characteristics of the milk drink enhanced with date syrup by employing near-infrared spectra (NIR) spectra and analyzed utilizing partial least-square regression (PLSR) and artificial neural network (ANN) analysis. The NIR spectrum proved to be highly effective in estimating the physiochemical attributes of the flavored milk drink. The ANN model outperformed the PLSR model in this context. RMSECV is considered a more reliable indicator of a model's future predictive performance compared to RMSEC, R2 ranged between 0.946 and 0.989. Consequently, non-destructive NIR technology demonstrates significant promise for accurately predicting and contributing to the entire production process of the product's properties examined.

This study addresses the central question that how can a precise measurement of the gluon Parton Distribution Function (PDF) be attained, thereby enhancing our understanding of the intricate quark-gluon composition within nucleons? Through a dual approach involving Quantum Chromodynamics (QCD) and high-energy particle collisions, the research combines computational tools and experimental techniques, focusing on protons and neutrons. Scattering experiments and advanced detectors are utilized to probe nucleon structure. Theoretical frameworks like QCD equations and the Momentum Sum Rule investigate Parton Distribution Functions at specific momentum fractions and energy scales. The primary goal is to achieve an accurate measurement of the gluon PDF, crucial for unraveling strong force complexities and internal nucleon dynamics. The study's theoretical plots and equations illustrate hypothetical behaviors of gluon distribution, quark distribution, and splitting functions, contributing to a deeper understanding of fundamental particles.

Woodland bat assemblages are usually structured in space by distance from the ground, water and obstacles, features often defining chiropteran hunting tactics. Consequently, bat species composition differs strongly among various habitats even within the same forest patch. However, when conducting local bat survey in Wolin National Park (WPN), we revealed unexpected uniformity in qualitative and quantitative structure of bat assemblages, based on mist netting and ultrasound recording. In total, 10 vespertilionid species were detected. In all methods and sampled habitats a single species, Pipistrellus pygmaeus, predominated, while no Barbastella barbastellus, an old forest specialist, was detected, despite the abundance of preferred daily roosts. We also reviewed literature for mist netted bat samples in four different habitats of lowland Polish forests. Samples usually clustered based on habitats and the same habitat classes often clustered very closely, despite representing geographically distant forests. The exception was WPN, where all four habitat classes formed a tightly packed cluster. We suppose that P. pygmaeus might act as a hyperabundant native species, a successful generalist that reduces the contribution of more specialized taxa in the assemblage. It probably benefits from both forest renaturation and anthropogenic cross-boundary subsidy, the latter including both roost availability and prey abundance.

Measles is targeted for elimination since 2001, with significant reduction in cases recorded worldwide, but outbreaks occur periodically due to immunization gaps. The present study analyzes the evolution of vaccination coverage rates (VCR) in Romania, a EU country with large measles epidemics during the last two decades, including an ongoing outbreak in 2023. Vaccination against measles is included in the National Immunization Program from 1979, initially as a single dose, and since 1994, with 2 doses. The vaccine uptake was initially high, with national VCR of >97%. However, from 2010 onwards, the VCR dropped and remained constantly under 90%. This decline was caused by several factors, including a decreasing number of general practitioners, discontinuities in vaccine supply, emigration, with increased numbers of children lost to follow-up and a surge in vaccine hesitancy. Additional decreases in the already low levels of VCR were recorded during the COVID-19 pandemic: in 2022 the VCR reached the lowest level in the last decade, with 83.4% for the first dose (6.6% decrease compared to 2019) and 71.4% for the second dose (4.4% decrease compared to 2019), with important subregional differences. The constant suboptimal vaccination coverage rate in Romania threatens the progress toward measles elimination.

Level index was introduced in 2017 for rooted trees which is a component of Gini index. In the origin, Gini index is a tool for economical investigations but Balaji and Mahmoud defined the graph theoretical applications of this index for statistical analysis of graphs. Level index is an important component of Gini index. In this paper we define a new graph polynomial which is called level polynomial and calculate the level polynomial of some classes of trees. We obtain some interesting relations between the level polynomials and some integer sequences.

In the rapidly evolving landscape of genetic engineering, the advent of CRISPR-Cas technologies has catalyzed a paradigm shift, empowering scientists to manipulate the genetic code with unprece-dented accuracy and efficiency. Despite the remarkable capabilities inherent to CRISPR-Cas sys-tems, recent advancements have witnessed the integration of small molecule to augment their functionality, introducing new dimensions to the precision and versatility of gene editing applica-tions. This review delves into the synergy between CRISPR-Cas technologies and small molecule drugs, elucidating the pivotal role of chemicals in optimizing target specificity and editing efficiency. By examining a diverse array of applications, ranging from therapeutic interventions to agricultural advancements, we explore how the judicious use of chemicals enhances the precision of CRISPR-Cas-mediated genetic modifications. In this review we emphasize the significance of small molecule drugs in fine-tuning the CRISPR-Cas machinery, which allows researchers to exert meticulous con-trol over the editing process. We delve into the mechanisms through which these chemicals bolster target specificity, mitigate off-target effects, and contribute to the overall refinement of gene edit-ing outcomes. Additionally, we discuss the potential of chemical integration in expanding the scope of CRISPR-Cas technologies, enabling tailored solutions for diverse genetic manipulation challenges. As CRISPR-Cas technologies continue to evolve, the integration of small molecule drugs emerges as a crucial avenue for advancing the precision and applicability of gene editing techniques. This re-view not only synthesizes current knowledge but also highlights future prospects, paving the way for a deeper understanding of the synergistic interplay between CRISPR-Cas systems and chemical modulators in the pursuit of more controlled and efficient genetic modifications.

We present a surface acoustic wave (SAW) sensor array for microRNA (miRNA) detection that utilizes photocatalytic silver staining on titanium dioxide (TiO2) nanoparticles as a signal enhancement technique for high sensitivity with an internal reference sensor for high reproducibility. A sandwich hybridization was performed on working sensors of the SAW sensor array that could simultaneously capture and detect three miRNAs (miRNA-21, miRNA-106b, and miRNA-155) known to be upregulated in cancer. Sensor responses due to signal amplification varied depending on the concentration of synthetic miRNAs. It was confirmed that normalization (a ratio of working sensor response to reference sensor response) screened out background interferences by manipulating data and minimized non-uniformity in the photocatalytic silver staining step by suppressing disturbances to both working sensor signal and reference sensor signal. Finally, we were able to successfully detect target miRNAs in cancer cell-derived exosomal miRNAs with performance comparable to the detection of synthetic miRNAs.

The mathematical structure underlying a sentence is made of two independent processing units in series. The conditional probability density function of sentence length (measured in words) recordable in the extended short–term memory (E–STM) buffer made of CF cells is Gaussian. The number of sentences that authors of Italian and English Literatures have written is compared to that theoretically available to them. The multiplicity factor α describes this comparison. α>1 is more likely than α<1 and often α≫1, therefore the same sentence pattern is reused many times. These texts are easier to read. Very few novels show α<1. In these cases, there are enough diverse sentence patters to convey meaning, but most of them are not used. Texts are more difficult to read, as measured by a universal readability index GU. A mismatch index IM synthetically describes the process. α, GU. and IM increase with year of publication. Future work will concern other literatures – including ancient ones as Greek and Latin – to confirm what, in our opinion, is general feature of human mind.

Marine lipids are recognized for their health promoting features, mainly for being the primary sources of omega-3 fatty acids, and therefore critical for human nutrition in an age when the global supply for these nutrients is experiencing an unprecedent pressure due to an ever-increasing demand. The seafood industry originates a considerable yield of co-products worldwide that, while already explored for other purposes, remain mostly undervalued as sustainable sources of healthy lipids, often being explored for low value oil production. These co-products are especially appealing as lipid sources since, besides the well-known nutritional upside of marine animal fat, particularly rich in omega-3 polyunsaturated fatty acids (PUFAs), they have also interesting bioactive properties, which may garner them further interest, not only as food, but also for other high-end applications. Besides the added value that these co-products may represent as valuable lipid sources, there is also the obvious ecological upside of reducing seafood industry waste. In this sense, repurposing these bioresources will contribute to a more sustainable use of marine animal food, reducing the strain on already heavily depleted seafood stocks. Therefore, untapping the potential of marine animal co-products as valuable lipid sources aligns with both health and environmental goals by guaranteeing additional sources of healthy lipids and promoting more eco-conscious practices.

This study introduces a novel approach by proposing a dressing impregnated with vancomycin and chlorhexidine for postoperative care, specifically targeting patients undergoing orthopedic surgeries. The research design involved a pilot study with a randomized control group, aiming to evaluate the vancomycin with chlorhexidine dressing's efficacy and safety. A total of 12 patients used impregnated dressing and 9 used the same dressing without impregnation. Despite limitations, including the small sample size and single-center study location, our findings demonstrate the safety of the impregnated dressing in trauma surgeries, indicating potential applicability in broader surgical contexts. In conclusion, this study contributes to the discourse on preventive strategies for SSIs, presenting a pioneering approach with the vancomycin and chlorhexidine-impregnated dressing. Future research endeavors, incorporating larger-scale studies and addressing study limitations, are crucial for advancing the understanding and implementation of effective postoperative care strategies.

This paper investigates the adaptability of four state-of-the-art Artificial Intelligence (AI) models to the Australian mammographic context through transfer learning, explores the impact of image enhancement on model performance and analyses the relationship between AI outputs and histopathological features for clinical relevance and accuracy assessment. A total of 1712 screening mammograms (n=856 cancer cases and n=856 matched normal cases) were used in this study. The 856 cases with cancer lesions were annotated by two expert radiologists and the level of concordance between their annotations was used to establish image subsets. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of Globally aware Multiple Instance Classifier (GMIC), Global-Local Activation Maps (GLAM), I&H and End2End AI models, both in the pre-trained and transfer learning modes, with and without applying the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm. The four AI models with and without transfer learning in the high-concordance subset outperformed those in the entire dataset. Applying the CLAHE algorithm to mammograms improved the performance of the AI models. In the high-concordance subset with transfer learning and CLAHE algorithm applied, the AUC of the GMIC model was highest (0.912), followed by GLAM model (0.909), I&H (0.893) and End2End (0.875). There were significant differences (P<0.05) in the performances of the four AI models between high-concordance subset and entire dataset. The AI models demonstrated significant differences in malignancy probability concerning different tumour size categories in mammograms. The performance of AI models was affected by several factors such as concordance classification, image enhancement and transfer learning. Mammograms with strong concordance of radiologists’ annotations, applying image enhancement and transfer learning could enhance the accuracy of AI models.

4-(2-Methyloxazol-4-yl)benzenesulfonamide was synthesized by the reaction of 4-(2-bromoacetyl)benzenesulfonamide with an excess of acetamide. The obtained compound was evaluated as a potential inhibitor of human monoamine oxidase (MAO) A and B and was found to inhibit these enzymes with IC50 values of 3.47 μM for MAO-B and 43.3 μM for MAO-A. Thus, the new selective MAO-B inhibitor was identified, which may be used as the lead compound for development anti-Parkinson’s disease agents.

Lipophilic oligonucleotide derivatives are a potent approach to the intracellular delivery of nucleic acids. The binding of these derivatives to serum albumin is a major determinant of their fate in the body, as its structure contains several sites of high affinity for hydrophobic compounds. This study focuses on the features of self-association and non-covalent interactions with human serum albumin of novel self-penetrating oligonucleotide derivatives. The study revealed that the introduction of a triazinyl phosphoramidate modification bearing two dodecyl groups at the 3' end region of the oligonucleotide sequence has a negligible effect on its affinity for the complementary sequence. Dynamic light scattering verified that the amphiphilic oligonucleotides under study can self-assemble into micelle-like particles ranging from 8 to 15 nm in size. The oligonucleotides with dodecyl groups form stable complexes with human serum albumin with a dissociation constant of approximately 10-6 M. The oligonucleotide micelles are simultaneously destroyed upon binding to albumin. Using an electrophoretic mobility shift assay and affinity modification, we examined the ability of DNA duplexes containing triazinyl phosphoramidate oligonucleotides to interact with Ku antigen and PARP1, as well as the mutual influence of PARP1 and albumin or Ku antigen and albumin upon interaction with DNA duplexes. These findings, together with the capability of dodecyl-containing derivatives to effectively penetrate different cells, such as HEK293 and T98G, indicate that the oligonucleotides under study can be considered as a platform for the development of therapeutic preparations with a target effect.

The pressing process and density profile of particleboards produced with addition of waste wood containing phenol-formaldehyde (PF) resin was presented. The particles were melamine-urea-phenol-formaldehyde (MUPF) resinated. Recovered particles were obtained from post-industrial waste plywood. The press closing time recorded during the pressing of mats containing only recovered particles in the core layer (100%), at a unit pressure of 3 MPa, in which the face layer rate was 50%, resin load for face and core layer was 12% and 10% was shorter by 29% than for the industrial particle mats. Regardless of the level of variability of independent factors the overheating time of mats to a temperature of 100 °C, containing recovered particles was 10% - 20% shorter than the time of overheating mats with industrial particles. The greatest impact (52%) on maximum density of the face layer of particleboards was demonstrated by the content of the recovered particles and the resin load (32%). The maximum density area of the face layer was located closer to the surface in particleboards produced with a higher (80%, 100%) content of the recovered particles, a higher (i.e. 12% and 10%, respectively, for face and core layer) resin load, a lower (35%) face layer rate and a higher (3 MPa ) unit pressure.

The frequent occurrence of rib fractures in slaughtered lambs results in significant economic loss to producers and processors in South Australia and raises concerns about the welfare of the animals. The prevalence of rib fractures became evident through the Enhanced Abattoir Surveillance (EAS) program introduced in 2007. The present study aimed to investigate the association between rib fracture prevalence in lambs at slaughter and their nutrition and management on the farm of origin. The slaughter of 30,055 lambs from 60 farms was monitored at a South Australian abattoir in November 2016. Rib fracture prevalence was 4% (range 0 - 18% per consignment), with all consignments of more than 240 lambs having at least one with fractured ribs. Traceback investigation on 56 of the 60 farms suggests that rib fractures most probably occur during routine husbandry procedures and, based on soil mineral analysis, are associated with calcium inadequacy. There was substantial variation between lines of lambs from different farms, and factors contributing to the differences included line size, region, and soil characteristics, including available calcium. There is a need to modify sheep husbandry and management practices to improve sheep welfare and reduce the cost of rib fractures to the sheep industry.

In this paper, we present a new parametric class of optimal fourth-order iterative methods to estimate the solutions of nonlinear equations. After the convergence analysis, we study the stability of this class by using the tools of complex discrete dynamics. This allows us to select those elements of the class with lower dependence on initial estimations. We verify by means of numerical tests that the stable members on quadratic polynomials perform better than the unstable ones, when applied to other non-polynomial functions. We also compare the performance of the best elements of the family with known methods, such as the schemes by Newton or Chun, among others, showing robust and stable behaviour.

Due to the particular structure of the beveloid gear, it can’t be hobbed directly by an ordinary gear hobbing machine. The existing processing method is complex and high-cost. Therefore, the mass production and industrialization of beveloid gears are limited. To improve the machining efficiency and accuracy of processing beveloid gears, we proposed a hobbing method via the modification of ordinary hobbing machines. At first, we completed the derivation and calculation of the relevant processing parameters of the beveloid gear based on the study of the structural characteristics of the beveloid gear and the principle of hobbing machining. Then, we proposed and designed a beveloid gear hobbing method, and the modification of the ordinary hobbing machine was completed by using a hanging wheel mechanism in synchronous belt type. Finally, we completed the actual hobbing of the beveloid gear, and the feasibility of the proposed method was verified. After that, we analyzed the machining error of the trial-produced beveloid gear, the results showed that the accuracy of the trial-produced beveloid gear met the 6-level standard, which also verified the accuracy of the proposed method.

Leaf area estimation is a critical component in the study of plant growth and productivity within agricultural systems. This research introduces the LeafArea package, a specialized tool designed to calculate the leaf area of six distinct Andean fruit species: S. quitoense, S. betaceum, P. peruviana, R. fruticosus, P. ligularis and P. edulis. Leveraging response variables such as species type, leaf length and width, the package employs advanced machine learning algorithms to estimate leaf area accurately. The primary focus of the study is to identify the most effective model for describing the relationship between leaf width, length, and area for each plant species. Currently, the LeafArea package utilizes four different machine learning algorithms, namely generalized linear model (GLM), generalized linear mixed model (GLMM), Random Forest and XGBoost. Among these, XGBoost stands out as a top-performing algorithm, exhibiting exceptional predictive accuracy. The evaluation metrics employed in the program provide valuable insights for researchers, aiding in informed decision-making. Specifically, XGBoost demonstrates significantly lower prediction errors and approaches a near-perfect R2 value, emphasizing its potential to enhance predictive accuracy. These results underscore the efficacy of machine learning techniques, as a compelling choice for researchers seeking precise and robust predictions in leaf area estimation. The LeafArea package thus represents a valuable tool for advancing our understanding of plant growth dynamics, resource allocation, and overall productivity within agricultural ecosystems.

The study’s objective is to analyse the mechanical properties of steel pipe piles as a part of a trestle bridge subjected to five years of natural marine corrosion degradation. Sixteen tensile specimens were extracted from the steel pipe piles in the splash, tidal, and immersion zones. The experimental tensile test results are used to establish regression equations defining elastic modulus, yield strength, strain hardening index, and strength coefficient for the true stress-strain curves of the three regions. A non-linear time-dependent mathematical model is exploited to identify the corrosion degradation using the data from one single corrosion degradation measurement campaign. The analysis indicated that the splash zone experiences the most severe corrosion degradation, and there are progressive losses in the mechanical properties of each zone as the corrosion degradation progresses. The established relationships of the mechanical properties, as a function of the ratio of corroded plate thickness to the as-built one, can be used as a fast-engineering approach to identify the mechanical properties of severely corroded piles. The corrosion degradation allowance is also defined using the First Order Reliability Method, accounting for existing uncertainties covered by the partial safety factors. By examining the impact of marine corrosion on the mechanical properties of marine structures and developing predictive models to assess the corrosion’s effect on material strength and corrosion allowance, the study aims to improve offshore structures’ safety, design, and maintenance.

The chemical reaction of ion-adsorption type rare earth during in-situ leaching process is accompanied by ion migration and charge movement, making the leaching process electrochemical in nature. The chemical reaction rate plays an important role in the leaching rate of rare earth elements. In this work, electrochemical impedance spectroscopy (EIS) was used to reveal characteristics of electrical resistance alteration and leaching rate of rare earth elements during in-situ leaching. The equivalent circuit model of the leaching process was established, and two critical parameters of solution resistance Rs and charge transfer resistance Rt were analyzed to reflect the electrochemical characteristics. According to the characteristics of electrical resistance alteration, the leaching process was divided into four stages: wetting, reaction, equilibrium, and top water stage. The resistance parameters Rs and Rt decreased first and then increased during the leaching process. The maximum value of Rs was 1330Ω∙cm2 at the end of the top water stage, and the minimum value was 135Ω∙cm2 at the beginning of the equilibrium stage. The maximum value of Rt was 8310Ω∙cm2 at the beginning of the leaching stage, and the minimum value was 21Ω∙cm2 at the end of the reaction stage. Rs and Rt were negatively correlated with the pore size and chemical reaction rate during leaching. With increasing of pore size and reaction rate , the resistance parameter decrease. This study provide a new idea for intelligent monitoring of rare earth ore.

The South of France is a biodiversity hotspot within Europe. Here, we present a comprehensive review of surveys conducted in the Cent Fonts aquifer, an overlooked subterranean biodiversity hotspot embedded in a region rich in stygobiotic species and threatened by climate change and water abstraction projects. Key studies, spanning from 1950 to 2006, show a progression in survey methods and results, although troglobiotic species remain poorly documented. With 43 stygobiotic species recorded, the Cent Fonts is the second richest stygobiont hotspot in Europe. Most species are regional endemics, a quarter of which are considered vulnerable by the IUCN. The Cent Fonts also hosts several relict species and is the type locality of four species. Such a high biological value clearly deserves to be preserved. Our analysis warns of a possible decline in biodiversity, as 8 of the species recorded in the 20th century were absent from the 2006 survey, suggesting potential threats of unknown origin. The capture of the Cent Font springs for water abstraction is discussed as a potential threat to this ecosystem and its unique biodiversity. Three new species of stygobiotic molluscs are described, one of which was collected in the Cent Fonts.

Localized jawbone invasion is a milestone in the progression of oral squamous cell carcinoma (OSCC). The factors that promote this process are not well understood. Sclerostin is known to be involved in bone metabolism and there are preliminary reports of its involvement in bone tumors and metastasis. To identify a possible involvement of sclerostin in the bone invasion process of OSCC, sclerostin expression was analyzed in vitro in two different human OSCC tumor cell lines by qRT-PCR, and the effect of recombinant human (rh)-sclerostin treatment on tumor cell capabil-ities was evaluated using proliferation, migration, and invasion assays. Undifferentiated human mesenchymal stem cells (hMSCs) were osteogenically differentiated and co-cultured with OSCC tumor cells to demonstrate potential interactions on migration characteristics. Sclerostin expres-sion was evaluated in clinical cases by immunohistochemistry at the OSCC jawbone interface in a cohort of 15 patients. Sclerostin expression was detected in both OSCC tumor cell lines in vitro and was also detected at the OSCC jawbone interface in clinical cases. Tumor cell proliferation rate, migration and invasion ability were increased by rh-sclerostin treatment. The migration rate of tumor cells co-cultured with osteogenically differentiated hMSCs was increased. The re-sults presented are the first data suggesting a possible involvement of sclerostin in the bone inva-sion process of OSCC, which needs to be further investigated

In order to analyze the spatial distribution characteristics of the cultural landscape of the Yangtze River (Nanjing section) and show the role of the Yangtze River culture in promoting regional economic development and cultural radiation, Based on the Knowledge graph technology and 3S technology, this paper conducts geographical positioning and spatial analysis of the Yangtze River cultural landscape in Nanjing, and analyzes the surrounding environment by combining remote sensing images and topographic data. Researches show that: The Yangtze River cultural landscape in Nanjing includes 74 landscape points of seven landscape types, and the distribution of landscape points shows a clustering trend, but the spatial distribution and aggregation degree of different types of cultural landscapes are different. Due to the influence of climate environment and water resources distribution, the surrounding cultural landscape has a low altitude and high vegetation coverage, showing obvious distribution characteristics along the river. This study is helpful to improve the coordination degree between cultural landscape protection and planning management, and can provide useful reference for the protection of cultural landscape of the Yangtze River.

The ability of deep learning to process vast data and uncover concealed malicious patterns has spurred the adoption of deep learning methods within the cybersecurity domain. Nonetheless, a notable hurdle confronting cybersecurity researchers today is the acquisition of a sufficiently large dataset to train deep learning models effectively. Privacy and security concerns associated with using real-world organization data have made cybersecurity researchers seek alternative strategies, notably focusing on generating synthetic data. Generative Adversarial Networks (GANs) have emerged as a prominent solution, lauded for their capacity to generate synthetic data spanning diverse domains. Despite their widespread use, the efficacy of GANs in generating realistic cyber attack data remains a subject requiring thorough investigation. Moreover, the proficiency of deep learning models trained on such synthetic data to accurately discern real-world attacks and anomalies poses an additional challenge that demands exploration. This paper delves into essential aspects of generative learning, scrutinizing their data generation capabilities, and conducts a comprehensive review to address the above questions. Through this exploration, we aim to shed light on the potential of synthetic data in fortifying deep learning models for robust cybersecurity applications.

Creating environmentally sustainable oral healthcare culture requires embedding contents in dental curriculum. This study aimed to explore the current knowledge and drivers among dental students and educators regarding environmentally sustainable dentistry (ESD) in the United Arab Emirates (UAE) and identify barriers and enablers to embrace it. A cross-sectional survey using online questionnaire was carried out in undergraduate dental educational institutes. Data analysis included descriptive statistics and thematic analysis. Most students and educators were not aware of ESD content in their curriculum. However, the majority of educators were familiar with ESD concept, while students were mostly unfamiliar. Nonetheless, students largely agreed on its im-portance and their interest in learning it, as they view it relevant to their future practice. Educators agreed that the dental profession has a responsibility to be environmentally friendly and expressed desire in introducing ESD content into the curricula. Several barriers were reported such as lack of knowledge, curriculum space, educational resources, and time. Meanwhile, enablers included providing training and resources. There is no explicit presence of ESD content in the dental curricula. Regardless of the lack of in-depth knowledge among educators and more so with students, they both have positive views toward incorporating ESD into dental curricula.

Febrile infections are a common cause of presentation to the emergency department (ED) in chil-dren. While viral infections are usually self-limiting, sometimes bacterial illnesses may lead to sepsis and severe complications. Inflammatory biomarkers such as C reactive protein (CRP) and procalcitonin are usually the first blood exams performed in the ED to differentiate bacterial and viral infections; the better understanding of immunochemical pathways has nowadays led to the discovery of new and more specific biomarkers that could play a role in the emergency setting. The aim of this narrative review is to provide the most recent evidence on biomarkers and predictor models combining them for serious bacterial infections (SBI) diagnosis in febrile children. Litera-ture analysis showed that inflammatory response is a complex mechanism in which many bio-chemical and immunological factors contribute to host response in SBI. CRP and procalcitonin still represent the most used biomarkers in the pediatric ED for the diagnosis of SBI. Their sensibility and sensitivity increase when combined and for this reason it is reasonable to take them both into consideration in the evaluation of a febrile children. The potential of machine learning tools, who represent a real novelty in medical practice, in conjunction with routine clinical and biological in-formation, may improve accuracy of diagnosis and target therapeutic options in SBI. However, studies on this matter are not yet validated in younger populations, making their relevance in pe-diatric precision medicine still uncertain. More data from further researches are needed to improve clinical practice and decision making using these new technologies.

This study centered on examining 60 different antibiotics by assessing their primary toxicity parameters through the pkCSM database. The parameters included Max. Tolerated Dose (Human) (log mg/kg/day), Oral Rat Acute Toxicity (LD50) (mol/kg), Oral Rat Chronic Toxicity (LOAEL) (log mg/kg_bw/day), and Minnow Toxicity (LC50) (log mM). The results highlight four potential antibiotics—cefotaxime, ceftriaxone, imipenem, and meropenem—that exhibited lower toxicity effects compared to other compounds. These findings imply a relatively favorable safety profile for these antibiotics concerning the specified toxicity parameters. However, it is crucial to interpret these outcomes within the context of the specific clinical application and to consider additional factors for a comprehensive safety assessment. It's essential to acknowledge that evaluating toxicity is intricate, and the determination of what is considered "less toxic" can rely on specific criteria and the context of use. Furthermore, individual responses to antibiotics may vary, and the selection of an antibiotic should be based on diverse factors, including the specific infection being treated, the patient's health, and potential side effects.

Bandung and Lembang are the cities that are chosen by many tourists (local and foreign) as their destinations. Geographically, these cities are placed side-by-side and each city has its own characteristics. As in Bandung, there are many hotels and culinary spots, meanwhile, in Lembang, there are many scenery tourism spots. Tourists usually have limited time to visit all the destinations on holiday, which makes them choose several tourist destinations to visit. In this paper, the tourism itinerary recommendation system is proposed by calculating the most optimal route between destinations and approaching the Vehicle Routing Problem with Time Windows. The optimal route is defined by using Dijkstra the shortest path algorithm by using the collaboration between the road information (road length, traffic condition, travel time, and weather condition) and criteria weight that is determined using the Analytics Hierarchy Process as the graph weights. According to the simulation results, the criteria weights are 6.9%, 62.7%, 18.6%, and 11.9% for Route Length, Traffic Condition, Travel Time, and Weather Condition respectively. Moreover, the optimal number of tourism itinerary plans for the tourist in this research is 4 destinations. As the usage of computational resources, it takes 31.8% of CPU and 61.9% of Memory usage. For the time processing, it increases exponentially as the increment of number of requested stops. The output of this research is expected to be a solution to the tourist itinerary plan, especially in Bandung and Lembang.

This research provides a computationally efficient numerical tool for predicting 3-D turbulent flows over hydrofoils. It addresses a gap in existing numerical methods by extending the capabilities of the laminar VIScous Vorticity Equation (VISVE) solver to handle 3-D turbulent flow scenarios. The implementation integrates the k − ω SST model into the 3-D VISVE solver using the Finite Volume Method (FVM), extending its capability to handle turbulent flows. The turbulence model is also parallelized to improve computational efficiency. The application of the newly developed model to 3-D hydrofoil cases expands its scope and serves as preparatory work for future rotational propeller applications. Rigorous testing includes a convergence analysis concerning grid numbers and time step sizes, and validation against a Reynolds-Averaged Navier-Stokes (RANS) solver ensures the reliability and accuracy of the enhanced VISVE solver for turbulent flow simulations. The turbulent VISVE solver offers advantages such as reduced computational domain and costs through a vorticity-based approach. Turbulence concentration within boundary layers and free shear flows does not compromise the advantages of the small computational domain. The simplified meshing process, automatically generated by denoting the number of panels on the hydrofoil, makes the solver accessible for researchers and engineers.

Nuclear fusion reactors are composed by several complex components whose behaviour may be not certain a priori. This uncertainty may have a significant importance in the evolution of fault transients in the machine, causing unexpected damages to its components. For this reason a suitable method for the uncertainty propagation during those transient is required. The Monte Carlo method would be the reference option, but it is, in most of the cases, not applicable due to the large amount of required simulations to be repeated. In this context the Polynomial Chaos Expansion has been considered as a valuable alternative. It allows to create a surrogate model of the original one in terms of orthogonal polynomials. Then, the uncertainty quantification is performed repeatedly calling this much simpler and faster model. Using the fast current discharge in the Divertor Tokamak Test Toroidal Field (DTT TF) coils as a reference scenario, this method has been applied: the uncertainty on the parameters of the Fast Discharge Unit (FDU) varistor disks is propagated to the simulated electrical and electro-magnetic relevant effects. Eventually two worst case scenarios have been analyzed from the thermal-hydraulic point of view with the 4C code, simulating a fast current discharge as a consequence of a coil quench. Eventually it has been demonstrated that the uncertainty on the inputs (varistor parameters) strongly propagates obtaining a wide range of possible scenarios in case of accidental transients. This result underlines the necessity to take into account and propagate all possible uncertainties in the design of a fusion reactor, according to the Best Estimate Plus Uncertainty approach.

The Digital Twin is one of the big technology trends of the last decade. In the course of its rapid expansion into the various fields of application, many different definitions emerged, tailored to the respective applications. Taxonomies can cluster the diversity and define application-specific archetypes. This paper presents a characterization of the Digital Twin in the context of structural mechanics and lightweight design. It begins by exploring various definitions of the Digital Twin concept and its application in different industries. The paper further analyzes the product life cycle of structures, dividing it into the design and operational phases and identifying the requirements for a Digital Twin in each phase. The structural design process is examined, including the definition of a structure and the stages of the product development process. Additionally, the paper discusses the operational phase of structures, highlighting the need for continuous monitoring, evaluation, and adaptation through Structural Health Monitoring (SHM) systems. The paper proposes two archetypes of Digital Twins for structures: a structure-designing Digital Twin for the design phase and a structure-monitoring Digital Twin for the operational phase. The findings provide a framework for implementing Digital Twins in structural mechanics, enabling digital design and monitoring of structures for improved performance and maintenance strategies.

Stroke remains one of the leading causes of death and disability worldwide. Current reperfusion treatments for ischaemic stroke are limited due to their narrow therapeutic window in rescuing ischaemic penumbra. Stem cell therapy offers a promising alternative. As a regenerative medicine, stem cells offer a wider range of treatment strategies, including long-term intervention for chronic patients, through the reparation and replacement of injured cells via mechanisms of differentiation and proliferation. The purpose of this review is to evaluate the therapeutic role of stem cells for ischaemic stroke. The paper discusses the pathology during acute, subacute, and chronic phases of cerebral ischaemic injury, highlights the mechanisms involved in mesenchymal, endothelial, haematopoietic, and neural stem cell-mediated cerebrovascular regeneration and evaluates the pre-clinical and clinical data concerning the safety and efficacy of stem cell-based treatments. Treatment of stroke patients with different type of stem cells appears to be safe and efficacious even at relatively higher concentrations irrespective of the route and timing of administration. Priming or preconditioning of cells prior to administration appears to help augment their therapeutic impact. However, larger patient cohorts and later phase trials are required to consolidate these findings.

Background and Objectives: Although adult spinal deformity (ASD) surgery brought about the improvement of quality of life in patients, it accompanied with a high invasiveness of surgery and several complications. Specifically, mechanical complications of rod fracture, instrumentation failures, and pseudarthrosis are still unsolved issues. To better improve these problems, the oblique lateral interbody fusion at L5/S1 (OLIF51) was introduced since 2015 in my institution. The objective of this study was to compare the clinical and radiographic outcomes of anterior-posterior combined surgery for ASD between the use of OLIF51 versus transforaminal interbody fusion (TLIF) at L5/S1. Materials and Methods :A total of 117 ASD patients received anterior-posterior correction surgeries either use of OLIF51 (35 patients) or L5/S1 TLIF (82 patients). In both groups, L1-5 OLIF and minimally invasive posterior procedures of hybrid or circumferential MIS were employed. The sagittal and coronal spinal alignment and spino-pelvic parameters are recorded preoperatively and at follow-up. The quality of life parameters and visual analogue scale were evaluated as well as surgical complications at follow-up. Results: The average follow-up period was thirty months (13-84). The average fused segments were eight (4-12). The operation time and estimated blood loss were significantly smaller in OLIF51 that those in TLIF. The PI-LL mismatch, LLL, L5/S1 segmental lordosis, and L5 coronal tilt were significantly better in OLIF51 than TLIF. The complication rate was statistically equivalent between two groups. Conclusion: The introduction of OLIF51 for adult spine deformity surgery led to the decrease of operation time and estimated blood loss as well as the improvement of sagittal and coronal correction when compared to TLIF.

Abstract: Rural digital governance is an inevitable requirement to improve the efficiency of rural governance, and is also an important means to realize the modernization of rural governance. In the context of the digital rural development strategy, the index measurement system of rural digital governance level is built around five key governance areas of "digital economy, digital ecology, digital culture, digital people's livelihood, and digital government affairs". The entropy weight Topsis model is used to measure and evaluate the level of rural digital governance in 31 provinces in China in 2021. The results show that there is a large gap in the level of digital governance in China's counties and villages, and the level of each region presents a decreasing spatial distribution from "east - middle - west". In terms of digital economy, the eastern region has a high score and good development, while the central and western regions have poor development. In terms of digital ecology, only the eastern region is higher than the national average; In terms of digital culture, only the central region is higher than the national average; In terms of digital livelihood and digital government, the central and eastern regions are slightly higher than the national average; The top three provinces in overall scores are Zhejiang, Guangdong and Jiangsu.

Penrose’s singularity from 1965 predicted that in the center of the black hole space-time curvature is infinite and consequently gravity force there is infinite. In 2014 NASA measured universal space has Euclidean shape. This means that stellar objects cannot curve universal space and that the space-time singularity model has no physical existence. In the center of black holes energy density of superfluid space is so low that the electromagnetic properties of space are changed. This causes electromagnetic forces between the nucleus and orbiting electrons to become unstable. In the center of a black hole, atoms are falling apart into elementary particles. Black holes are rejuvenating systems of the universe, they transform old matter into fresh energy in the form of elementary particles. Astrophysical jets are the outcome of this process.

Bambara groundnut (BG) (Vigna subterranean L. verdc) is a highly nutritious and economically important leguminous crop of African origin that forms symbiotic relationships nitrogen fixing rhizobia, but it has a low yield. Currently, there is paucity of information on effective rhizobium inoculant, (to improve the yield), for BG which are cheaper and safer alternatives to chemical fertilizers. Indigenous rhizobia strains were trapped from 54 farm soils collected at three Nigerian states (Niger, Kaduna and Kano). Six selected rhizobium strains (Bradhyrhizobium spp) were identified using 16S rDNA sequencing, applied as inoculant in field experiment using completely randomized block design and compared with USDA110 strain (Bradhyrhizobim japonicum), urea fertilizer and un-inoculated plants on 2 selected BG varieties (TVSU1248 and TVSU 631). Nutrient utilization and nitrogen fixation in plants were determined at 6 weeks while leaf chlorophyll was determined forth-nightly. Seed yield was determined at maturity. The strains increased the %nitrogen (1.33±0.10 - ≥1.37±0.05), and %phosphorous (0.48±0.02 - ≥0.51±0.02), %nitrogen fixed (21.07±2.38 - ≥61.30±6.13), nodulation (72.50±21.075 - 154.00±23.79) and leaf chlorophyll were ≥49.74±1.47mg/L, ≥51.82±1.86mg/L and ≥49.65±1.56mg/L at 2nd, 4th and 6th week after planting respectively and the yield of BG (from average of 398.6 Kgha-1 to 1454.725 Kgha-1). Seed yield was highest (1869.85±273.68 Kgha-1) in BG variety TVSU1248 using BN5 strain. Indigenous Bambara-symbiotic strains significantly increased the seed yields, and plant nutrient, showing their potential as use for inoculant to improve the yield of Bambara groundnut.

C-peptide is used as a measure of endogenous insulin production. Given that insulin and C-peptide are produced in equal amounts, C-peptide is typically used to differentiate between external and endogenously produced insulin in insulin-treated type 1 diabetes mellitus (T1DM). In a clinical setting, a decline in C-peptide is regarded as a loss of beta cell function. However, physiological conditions may also be associated with low C-peptide levels. The authors of this paper use a low-carbohydrate diet, the so-called paleolithic ketogenic diet (PKD), in the treatment of various conditions and observed that C-peptide is typically low on this diet. In order to characterize C-peptide levels on this diet, we designed a study to retrospectively assess C-peptide levels in 100 non-T1DM subjects. We found that 55% of the subjects had a C-peptide level below the standard reference range. C-peptide levels correlated with glucose levels. A significant correlation was found between C-peptide and age, with younger subjects having lower C-peptide levels. Males also showed lower C-peptide levels than females. Given the increasing number of patients using low-carbohydrate diets worldwide, physicians should be aware of laboratory correlates of low-carbohydrate diets, including low C-peptide levels, most importantly to prevent incorrect T1DM diagnosis.

In the rapidly evolving landscape of wireless communication, each successive generation of networks has achieved significant technological leaps, profoundly transforming the way we connect and interact. From the analog simplicity of 1G to the digital prowess of 5G, the journey of mobile networks has been marked by constant innovation and escalating demands for faster, more reliable, and more efficient communication systems. As 5G becomes a global reality, laying the foundation for an interconnected world, the quest for even more advanced networks leads us to the threshold of the sixth-generation (6G) era. This paper presents a hierarchical exploration of 6G networks, poised at the forefront of the next revolution in mobile wireless technology. This study delves into the technological advancements that underpin the need for 6G, examining its key features, benefits, and the key enabling technologies. We dissect the intricacies of cutting-edge innovations like terahertz communication, ultra-massive MIMO, artificial intelligence (AI), machine learning, quantum communication, and re-configurable intelligent surfaces. Through a meticulous analysis, we evaluate the strengths, weaknesses, and state-of-the-art research in these areas, offering a wider view of the current progress and potential applications of 6G networks. Central to our discussion is the transformative role of AI in shaping the future of 6G networks. By integrating AI and machine learning, 6G networks are expected to offer unprecedented capabilities, from enhanced mobile broadband to groundbreaking applications in areas like smart cities and autonomous systems. This integration heralds a new era of intelligent, self-optimizing networks that promise to redefine the parameters of connectivity and digital interaction. This paper also addresses critical challenges in the deployment of 6G, from technological hurdles to regulatory concerns, providing a holistic assessment of potential barriers. By highlighting the interplay between 6G and AI technologies, this study not only maps out the current landscape but also lights the path forward in this rapidly evolving domain. This paper aims to be a cornerstone resource, providing essential insights, addressing unresolved research questions, and stimulating further investigation into the multifaceted realm of 6G networks. By highlighting the synergy between 6G and AI(Artificial Intelligence) technologies, we aim to illuminate the path forward in this rapidly evolving field.

Transitions from seed to seedling represent a critical developmental step in the life cycle of higher plants, dramatically affecting plant ontogenesis and stress tolerance. The release from dormancy to acquiring the germination ability is defined by a balance of phytohormones, with a substantial contribution of abscisic acid (ABA), which inhibits germination. We studied the embryonic axes of Pisum sativum L. before and after radicle protrusion. Our previous work compared RNA sequencing-based transcriptomics in the embryonic axes isolated before and after radicle protrusion. The current study aims to analyze ABA-dependent gene regulation during the transition of embryonic axes from germination to post-germination stage. First, we determined the levels of abscisates (ABA, phaseic acid, dihydrophaseic acid, and neo-phaseic acid) using the ultra-high-performance liquid chromatography-tandem mass spectrometry. Second, we made a detailed annotation of ABA-associated genes using RNA sequencing-based transcriptome profiling. Finally, we analyzed the DNA methylation pattern in the promoters of the PsABI3, PsABI4, and PsABI5 genes. We showed that changes in the abscisate profile are characterized by the accumulation of ABA catabolites, and the ABA-related gene profile is accompanied by the upregulation of genes controlling the seedling development and the downregulation of genes controlling the water deprivation. The expression of ABI3, ABI4 and ABI5, which encode the crucial transcription factors during late maturation, was downregulated by more than 20-fold, and their promoters exhibited a high level of methylation already at the late germination stage. Thus, although ABA remains important, other regulators seems to be involved in the transition from seed to seedling.

Base excision repair (BER) is the predominant pathway to remove most forms of hydrolytic, oxidative and alkylative DNA damage. The precise functioning of BER is achieving by the regulation of each step by regulatory/accessory proteins, with the most important of which being poly(ADP-ribose) polymerase 1 (PARP1). The PARP1 regulatory functions extend to many cellular processes including regulation of mRNA stability and decay. PARP1 can therefore affect BER both at the level of the BER proteins and at the level of their mRNAs. Systematic data on how the PARP1 content affects the activities of key BER proteins and the levels of their mRNAs in human cells are extremely limited. In this study the CRISPR/Cas9 based technique has been used to knocked out the PARP1 gene in the human HEK 293FT line. The obtained cell clones with putative PARP1 deletion were characterized by several approaches including: PCR analysis of deletions in genomic DNA, Sanger sequencing of genomic DNA, qPCR analysis of PARP1 mRNA, western-blot analysis of whole-cell-extract proteins with anti-PARP1 antibodies, and the PAR synthesis in the whole-cell-extracts. qPCR analysis of mRNAs coding the BER related proteins: PARP2, uracil DNA glycosylase 2, AP endonuclease 1, DNA polymerase β, DNA ligase III and XRCC1 did not reveal crucial influence of PARP1 knockout. The corresponding catalytic activities in the whole-cell extracts (WCEs) evaluated in parallel did not differ significantly between mutant and parental cell lines. No considerable influence of poly(ADP-ribose) synthesis on the activity of the above WCE enzymes was revealed.

Crystalline phase engineering is a prominent strategy for synergistically optimizing the sur-face-body phases of a catalyst. In this work, TiO2 nanosheets assembled into nanotubes (TNSTs) with two-phases of anatase and rutile were firstly synthesized via crystal engineering by simple thermal annealing, and subsequently loaded with Ru nanoparticles to create efficient benzene hydrogenation catalyst Ru/TNSTs. The well- designed nanosheet-tubes structure boasts large specific surface area and excellent transmission channels, which effectively prevents the ag-glomeration and deactivation of loaded Ru nanoparticles, as well as promotes the internal diffu-sion in the reaction process of benzene hydrogenation to cyclohexene. Furthermore, titanium dioxide nanosheet-tubes contain numerous Ti3+ defects, which not only improves the overall generation rate of cyclohexene, but also enhances the suppression of cyclohexene adsorption. Most importantly, the two-phases of titanium dioxide increases the ratio of the electron defi-ciencies of Ru and promotes cyclohexene desorption. These synergistic properties enhance the selectivity and efficiency of the Ru/TNSTs catalysts, resulting in excellent performance in the hydrogenation of benzene to cyclohexene. Especially the Ru/TNSTs-4 catalyst achieves a 95% in-itial selectivity and 51% yield of cyclohexene in the reaction, outperforming most supported Ru-based catalysts. This work may provide new perspectives for designing efficient benzene hydrogenation catalysts via crystalline phase engineering.

In order to utilize high-alumina coal gangue (HACG) as auxiliary cementitious admixture, it is of fundamental significance to thermally activating Al2O3 effectively in HACG and promoting formation of hydratable products containing Al2O3. In this paper, a new preparation technology is developed to make HACG auxiliary cementitious admixture by thermal activation of HACG-Ca(OH)2 (CH) mixture. HACG powders mixed with 20wt.% CH were calcined within a temperature range of 600-900oC, the thermal transformation and mineral phase formation were analyzed by thermogavimetric analyzer (TGA), X-ray diffractometer (XRD), scanning electron microscope (SEM) and energy dispersive X-ray spectrometer (EDS). The hydration reaction between activated HACG-CH mixture and cement was also investigated. HACG experienced a conventional transformation from kaolinite to metakaolin at 600oC and finally to mullite at 900oC. However, CH underwent an unexpected transformation process from CH to CaO, then to CaCO3, and finally to CaO again with increasing calcining temperature. These substances states were associated with dehydroxylation of CH, chemical reaction between CaO and CO2 generating from combustion of carbon in HACG, and decomposition of CaCO3, respectively. It is the formation of a large amount of CaO above 800oC that favors the formation of hydratable products containing Al2O3 in the calcining process and C-A-H gel in hydration process. The mechanical properties of HACG-cement mortar specimens were measured, from which the optimal calcination temperature for preparing HACG auxiliary cementitious admixture was determined to be 850oC. As compared with pure cement mortar specimens, the maximum 28-d flexural and compressive strength of HACG-cement mortar specimens increased by 5.4% and 38.2%, respectively.

Several life contingency agreements are based on the assumption that policyholders have impaired life expectancy attributable to factors such as lifestyle, social class, or preexisting health issues. Quantifying two crucial variables, augmented death probabilities and the discount rate of projected cash flows, is essential for pricing such agreements. Information regarding the correct values of these parameters is subject to vagueness and imprecision, which further intensifies if impairments must be considered. This study proposes modelling mortality and interest rates using a generalization of fuzzy numbers (FNs), known as intuitionistic fuzzy numbers (IFNs). Consequently, this paper extends the literature on life contingency pricing with fuzzy parameters, where uncertainty in variables, such as interest rates and death probabilities, is modelled using FNs. While FNs introduce epistemic uncertainty, the use of IFNs adds bipolarity to the analysis by incorporating both positive and negative information regarding actuarial variables. Our analysis focuses on two agreements involving policyholders with impaired life expectancy: determining the annuity payment in a substandard annuity and pricing a life settlement over a whole life insurance policy. In particular, we emphasize modelling interest rates and survival probabilities using triangular intuitionistic fuzzy numbers (TIFNs) owing to their ease of interpretation and implementation.

Through the refinement of approaches to applying visual augmentation to virtual environments, the possibilities of utilising this process in robotics continues to be explored. However these endeavours have only yielded a collaborative relationship between the two technologies, where the augmented reality (AR) component is separate from the robot functionality. Regarding telepresence robots, research has shown that their perceived usefulness wanes in comparison to that of video conferencing tools as they do not offer a level of immersion and modified visual experience to justify their use. Therefore this paper contributes a novel virtually augmented robot (VAR) model that embeds AR functionality into telepresence, through the use of augmentation and facial recognition sub-models and algorithms. Experimental results show that using pulse width modulation (PWM), duty cycles, digital signals and accelerometer angles provides an approach for stabilising robot motion and the transference of human to robot head movement. The results also show the benefit of having a robot model with intrinsic AR functionality, as it offers a greater level of immersion and visual control of an environment.

Antimicrobial resistance (AMR) is a growing public health issue worldwide that affects the world economy. The concern associated with this issue increased during the COVID-19 pandemic. The misuse of antibiotics during the COVID-19 pandemic will have catastrophic implications for the control of AMR. In 2019, the coronavirus illness COVID-19 first appeared in China. COVID-19 infection is a surface-to-surface communicable disease. It is considered the most vital global health disaster of the century. It has rapidly spread around the world and is the greatest challenge for humankind. This chapter discusses the origin, symptoms, transmission, treatment, and recommendations of the COVID-19 disease.

A new approach for predicting the geometrical characteristics of the mixing behavior of an inclined dense jet for angles ranging from 15° to 85° is proposed in this study. This approach is called group method of data handling (GMDH) which is based on the artificial neural network (ANN) technique. The proposed model was trained and tested using existing experimental data reported in literature. The model was then evaluated using statistical indices as well as compared with analytical models from previous studies. The results of the coefficient of determination (R2) indicate a high accuracy of the proposed model with values of 0.9719 and 0.9513 for training and testing for the dimensionless of the distance from the nozzle to the return point xr/D, and 0.9454 and 0.9565 for training and testing for the dimensionless of the terminal rise height yt/D . Moreover, four previous analytical models were used to evaluate the GMDH model. The results showed the superiority of the proposed model in predicting the geometrical characteristics of the inclined dense jet for all tested angles. Finally, the standard error of estimate (SEE) was applied to demonstrate which model performed the best in terms of getting closer to the actual data. The results illustrate that all fitting lines of the GMDH model performed very well for all geometrical parameter predictions and was the best model with approximately 10% error, which was the lowest value of error among the models. Therefore, this study confirms that the GMDH model can be used to predict the geometrical properties of the inclined negatively buoyant jet with high performance and accuracy.

A symbolic analysis of Archimedes’ periodical number system is developed, from which a natural link emerges with the modern positional number systems with zero. After the publication of Fibonacci’s Liber Abaci, the decimal Indo-Arabic positional system was the basis of the algorithmic and algebraic trend of modern mathematics, but even if zero plays a crucial role in algebra and mathematical analysis, zeroless positional systems show the same capability of producing efficient arithmetical algorithms based on operation tables over digits. The crucial role of digits is assessed, by considering a representation of numbers based on strings in lexicographic order. A new algorithm for the determination of decimal periods is presented,, by remarking the cruciality of this topic in number theory. Periods of ordinal numbers, and enumerations of recursive enumerability are shortly recalled. Concluding remarks are formulated about the deep relationship among numbers and information, which shed new light on a red line passing through the whole history of mathematics

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

In vertebrates, oligodendrocytes (OLs) are glial cells of the central nervous system (CNS) responsible for the formation of the myelin sheath that surrounds the axons of neurons. The myelin sheath plays a crucial role in the transmission of neuronal information by promoting the rapid saltatory conduction of action potentials and providing neurons with structural and metabolic support. Saltatory conduction, first described in the peripheral nervous system (PNS), is now generally recognized as a universal evolutionary innovation to respond quickly to the environment: myelin helps us think and act fast. However, the function of myelin in the CNS, particularly in the brain, is not necessarily to act quickly, but rather to act correctly. In this respect, myelin should primarily play a role in synchronizing the different neuronal networks, a synchrony that occurs in the form of oscillations (or rhythms) relevant for specific information processing. Interestingly, myelin has been directly involved in different types of cognitive processes relying on brain oscillations, and myelin plasticity is currently considered to be part of the fundamental mechanisms for memory formation and maintenance. However, despite ample evidence showing the involvement of myelin in cognition and neurodevelopmental disorders characterized by cognitive impairments, the link between myelin, brain oscillations, cognition and disease is not yet fully understood. In this review, we aim to highlight what is known and what remains to be explored to understand the role of myelin in high order brain processes.

Biofilm-related infections play a significant role in the development and persistence of ventilator-associated pneumonia. Pseudomonas aeruginosa frequently causes biofilm-related infections associated with ventilator tubing. Glucosamine gold nanoparticles (AuNPs) may exhibit antibiofilm properties; however, more studies, including combinatorial therapy with antibiotics, are needed to explore their potential applications in clinical settings. This study aimed to investigate the biofilm inhibition properties of glucosamine AuNPs in combination with meropenem against Pseudomonas aeruginosa ATCC 9027 on the endotracheal tube. A biofilm inhibition assay of glucosamine AuNPs at 0.02 mg/ml, both singly and in combination with meropenem at 1 mg/ml, was carried out against Pseudomonas aeruginosa ATCC 9027 on an endotracheal tube using the tissue culture plate method. Scanning electron microscopy was performed for visualization. Glucosamine AuNPs at 0.02 mg/ml combined with meropenem at 1 mg/ml showed greater biofilm inhibition (72%) than glucosamine nanoparticles at 0.02 mg/ml alone (26%) on the endotracheal tube (p=0.001). The scanning electron microscopic visualization revealed that the untreated Pseudomonas aeruginosa biofilm was denser than the glucosamine nanoparticles-treated biofilm either combined with meropenem or glucosamine nanoparticles alone. The combination of glucosamine AuNPs and meropenem may have the synergistic effect to inhibit biofilm production of Pseudomonas aeruginosa on the endotracheal tube in patient with mechanical ventilation. Conducting additional experiments to explore the impact of combining glucosamine-coated gold nanoparticles (AuNPs) with meropenem on the inhibition of biofilm production by clinical Pseudomonas aeruginosa isolates would be beneficial.

This study investigates the socio-economic determinants correlated with Post-Traumatic Stress Disorder (PTSD) symptoms amid the 'Guardian of the Walls' operation, in the Israel-Hamas conflict. Our investigation primarily focused on assessing the effects of missile strikes on Israeli civilians. By conducting an in-depth statistical analysis of individual experiences, we sought to unravel the correlation between socioeconomic status and PTSD susceptibility.Our findings reveal a stark disparity in PTSD risks across different socio-economic groups. Individuals from lower socio-economic backgrounds exhibited a notably higher propensity for PTSD symptoms, suggesting that socio-economic adversity intensifies the psychological toll of conflict exposure. Conversely, higher education and stable family environments appeared to mitigate PTSD risks, underscoring the protective role of certain socio-economic factors.The study's implications extend far beyond the immediate context of the Israel-Hamas conflict. By elucidating the heightened vulnerability of lower socio-economic groups to PTSD, it calls for a nuanced approach to mental health intervention in conflict zones. This approach should not only address the direct psychological impact of conflict but also consider the broader socio-economic fabric that shapes individual experiences of trauma.This research contributes to a growing body of knowledge on PTSD in conflict settings, offering valuable insights for policymakers, mental health professionals, and humanitarian organizations. By highlighting the socio-economic dimensions of PTSD, it advocates for more comprehensive, context-sensitive mental health strategies. Such strategies are crucial for addressing the complex array of factors influencing mental health in conflict zones, ultimately paving the way for more resilient and supportive communities.

Small island developing states (SIDS) traditionally face a set of challenges like the narrow economic structure, environmental issues, and dependence on a few ranges of economic activities forcing them to open the economy to the exterior. Therefore, their development model, like in Cape Verde depends on migration, remittances, dependence on aid, tourism, and state employment. The current research offers an insight about the nature of Cape Verde’s economy as a SIDS and the degree to which its economy depends on tourism and government services, both of which are supported through aid programs. Understanding Cape Verde’s development model is important to clarify the challenges the country faces, and its development needs to gather a long-term resilience and to understand if it is changing from a MIRAB (Migrations, Remittances, Aid and Bureaucracy) model into another one.

When applying deep learning methods to detect micro defects on low-contrast LCD surfaces, there are challenges related to the imbalance in samples dataset, as well as the complexity and laboriousness of annotating and acquiring target image masks. In order to solve these problems, a method based on sample and mask auto-generation for deep generative network models is proposed. We first generate an augmented dataset of negative samples using a generative adversarial network(GAN), and then highlight the defect regions in these samples using the training method constructed by the GAN to generate masks for the defect images automatically. Experimental results shows the effectiveness of our proposed method, as it allows for the simultaneous generation of LCD image samples and their corresponding image masks. Through a comparative experiment on the deep learning method Mask R-CNN, we demonstrate that the automatically obtained image masks have high detection accuracy.

Thermoplastic composites are continuously replacing thermosetting composites in lightweight structures. However, the accomplished work on the fatigue behavior of thermoplastics is quite limited. In the present work, we propose a numerical modeling approach for simulating fatigue delamination growth and predicting the residual tensile strength of quasi-isotropic TC 1225 LM PAEK thermoplastic coupons. The approach is supported and validated by tension and fatigue (non-interrupted and interrupted) tests. Fatigue delamination growth is simulated using a mixed-mode fatigue crack growth model, which is based on the cohesive zone modeling method. All interfaces between the thermoplastic plies were modelled using cohesive elements. Quasi-static tension analyses on pristine and fatigued coupons were performed using a progressive damage model implementing a set of Hashin-type strain-based failure criteria and a damage mechanics-based material property degradation module. Using the fatigue model, delamination growth was predicted as a function of number of cycles at all interfaces. The results agree well with C-scan images taken on fatigued coupons during interruptions of fatigue tests. An unequal and unsymmetric delamination growth was predicted due to the quasi-isotropic lay-up. Moreover, the combined models capture the decrease in the residual tensile strength of the coupons. In the quasi-static tension analysis of the fatigued coupons, the driving failure mechanisms are the fast propagation of the pre-existing delamination and the severe matrix cracking.

Lophomonas are flagellated protozoa which have been increasingly associated with upper and lower airway infection in humans. The prevalence and characterization of this disease in the critically ill remains poorly understood. We present a series of eleven ICU patients with confirmed Lophomonas spp. identification in respiratory samples.

Disposable surgical gowns are usually made from petroleum-based synthetic fibers that do not naturally decompose, impacting the environment. A promising approach to diminish the environmental impact of disposable gowns involves utilizing natural fibers and/or bio-based synthetic fibers. In this study, composite web from polylactic bicomponent fiber and natural fibers, cattail and kapok fiber, were prepared by hot-press method. Only the sheath region of the PLA bicomponent fiber melts, acting as an adhesive that enhanced the strength and reduced the thickness of the composite web compared to its state before hot-pressing. Mechanical and physical properties of composite webs were evaluated. Composite webs created from kapok fiber displayed a creamy yellowish-white color, while those made from cattail fiber showed a yellowish-brown color. Composite webs exhibit hydrophobic properties when adding the natural fiber. The maximum natural fiber content, at a ratio of 30, can be incorporated into composite webs while preserving mechanical properties and proper water vapor permeability. This nonwoven material presents an alternative with the potential to replace petroleum-based surgical gowns.

Using metaheuristics, such as the Evolutionary Algorithm (EA), within control structures is a realistic approach for certain optimal control problems. Their role is often predicting the optimal control values over a prediction horizon using a process model (PM). The big computational effort sometimes causes problems. Our work addresses a new issue: whether a machine learning (ML) algorithm could “learn” the optimal behaviour of the couple (EA, PM). A positive answer is given by proposing datasets apprehending this couple's optimal behaviour and appropriate ML models. Following a design procedure, a number of closed-loop simulations will provide the sequences of optimal control and state values, which are collected and aggregated in a data structure. For each sampling period, datasets are extracted from the aggregated data. The ML algorithm experiencing these datasets will produce a set of regression functions. Replacing the EA predictor with the ML model, new simulations are carried out, proving that the state evolution is almost identical. The execution time decreases drastically because the PM’s numerical integrations are totally avoided. The performance index equals the best-known value. In different case studies, the ML models succeeded in capturing the optimal behaviour of the couple (EA, PM) and yielded efficient controllers.

Polysaccharide from Ficus carica L. (FCP) exert multiple biological activities, as a biological macromolecule, the available knowledge about the specific structures and mechanisms of biological activity of purified 'Brunswick' fig polysaccharide is currently limited. In the present study, by chemical purification and characteristics identified via specific instruments, and then the impact of FCP on the immunomodulation activity in vitro and in vivo was examined. Structural char-acteristics showed that the molecular weight of the FCP was determined to be 127.5 kDa, the primary monosaccharides present in the FCP were galacturonic acid (GalA), arabinose (Ara), galactose (Gal), rhamnose (Rha), glucose (Glc), and xylose (Xyl) at a ratio of 0.321:0.287:0.269:0.091:0.013:0.011. Based on the investigation of in vitro immunomodulatory ac-tivity, FCP was found to stimulate the production of NO, TNF-α, and IL-6 and increased the pi-nocytic activity of macrophages. Further analysis revealed that FCP activated macrophages by interacting with toll-like receptor 4 (TLR4). Moreover, the in vivo test results indicate that FCP showed significant increase serum pro-inflammatory factors in immunosuppressed mice. Overall, this study suggests that FCP has the potential to be utilized as a novel immunomodulator in the pharmaceutical and functional food industries.

This article aims to delve into the Equity, Diversity and Inclusivity (EDI) issues prevalent in the engineering disciplines in Canada and Spain, shedding light on the common obstacles faced by underrepresented individuals and highlighting potential strategies to foster a more inclusive and diverse engineering community in these nations. Two strategic lines have been identified: (a) facilitating university education access to underrepresented and minority groups, and (b) Accompanying and guiding such students during university training, setting them up for successful future careers. The article also shows the sets of strategies employed in Canada and Spain, clearly distinguishing the approach taken in the two countries. While in Canada, there is a more decentralized approach wherein the universities device their strategies and agenda to address EDI issues, in Spain there is a stronger and direct involvement of the government to ensure a comprehensive, system-wide approach to tackling EDI issues in academia.

While machine learning (ML) has been quite successful in the field of structural health monitoring (SHM), its practical implementation has been limited. This is because ML model training requires data containing a variety of distinct damaged instances captured from a real structure and the experimental generation of such data is challenging. One way to tackle this issue is by generating training data through numerical simulations. However, simulated data cannot capture the bias and variance of experimental uncertainty. To overcome this problem, this work proposes a deep learning-based domain transformation method for transforming simulated data to the experimental domain. Use of this technique has been demonstrated for debonding location and size prediction of stiffened panels using a vibration-based method. The results are satisfactory for both, debonding location and size prediction. This domain transformation method can be used in any field where experimental data for training machine learning models is scarce.

This article introduces a new physically based Lyapunov function difinition, which can be used as acoustic energy for finite amplitude pressure oscillations in reacting systems especially in combustion chambers. Reacting flow is seen as an open, non-equilibrium (parameters are distributed unevenly locally) thermodynamic system. This Lyapunov function is defined as the maximum mechanical work, which could be extracted by a heat engine from studied system, if this system would be disconnected from inlet and outlet and from any other surrounding environment, and the engine could transfer to the surrounding environment only mechanical work.

From the mid-19th century, Collegiate Gothic architecture gained prominence among American universities. Subsequently, through the efforts of American missionaries, the Collegiate Gothic style spread to Christian universities in Asia. Specifically, this study concentrates on the nuanced relationship between the transnational missionary routes and adopting the Collegiate Gothic style, primarily focusing on Anderson Hall at Soochow University, China. The investigation meticulously dissects the multifaceted factors influencing the choice of architectural styles, considering the perspectives of missionaries, architects, and other key stakeholders. Through an intricate analysis of Anderson Hall, this research illuminates the unique characteristics of Collegiate Gothic architecture. By unraveling the complex layers of East Asian campus heritage, this study enriches our comprehension of its origins. It establishes a robust foundation for guiding the preservation and revitalization of architectural styles within university campuses. This scholarly inquiry holds particular significance for experts in academic heritage conservation.

The temporo-spatial theory of consciousness postulates that the brain implements its own inner time and space for conscious processing of outside world. In line with this hypothesis, I present a mechanistic model of mutually connected processes that encode the inner space and time. The model is used to elaborate the binding mechanism between two sets of processes representing the inner space and time, respectively. Further, a stochastic version of the model is developed to investigate the interplay between the binding strength and noise. The spectral entropy is used to characterize the noise effects on the systems of processes when the binding strength is varied. The stochastic modeling results reveal that the spectral entropy values for strongly bound systems have similar entropy values for weakly bound or even decoupled systems. Thus, the analysis performed in this study allows to conclude that the binding mechanism is noise-resilient.

In the evolving landscape of Portfolio Management (PM), the fusion of advanced machine 1 learning techniques with traditional financial methodologies has opened new avenues for innovation. 2 Our study introduces a cutting-edge model combining Deep Reinforcement Learning (DRL) with 3 a Non-stationary Transformer architecture. This model is specifically designed to decode complex 4 patterns in financial time series data, enhancing portfolio management strategies with deeper insights 5 and robustness. It effectively tackles the challenges of data heterogeneity and market uncertainty, 6 key obstacles in PM. Our approach integrates key macroeconomic indicators and targeted news 7 sentiment analysis into its framework, capturing a comprehensive picture of market dynamics. This 8 amalgamation of varied data types addresses the multifaceted nature of financial markets, enhancing 9 the model’s ability to navigate through the complexities of asset management. Rigorous testing 10 demonstrates the model’s efficacy, highlighting the benefits of blending diverse data sources and 11 sophisticated algorithmic approaches in mastering the nuances of PM.12

This paper provides a proof of concept for a linear electric generator that can be used to harvest energy from various sources of linear motion, such as vibrations, free-piston engines and wave energy. The generator can be used to power small electronic devices, such as sensors, or charge household batteries. Literature was reviewed to develop an understanding about the applications, control methods, excitation methods and mechanics of rotating and linear electric machines. A bidirectional, two-sided linear machine was designed with two stator cores and a single mover core. The stator windings and mover winding can be independently excited, allowing for three modes: no mover excitation, DC excited mover, and AC excited mover. Simulations results showed that the magnetic flux generated by DC excited stator cores were concentrated in the centre of the mover core. The use of two stator cores eliminates lateral flux in the mover core when it is not excited, minimising attraction and repulsion forces. Parametric analysis showed that flux cutting occurred in all operation modes, verifying that the generator will produce power when operating. Hardware tests produced an output current when the machine is electrically and mechanically excited, verifying the proposed design.

Alectinib hydrochloride is an anticancer medication used for the first-line treatment of non-small cell lung cancer. Although it has been approved for medical use ten years ago, and three polymorphs of this substance were proposed based on X-ray diffraction patterns, their crystal structures remained unknown to date. The main problem was preparation of high quality single crystals due to very low solubility of the salt. Herein we report on molecular and crystal structure of form I of alectinib hydrochloride as obtained by powder X-ray diffraction data from laboratory source. The refinement revealed that the nitrogen atom of the morpholinyl ring is protonated. The chloride anion interacts with the H(N) atoms of the morpholine and benzo[b]carbazole rings to form infinite H-bonded chains.

Methane is a greenhouse gas and identified as a key driver of near-term climate change. Bottom-up approaches estimate annual methane loss from US natural gas production and transport at 6 Tg, but recent studies suggest this may be an underestimate. To investigate this possibility, an equipment-based emissions inventory, using EPA emission factors, was developed to calculate methane emissions from oil and gas operations in the Delaware Basin, USA. Emission factors and activity data were then updated using contemporary and region-specific measurement data. The original inventory estimated emissions at 315 Gg CH4 y-1 (gas production-normalized rate of 0.6% loss), while the updated inventory estimated emissions of 1,500 Gg CH4 y-1 (2.8% loss). The largest changes resulted from large fugitive emissions from oil production (+430 Gg CH4 y-1), updating maintenance activity emissions (+214 Gg CH4 y-1), considering flaring inefficiency (+174 Gg CH4 y-1), and the inclusion of associated gas venting (+136 Gg CH4 y-1). This study suggests that a systematic underestimate probably exists in current bottom-up inventories and identifies sources currently missing or may be incorrect. We also strongly recommend that emission factors should be validated through direct comparison against measurement campaigns that include long-tail distributions typical of oil and gas activities.

In the present study, the effect of melatonin and sodium nitroprusside treatments on the improvement of high temperature tolerance in California Wonder green bell pepper plant was studied. For this purpose, a factorial experiment was conducted in form of a completely randomized design in three replications at Zabol University's Faculty of Agriculture. In this research, green bell pepper plants of Wonder cultivar were exposed to different temperature treatments (25°C, 35°C and 40°C) for 24 hours after being sprayed (foliar application) with 0μM, 50μM and 100μM concentrations of melatonin and Sodium nitroprusside. Results showed that Instantaneous leaf water consumption efficiency in 40°C temperature treatment with 50μM and 100μM melatonin increased. Also in 40°C temperature with 100µM melatonin, fruit dry weight in compared to control (0uM) 13.15% increased. Also, melatonin and sodium nitroprusside treatments in compared to control treatment improved fruit characteristics and reduced Appearance Characteristics of Fruit Marketability (ACFM) number. Under 40°C temperature treatment in compared to control temperature (25°C), fruit total soluble solids (TSS) 18.50% decreased also under 100μM melatonin treatment, fruit TSS 20.69% was increased compared to control treatment (0μM). Also fruit fructose at 40°C temperature in compared to 25°C temperature treatment 5.52% reduced. Fruit calcium at 35°C and 40°C temperature in compared to control temperature 6.96% and 15.65% decreased respectively. At temperature 35°C under foliar application of 100uM sodium nitroprusside, fruit copper in compared to control 28.93% increased.