Fourteen (14) rack-mounted polycrystalline modules installed on the concrete roof of the solar energy applications laboratory at the Kwame Nkrumah University of Science and Technology (KNUST) in Ghana, a hot humid environment were assessed after 19 years of continuous outdoor expodure. The physical state of the modules was documented using a visual inspection checklist. They were further assessed by current-voltage (I-V) characterization and thermal imaging. The modules were found to be in good physical state, except some bubbles on front side and minor discolouration/corrosion at edge of the cells. Compared with reference values, the performance decline of the modules observed over the exposure period was: nominal power (P_nom), 21% to 35%; short circuit current (I_sc), 5.8% to 11.7%; open circuit voltage (V_oc) 3.6% to 5.6% and 11.9% to 25.7% for fill factor (FF). It is hoped that this study will provide some helpful information to project developers, manufacturers and the research community on the long-term performance of PV modules in Ghana.

The notion of hierarchy is a key characteristic of any complex system. This paper explores which notions of hierarchy are being used in the field of management and organization studies. Four distinct types of hierarchy are identified: a ladder of formal decision-making authority, a ladder of achieved status, a self-organized ladder of responsibility, and an ideology-based ladder. A social mechanism-based perspective serves to define and distinguish these four types. Subsequently, the typology is further developed by comparing the four hierarchy types in terms of their tacit/explicitness, (in)transitivity, and behavior- versus cognition-centeredness. This review article contributes to the literature by dissecting the general metaphor of hierarchy into four different constructs and their social mechanisms, which serves to create a typology of the various ways in which complex systems can be characterized as being hierarchical. This typology can inform future research drawing on any type of hierarchy.

Bioimpedance analysis (BIA) is a validated non-invasive technique already proven to be useful for the diagnosis, prognosis, and management of body fluids in subjects with heart failure (HF) and chronic kidney disease (CKD). Although BIA has been widely employed for research purposes, its clinical application is still not fully widespread. The aim of this review is to provide a comprehensive overview of the state of art of BIA utilization by analysing the clinical benefits, limitations, and the potential future developments in this clinically unexplored field.

Papillomaviruses (PVs) are oncogenic and infect the skin and mucosa of various host species. Considering the recent advances in research on PVs using rolling circle amplification (RCA) followed by high-throughput sequencing (HTS), in this study, we aimed to investigate the bovine papillomavirus (BPV) types associated with proliferative lesions in the upper alimentary tract of an affected bull and characterize the viral strains through complete genome sequencing using this strategy. We analyzed the PV strains associated with two hyperplastic esophageal lesions through PCR using degenerate primer pairs and RCA, followed by HTS. HTS of the libraries generated using RCA products provided the whole genome sequence of BPV4 present in squamous papilloma, whereas, the complete genome sequence of BPV2 and subgenomic fragments of BPV4 were identified in carcinoma in situ (CIS). We, for the first time, have sequenced BPV2 identified from the CIS of the bovine upper alimentary canal. Additionally, RCA followed by HTS allowed characterization of the mixed infection by BPV2 and BPV4 in this lesion. These data reveal that BPV4 is not the only BPV type present in CIS of the esophageal mucous membrane; moreover, a mixed infection caused by BPV2 and BPV4 at the tested anatomical site was demonstrated.

Pachychoroid neovasculopathy (PNV) is a pachychoroid-spectrum disease. As blood circulation throughout the choroid may be involved in PNV pathogenesis, analysis using ultra-wide-field (UWF) fundus imaging is crucial. We evaluated choroidal thickness after half-fluence photodynamic therapy (PDT) combined with intravitreal aflibercept injection for PNV using UWF swept-source optical coherence tomography. Seventeen eyes with PNV that underwent half-fluence PDT with adjuvant single intravitreal aflibercept injection were analyzed. To compare choroidal thicknesses in the central and peripheral choroids, we set subfields <3, <9, and 9–18 mm from the fovea. The <9- and 9–18-mm subfields were divided into four quadrants. Choroidal thickness in each subfield decreased significantly after half-fluence PDT (P<0.001); this reduction was more pronounced in the central area. We also investigated the relationship between the dominant side of the deep choroidal veins that harbor choroidal vein efflux from the macula. When choroidal thickness in the supratemporal and infratemporal 9x9-mm subfields were evaluated, the ratio of choroidal thickness reduction was not significantly different between the dominant and non-dominant sides. The dominant side was not associated with the extent of choroidal thickness reduction in PNV. In conclusion, half-fluence PDT caused thinning of the entire choroid, especially in the central area, in PNV.

Rising temperature is among the most remarkably stressful phenomena induced by global climate changes with negative impacts on crop productivity and quality. It has been previously shown that volatiles belonging to the isoprenoid family can confer protection against abiotic stresses. In this work, two Vitis vinifera cv. ‘Chardonnay’ clones (SMA130 and INRA809) differing for a mutation of the DXS gene encoding for 1-deoxy-D-xylulose-5-phosphate (the first dedicated enzyme of the 2C-methyl-D-erythritol-4-phosphate (MEP) pathway) and involved in the regulation of isoprenoids biosynthesis were investigated in field trials and laboratory experiments. Leaf monoterpene emission, chlorophyll fluorescence and gas-exchange measurements were assessed over three seasons at different phenological stages and either carried out in vivo or controlled conditions under contrasting temperatures. A significant (p<0.001) increase in leaf monoterpene emission was observed in INRA809 when plants were experiencing high temperatures and over two experiments while no differences were recorded for SMA130. Significant variation was observed for the rate of leaf CO2 assimilation under heat stress, with INRA809 maintaining higher photosynthetic rates and stomatal conductance values than SMA130 (p=0.003) when leaf temperature increased above 30°C. At the same time, maximum photochemical quantum yield of PSII (Fv/Fm) was affected by heat stress in the non-emitting clone (SMA130), while the INRA809 showed a significant resilience of PSII under elevated temperature conditions. Consistent data were recorded between field seasons and temperature treatments in controlled environment conditions suggesting a strong influence of monoterpene emission on heat tolerance under elevated temperatures. This work provides further insights on the photoprotective role of isoprenoids under high temperatures in Vitis vinifera and additional studies should focus at unravelling the mechanisms underlying heat tolerance on the monoterpene-emitter grapevine clone.

We describe the design and construction of coils to compensate the earth's magnetic field in the vertical cryostat GERSEMI in the FREIA laboratory at Uppsala University.

In recent years, numerous topologies of single phase and three phase Field Excited Flux-Switching Machine (FEFSM) have been developed for several applications. Comparative study of three types of single-phase low-priced Field Excited Flux-Switching Machine (FEFSM) is presented in this paper. Both the conventional 8S/4P sub-part rotor design and 6S/3P salient rotor design have an overlapped winding arrangements between armature coil and field excitation coil that depicts high copper losses as well as results in increased size of motor. Additionally, FEFSM with salient structure of the rotor have high flux strength in the stator-core that has much impact on high iron losses. Copper consumption and iron loss being a crucial proportion in total machine losses. Therefore a novel topology of single phase modular rotor field excited FSM with 8S/6P configuration is proposed, which enable non-overlap arrangement between armature coil and FEC winding that facilitates devaluation in the copper losses. The proposed modular rotor design acquires reduced iron losses as well as reduced active rotor mass comparatively to conventional rotor design. It is very persuasive to analyze the best range of speed for these rotors to avoid cracks and deformation, the maximum tensile strength (can be measured with principal stress in research) of the rotor analysis is conducted using JMAG. A deterministic optimization technique is used to enhance the performance of 8S/6P modular rotor design. The electromagnetic performance of conventional sub-part rotor design, F1-A3-3P design and proposed novel-modular rotor design are analyzed by 3D-Finite Element Analysis (3D-FEA), includes flux linkage, flux distribution, flux strength, back-EMF, cogging torque, torque characteristics, iron losses and efficiency.

In this paper, mean-field type games between two players with backward stochastic dynamics are defined and studied. They make up a class of non-zero-sum differential games where the players' state dynamics solve backward stochastic differential equations (BSDEs) that depend on the marginal distributions of player states. Players try to minimize their individual cost functionals, also depending on the marginal state distributions. Under some regularity conditions, we derive necessary and sufficient conditions for existence of Nash equilibria. Player behavior is illustrated by numerical examples, and is compared to a centrally planned solution where the social cost, the sum of player costs, is minimized. The inefficiency of a Nash equilibrium, compared to socially optimal behavior, is quantified by the so-called price of anarchy. Numerical simulations of the price of anarchy indicate how the improvement in social cost achievable by a central planner depends on problem parameters.

Texas cotton production is facing challenges arising from increased temperatures and extended droughts. One potential solution to mitigate these environmental stresses lies in enhancing soil health through measures aimed at increasing soil organic matter and microbial biomass. Our field study investigated the effectiveness of adding residue on soil surface to increase soil organic matter content, microbial biomass, and cotton production under experimental warming with open-top chambers (OTCs). The OTCs raised the air temperature by 2 °C but did not affect soil temperature. OTCs also increased microbial biomass and soil respiration rate. Residue addition increased moisture content in non-irrigated (i.e., dryland) soils under experimental warming and concurrently reduced the daily temperature range in warmed plots. Furthermore, residue addition increased microbial biomass and soil respiration, particularly under OTC treatments in dryland soils. We also observed increased soil organic matter, microbial biomass, cotton biomass, and yield in irrigated fields compared to dryland. Our findings suggest that residue retention can mitigate the adverse effects of warming by stabilizing soil microclimate and enhancing soil organic matter and microbial biomass levels, especially in drylands. This, in turn, can help attenuate the potential impacts of future climate change on soil health and crop production in semiarid environments.

Lord Kelvin believed that the electromagnetic aether must also generate gravity. Presently, we have no methods to determine the density of the electromagnetic aether, or we say the $\Omega(1)$ substratum. Thus, we also suppose that vacuum is filled with another kind of continuously distributed substance, which may be called the $\Omega(2)$ substratum. Based on a theorem of V. Fock on the mass tensor of a fluid, the contravariant energy-momentum tensors of the $\Omega(1)$ and $\Omega(2)$ substrata are established. Quasi-static solutions of the gravitational field equations in vacuum are obtained. Based on an assumption, relationships between the contravariant energy-momentum tensors of the $\Omega(1)$ and $\Omega(2)$ substrata and the contravariant metric tensor are obtained. Thus, the cosmological constant is calculated theoretically. The $\Omega(1)$ and $\Omega(2)$ substrata may be a possible candidate of the dark energy. According to the theory of vacuum mechanics, only those energy-momentum tensors of discrete or continuously distributed sinks in the $\Omega(0)$ substratum are permitted to act as the source terms in the generalized Einstein's equations. Thus, the zero-point energy of electromagnetic fields is not qualified for a source term in the generalized Einstein's equations. Some people believed that all kinds of energies should act as source terms in the Einstein's equations. It may be this unwarranted belief that leads to the cosmological constant problem. The mass density of the $\Omega(1)$ and $\Omega(2)$ substrata is equivalent to that of around $3$ protons contained in a box with a volume of $1$ cubic metre.

Some vessels do not comply with maritime rules, particularly in port and safety zones; they must be detected to avoid incidents. Due to background noise and congestion interference at the sea surface, it is difficult to accurately detect these vessels when it is getting dark, especially smaller ones. For these reasons, this paper proposes and develops an improved multi-structural mor-phology (IMSM) approach to eliminate all this noise and interference. The vessel target is sepa-rated from the sea surface backdrop using weighted morphological filtering of many groups of structural components. Then, the neighborhood-based adaptive fast median filtering is used to filter out impulse noise. Finally, the characteristic morphological model of the vessel target is established using the connected domain; this permits eliminating the sea surface congestion and locating vessels movement in real-time. Multiple tests were carried out in a small and discon-tinuous area of the vessel’s inter-frame motion. The results of many groups of data collected show that the proposed approach can effectively eliminate the background noise and congestion in-terference in the monitoring video. The detection accuracy rate and the processing time have increased by approximately 3.91% and 1.14s, respectively.

In an industrial environment, the quality assurance of weld seams requires extensive efforts. The most commonly used methods for that are expensive and time-consuming destructive tests, since quality assurance procedures are difficult to integrate into production processes. Beyond that, available test methods allow only the assessment of a very limited set of characteristics. They are either suitable for determining selected geometric features or for locating and evaluating internal seam defects. The presented work describes an evaluation methodology based on microfocus X-ray computed tomography scans (µCT scans) which enable the 3D characterization of weld seams, including internal defects such as cracks and pores. A 3D representation of the weld contour, i.e., the complete geometry of the joint area in the component with all quality-relevant geometric criteria, is an unprecedented novelty. Both the dimensions of the weld seam and internal defects can be revealed, quantified with a resolution down to a few micrometers and precisely assigned to the welded component. On the basis of the methodology developed within the framework of this study, the results of the scans performed on the alloy AA 2219 can be transferred to other aluminum alloys. In this way, the data evaluation framework can be used to obtain extensive reference data for the calibration and validation of inline process monitoring systems employing Deep Learning-based data processing.

In the present paper, we propose a wavelet method to study the impact of electronic media on economic situations. We precisely apply wavelet techniques versus classical methods to analyze economic indices in the market. The technique consists firstly in filtering the data from unprecise circumstances (noise) to construct next a wavelet denoised contingency table. Next, a thresholding procedure is applied to such a table to extract the essential information porters. The resulting tables subject finally to correspondence analysis before and after thresholding. As a case of study, we are empirically concerned with the 2030 KSA vision in electronic and social media. Effects of the electronic media texts about the trading 2030 Vision on the Saudi and global economy have been studied. Recall that the Saudi market is the most important representative market in the GCC continent. It has both regional and worldwide influence on economies and besides, it is characterized by many political, economic, and financial movements such as the worldwide economic NEOM project. The findings provided in the present paper may be applied to predict future GCC markets situation and thus may be a basis for investors’ decisions in such markets.

Users of meteorological forecasts are often faced with the question of whether to make a decision now based on the current forecast or whether to wait for the next and hopefully more accurate forecast before making the decision. One would imagine that the answer to this question should depend on the extent to which there is a benefit in making the decision now rather than later, combined with an understanding of how the skill of the forecast improves, and information about the possible size and nature of forecast changes. We extend the well-known cost-loss model for forecast-based decision making to capture an idealized version of this situation. We find that within this extended cost-loss model, the question of whether to decide now or wait depends on two specific aspects of the forecast, both of which involve probabilities of probabilities. For the special case of weather and climate forecasts in the form of normal distributions we derive a simulation algorithm, and equivalent analytical expressions, for calculating these two probabilities. We apply the algorithm to forecasts of temperature and find that the algorithm leads to better decisions relative to three simpler alternative decision-making schemes. Similar problems have been studied in many other fields, and we explore some of the connections.

This paper presents a novel approach to sentiment analysis specifically customized for predicting stock market movements, bypassing the need for external dictionaries which are often unavailable for many languages. Our methodology directly analyzes textual data, with a particular focus on context-specific sentiment words within neural network models. This specificity ensures our sentiment analysis is both relevant and accurate in identifying trends in the stock market. We employ sophisticated mathematical modeling techniques to enhance both the precision and interpretability of our models. Through meticulous data handling and advanced machine learning methods, we leverage large datasets from Twitter and financial markets to examine the impact of social media sentiment on financial trends. We achieved an accuracy exceeding 75%, highlighting the effectiveness of our modeling approach, which we further refined into a convolutional neural network model. This achievement contributes valuable insights into sentiment analysis within the financial domain, thereby improving the overall clarity of forecasting in this field.

This study is part of an extended investigation into the quantitative detection of therapeutic molecules with antineoplastic properties, specifically focusing on bleomycin. The objective is to minimize adverse effects while maximizing therapeutic effectiveness. We are presenting the results for bleomycin detection, in terms of cyclic voltammetry and electrochemical impedance spectroscopy. We are continuing an approach we have recently started, of an electrochemical biosensor based on graphene, which is evidenced to be a revolutionary nanomaterial. The vertical graphene biosensor exhibited improved sensitivity, faster response, faster occurrence of the chemical reactions, and higher electrode surface conductivity, than the classical gold IDE sensor. The construction of the electrochemical sensor involved growing vertically aligned graphene nanosheets on the conductive surface of interdigitated electrodes. The results for bleomycin detection emphasized that a simpler surface modification method proved to be more efficient.

Modern research applies the Open Science approach that fosters the production and sharing of Open Data according to the FAIR (Findable, Accessible, Interoperable, Reusable) principles. In the geospatial context this is generally achieved through the setup of OGC Web services that implements open standards that satisfies the FAIR requirements. Nevertheless, the requirement of Findability is not fully satisfied by those services since there’s no use of persistent identifiers and no guarantee that the same dataset used for a study can be immutably accessed in a later period: a fact that hinders the replicability of research. This is particularly true in recent years where data-driven research and technological advances have boosted frequent updates of datasets. Here, we review needs and practices, supported by some real case examples, on frequent data or metadata updates in geo-datasets of different data types. Additionally we assess the currently available tools that support data versioning for databases, files and log-structured tables. Finally we discuss challenges and opportunities to enable geospatial web services that are fully FAIR: a fact that would provide, due to the massive use and increasing availability of geospatial data, a great push toward open science compliance with ultimately impacts on the science transparency and credibility.

Addressing sustainable mobility in urban areas has become a priority in today’s society, given the growing population and increasing vehicular flow in these areas. Intelligent Transportation Systems have emerged as innovative and effective technological solutions to address these challenges. Research in this area has become crucial, as it contributes not only to improve mobility in urban areas, but also to positively impact the quality of life of its inhabitants. To address this, a dynamic clustering methodology for vehicular trajectory data is proposed which can provide an accurate representation of the traffic state. Data was collected for the city of San Francisco, a dynamic clustering algorithm was applied and then an indicator was applied to identify areas with traffic congestion. Several experiments were also conducted with different parameterizations of the forgetting factor of the clustering algorithm. The results showed in terms of precision that the dynamic clustering methodology achieved high match rates compared to the congestion indicator applied to static cells.

Traditional underground pipeline inspection primarily relies on closed-circuit television (CCTV) systems, capturing visual data of deformations within sewer systems for manual assessment of their types and severity. However, these methods heavily rely on human expertise, which leads to subjective detection with limited accuracy. Moreover, they lack the capability for quantitative analysis of deformation extent, hindering accurate assessments and limiting overall inspection effectiveness. To address these challenges, this paper proposes a method for quantitatively detecting geometric deformations in underground pipe corridors using laser point cloud data. The approach, employing laser scanning with a 3D scanner, enables objective detection of internal pipeline deformations and quantitative assessment of blockage levels. In comparison to traditional CCTV-based methods, this approach offers advantages in objectivity and quantification, thereby improving detection reliability, accuracy, and overall efficiency.

Matrix Factorization is a long established method employed for analyzing and extracting valuable insight recommendations from complex networks containing user ratings. The execution time and computational resources demanded by these algorithms pose limitations when confronted with large datasets. Community detection algorithms play a crucial role in identifying groups and communities within intricate networks. To overcome the challenge of extensive computing resources, we present a novel parallel computation framework utilizing community information available in the rating network. Our proposed approach named as Community-based Matrix Factorization(CBMF), parallelizes matrix factorization technique by dividing the network into communities using existing community detection algorithms. We prove that this parallel approach not only increases the quality of recommendations in connection with Root Mean Square Error (RMSE), but also yields substantial performance improvement. We empirically evaluate our idea on diverse datasets and present comprehensive experimental results. These results serve as empirical evidence of the effectiveness and performance gains offered by our parallel computation framework.

Smart farming, as a branch of the Internet of Things (IoT), combines the recognition of agricultural economic competencies, the progress of data and information collected from connected devices with statistical analysis to characterize the essentials of the assimilated information, allowing farmers to make intelligent conclusions that will maximize the harvest benefit. However, the integration of advanced technologies requires the adoption of high-tech security approaches. In this paper, we present a framework that promises to enhance the security and privacy of smart farms by leveraging the decentralized nature of blockchain technology. The framework stores and manages data acquired from IoT devices installed in smart farms using a distributed ledger architecture, which provides secure and tamper-proof data storage and ensures the integrity and validity of the data. The study uses the AWS cloud, ESP32, the smart farm security monitoring framework, and the Ethereum Rinkeby smart contract mechanism, which enables automated execution of pre-defined rules and regulations. As a result of a proof-of-concept implementation, the system can detect and respond to security threats in real time, and the results illustrate its usefulness in improving the security of smart farms.

This review focus on a critical analysis of nanocatalysts for Advanced Reductive Processes (ARP) and Oxidation Processes (AOP) designed for the degradation of poly/perfluoroalkyl substances (PFAS) in water. Ozone, ultraviolet and photocatalyzed ARP and/or AOP will be the basic treatment technologies. Besides the review of the nanomaterials with greater potential as catalyst for advanced processes of PFAS in water, the perspectives for its future development considering sustainability considerations will be discussed. Moreover, a brief analysis of the current state of the art of the ARP and AOP for the treatment of PFAS in water will be presented.

The high penetration of intermittence resources in the energy market accelerates significantly the decarbonization process but, on the other hand, the electrical system has to face the problem of unbalances. Renewable Energies Sources (RES) are hard to precisely forecast, and power plants are not able to predict the amount of energy that they can provide far from the real time delivery. In this frame, the intraday market gets a fundamental role allowing agents to adjust their position close to the delivery time. In this work we suggest an agent-based model of intraday market combined with genetics algorithms to understand what the best strategy could be adopted by players in order to optimize the market efficiency in terms of welfare and unsold quantity. In the first part we show the effect on the market prices of different scenarios in which players aim at maximizing their revenues and selling/buying all their volumes. In the second part we show the effect of a particular genetic algorithm on the model, focusing on how agents can adapt their strategy to enhance the market efficiency. Comparative analyses are also performed to investigate how the welfare of the system increases as well as the unsold quantity decrease when genetic algorithm is introduced

Powder mixture with given molar ratio Ca/P = 1.67 consisting of brushite (calcium hydrophosphate dihydrate) CaHPO4·2H2O, calcium oxalate monohydrate CaC2O4·H2O in form of whewellite and weddellite and some quantity of quasi-amorphous phase was obtained as a result of the interaction of hydroxyapatite powder Ca10(PO4)6(OH)2 with an aqueous solution of oxalic acid H2C2O4 at a molar ratio of Ca10(PO4)6(OH)2/H2C2O4 = 1:4 under mechanical activation conditions. This powder mixture was used to produce microporous monophase ceramics based on hydroxyapatite Ca10(PO4)6(OH)2 with aperient density of 1.25 g/cm3 after firing at 1200 oC. Microporosity of sintered ceramics was formed due to presence of particles with plate-like morphology, restraining shrinkage during sintering. Microporous ceramics based on hydroxyapatite Ca10(PO4)6(OH)2 with roughness of the surface as a consequence of the created microporosity can be recommended as a biocompatible material for the bone defects treatment and as a substrate for bone cell cultivation.

Dental pulp tissue engineering (TE) quests to regenerate dentin/pulp complex by combining a suitable supporting matrix, stem cells, and biochemical stimuli. Such procedures foresee a matrix that can be easily introduced into the root canal system (RCS) and tightly adhere to dentin walls to assure the dentin surface's proper colonization with progenitor cells capable of restoring the dentin/pulp complex. Herein was investigated an injectable self-setting hyaluronic acid-based (HA) hydrogel system, formed by aldehyde-modified (a-HA) with hydrazide-modified (ADH), enriched with platelet lysate (PL), for endodontic regeneration. The hydrogels' working (wT) and setting (sT) times, the adhesion to the dentine walls, the hydrogel's microstructure, and the delivery of human Dental Pulp Cells (DPCs) were studied in vitro. Hydrogels incorporating PL showed a suitable wT and sT and a porous microstructure. The tensile tests showed that the breaking point occurs after 4.13 mm deformation. While in the indentation test after 1.3 mm deformation. Both breaking points occur in the hydrogel extension. The HA/PL hydrogels exhibited supportive properties and promoted cell migration toward dentin surfaces in vitro. Overall, these results support using PL-laden HA injectable hydrogels (HA/PL) as a biomaterial for DPCs encapsulation, thereby displaying great clinical potential towards endodontic regenerative therapies.

Laser powder bed fusion (L-PBF) is a type of additive manufacturing technology that processes metal powders into a component. Support structures are an essential part of the L- PBF process as they transfer the laser-induced heat during and shortly after the process to the substrate, sustaining positional accuracy of downward facing surfaces of the component. Since the use of support structures is inevitable, optimized designs for them are crucial in realizing more sustainable production process. In a serial production setup, reducing the lead time and cost of a non-value-added process step like support structure removal is of significance when improving the overall business case and competitiveness.The goal of this study was to verify the applicability of lattice-based support structures for L-PBF. To achieve this, different lattice types as support structures were designed. They were tested, compared and verified for a Siemens gas turbine component. The results showed that the generated lattice-based support structures could be suitable for L-PBF. The supports had to be designed appropriately such that they could preserve the geometry of the part. Furthermore, they had to have a short fabrication time and to be removable easily, preferably without machining or sawing.

As new treatment modalities are being explored in neuro-oncology, viruses are emerging as a promising class of therapeutics. Virotherapy consists of introduction of either wild-type or engineered viruses to the site of disease, where they exert anti-tumor effect. These viruses can either be non-lytic, in which case they are used to deliver gene therapy, or lytic, which induce tumor cell lysis and subsequent host immunologic response. Replication-competent viruses can then go on to further infect and lyse neighboring glioma cells. This treatment paradigm is being explored extensively in both preclinical and clinical studies for a variety of indications. Virus-based therapies are advantageous due to the natural susceptibility of glioma cells to viral infection, which improves therapeutic selectivity. Furthermore, lytic viruses expose glioma antigens to the host immune system and subsequently stimulate an immune response that specifically targets tumor cells. This review surveys the current landscape of oncolytic virotherapy clinical trials in high-grade glioma, summarizes preclinical experiences, identifies challenges associated with this modality across multiple trials, and highlights potential to integrate this therapeutic strategy into promising combinatory approaches.

Plants and plant-derived food products have been used for medicinal purposes since the ancient. Medicinal Plant-based functional foods or plant-based dietary compounds are a re-emerged interest for their therapeutic benefits and nutritive supports which has implicated in healthcare systems across the world. Neurological disorders are one of the greatest threats to public health and according to the World Health Organization, about 100 million people are affected globally by several neurological and mental ailments. In a traditional medication system, medicinal plants have been applied as both neuro-therapeutic purposes and micro-macro nutrients provider for the wellbeing of psychological states e.g. anti-depressant, anti-anxiety, anti-convulsions, anti-dementia, anti-psychotic, etc. Herein, it is a topic of great interest to present a conceptual aspect by reviewing relevant scientific literature about the plant-based functional foods or bioactive phytochemicals for the prevention and treatment of mental and neurological disorders. From the literature assessment, we have found that nutritional neuroscience is becoming an advanced research discipline and there has been a growing pile of evidence concerning the therapeutic use of plant-based functional foods and/or plant-derived food compounds for the management of neurologic health, evolving with promising impact over the time.

The influence of lignin modification on drug release and pH-dependent releasing behaviour of oral solid dosage form was investigated using three different formulations. The first formulation contains microcrystalline cellulose (MCC101) as excipient and paracetamol as active pharmaceutical ingredient (API). The second formulation includes Alcell lignin and MCC 101 as excipient and paracetamol, and the third formulation consists of carboxylated Alcell lignin, MCC 101 and paracetamol. Direct compaction was carried out in order to prepare the tablets. Lignin can be readily chemically modified due to the existence of different functional groups in its structure. The focus of this investigation is on lignin carboxylation and its influence on paracetamol control release behaviour at varying pH. Results suggest that carboxylated lignin tablets had the highest drug release, which is linked to their faster disintegration and lower tablet hardness.

Speech/music classification that facilitates optimized signal processing from classification results has been extensively adapted as an essential part of various electronics applications, such as multi-rate audio codecs, automatic speech recognition, and multimedia document indexing. In this paper, a new technique to improve the robustness of speech/music classifier for 3GPP enhanced voice service (EVS) using long short-term memory (LSTM) is proposed. For effective speech/music classification, feature vectors implemented with the LSTM are chosen from the features of the EVS. Experiments show that LSTM-based speech/music classification produces better results than conventional EVS under a variety of conditions and types of speech/music data.

Plants, among which pumpkins (Cucurbita spp.), represent a good source of nutrients and bioactives with interesting health-promoting properties. In this research, carotenoid extracts obtained from the pulp of eight pumpkin varieties, belonging to the C. moschata and C. maxima species, were tested for cytotoxicity on SH-SY5Y neuroblastoma cells. The results showed that pumpkin bioactives exert a cytotoxic action against the tested cells, in particular Butternut extract at 100 μmol/L concentration after 24h of treatment and Mantovana extract at 50 μmol/L after 48 h. Moreover, the carotenoid extracts also showed interesting in vitro antioxidant activity. To fully characterize the qualitative and quantitative profile of carotenoids in the tested extracts, a high-performance chromatographic technique was performed, revealing that pumpkin pulp carotenoids were mainly represented by β-carotene, mono- and di- esterified hydroxy- and epoxy- carotenoids. Moreover, the carotenoid dataset was also useful for discriminating samples from two different species. In conclusion, the results of the present study highlight the intriguing potential of pumpkin carotenoids in the development of related anticancer drugs and chemotherapeutic adjuvants.

Research on high-volume fly ash concrete, which utilizes large quantities of fly ash, has been actively conducted to promote resource recycling and reduce carbon dioxide emissions. However, while cement mixed with fly ash exhibits different temperature sensitivities compared to traditional cement, its hydration and mechanical properties vary depending on curing conditions. Despite this, there is a significant gap in research on this topic. In this study, high-volume fly ash concrete was produced with fly ash replacement rates of 35 % and 55 %. Compression strength tests were performed at various curing ages under three different curing temperature conditions, and the results were analyzed. Additionally, an isothermal calorimeter was used to analyze hydration characteristics under different curing conditions. The results indicated that concrete with high fly ash content was more sensitive to curing temperature compared to ordinary Portland cement.

To be CMOS-compatible, a low preparation temperature (&lt; 500 °C) of ferroelectric films is required. In this study, BiFeO3 films were successfully fabricated at a low annealing temperature (&lt; 450 °C) on aluminum foils by a metal-organic decomposition process. The annealing atmosphere on performance of BiFeO3 films was assessed at 440 ± 5℃. By replacing an O2-rich atmosphere with an N2-rich one, a better crystalline morphology was achieved in BiFeO3 films, resulting in better electric properties targeted for high-density ferroelectric random-access memory applications. These properties included a large remnant polarization (Pr~78.1 μC/cm2 @ 1165.2 kV/cm) and a high rectangularity (~91.3% @ 1165.2 kV/cm) of the P-E loop, along with excellent charge-retaining ability up to 1.0 × 103 s and a fatigue resistance reaching 1.0 × 109 switching cycles. The enhanced performance of BiFeO3 film in an N2-rich atmosphere maybe originated from the slightly high content of oxygen vacancies during the annealing process. Furthermore, decent electrical properties (Pr~70 μC/cm2 @ 1118.1 kV/cm) of the BiFeO3 films were achieved at a very low annealing temperature of 365 ±5 °C on aluminum foil substrates. These results offer a new idea for lowering the annealing temperature for integrated ferroelectrics in high-density FeRAM applications.

In this paper, the results of a high-precision control survey carried out in the underground mining of the Oyu Tolgoi project using terrestrial laser scanning technology are presented. The purpose of the measurements was to ensure that the direction, total length and volume of the penetration and excavation works were being implemented in accordance with the planned and designed dimensions. The coordinates of the geodetic traverse checkpoints were also assessed. In addition, we checked a traverse network of 18 checkpoints in the tunnel of the selected underground level. These checkpoints were repeatedly measured four times by two using readings of the Trimble S7 1” total station and were processed using the Compass/Bowditch method with Trimble Business Center software. All points except for one were within the tolerance limits. Based on these points, the excavation length and volumes were determined using the terrestrial laser scanners (TLSs) Trimble X7 and Trimble SX12 [25]. The difference between the planned work quantity provided by the Oyu Tolgoi project and the actual values measured using laser scanner was calculated with the comparative method. The TLS partial control measurements in the excavations made through the ore bodies revealed a length of 20285.72m and a volume of 441128.80m3 for the seven underground mine levels, while their project values were 16158.26m length and 422837.50m3 volume.

The two combined technologies WPT and AI still have huge prospects for several industries such as consumer electronics and industry. This paper looks at the recent developments in WPT, particularly concerning AI-improved efficiency, range, and reliability. AI-driven also works to control power, manage device alignment, and test when maintenance is necessary, this makes powering smarter and more efficient. Accuracy is given by deploying machine learning and computer vision, and on the other hand, the maintenance procedure is done through predictions. Furthermore, the ability of the management system to include the use of AI in power regulation enables the control of consumption based on the load. In this study, the positive future effect of AI is discussed concerning improvements in WPT technologies, which is paramount in subsequent applications. Based on the results, it is essential to continue the investigation of the topic within this interdisciplinary science to advance existing problems and discover novel possibilities for evolution. Data based on experiments shows a significant improvement in the efficiency of information transfer where AI is used with rates up to 25% higher than those using the traditional ways. Additionally, advanced maintenance forecasting algorithms improve system availability by cutting down on 30% of the downtimes when applied in real-life applications of AI technology. The study also looks at the possibilities of the outlook to the future including emergence of the distributed artificial intelligence for autonomous WPT network, and additional potential of quantum computing for the use to improve the algorithm. This indicates that there is a new era for the convergence of WPT and AI to enhance the progress of power transfer system in conditions of elegant, efficient, and robust.

Our recent analysis of empirical limit order flow data in financial markets reveals a power-law distribution in limit order cancellation times. These times are modeled using a discrete probability mass function derived from the Tsallis q-exponential distribution, closely aligned with the second form of the Pareto distribution. We elucidate this distinctive power-law statistical property through the lens of agent heterogeneity in trading activity and asset possession. Our study introduces a novel modeling approach that combines fractional Lévy stable motion for limit order inflow with this power-law distribution for cancellation times, significantly enhancing the prediction of order imbalances. This model not only addresses gaps in current financial market modeling but also extends to broader contexts such as opinion dynamics in social systems, capturing the finite lifespan of opinions. Characterized by stationary increments and a departure from self-similarity, our model provides a unique framework for exploring long-range dependencies in time series. This work paves the way for more precise financial market analyses and offers new insights into the dynamic nature of opinion formation in social systems.

Presence detection is essential in many applications, including smart homes, office automation, and public space management. Traditional technologies like infrared sensors and cameras frequently encounter obstacles due to privacy concerns, high costs, and complexity. The study provides a novel way to detect presence based on Wi-Fi signals and machine learning algorithms, utilizing the ESP8266 microcontroller. The suggested system attempts to reliably detect the presence of people in a given place by evaluating fluctuations in Wi-Fi signal strength and patterns. The theoretical basis of this strategy is investigated, including the ESP8266’s capabilities for Wi-Fi data gathering and the use of machine learning methods for data analysis. The methodology includes data collecting with the ESP8266, preprocessing, feature extraction, and training and evaluating machine learning models. This system’s potential uses include smart home automation, office occupancy tracking, and crowd management in public settings. The paper also discusses potential issues such as signal interference, data privacy concerns, and the limitations of Wi-Fi detection. Future work is also mentioned, including the suggested system’s installation and testing and enhancement proposals to improve accuracy and scalability. This research aims to provide a cost-effective, non-intrusive, and scalable presence detection system by harnessing the power of Wi-Fi signals and machine learning, enhancing intelligent environments

This review is dedicated to sustainable practices in liquid chromatography. HPLC and UHPLC methods contribute significantly to routine analytical techniques. Therefore, the transfer of classical liquid chromatographic methods into sustainable ones is of utmost importance in moving toward sustainable development goals. Among other principles to render a liquid chromatographic method green, substitution of the organic solvent component in the mobile phase with a greener one received great attention. This review concentrates on choosing the best alternative green organic solvent to replace the classical solvent in the mobile phase for easy rapid transfer to a more sustainable normal phase or reversed-phase liquid chromatography. The main focus of this review will be on describing the transfer of non-green to green and white chromatographic methods in an effort to elevate the sustainability best practice in analytical chemistry. The greenness properties and greenness ranking in addition to the chromatographic suitability of seventeen organic solvents for liquid chromatography are mentioned to have a clear insight into the issue of rapidly choosing the appropriate solvent to transfer a classical HPLC or UHPLC method into a more sustainable one. A simple guide is proposed for making the liquid chromatographic method more sustainable.

The review explores the therapeutic potential of mangrove plants as sources of bioactive compounds, particularly focusing on their anti-inflammatory properties. Mangroves, found in tropical and sub-tropical tidal coasts, exhibit unique ecological and biological activities. The review compiles and examines 136 research findings published between 1982 and 2018, with 41 studies specifically addressing the anti-inflammatory properties of mangroves in Indian coastal regions, including the Andaman and Nicobar Islands. It summarizes the chemical structures, molecular weights, formulas, solvents, and biological activities of these mangroves, as reported by various researchers over time. The data underscore the significant potential of tropical Indian mangroves in anti-inflammatory applications. However, a notable research gap exists regarding the extraction of bioactive compounds from mangrove species in the Andaman and Nicobar Islands compared to other regions such as Gujarat, Maharashtra, Goa, Karnataka, Kerala, Tamil Nadu, Andhra Pradesh, Odisha, West Bengal, and Puducherry. Overall, the compilation provides valuable insights into mangrove-based studies for drug discovery research, emphasizing the need for further exploration and exploitation of these natural resources.

Euler’s product formula over the primes and Euler’s zeta function equate to enshrine the Fundamental Theorem of Arithmetic that every integer > 1 is the product of a unique set of primes. The product formula has no zero, and with a domain ≤1 Euler’s zeta diverges. Dirichlet’s eta function η(s), negates alternate terms of zeta, permitting convergence when s∈C and Re(s) < 1, and its non-trivial zeros {ρ}, have a deep relationship with the distribution of the primes. The Riemann Hypothesis is that all the non-trivial zeros have Re(ρ) = 1/2. This work examines the symmetries in a partial Euler’s zeta series with a complex domain equating it to the difference between two finite vector series whose matched terms have mirror-image arguments, but whose magnitudes differ when Re(s) ≠ 1/2. Analytical continuation generates a modified eta series η_l(s), in which every l^th term is multiplied by (1-l). If the integer l is appropriately determined by the Im(s), similar paired finite vector series have a difference that closely follows η_l (s) and their terminal vectors intersect in a unique way permitting zeros only when Re(s) = 1/2. Furthermore, those vectors tracking the derivatives of the series, have a special relationship permitting zeros of the differential only when Re(s) > 1/2.

The current study characterizes the transient M/M/1 queue manifold info-geometrically, through devising Fisher Information matrix(FIM) and its inverse(IFIM). Additionally, the impact of stability on the existence of IFIM and explore the geodesic equations of motion has been revealed. More potentially, the paper discusses the relationship between stability and the Gaussian curvature, as well as the connections between queueing theory, information geometry, , Riemannian geometry, and the Theory of Relativity.

The discovery of antibiotics was one of the greatest achievements in human history, however, antibiotic resistance evolved no later than the introduction of antibiotics. The rapid evolution of antibiotic-resistant pathogens soon became a nightmare and remained a global healthcare threat. There is an urgent need to have new alternatives or new strategies to combat the multi-drug resistant superbugs such as methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococci (VRE), carbapenem-resistant Pseudomonas aeruginosa (CR-PA), extended-spectrum β-lactamases (ESBL) bearing multidrug-resistant Acinetobacter baumannii (MDR-AB), Escherichia coli, and Klebsiella pneumonia. Antimicrobial peptides (AMPs) have been considered promising agents equipped with unique mechanisms of action along with several other benefits to fight the battle against drug-resistant superbugs. Overall, the current review summarizes the mechanisms of drug-resistant development, the mechanism of action adopted by AMPs to combat drug-resistant pathogens, and the immunomodulatory properties of AMPs. Additionally, we have also reviewed the synergistic potential of AMPs with conventional antibiotics and the associated challenges and limitations of AMPs in the way of pharmacological development for therapeutic applications in clinical settings.

Warsaw is among European cities with the worst atmospheric air quality, mainly due to very high pollution emitted by the residential sector and road traffic. This results in high concentrations of particulate matter and nitrogen oxides, often exceeding WHO standards. The paper discusses the current and expected effects of actions taken by the Warsaw authorities, to significantly improve air quality in the city. The Clean Air Program currently implemented mainly involves the reduction, and ultimately the total elimination, of coal combustion in all heat sources of the municipal sector, which is identified in numerous publications as the main source of air quality degradation in cities. The program's goal, which timeframe covers the years 2018-2029, is a definite reduction in particulate pollution. The second part of the remedial activities, covering the years 2024-2034, mainly concerns the reduction of nitrogen oxide pollution, the main source of which is urban road traffic. In the latter case, the expected effects of introducing Low-Emission Zone (launched July 2024) in the city center are considered. According to the project, the zone's implementation will consist of five two-year stages, in which the car emission limits will gradually tighten. The paper compares the effectiveness of two being considered versions, differing in size zones.

Introduction: Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss, predominantly affecting older adults. Understanding the multifaceted factors contributing to AD is crucial for developing effective prevention and intervention strategies. This narrative review synthesizes current literature on the various factors influencing the development and progression of AD in older adult populations.Methods: A comprehensive search was conducted across electronic databases including PubMed, Web of Science, and PsycINFO using relevant keywords such as "Alzheimer's disease," "risk factors," "genetics," "environmental factors," and "lifestyle." Studies published between 2000 and 2023 were included, focusing on factors associated with AD in individuals aged 65 years and older.Results: The review identified several key factors contributing to AD in older adults. Genetic predisposition, particularly the presence of apolipoprotein E (APOE) ε4 allele, emerged as a significant risk factor. Environmental factors such as air pollution, pesticides, and heavy metals were also implicated. Furthermore, lifestyle factors including physical inactivity, poor diet, and smoking were associated with increased AD risk. Chronic conditions such as diabetes and cardiovascular diseases were found to exacerbate cognitive decline in older adults.Conclusion: This narrative review highlights the complex interplay of genetic, environmental, and lifestyle factors in the development and progression of Alzheimer's disease among older adults. Understanding these factors is crucial for targeted interventions aimed at reducing AD risk and improving cognitive health outcomes in aging populations. Future research should focus on longitudinal studies and personalized medicine approaches to elucidate specific mechanisms underlying AD pathogenesis and to develop effective preventive strategies.

This research aims to investigate psychological anxiety factors, particularly Music Performance Anxiety (MPA), that influence the sustainability of music learning systems. This study employs an innovative integration of qualitative and quantitative methodologies, marking the first use of a nonlinear system paired with a comprehensive data framework for analyzing questionnaire responses. This approach allows for a detailed examination of the effects of these factors on academic outcomes. Previous research has primarily focused on the fragmented music learning system from the perspective of teachers' instructional strategies, emphasizing phased teaching methods and learning objectives which focus often neglected a significant subset of music learners. Addressing this oversight, the current study specifically centers on the emotional aspects of anxiety within music learning systems, with a particular emphasis on students, who play a crucial role in music education. This perspective enables a deep exploration of how MPA and other related emotional factors affect music learning systems. A notable innovation of this research is the development of a stochastic nonlinear system designed to model the psychological factors impacting student music learning, complemented by a quantitative model that assesses actual learning outcomes. By analyzing this nonlinear system, the research identifies weight values for various negative emotions, particularly those related to MPA, that significantly influence the music learning process. The integration of MPA and other anxiety related emotional factors with practical learning outcomes provides a comprehensive understanding of their combined impact on the music learning system. These insights are invaluable for educators and policymakers aiming to enhance both the effectiveness and emotional well-being within music education. This comprehensive approach offers a novel perspective in understanding and improving the dynamics of music education through a more empathetic and scientifically grounded lens.

This paper is motivated by spatio-temporal pattern in the occurrence of Leishmaniasis in Afghanistan and the relatively high number of zero counts. We hold the view that correlations that arise from spatial and temporal sources are inherently distinct. Our method decouples these two sources of correlations, there are at least two advantages in taking this approach. First, it circumvents the need to inverting a large correlation matrix, which is a commonly encountered problem in spatio-temporal analyses. Second, it simplifies the modelling of complex relationships such as anisotropy, which would have been extremely difficult or impossible if spatio-temporal correlations were simultaneously considered. We identify three challenges in the modelling of a spatio-temporal process: (1) accommodation of covariances that arise from spatial and temporal sources; (2) choosing the correct covariance structure and (3) extending to situations where a covariance is not the natural measure of association. Moreover, because the data covers a period that overlaps with the US invasion of Afghanistan, the high number of zero counts may be the result of no disease incidence or lapse of data collection. To resolve this issue, a model truncated at zero built on a foundation of the generalized estimating equations was proposed.

In a recent paper: “On the time dependency of a₀” the authors claim that they have tested “one of the predictions of the Scale Invariant Vacuum (SIV) theory on MOND” by studying the dependence of the Modified Newtonian Dynamics (MOND) accelera- tion at two data sets, low-z (3.2 × 10⁻⁴ ≤ z ≤ 3.2 × 10⁻²) and high-z (0.5 ≤ z ≤ 2.5). They claim “both samples show a dependency of a₀ from z”. Here, the work men- tioned above is revisited. The explicit analytic expression for the z-dependence of the a0 within the SIV theory is given. Furthermore, the first estimates of the Ω_m within SIV theory give Ω_m = 0.28 ± 0.04 using the low-z data only, while a value of Ω_m = 0.055 is obtained using both data sets. This much lower Ωm leaves no room for non-baryonic matter! Unlike in the mentioned paper above, the slope in the z- dependence of A₀ = log10(a₀) is estimated to be consistent with zero Z-slope for the two data sets. Finally, the statistics of the data are consistent with the SIV predic- tions; in particular, the possibility of change in the sign of the slopes for the two data sets is explainable within the SIV paradigm; however, the uncertainty in the data is too big for the clear demonstration of a z-dependence yet.

This study presents a detailed investigation of the application of superquadrics in small-angle scattering (SAS), a technique essential in materials science, biology, and physics for investigating structural properties at the nanoscale and microscale. Superquadrics, a family of geometric shapes known for their versatility in representing a wide range of forms, are employed to model complex structures in SAS studies. We examine the parametric nature of superquadrics and their ability to efficiently describe shapes from simple balls to intricate star-like forms. We demonstrate the application of superquadrics through a rigorous analysis of SAS simulated data, including scattering intensity patterns and pair-distance distribution functions. This allows us to reveal insights into key structural characteristics of various materials, such as the size and shape. We also demonstrate the efficacy of superquadrics in accurately modeling experimental small-angle X-ray scattering data from a chimeric protein complex, showcasing their potential in biological systems analysis. The findings offer a robust framework for future research and application in diverse fields, including materials science, nanotechnology, and bioengineering.

The electronic structure of 7/9-AGNR superlattices with up to eight unit cells has been studied by means of state of the art Density Functional Theory (DFT) and also by two model Hamiltonians, the first one including only local interactions (Hubbard model, Hu) while the second one is extended to allow long-range Coulomb interactions (Pariser, Parr and Pople model, PPP). Both are solved within mean field approximation. At this approximation level, our calculations show that 7/9 interfaces are better described by spin non-polarized solutions than by spin-polarized wavefunctions. Consequently, both Hu and PPP Hamiltonians lead to electronic structures characterized by a gap at the Fermi level that diminishes as the size of the system increases. DFT results show similar trends although a detailed analysis of the density of states around the Fermi level shows quantitative differences with both Hu and PPP models. Before improving model Hamiltonians, we interpret the electronic structure obtained by DFT in terms of bands of topological states: topological states localized at the system edges and extended bulk topological states which interact between them due to the long-range Coulomb terms of Hamiltonian. After careful analysis of the interaction among topological sates, we find that the discrepancy between ab initio and model Hamiltonians can be resolved considering a screened long-range interaction that is implemented adding an exponential cutoff to the interaction term of PPP model. In this way, an adjusted cutoff distance λ = 2 allows a good recovery of DFT results. In view of this, we conclude that the correct description of the density of states around the Fermi level (Dirac point) needs the inclusion of long-range interactions well beyond Hubbard model but not completely unscreened as is the case for the PPP model.

The demand for polymer composites with improved mechanical and electrical properties is crucial for advanced aerospace, electronics, and energy storage applications. Single-walled carbon nanotubes (SWCNTs) and iron oxide (Fe₃O₄) nanoparticles are key fillers that enhance these properties, yet challenges like orientation, uniform dispersion, and agglomeration must be addressed to realize their full potential. This study focuses on developing SWCNTs/Fe₃O₄ epoxy composites by keeping the SWCNT concentration constant at 0.03 Vol.% and varying Fe₃O₄ concentrations at 0.1, 0.5, and 1 Vol.% with two different configurations: randomly orientated (R-) and magnetic field-assisted horizontally aligned (A-) SWCNTs/Fe3O4 epoxy composites and investigates the effects of filler concentration, dispersion, and magnetic alignment on the mechanical and electrical properties. The research reveals that both composite configurations achieve an optimal mechanical performance at 0.5 Vol.% Fe₃O₄, while A- SWCNTs/Fe3O4 epoxy composites outperformed at all concentrations. However, at 1 Vol.% Fe₃O₄, mechanical properties decline due to nanoparticle agglomeration, which disrupts stress distribution. In contrast, electrical conductivity peaks at 1 Vol.% Fe₃O₄, indicating that the higher density of Fe₃O₄ nanoparticles enhances the conductive network despite the mechanical losses. This study highlights the need for precise control over filler content and alignment to optimize mechanical strength and electrical conductivity in SWCNTs/Fe₃O₄ epoxy nanocomposites.

Dendritic cell (DC) cancer vaccines are a promising therapeutic approach, leveraging the immune system to fight tumors. These vaccines utilize DCs' ability to present tumor-associated antigens to T cells, triggering a robust immune response. DC vaccine development has progressed through three generations. The first generation involved priming DCs with tumor-associated antigens or messenger RNA outside the body, showing limited clinical success. The second generation improved efficacy by using cytokine mixtures and specialized DC subsets to enhance immunogenicity. The third generation uses blood-derived DCs to elicit a stronger immune response. Clinical trials indicate that cancer vaccines have lower toxicity than traditional cytotoxic treatments. However, achieving significant clinical responses with DC immunotherapy remains challenging. Combining DC vaccines with immune checkpoint inhibitors (ICIs) such as anti-cytotoxic T-lymphocyte Antigen 4 and anti-programmed Death-1 antibodies has shown promise by enhancing T cell responses and improving clinical outcomes. These combinations can transform non-inflamed tumors into inflamed ones, boosting ICIs' efficacy. Current research is exploring new checkpoint targets like LAG-3, TIM-3, and TIGIT, considering their potential with DC vaccines. Additionally, engineering T cells with chimeric antigen receptors or T cell receptors could further augment the anti-tumor response. This comprehensive strategy aims to enhance cancer immunotherapy, focusing on increased efficacy and improved patient survival rates.

Two experiments were conducted to develop a Nano green manganese and assess its effect on grapevines. The first experiment was microbiological, where several incorporation strategies were utilized to enrich the yeast with manganese, as follows: (1) adding manganese to the liquid medium (growth phase), (2) adding after 24 h of incubation (non-growth phase). As the results, growth phase reduced the possibility of medium contamination. Manganese concentration in the yeast cells was increased as that of manganese sulphate in the medium. Manganese incorporation in yeast cells was 99.93% higher than that of the medium at 0.0195 g/l of manganese. Although the concentration of manganese in the medium raised the OD of yeast cell biomass, manganese sulphate had no passive influence on it. The second experiment was horticultural, done on Flame Seedless grapevines, since both active fresh and frozen yeast enriched with manganese resulted from the first experiment were sprayed twice a year at 10 or 20 cm3/l comparing with manganese sulphate, and manganese chelate. The results demonstrated that yeast extracts in both forms increased the yield and improved fruit properties. The most effective treatment on vegetative growth, yield and fruit properties was the frozen yeast enriched with manganese at 20 cm3/l.

The occurrence of ovarian dysfunction is often due to the imbalance between the formation of reactive oxygen species (ROS) and the (in)effectiveness of the antioxidative defense mechanisms. Primary sources of ROS are the respiratory electron transfer and the activity of NADPH oxidases (NOX), while Superoxide dismutases (SOD) are the main key reg-ulators that control the levels of ROS and reactive nitrogen species intra- and extracel-lularly. Because of their central role, SODs are the subject of research on human ovarian dysfunction, but the sample acquisition is low. The high degree of cellular and molecular similarity between Drosophila melanogaster ovaries and human ovaries provides this model organism with the best conditions for analyzing the role of ROS during ovarian function. In this study, we clarify the localization of the ROS producing enzyme dNox within ovaries of Drosophila melanogaster and by a tissue specific knockdown, we show that dNox derived ROS are involved in the chorion hardening process. Furthermore, we analyze the dSod3 localization and show that reduced activity of dSod3 impacts egg laying behavior, but not the chorion hardening process.

The corrosion behavior of the TiTaNbZrAg alloys with different amounts of Tantalum (0 %, 10 % and 20%) and with distinct surface topography (smooth and rough) was investigated in phosphate buffer solution (PBS) for long-time immersion (1000 hours). The corrosion resistance was studied by Open circuit potential (OCP), potentiodynamic polarization (PP) and electrochemical impedance spectroscopy (EIS). From the potentiodynamic investigations, it was observed that all types of samples show good corrosion resistance (i.e. Rcorr < 10µm y-1) and may be used successfully for medical applications. However, the samples with smooth surface and with a certain amount of Ta (10 % and 20%) exhibit the best corrosion performance (Rcorr < 1µm y-1). As regard the samples with rough surface, the results evidenced that they show lower corrosion resistance (1< Rcorr < 3 µm y-1), suggesting that the Ta presence not necessary brings about a very good corrosion protection. Actually, the synergetic effect of both the presence of Ta and surface roughness plays an important role in corrosion behavior. Based on literature reports, we assume that the good corrosion resistance results from the good stability of the film, formed mainly from Ta2O5 and TiO2, formed on the alloy surface during immersion in PBS.

The Source Region of the Yellow River (SRYR), renowned as the "Water Tower of the Yellow River", serves as an important water conservation domain in the upper reaches of the Yellow River, significantly influencing water resources within the basin. Based on the Weather Research and Forecasting (WRF) Model Hydrological modeling system (WRF-Hydro) model, the key variables of the atmosphere-land-hydrology coupling processes over the SRYR during the 2013 rainy season are analyzed. The investigation involves a comparative analysis between the coupled WRF-Hydro and the standalone WRF simulations, focusing on the hydrological response to the atmosphere. The results reveal that the WRF-Hydro model's proficiency in depicting streamflow variations over the SRYR, yielding a Nash Efficiency Coefficient (NSE) of 0.44 and of  0.61 during the calibration and validation periods, respectively. Compared to the standalone WRF simulations, the coupled WRF-Hydro model demonstrates enhanced performance in soil heat fluxes simulations, reducing the mean Root Mean Square Error (RMSE) of surface soil temperature by 0.96 K and soil moisture by 0.01 m\textsuperscript{\textsuperscript{3}}/m\textsuperscript{\textsuperscript{3}}. Furthermore, the coupled model adeptly captures the streamflow variation characteristics with the NSE of 0.33. This underscores the significant potential of the coupled WRF-Hydro model for delineating coupled atmosphere-land-hydrology processes in regions characterized by cold climates and intricate topography.

Pakistan flora is enriched with potent bioactive compounds that must be explored while Alzheimer's disease (AD) poses a global challenge driven by neurochemical imbalances. Acetylcholinesterase (AChE) inhibitors traditionally alleviate symptoms, but addressing the root cause remains elusive. This gap has led to the exploration of herbal sources for interventions. In this context, we analyzed fifty 50 medicinal plants for their phytochemical composition and antioxidant and acetylcholinesterase inhibition activities. AChE activity was measured using Ellman’s method. Santalum album exhibited significant AChE inhibition (86.2%), surpassing galantamine hydrobromide (81.8%). Promising inhibition was also seen in Bombax ceiba (77.8%), Acacia karoo (52.9%), and Phaseolus lunatus (50.1%). Detailed analysis revealed Santalum album's abundance in terpenoids, flavonoids, tannins, and phenolics, potentially correlating with its antioxidant and AChE inhibitory effects. Acacia karoo demonstrated elevated levels of total alkaloids, antioxidants, terpenoids, and tannins. Both Acacia karoo and Santalum album show promise for AD intervention due to their AChE inhibitory activities and unique phytochemical attributes, warranting further exploration, particularly for Acacia karoo's novel potential in AChE inhibition, to advance targeted AD therapeutics utilizing natural resources. This study contributes to the search for effective AD strategies from nature's pharmacological resources.

Pediatric onset multiple sclerosis (POMS), characterized by the onset of multiple sclerosis before the age of 18, is gaining increased recognition. Approximately 5 percent of MS cases manifest before the age of 18, with less than 1 percent occurring before the age of 10. Despite its rarity, pediatric MS exhibits distinct characteristics, with an association between younger age at onset and a comparatively slower disease progression. Despite this slower progression, individuals with POMS historically reach disability milestones at earlier ages than those with adult-onset multiple sclerosis. While various immunomodulatory agents demonstrate significant benefits in MS treatment, such as reduced relapse rates and slower accumulation of brain lesions on magnetic resonance imaging (MRI), the majority of disease-modifying therapies (DMTs) commonly used in adult MS lack evaluation through pediatric clinical trials. Current evidence is predominantly derived from observational studies. This comprehensive review aims to consolidate existing knowledge on the mechanisms of action, efficacy, safety profiles, and recommended dosages of available DMTs specifically in the context of pediatric MS. Furthermore, the review outlines recent advancements and explores potential medications still in developmental stages, providing a thorough overview of the current landscape and future prospects for treating POMS.

Elastic properties of materials and their changes with temperature are important for their applications in engineering. A study on the influence of phase composition of AISI 4130 alloy on Young's modulus (Ed), shear modulus (Gd), and damping (Q-1) was carried out by Impulse Excitation Technique (IET). The material characterization was carried out using confocal microscopy, XRD, MET, HV, and dilatometry. A stable structure, composed of ferrite (BCC) and pearlite (α-Fe+Fe3C), was obtained by annealing. Metastable structure of martensite (BCT) was obtained by quenching. The Ed, Gd, and Q-1 were measured, varying the temperature from RT to 900 °C. The values of Ed and Gd, at RT, were determined as 201.5 and 79.2 GPa (annealed), and 190.13 and 76.5 GPa (quenched), respectively. In the annealed steel, the values Ed and Gd decrease linearly on heating up to 650 °C, with the thermal expansion. In the quenched steel, weak changes in the dilatometric curve, Ed, Gd, and Q-1, in the range of 350-450 °C, indicated decompositions of the martensitic phase. Sharp decrease in the moduli and high peak of Q-1, was observed for both samples around 650-900 °C, revealing low lattice elastic stability of the phases during transformations α(BCC)+Fe3C↔γ(FCC).

The article presents a non-destructive test system based on electrical impedance tomography for monitoring flood embankments. The technology of cyber-physical systems and the Internet of Things with the use of electrical impedance tomography enables real-time monitoring of flood embankments. This solution provides a visual analysis of damage and leaks, which allows for quick and effective intervention and possible prevention of danger. A dedicated solution based on the IT structure, dedicated laboratory models and a dedicated measurement system with various types of sensors and machine learning algorithms for image reconstruction has been developed. The system includes specialized intelligent devices for tomographic measurements. The application contains the analysis of anomalies occurring in the structure of the object as a result of damage or danger and breaking the shaft during the flood. The presented solution enables ongoing monitoring of objects by collecting measurement results, forecasts and simulations. The main advantage of the proposed system is the spatial ability to analyse shafts, high accuracy of imaging and high speed of data processing. The use of tomographic techniques in conjunction with image reconstruction algorithms allow for non-invasive and very accurate spatial assessment of humidity and damages of flood embankments. The presented results show the effectiveness of the presented research.

Abstract: The morphological characteristics of the tongue of the Rahmani sheep (Ovis aries) were described using gross inspection, morphometry analysis, and scanning electron microscopy. Nine mature male sheep heads were slaughtered, and samples were taken right away. The tongue was dissected, and various samples were obtained for SEM. The tongue had two different types of lingual papillae: mechanical (filiform, conical, and lenticular papillae) and gustatory (fungiform and vallate papillae). The main papillae and several secondary and tertiary papillae combine to produce each filiform papilla. On the dorsal surface of the tongue, there were five different types of conical papillae dispersed throughout, as well as three huge conical papillae and various-sized flattening papillae in front of the frenulum linguae. Furthermore, on the torus linguae, two different types of lenticular papillae were found. The majority of fungiform papillae possessed prominent taste buds' pores and were button-shaped with a central depression region, particularly in the rostral section of the tongue. On either side of the torus linguae, there are two rows of round, elliptical, pyramidal, and oval circumvallate papillae. Each papilla is surrounded by flat, broad, undulating annular rods and papillary grooves. The lingual surface also included numerous lin-gual gland openings in a variety of forms, which increased in number at the root. Finally, variations in the form, size, and number of lingual papillae, as well as the distribution of lingual gland openings along the lingual surface, may provide efficiency to the Rahmani sheep's tongue when feeding hard forages and high fiber foods.

Pet nutrition awareness has risen enormously, with an increasing interest in homemade diets aimed at controlling food composition. Literature in this field is scarce, especially regarding the homemade diet’s long-term effects on pathological conditions. This prospective study encompassed 167 healthy and sick dogs subjected to a customized dietary plan based on homemade food. After an initial visit, dog owners provided questionnaires with follow-up data on their perceptions of physical signs changes or symptom modifications. 104 (62%) subjects maintained the homemade diet, while 63 reverted to their previous diet. The median follow-up was 14 months. Out of 31 healthy dogs that continued the nutritional plan, 70% exhibited improvements in their coat condition and 47% a decrease in evacuation frequency. Regarding weight loss goals, 67% of dogs achieved their target. The 67 pathological dogs that completed the follow-up were primarily affected by gastrointestinal and dermatological disorders. Dogs with chronic enteropathy improved their symptoms in 95% of the cases, subjects with dermatological pathologies in 83%, and patients presenting both disorders in 100%. These clinical results are promising. Personalized and well-balanced homemade diets noticeably enhanced the overall pet’s health, with almost a complete remission of symptoms in pathological dogs.

This study, based on proactive motivation theory, explores the relationship between perceived overqualification, digital leadership, and constructive deviant behavior, as well as generational differences. Using data collected in two waves from 596 employees, the results show that perceived overqualification positively influences constructive deviant behavior, and digital leadership enhances this effect. Employees born in the 1980s are most influenced by both factors, followed by those born in the 1990s, where the effect of digital leadership is less significant. The study suggests that effectively utilizing digital leadership and recognizing generational differences in perceived overqualification can help organizations better manage overqualified talent, improving employee satisfaction and productivity.

The pH dependence of the free energy level of the flash induced primary charge pair P+IA– was determined by combination of the results from indirect charge recombination of P+QA– and from delayed fluorescence of the excited dimer (P*) in reaction center of photosynthetic bacterium Rhodobacter sphaeroides where the native ubiquinone at the primary quinone binding site QA was replaced by low potential anthraquinone derivatives. The following observations were made: 1) The free energy state of P+IA– was pH independent below pH 10 (–370 ± 10 meV relative to that of the excited dimer P*) and showed remarkable decrease (about 20 meV/pH unit) above pH 10. A not insignificant part of the dielectric relaxation of the P+IA– charge pair (about 120 meV) should come from protonation related changes. 2) The single exponential decay character of the kinetics proves that the protonated/unprotonated P+IA– and P+QA– states are in equilibria and the rate constants of protonation konH +koffH is much larger than that of the charge back reaction kback ~103 s-1. 3) Highly similar pH profiles were measured for the free energy states of P+QA– and P+IA–, indicating that the same acidic cluster around QB should response to both anionic species. This was supported by model calculations based on anticooperative proton distribution in the cluster with key residues of GluL212, AspL213, AspM17 and GluH173 and on effect of polarization of the aqueous phase on the electrostatic interaction. The larger distance of IA– from the cluster (25.2 Å) than that of QA‒ (14.5 Å) is compensated by smaller effective dielectric constant (6.5 ± 0.5 and 10.0 ± 0.5, respectively). 4) The P* → P+QA− and IA‒QA → IAQA− electron transfers are enthalpy driven reactions with exemption of very large (>60%) or negligible entropic contributions in cases of substitution by 2,3-dimethyl-AQ or 1-chloro-AQ, respectively. The possible structural consequences are discussed.

In an era where the proliferation of large language models blurs the lines between human and machine-generated content, discerning text authenticity is paramount. This study investigates transformer-based language models—BERT, RoBERTa, and DistilBERT—in distinguishing human-written from machine-generated text. By leveraging a comprehensive corpus, including human-written text from sources such as Wikipedia, WikiHow, various news articles in different languages, and texts generated by OpenAI's GPT-2, we conduct rigorous comparative experiments. Our findings highlight the superior effectiveness of ensemble learning models over single classifiers in this critical task. This research underscores the versatility and efficacy of transformer-based methodologies for a wide range of natural language processing applications, significantly advancing text authenticity detection systems. The results demonstrate competitive performance, with the transformer-based method achieving an F-score score of 0.83 with RoBERTa-large (monolingual) and 0.70 with DistilBERT-base-uncased (multilingual).

Digital recruitment systems have revolutionized the hiring paradigm, imparting exceptional efficiencies and extending the reach for both employers and job seekers. This investigation scrutinizes the efficacy of classical machine learning methodologies alongside advanced large language models (LLMs) in aligning resumes with job categories. Traditional matching techniques, such as Logistic Regression, Decision Trees, Naïve Bayes, and Support Vector Machines, are constrained by the necessity of manual feature extraction, limited feature representation, and performance degradation, particularly as dataset size escalates, rendering them less suitable for large-scale applications. Conversely, LLMs like GPT-4, GPT-3, and LLAMA, adeptly process unstructured textual content, capturing nuanced language and context with greater precision. We evaluate these methodologies utilizing two datasets comprising resumes and job descriptions to ascertain accuracy, efficiency, and scalability. Our results reveal that while conventional models excel with structured data, LLMs significantly enhance the interpretation and matching of intricate textual information. This study highlights the transformative potential of LLMs in recruitment, offering insights into their application and future research avenues.

The 3 31 nucleotide minihelix tRNA theorem describes evolution of type I and type II tRNAs to the last nucleotide. In databases, type I and type II tRNA V loops (V for variable) were improperly aligned, but alignment based on the theorem is accurate. Type II tRNA V arms were a 3’-acceptor stem (initially CCGCCGC) ligated to a 5’-acceptor stem (initially GCGGCGG). The type II V arm evolved to form a stem-loop-stem. In Archaea, tRNALeu and tRNASer are type II. In Bacteria, tRNALeu, tRNASer and tRNATyr are type II. The positioning of the type II V arm is determined by the number of unpaired bases just 5’ of the Levitt base (Vmax). For Archaea, tRNALeu has 2 unpaired bases, and tRNASer has 1 unpaired base. For Bacteria, tRNATyr has 2 unpaired bases, tRNALeu has 1 unpaired base and tRNASer has 0 unpaired bases. Thus, the number of type II tRNAs is limited by the possible set points of the arm. From analysis of aminoacyl-tRNA synthetase structures, contacts to type II V arms appear to adjust allosteric tension communicated primarily via tRNA to aminoacylating and editing active sites. To enhance allostery, it appears that type II V arm end loop contacts may tend to evolve to V arm stem contacts.

Integrated crop-livestock production (ILP) is an interesting alternative for more sustainable soil use. However, more studies are needed to analyze soil pore properties under ILP at the micrometer scale. Thus, this study proposes a detailed analysis of soil pore architecture at the micrometer scale in three dimensions. For this purpose, samples of an Oxisol under ILP subjected to minimum tillage (MT) and no-tillage (NT) with ryegrass as cover crop (C) and silage (S) were investigated. The soil micromorphological properties of the soil were analyzed using X-ray microtomography. The MT(C) system showed the highest values of porosity (c. 20.4%), connectivity (c. 32.8×103), volume (c. 26%), and number of pores (c. 32%) in a rod-like shape. On the other hand, the MT(S), NT(C), and NT(S) systems showed higher tortuosities (c. 2.2, c. 2.0, and c. 2.1) and lower pore connectivities (c. 8.3×103, c. 6.9×103, and c. 6.2×103), especially in S use. Ellipsoidal and rod-shaped pores predominated over spheroidal and disc-shaped pores in all treatments. The results of this study show that the use of ryegrass as a cover crop improves soil physical properties, especially in MT. For S use, the type of soil management (MT or NT) did not show any differences.

Perceived peer support is a critical factor in the academic adjustment of higher vocational college students. While previous studies have explored this relationship, few studies have delved into the underlying mechanisms. This study surveyed 9782 students from 35 higher vocational colleges in 13 provinces and cities in China to explore the relationship and mechanisms between perceived peer support and academic adjustment. Drawing on Conservation of Resources theory and Social Support Resource theory, the findings revealed that perceived peer support not only directly predicted the academic adjustment of higher vocational college students, but also indirectly through the independent mediating effect of academic hope and professional identity, as well as the chain-mediating effect of academic hope to professional identity. Additionally, students from vocational high schools showed a more significant increase in academic hope due to perceived peer support compared to those from general high schools, highlighting the moderating effect of educational background. The study provided a new theoretical perspective for understanding the complex mechanisms of academic adjustment in students and offers valuable guidance for educational practice, emphasizing the importance of fostering perceived peer support, academic hope, and professional identity in higher vocational education.

Due to the continued deepening of today’s mining projects, there is a need to develop new or improved rockbolts that are strong and yielding and have high energy absorption when exposed to dynamic loading. Impact tests can provide useful information about the dynamic response of rockbolts but most laboratory tests involve high costs in preparation and result validation. Numerical modeling is an alternative that, in addition to complementing laboratory results, can be used to represent the process of deformation and energy absorption of support elements. In this paper the implementation and results obtained from a finite difference (FDM) numerical model are presented. The model functions as a simulation tool to illuminate all the elements that conform the large-scale (1:1) impact test and their behavior and influence on the dynamic response of a threadbar bolt (22 mm nominal diameter). The model was calibrated using published results and based on these results as well as parametric analysis, the response of each component (steel tube, grout, and bolt) could be identified and its behavior in terms of absorbed energy and displacement could be observed. Results show the model can provide important preliminary information to make design decisions about support elements design.

Partially state-owned firms are common in both developed and developing countries and contribute around 10% of the world's GDP. This has led to a rich literature exploring various aspects of competition between such “mixed”-ownership firms. This paper contributes to the existing literature by studying the effects of mixed ownership on the intensity of competition in oligopoly markets. Our findings indicate that state ownership exerts an anti-competitive influence, with a higher state ownership share resulting in less aggressive behavior by firms in the product market. This result implies that industries with a higher proportion of state ownership yield lower total surplus. Further, when considering factors such as taxes, soft budget constraints, and weak property rights, the anti-competitive effects of state ownership are accentuated.

A novel Gram-stain-negative, facultatively anaerobic and mixotrophic bacterium, designated as strain LZ166T, was isolated from the bathyplagic seawater in the western Pacific Ocean. Cells were short rod-shaped, oxidase- and catalase- positive, and motile by means of lateral flagella. Growth of strain LZ166T was observed at 10-45 ℃ (optimum, 34-37 ℃), at pH 5-10 (optimum, 6-8) and in the presence of 0-5% NaCl (optimum, 1-3%). Phylogenetic analysis based on the 16S rRNA gene showed that strain LZ166T shared the highest similarity (98.58%) with Aquibium oceanicum B7T, and formed a distinct branch within the Aquibium genus. Genomic characterization, including average nucleotide identity (ANI, 90.73-76.79%), average amino identity (AAI, 88.50-79.03%) and digital DNA-DNA hybridization (dDDH, 36.1-22.2%) values between LZ166T and other species within the Aquibium genus, further substantiated its novelty. The genome of strain LZ166T was 6,119,659 bp in size with a 64.7 mol% DNA G+C content. The predominant fatty acid was summed feature 8 (C18:1ω7c and/or C18:1ω6c). The major polar lipids identified were Diphosphatidylglycerol (DPG), phosphatidylethanolamine (PE), glycolipid (GL) and phosphatidylglycerol (PG), with ubiquinone-10 (Q-10) as the predominant respiratory quinone. Genomic annotation indicated the presence of genes for a diverse metabolic profile, including pathways for carbon fixation via the Calvin–Benson–Bassham cycle and inorganic sulfur oxidation. Based on polyphasic taxonomic results, strain LZ166T represented a novel species of the genus Aquibium, for which the name Aquibium pacificus sp. nov., is proposed, with the type strain LZ166T (= MCCC M28807T = KACC 23148T = KCTC 82889T).

The prevalence of food allergy has increased over the last decades and consequently the food labeling policies have improved over the time in different countries to regulate allergen presence in foods. In particular, Reg 1169 in EU mandates the labelling of 14 allergens whenever intentionally added to foods, but the inadvertent contamination by allergens still remains uncovered topic. In order to warn consumers on the risk of cross-contamination occurring in certain categories of foods, a precautionary allergen labelling system has been put in place by food industries on voluntary basis. In order to reduce the overuse of PAL, reference doses and action limits have been proposed by the VITAL project representing a guide in this jeopardize scenario. Development of sensitive and reliable mass spectrometry methods are therefore of paramount importance in this regard to check the contamination levels in foods. In this paper we describe the development of a managed time MRM method based on a triple quadrupole platform for milk and egg quantification in processed food. The method was in house validated and allowed to achieve levels of proteins lower than 0.2mg of total milk and egg proteins respectively in cookies, challenging the doses recommended by VITAL. The method was finally applied to cookies labeled as milk and egg-free. This method could represent in perspective a promising tool to be implemented along the food chain to detect even tiny amounts of allergens contaminating food commodities.

The conservation of the main protease in viral genomes, combined with the absence of a homologous protease in humans, makes this enzyme family an ideal target for developing broad-spectrum antiviral drugs with minimal host toxicity. GC-376, a peptidomimetic 3CL protease inhibitor, has shown significant efficacy against coronaviruses. Recently, a GC-376-based PROTAC was developed to target and induce the proteosome-mediated degradation of the dimeric SARS-CoV-2 3CLPro protein. Extending this approach, the current study investigates the application of the GC-376 PROTAC to the 3CPro protease of Enteroviruses, specifically characterizing its interaction with CVB3 3CPro through X-ray crystallography, NMR and biophysical techniques. The present structural data show that there are some changes between the binding of CVB3 3CPro and SARS-CoV-2 3CLPro, but the overall similarity is strong. The most notable variation is the orientation of the phenylmethyl ester of GC-376 with the S4 subsite of the proteases. This is linked to the flexibility of the protein structure around the region of the catalytic triad shown by our NMR data. Other structural variations include distinct ligand interactions in subsites S1 and S2, influenced by the presence of Glu71 in CVB3 3CPro. Despite these differences, the GC-376 PROTAC fits well within the binding sites of both proteases, demonstrating its potential as a broad-spectrum antiviral agent.

The objective of this study was to apply simulation and computational intelligence techniques using artificial intelligence and genetic algorithm for economic and environmental optimization of the reverse network (manufacturers, waste managers and recyclers in São Paulo, Brazil) of waste electrical and electronic equipment (WEEE) to promote circular economy. For the economic evaluation, the reduction of: fuel, drivers, insurance, depreciation, maintenance and charges was considered and for the environmental evaluation, the environmental impact was measured in the abiotic, biotic, water, land, air and greenhouse gases compartments. It is concluded that the optimized structure of the WEEE reverse chain for São Paulo, Brazil reduced the number of collections, making the most of the cubage. It also generated economic and environmental gains, contributing to the strategic actions of the circular economy. Thus, the proposed simulation allows replication in organizational practice, mainly to meet the 2030 agenda on reducing the carbon footprint generated in transport in large cities. Thus, this study can guide companies on structuring the reverse WEEE chain in São Paulo, Brazil for economic and environmental optimization, a relevant aspect considering the exponential generation of WEEE, requiring the implementation of the national solid waste policy, and subsequently the signature of the electronics sector agreement in São Paulo.

This study aims at providing a climatological analysis of annual and long-term variability of dry periods in the Polish Carpathians in the period of 35 years between 1986 and 2020. Aside days with precipitation, dry periods, namely sequences of days with no precipitation, constitute an inherent characteristic of the climate. The input data for the research was formed by daily precipitation totals from 17 meteorological stations acquired from the Institute of Meteorology and Water Management - National Research Institute, and T. Niedźwiedź catalogue of circulation types over southern Poland. Frequency of dry periods of different duration has been presented. The incidence of long-term periods has been related to the atmospheric circulation. An analysis was performed regarding the change of the average quantity and average length of dry sequences in the 35-year period covered. At most stations, there were no statistically significant trends with respect to the analysed dry day characteristics. This is an obvious result of high variability year-to-year, which means that exclusively large changes may achieve statistical significance. Dry days have been evidenced to related to circulation types. A vast majority of dry days is related to anti-cyclonal systems, particularly the anti-cyclonal wedge (Ka) and western anti-cyclonal (Wa) situations.

In today's intricate media landscape, the resilience and relevance of public service media (PSM) depend on their capacity to align with the diverse and evolving expectations of the public. However, the audience perspective is often overlooked, resulting in a limited understanding of public expectations. This study employs a bottom-up approach that allows for a re-evaluation of the expectations from the audience's viewpoint. It investigates the public's expectations for PSM, drawing on data from 10 focus group discussions (with 60 participants) conducted in the Czech Republic. The findings indicate that expectations can be categorized into four primary dimensions: (1) the expected roles and functions of PSM; (2) the general characteristics of the PSM content (defining the desired nature of PSM content); (3) the principles governing the functioning of PSM (outlining how PSM should operate); and (4) specific requirements concerning PSM news and non-news content. In the latter dimension, objectivity emerged as one of the most critical expectations and a major source of dissatisfaction. While participants collectively value objectivity, they disagree on its definition. A deeper examination revealed that certain public expectations may be unattainable due to the simplistic view of objectivity held by some.

Three species of subfamily Cultrinae currently live in Korea, but Erythroculter erythropterus has been introduced into the Nakdonggang River and has taken over the habitat, reducing the habitat of Culter brevicauda. Only the endangered species C. brevicauda still lives in the Yeongsangang River, and it is necessary to be careful not to introduce E. erythropterus in the future. And Hemiculter eigenmanni is also found throughout the country. In order to effectively manage and conserve the species in its various habitats and against invasions, this study was initiated. The ultrastructure of the egg envelopes of three species of Cultrinae— E. erythropterus, C. brevicauda, and H. eigenmanni, inhabiting the Geumgang and Yeongsangang Rivers were observed. It was found that the zona radiata of the egg envelopes of all three species were divided into two layers–an outer and inner layer, with the outer surface having a non-structural form. This form is characteristic of fishes with muddy, stagnant habitats or spawning grounds. The number of pore canals on the surface of the egg envelopes was 83 for E. erythropterus, 75 for C. brevicauda, and 58 for H. eigenmanni per 10 ㎛2, and the thickness was 7.89±0.34 ㎛, 12.27±0.46 ㎛, and 7.42±0.24 ㎛, respectively. The shape of the micropyle demonstrated a funnel shape narrowing toward the inner diameter in all three species, and the size of the inner diameter was 6.62±0.29 (6.09~7.10) ㎛ in E. erythropterus, 4.19±0.39 (3.39~4.58) ㎛in C. brevicauda, and 3.98±0.46 (3.47~4.93) ㎛in H. eigenmanni. The differences between species were identified in the number of pore canals, thickness, and micropyle inner diameter of egg envelopes, which were species-specific. Our study revealed a morphological mechanism in the egg envelope that prevents the formation of interspecific hybrids, and these features can be taxonomic traits that clarify species names. It also provided useful data for the production (breeding) of the second generation in aquaculture.

It is concerning that Cameroon's urban centers are experiencing an alarming rise in air pollution as a result of urbanization, population growth, industrial activity, and transportation emissions. We examined the causes, health impacts, research methodology, case studies, and government measures to address the urgent issue of air pollution in Cameroon's urban regions. We have emphasized how Cameroon's air pollution levels have significantly increased as a result of causes like population expansion, urbanization, industrial emissions, and automobile exhaust A thorough discussion of the negative health impacts of extended exposure to air pollution is included, with special attention to the sensitivity of the old and young. These effects include respiratory disorders, cardiovascular ailments, and early mortality. We emphasized the pressing need for all-encompassing strategies to address air pollution, such as increased public awareness campaigns, stronger emissions regulations, the development of renewable energy sources, and better waste management. The techniques employed in studies on air pollution, like as epidemiological research and air quality monitoring, are also explained to provide light on the unique health dangers that Cameroonian urban dwellers must contend with. We emphasized in our conclusion the significance of joint efforts by legislators, medical professionals, and the general people to reduce air pollution and protect public health in Cameroon in order to create a cleaner and healthier future. In order to protect public health in the future, it is imperative that Cameroon's air pollution be addressed.

Local polynomial smoother (LPS) is a weighted local least-squares nonparametric method. It provides a local Taylor series fit of the data at any location and can be directly used in a differential equation to provide a numerical scheme. In this article, we introduce this new nonparametric idea based on local polynomial smoother, for acquiring the numerical solution of the Bagley-Torvik fractional-order differential equations. Furthermore, this paper will present a numerical comparison with some methods, such as legendre operational matrix and pseudo-spectral method. The efficiency and accuracy of the LPS method are demonstrated by two numerical examples.

At the beginning of any electric arc welding process, a regime called transient regime will always occur, characterized by the continuous variation of the energy flow, also resulting in the variation of the cooling rate of the welded joint. Consequently, the weld bead hardness varies from a maximum value to an approximately constant value, and this phenomenon can be represented by an asymptotic exponential function. For several welded specimens, it would be possible to fit a non-linear regression for each specimen, however, it would be a difficult task to combine different regressions in a single analysis. The objective of this study is to evaluate the applicability of mixed-effects models and artificial neural networks to predict the longitudinal hardness of the weld bead in the initial transient regime. To this end, linearized and nonlinear mixed-effects models and artificial neural networks with different architectures were fitted. Finally, valid models were obtained with all approaches, with artificial neural network model slightly better fitted. However, the explainability capacity of the linearized mixed-effects model was superior, showing that the relative thickness, one of the predictor variables, was responsible for 48% of the variation in longitudinal hardness of weld bead.

The aerospace industry has made extensive use of titanium alloy material due to its exceptional qualities, which include high strength, low weight, and resistance to corrosion. However, these qualities also pose challenges for the material's processing. This paper examines the Ti6Al4V milling endmills coating. First, an analysis is done on the solubility of Ti and Si elements. It is discovered that W and Co elements are far more soluble in Ti than Si and Zr elements, which can effectively stop element diffusion. Next, the base's composition was planned. It was discovered that when the amount of Al increased, the base's surface roughness increased while its hardness and elastic modulus decreased. The binding force between the substrate and the base was greater at 50: 50 Ti:Al ratio. TiSiN and TiSiN/ZrN functional layer properties are examined. When Zr is added to TiSiN/ZrN coating, it improves the coating's hardness and elastic modulus, increases density, and decreases surface roughness and friction coefficient when compared to TiSiN coating. Lastly, an analysis of the initial and intermediate tool wear was done using the Ti6Al4V milling experiment. It was discovered that adding Zr element could successfully extend the tool's cutting life by preventing adhesive wear.

The relationship between nations is largely seen as a peripheral issue in the recent history of political philosophy and in the majority of discussions of political philosophy issues today. The idea of a universal natural state were countries are seen as essentially self-sufficient, functional units, and have been proposed to represent the relative lack of moral standards guiding relationships between nations. At one extreme of the tradition, international thought has substituted raison d'état being the highest norm for any universal laws governing relations between states, a view embodied by Machiavelli, Rodin, and others and Hobbes , The lack of supranational political powers has led to the conclusion that, even in cases where the possibility of international moral relationships has been acknowledged, such as in post-Grotian publications on international law, these ties are significantly weaker than in-tranational social bonds. The justification and aversion to war—the primary mode of social in-teraction in the natural condition of the world—is the only issue in the field of global relations to have received substantial theoretical study. Even though this disregard was justified in the past, a number of recent events force us to re-consider the "recalcitrance of international affairs to being theorized about."2. The growing gap between both prosperous and impoverished nations; the emergence of centers of economic in-fluence beyond the reach of effective state regulation; the emergence of severe food and energy shortages brought on, at least in part, by national governments' pursuit of disorganized and uncontrolled growth policies; the growing sensitivity of domestic Countries to the outside eco-nomic, political, and cultural events are some of these developments , requests from third-world nations for greater equal access to international politics and economy. To put it in terms more familiar to conversations about this topic, the rise of "low politics" in negotiation and "welfare questions" within global forums corresponds with the growing influence of transnational con-nections and international agreements on human well-being. Not because "high politics"—that is, the threat and prevention of war—has lost significance; rather, it is just one issue among many for which international cooperation is now required in order to find answers.

Owing to the growing concerns due to dwindling fossil fuel reserves, increasing energy demand and climate emergency, it is imperative to develop and deploy sustainable energy technologies to ensure future energy supply as well as transition to the net zero world. In this context, there is great potential in the biorefinery concept for supplying drop in biofuels in the form of biodiesel. Biodiesel as a fuel can certainly bridge the gap where electrification or the use of hydrogen is not feasible, for instance heavy vehicles, farm and marine transportation sector. However, biodiesel industry also leads to formation of large amount of crude glycerol as the byproduct. Crude glycerol due to presence of several impurities may not be a suitable feedstock for all high value products derived from glycerol but fits well with glycerol esterification for producing glycerol acetins, which have numerous applications. This review critically looks at the processes using nanostructured solid/liquid acid catalysts for glycerol esterification including the economic viability of the scale up.

Open source software such as OpenDSS has given a lot of help to distribution network researchers and educators. With high penetration of distributed renewable energy resources into distribution network, tradition distribution steady state analysis software such as OpenDSS is faced with difficulty in handling distributed generators. Three-phase distributed generators are often modeled in sequence frame while unbalanced distribution network are usually modeled in phase frame. So a load flow in sequence-phase coupled frame is proposed to handle models described in both frames. Voltage controlled DGs which are difficult to cope with in OpenDSS are handled in proposed program. The steady state analysis platform is programmed with open source Modelica language and the main aim of this paper is to introduce an open source platform for active distribution network steady analysis include load flow and short circuit analysis which can be easily adopted and improved by other educators and researchers.

Mobile inspections conducted by intelligent tunnel robots are instrumental in broadening the inspection reach, economizing on inspection expenditures, and augmenting the operational efficiency of inspections. Despite differences from fixed surveillance, mobile-captured traffic videos have complex backgrounds and device conditions that interfere with accurate traffic event identification, warranting more research. This paper proposes an improved algorithm based on YOLOv9 and DeepSORT for intelligent event detection in edge computing mobile device using the intelligent tunnel robot. The enhancements comprise the integration of the Temporal Shift Module to boost temporal feature recognition and the establishment of logical rules for identifying diverse traffic incidents in mobile video imagery. Experimental results show that our fused algorithm achieves a 93.25% accuracy rate, an inprovement of 1.75% over the baseline. The algorithm is also applicable to inspection vehicles, drones, and autonomous vehicles, effectively enhancing the detection of traffic events and improving traffic safety.

Electric vehicles are in focus and growing, with new adoptions every day. Its wide use represents a new scenario and challenge for the electrical power system due to the high charge storage requirements. Predicting these loads using artificial neural networks proves to be a very efficient tool for solving time series. This work uses a multilayer perceptron network through supervised backpropagation training with Bayesian regularization to improve generalization, reducing overfit- ting errors. In this research, the aggregation of the actual consumption of 200 homes and 348 plug-in electric vehicles is used in the training and forecasting process, and to validate the method developed, MAPE was used. Short-term forecasts were made considering the year’s four seasons, predicting the next 24 hours of total aggregate demand from homes and vehicles. The methodology presented significant and relevant results using hybrid training for the problem, with the potential to be applied in the real world.

Provenance trials provide a valuable opportunity to evaluate the impact of extreme events on growth and wood properties. In this study, we have evaluated 81 Norway spruce provenances, tested in three provenance trials established in the Romanian Carpathians in 1972. The response to drought of the Norway spruce provenances – resistance, recovery, resilience, and relative resilience, has been examined, as well as the relationship between climate and growth, and the correlations between wood traits, the coordinates of origin and drought resilience indices. In each provenance trial, there were significant differences between provenances and years regarding wood widths and latewood percentage (LWP). Regarding the drought extreme events, the years when it occurred in all three provenance trials were 2000 and 2003. Significant differences between provenances for at least one drought resilience index have been found in all provenance trials, for the year 2000. By using subperiods of 25 years, changes in the relationship between climate and growth have been observed. Several provenances with high radial growth and good resistance and/or recovery have been identified. Provenances that performed better in common garden experiments could be used in assisted migration even beyond the current natural range.

Medium-Long term impacts of Antiretroviral drugs on arterial blood pressure in people living with HIV in Malawi.SAGNO Jean Bpatiste², Loenardo Palombi¹ , Giuseppe Liotta¹, Victor T Tolno², Sangare H Mamary², Jere Haswel ².1= University of Tor vergata Roma, 2= Dream Health center MalawiKey Words: HIV, hypertension ABSTRACTIntroduction: We aimed to explore the medium-long term impacts of Anti-Retroviral Treatment (ART) on Hypertension in a sample of HIV-positive in Malawi. Methodology: This was a retrospective case control study carried out at DREAM health Centre in Blantyre/Malawi on patients who were enrolled from 2005 to 2019, Information about age, gender, blood pressure, ART regimen, BMI, CD4 count, Viral load, Biochemistry, hemoglobin, marital status, education level, survival and period on ARVs were retrieved from data base from 01/01/2006 to 31/12/2015.. In total, we enrolled (alive and on HAART)1350 patients > 18 years (mean age: 43.4 and the SD was ±10.7 with 1031 (65.9%) females and 534 (34.1%) males who were taking (or have taken) ARVs for more than 6 months at the date of enrollment and who were not affected by hypertension or potentially related diseases like Renal failure at the enrollment. The mean observation time, from the HAART initiation was 77 months per person (SD±40). Results: The sample was made up by two groups of patients, 675 who developed hypertension and 675 who did not, with similar age and gender composition. Among patients with hypertension, 30/675 (4.4%) developed a stage 3 hypertension, 154 a stage 2 (22.8%) and 491 a stage 1 (72.8%). Hypertension stages were not associated to statistic significant differences of age and/or gender ( p=0.422, p=0.281 respectively). At baseline, patients who developed hypertension showed higher hemoglobin, higher CD4 count and lower VL ( P<0.001). Patients on AZT-based regimen and TDF based regimen were at high risk to develop hypertension while PI-based regimen was protective to hypertension (P<0.001). In a multivariate analysis, factors independently associated to Hypertension were higher CD4 count and Body Mass Index at the visit date, while Baseline Viral Load and PI-Including regimes were protective factors. Education level was inversely associated with risk of hypertension, while being married was associated of risk of hypertension (p<0.001). Mortality rate among hypertensive patients was 1.6% for those treated for hypertension against the 3.6% for those not treated. Conclusion: this study shows a protective action of PI-including regimens compared with AZT based regimen that is associated to an increased risk of hypertension. Factors related to a better general health status are associated to an higher risk of hypertension as well as lower education, older age and male gender. Treatment should be started as soon as Hypertension stages 2-3 are reached and control by behavioral factors is no longer effective.

Bloody stools in the newborn may be a clue for several clinical entities of varying severity ranging from a transient hematochezia to food protein induced allergic proctocolitis (FPIAP) or necrotizing enterocolitis (NEC). To distinguish among them at an early stage is challenging, but crucial, as the treatment and prognosis are different. We conducted a monocentric retrospective study including all preterm infants admitted to the NICU of the Vittore Buzzi Children’s Hospital (Milan) with bloody stools from December 2022 to May. Patients diagnosed with NEC exhibited a significantly lower eosinophil count and higher procalcitonin levels than both patients with CMPA and patients with transient hematochezia, as well as a statistically significant increase in pathological features at abdomen ultrasounds and abdominal X-rays. In contrast, no Lab markers or imaging have been demonstrated to be useful in distinguishing between transient hematochezia and FPIAIP. Thus, after excluding a diagnosis of NEC the only way to confirm the FPIAP is the oral food challenge, which can be performed even in premature newborns presenting blood stools, otherwise healthy, under medical supervision, in order to identify infants who may benefit from a cow’s milk free diet.

Eutrophication, a global concern, impacts water quality, ecosystems, and human health. It’s crucial to monitor algal blooms in freshwater reservoirs, as they indicate the trophic condition of a waterbody through Chlorophyll-a (Chla) concentration. Traditional monitoring methods, however, are expen-sive and time-consuming. Addressing this hindrance, we developed models using remotely sensed data from the Sentinel-2 satellite for large-scale coverage, including its bands and spectral indexes, to estimate the Chla concentration on 149 freshwater reservoirs in Ceará, Brazil. Several machine learning models were trained and tested, including k-nearest neighbours, random forests, extreme gradient boosting, the least absolute shrinkage, group method of data handling (GMDH), and sup-port vector machine models. A stepwise approach determined the best subset of input parameters. Using a 70/30 split for the training and testing datasets, the best-performing model was the GMDH, achieving an R2 of 0.91, MAPE of 102.34%, and RMSE of 20.38 g/L, which are values consistent with the ones found in the literature. Nevertheless, the predicted Chla concentration values were most sensitive to the red, green, and near infra-red bands.

Silybin is a natural compound extensively studied for its hepatoprotective, neuroprotective and anti-cancer properties. Envisioning the enhancement of silybin potential by suitable modifications in its chemical structure, here, a series of new 7-O alkyl silybins derivatives were synthesized by Mitsunobu reaction starting from the silybins and tyrosol-based phenols, such as tyrosol (TYR, 3), 3-methoxytyrosol (MTYR, 4) and 3-hydroxytyrosol (HTYR, 5). This research sought to explore the antioxidant and anticancer properties of new eighteen derivatives and their mechanisms. In particular, the antioxidant properties of new derivatives outlined by DPPH assay, showed a very pronounced activity depending on the tyrosyl moiety (HTYR&gt;MTYR&gt;&gt;TYR). A significant contribution of the HTYR moiety was observed for silybins and 2,3-dehydro-silybin based derivatives. According to the very potent antioxidant activity, 2,3-dehydro-silybin derivatives 15ab, 15a and 15b exerted the most potent anticancer activity in human prostate cancer PC-3 cells. Furthermore, flow cytometric analysis for cell cycle and apoptosis revealed that 15ab, 15a and 15b induce strong G1 phase arrest and increase late apoptotic population in PC-3 cells. Additionally, western blotting for apoptotic marker cleaved caspase-3 confirmed apoptosis induction by these silybin derivatives in PC-3 cells. These findings hold significant importance in the investigation of anticancer properties of silybin derivatives and strongly encourage swift investigation in pre-clinical models and clinical trials.

Background: The advantage of a robotic assisted (RARP) over a laparoscopic (LRP) approach in radical prostatectomy (RP) remains to be demonstrated. Aim of the study is to use a homogeneous population in real life and single surgeon surgery, to analyze the oncological and functional results based on the type of the surgical approach. Methods: This is a prospective trial on non-metastatic prostate cancers (PC) patients considered after multidisciplinary decision to RP, using RARP or LRP. A real-life setting was analyzed at our Urological Departments, using homogeneous criteria for the management of PC cases and a one surgeon experience on 444 cases (284 LRP and 160 RARP) .Results: Mean operative time was significantly lower in RARP (173.33±44.3 min) than in LRP (153.21±25.1 min) (p<0.001). In cases submitted to an extended lymph node dissection (eLND), the mean number of lymph nodes removed was 15.16±7.83 and 19.83±4.78 respectively in LRP and RARP procedures (p<0.001), but positive lymph nodes (pN1) were similarly found in 15.8% of LRP patients and 13.6% of RARP patients (p=0.430). Surgical margins (SM) positivity was not significantly higher in RARP group (20.0%) when compared to LRP group (15.9%) (p=0.145). During the postoperative follow-up, a biochemical recurrence (BCR) was detected in 14.4% and 7.5% of cases in the LRP and RARP group respectively (p=0.014). Better results of PAD test at 3-month interval using RARP approach (mean pad weight 75.57±122 grams and 14±42 grams respectively in LRP and RARP (p<0.01)) were described. Conclusions: In the comparison between RARP and LRP approach, a clear advantage of the robotic approach is a significant reduction in operating times, days of hospitalization and postoperative catheterization compared to laparoscopic surgery. It is not possible to describe any certain oncological advantage both in terms of surgical margins and pathological lymph nodes removed. In RARP cases a reduction to the limit of significance is described in terms of biochemical recurrence. RARP produces a more rapid recovery of urinary continence at 3 months postoperatively without significant advantages in terms of erective potency recovery.

COVID-19 was a terrible worldwide pandemic that caused a global public health crisis, with numerous deaths and a severe economic depression. To suppress the spread of COVID-19 and initiate patient isolation and contact tracing to reduce its effect, early diagnosis was required, with real-time reverse transcriptase polymerase chain reaction (RT-PCR) swab test being the most widely used. However, the RT-PCR test was sometimes found to be lengthy and inaccurate and; for that reason, in many cases of severe complications of COVID-19 pneumonia, chest screening with radiography imaging was preferred. In this paper, we carried out a study for COVID-19 detection from computed tomography images, and compared the obtained results using deep learning (DL) and support vector machine (SVM). The findings showed that, despite the excellent results shown by deep learning, the accuracy in predicting COVID-19 using SVM, in the presence of small databases, was slightly higher than DL. The execution time using SVM was also shorter

This study was to identify clinical cancer biomarkers for recurrent gastric cancer survivors using artificial intel-ligence. From a hospital-based cancer registry database in Taiwan, the datasets of the incidence of recurrence and clinical risk features were included in 2476 gastric cancer survivors. We benchmarked Random forest with MLP, C4.5, AdaBoost, and Bagging algorithms on metrics and leveraged synthetic minority oversampling technique (SMOTE) for imbalanced dataset issues, cost-sensitive learning for risk assessment, and SHapley Additive ex-Planations (SHAP) for feature importance analysis in this study. Our proposed Random forest outperformed the other models with an accuracy of 87.9%, a recall rate of 90.5%, an accuracy rate of 86% and F1 of 88.2% on re-current category by a 10-fold cross-validation in a balanced dataset. We identified clinical features of recurrent gastric cancer, which are the top five features, stage, number of regional lymph node involvement, Helicobacter pylori, BMI(body mass index), and gender, which significantly affect the prediction model's output, are worth paying attention to in the following causal effect analysis. Using an artificial intelligence model, the risk factors for recurrent gastric cancer could be identified and cost-effectively ranked according to their feature importance. In addition, they should be crucial clinical features to provide physicians with the knowledge to screen high-risk patients in gastric cancer survivors as well.

Ethanolic extracts of propolis collected from Apis mellifera hives have been shown to reduce Nosema ceranae infection in honey bee workers. This study aimed to determine the propolis concentration that optimizes the control of N. ceranae infection in honey bee workers. Newly emerged worker bees were individually fed 2 μL of 50% sucrose solution (w/v) containing 105 N. ceranae spores per bee, and treated with 0%, 25%, 50%, and 75% ethanolic extracted propolis in 50% sucrose solution (v/v). The treated bees were maintained in cages at 34 ± 2˚C and 55 ± 5% RH throughout the study. The number of dead bees was counted and removed from the cages daily for 30 days to generate survival curves. The number of N. ceranae spores per bee (infectivity) was quantified using a hemocytometer, and the number of infected bees per hundred bees (infection rate) was determined. The survival rates of N. ceranae infected bees fed 25%, 50%, and 75% propolis (NP1, NP2, NP3, respectively) were significantly higher than those of infected bees not fed propolis (NO). Furthermore, the infectivity and infection rates of NP2 and NP3 groups were significantly lower than those of the NO group. The infectivity and infection rates of the NP1 group were not different than those of the NO group. Our data suggest that 50% and 75% propolis extracts are appropriate concentrations for treating N. ceranae infection in honey bees. Ethanolic extracted propolis can be an alternative treatment for N. ceranae infection in Western honey bees.

Breast cancer is the most widespread malignancy in women from corner to corner of the world. Nanostructured lipid carrier (NLC) proved its efficacy in the treatment of cancer. NLC loaded with Imatinib (IMA) (NANIMA) was prepared and evaluated for in vitro efficacy in MCF-7 breast cancer cells. Hot homogenization method was used for the preparation of NANIMAs. Aqueous solution of surfactants (hot) was mixed with molten mixture of stearic acid and sesame oil (hot) under homogenization. The prepared NANIMAs were characterized and evaluated for size, polydispersity index, zeta potential, encapsulation efficiency, release studies, stability studies and MTT assay (cytotoxicity studies). The optimized NANIMA revealed particle size of 104.63 ± 9.55 d.nm, PdI of 0.227 ± 0.06 and EE of 99.79 ± 0.03. All NANIMAs revealed slow and sustained release behaviour. The surfactants used in the preparation of NANIMAs exhibited their effects on particle size, zeta potential, encapsulation efficiency, stability studies and release studies. The cytotoxicity studies unveiled 8.75 times increase in cytotoxicity for optimized NANIMA (IC50 = 6 µM) when compared with IMA alone (IC50 = 52.5 µM) on MCF-7 breast cancer cells. After this, NLC containing IMA possibly will be employed for the cure of breast cancer. A lesser amount of IMA loaded NLC will be sufficient than IMA alone for the treatment of breast cancer. Moreover, the patient will exhibit not as much of adverse effects as in case of IMA alone. Consequently, NANIMA could prove to be useful for effective therapeutic outcome in breast cancer treatment.

The management of carbapenem-resistant infections is often based on colistin, tigecycline, aminoglycosides and their combinations. However, in a recent systematic review we found that Gram-negative bacteria (GNB) co-resistant to carbapanems, aminoglycosides, colistin and tigecycline (CACT-resistant) are increasingly being reported worldwide. Clinical data to guide the treatment of CACT-resistant GNB are scarce and based exclusively on few case reports and small case series but seem to indicate that appropriate (in vitro active) antimicrobial regimens, including newer antibiotics and synergistic combinations, may be associated with lower mortality. In this review we consolidate the available literature to inform clinicians dealing with CACT-resistant GNB about treatment options by considering the mechanisms of resistance to carbapenems. In combination with rapid diagnostic methods that allow fast detection of carbapenemase production, the approach proposed in this review may guide a timely and targeted treatment of patients with infections by CACT-resistant GNB. Specifically, we focus on the three most problematic species, namely Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii. Several treatment options are currently available for CACT-resistant K. pneumonia. Newer β-lactam-β-lactamase combinations, including the combination of ceftazidime/avibactam with aztreonam against metallo-β-lactamase-producing isolates, appear to be more effective compared to combinations of older agents. Options for P. aeruginosa (especially metallo-β-lactamase-producing strains) and A. baumannii remain limited. Synergistic combination of older agents (e.g. colistin- or fosfomycin-based synergistic combinations) may represent a last resort option but their use against CACT-resistant GNB requires further study.

This study introduces the Data-Driven Personalized Learning Model (DDPLM), a sophisticated framework designed to enhance foreign language acquisition through the integration of big data analytics. Implemented within the educational platforms Edmodo and Duolingo, DDPLM utilizes real-time data processing to tailor learning paths and content dynamically to individual learner needs. Our findings indicate significant improvements in language learning efficiency, engagement, and retention. The model's adaptability across different digital environments showcases its potential scalability and effectiveness in various educational contexts. Additionally, the research addresses the critical role of personalized feedback and adaptive challenges in maintaining learner motivation and promoting deeper linguistic comprehension. The outcomes suggest that DDPLM significantly transforms traditional language education, making it more personalized, efficient, and aligned with individual learning preferences.

Polarimetric Synthetic Aperture Radar (PolSAR) images encompass valuable information that can facilitate extensive land cover interpretation and generate diverse output products. Extracting meaningful features from PolSAR data poses challenges distinct from those encountered in optical imagery. Deep Learning (DL) methods offer effective solutions for overcoming these challenges in PolSAR feature extraction. Convolutional Neural Networks (CNNs) play a crucial role in capturing PolSAR image characteristics by leveraging kernel capabilities to consider local information and the complex-valued nature of PolSAR data. In this study, a novel three-branch fusion of complex-valued CNN named Shallow to Deep Feature Fusion Network (SDF2Net) is proposed for PolSAR image classification. To validate the performance of the proposed method, classification results are compared against multiple state-of-the-art approaches using the Airborne Synthetic Aperture Radar (AIRSAR) datasets of Flevoland, San Francisco, and ESAR Oberpfaffenhofen dataset. The results indicate that the proposed approach demonstrates improvements in OA, with 1.3% and 0.8% enhancement for the AIRSAR datasets and 0.5% improvement for the ESAR dataset. The analyses conducted on the Flevoland data underscore the effectiveness of the SDF2Net model, revealing a promising OA of 96.01% even with only 1% sampling ratio.