Antiangiogenic therapy (AAT) is an indirect oncological modality which is aimed at disruption of cancer cells nutrient supply. Invasive tumors have been shown to possess inherent resistant to this treatment, while compactly growing benign tumors react to it by shrinkage. It is generally accepted that AAT by itself is not curative. This study presents a mathematical model of non-invasive tumor growth with physiologically justified account of alteration of microvasculature and biomechanical aspects during tumor growth and AAT. In untreated setting the model reproduces tumor growth with saturation, where the maximum tumor volume depends on the level of angiogenesis. The outcomes of simulations of AAT depend on the tumor size at the moment of treatment initiation. If it is close to the stable size of avascular tumor grown in absence of angiogenesis, then the tumor is rapidly stabilized by AAT. Treatment of large tumors is accompanied by displacement of normal tissue due to the tumor shrinkage. During it, microvasculature undergoes distortion which degree depends on the displacement distance. As it affects tumor nutrient supply, the stable size of a tumor that undergoes AAT negatively correlates with its size at the beginning of treatment. For sufficiently large initial tumors, the long-term survival of tumor cells is compromised by competition with normal cells for severely limited inflow of nutrients, which makes AAT effectively curative.

Heterogeneous systems of limited capacity have general applications in manufacturing, but also for logistic or service systems, due to the differences in server or workstation performance or work assignment, in close relationship with system flexibility, where saturation and blocking are ordinary situations of systems with high demand and limited capacity, so accurate loss quantification is essential for performance evaluation. Multi-class systems of limited capacity have been studied much less than parallel homogeneous systems (Erlang models). In this context, accurate models for parallel heterogeneous ordered-entry systems are developed: without any prior queue, M/Mi/c/c, and with a k capacity queue M/Mi/c/c+k. These new matrix models give an exact state formulation, and their accuracy is verified through discrete event simulation and comparison with literature results. Also, the effect of queue capacity is studied in relationship with the pattern of service rates. Next, the heterogeneous recirculating system model is also developed with good approximation results. Finally, the proposed models are applied to evaluate systems with non-exponential service times, through a new hybrid methodology by combining the Markovian model and the Monte Carlo Method (MCM) for normal or lognormal service times that also yield useful good approximations to the simulated system.

Tomato (Solanum lycopersicum L.) is one of the most commercially essential vegetable crops cultivated worldwide. In addition to the nutritional value, tomato is an excellent model for studying climacteric fruits' ripening process. Despite this, the available natural pool of genes that allows expanding phenotypic diversity is limited, and the difficulties of crossing using classical selection methods when stacking traits increase proportionally with each additional feature. Genetic engineering makes it possible to introduce changes in genes of interest without changing the allelic combinations characteristic of successful commercial varieties, to enhance the expression of existing genes, to create and transfer artificial and heterologous genes, and much more. However, this requires understanding the fundamental principles of the molecular interaction. Although the leading candidate genes for these components have been identified, a complete picture of their relationship has yet to be formed. The review summarizes the latest (2017-2023) achievements related to studying the ripening processes of tomato fruits. In this work, an attempt is made to systematize the results of various research and display the interaction pattern of genes regulating the process of tomato fruit ripening.

To support pathologists in breast tumor diagnosis, deep learning plays a crucial role in the development of histological whole slide image (WSI) classification methods. However, automatic classification is challenging due to the high-resolution data and the scarcity of representative training data. To tackle these limitations, we propose a deep learning-based breast tumor gigapixel histological image multi-classifier integrated with a high-resolution data augmentation model to process the entire slide by exploring its local and global information and generating its different synthetic versions. The key idea is to perform classification and augmentation in feature latent space, reducing the computational cost while preserving the class label of the input. We adopt a deep learning-based multi-classification method and evaluate the contribution given by a Conditional Generative Adversarial Network-based data augmentation model on the classifier’s performance for three tumor classes in the BRIGHT Challenge dataset. The proposed method has allowed us to achieve an average F1 equal to 69.5, considering only the WSI dataset of the Challenge. The results are comparable to those obtained by the Challenge winning method (71.6), also trained on the annotated tumor region dataset of the Challenge.

In the paper we present a new test for comparison of the means of multivariate samples with unknown distributions. The test is based on the comparison of the distributions of the distances between the samples’ elements and their means using univariate two-sample Kolmogorov-Smirnov test. The activity of the suggested method is illustrated by numerical analysis of the real-world and simulated data.

{Here, we propose a new tool to estimate the complexity of a time series: the entropy of difference (ED). The method is based solely on the sign of the difference between neighbouring values in a time series. This makes it possible to describe the signal as efficiently as prior proposed parameters such as permutation entropy (PE) or modified permutation entropy (mPE), but (1) reduces the size of the sample that is necessary to estimate the parameter value, and (2) enables the use of the Kullback-Leibler divergence to estimate the "distance" between the time series data and random signals.

The real-time Railway Traffic Management Problem (rtRTMP) is discussed in the field of railway transportation. In this paper, rtRTMP is considered for planning shunting routes based on the use of routing methods on a spatial-temporal graph. An approach and algorithm of Spatial-Temporal Graph formation for rail yard transportation network is proposed. The idea is to construct an undirected loop-free Double Vertex Graph for determining optimal shunting routes consisting of several half-runs for several trains shunting under draw-out tracks capacity constraints. Experimental results on the rail yard simulation model are presented.

Solid tumors are composed of a highly complex and heterogenic microenvironment, with increasing metabolic status, playing a crucial role in the clinical therapeutic outcome of conventional treatments and innovative tumor nanomedicines. Scientists, have devoted great effort in conquering the tumor microenvironment (TME) challenges, in respect of effective drug accumulation and activity in tumor site, overcoming the obstacles of abnormal vasculature, dense stroma and extracellular matrix, hypoxia, and pH gradient acidosis. In this conquest, nanomedicines targeting distinct TME features have flourished, in order to increase site specificity and deep penetration, for effective antitumor activity, and further reprogram TME promoting suppression of cancer stem cells and metastasis. Thereby, several successful nanomedicine therapeutics have been under clinical trials, and further applied in clinical practice. Various novel strategies have been employed in preclinical studies and clinical trials, among which nanomedicines based on biomaterial, that have shown great promise in improving the therapeutic efficacy, reducing side effects, and promoting synergistic activity for TME targeting. In this review, we have focused on the targeting mechanisms for solid TME by nanomedicines based on the application of natural and synthetic biomaterials. We have described critical formulations that have been considered for the design of stimuli-responsive nanomedicines for TME. The development of such systems, has significantly advanced the application of biomaterials, in combinational therapies and in immunotherapies, for improved effectiveness.

Conventional heat treatment is not capable of converting a sufficient amount of retained austenite into martensite in high-carbon or high-carbon and high-alloyed iron alloys. Cryogenic treatment induces the following alterations in the microstructures: (i) a considerable reduction in the retained austenite amount, (ii) formation of refined martensite coupled with an increased number of lattice defects, such as dislocations and twins, (iii) changes in the precipitation kinetics of nano-sized transient carbides during tempering, and (iv) an increase in the number of small globular carbides. These microstructural alterations are reflected in mechanical property improvements and better dimensional stability. A common consequence of cryogenic treatment is a significant increase in the wear resistance of steels. The current review deals with all the mentioned microstructural changes as well as the variations in strength, toughness, wear performance, and corrosion resistance for a variety of iron alloys, such as carburising steels, hot work tool steels, bearing and eutectoid steels, and high-carbon and high alloyed ledeburitic cold work tool steels.

This study addresses the escalating threat of data theft ransomware, a form of cyberattack that exfiltrates sensitive information from victim networks and demands ransom for its non-disclosure. Unlike traditional crypto-ransomware, data theft ransomware leverages various infiltration techniques to gain unauthorized access and control over critical data assets. The study introduces a novel Moving Target Defense (MTD) framework, specifically designed for the Windows operating system environment, to counter these sophisticated attacks. MTD increases the unpredictability of the system by dynamically altering its configurations, thereby disrupting the adversary's ability to execute successful attacks. Our research includes the development and empirical evaluation of the MTD framework, demonstrating its effectiveness in reducing ransomware operational capabilities through quantitative analysis, qualitative observations, and statistical significance testing. We also explore the challenges and complexities involved in implementing MTD in real-world scenarios and propose strategies to overcome these barriers. The study concludes with recommendations for future research directions and the potential of MTD in enhancing cybersecurity defense mechanisms.

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

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

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

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

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

Conflicts are frequent within the complex professional environment of the construction industry. If claims cannot be overcome amicably, they result in disputes that lead to litigation. Identification of the causes of these claims and their impact on the duration, cost, and quality of the final project is expected to facilitate the prevention of unsuccessful performance of construction contracts. The novelty of this study is that after codifying the most common causes of construction contract claims derived from the extant literature, they are further investigated in terms of their probability of occurrence and the perceived impact they have on the project completion time, its total cost, and quality. Based on calculated relative importance indices from expert opinion, this paper proposes probability and severity of impact values for 39 common causes of claims in the construction industry. These can be applied to calculate their risk values for stakeholders in public construction contracts to plan mitigation measures of contractual claims. The findings show that the top five riskiest causes of contractual claims in the Greek construction industry are changes in quantities, work, or scope, design quality deficiencies or errors, payment delays, delays in work progress, and the financial failure of the contractor.

Wendan (a type of pomelo), as a popular fruit in China, is less known in other countries. Its peel is widely used in food and traditional medicine. Four different origins of Wendan pomelo were selected, and crude extracts were obtained by the Soxhlet extraction method. The composition of Wendan peel was analyzed by high-performance liquid chromatography-mass spectrometry (HPLC-MS) in positive ion mode. The compounds were identified by searching the Metabolite Link (METLIN), Spectral Database for Organic Compounds (SDBS) and referring to literature reports. A total of 20 compounds were identified among the samples from the four origins, of which 8 compounds were common. The majority of the compounds belonged to the flavonoid and coumarin classes, Meranzin hydrate was identified for the first time in pomelo peel. In vitro antioxidant activity experiments showed that samples from Taizhou, Zhejiang exhibited the highest antioxidant activity in the DPPH, ABTS, and FRAP assays, with values of 0.59 mg/mL, 97.06 μmol TE/g, and 60.62 μmol Fe2+/g, respectively. Samples from Zhangzhou, Fujian showed antioxidant activity second only to the samples from Taizhou, Zhejiang. The sample from Zhangzhou, Fujian Province, showed excellent inhibitory activity in the α-glucosidase inhibition assay (IC50=7.99 mg/mL).

The purpose of the present study was to develop an experimental model for studying of the intra-articular knee movements depending on the work of the knee joint and applied muscle groups in isometric stretching conditions with different tens. The experimental procedure includes ultrasound examination of a knee joint after isometric stretching of healthy men (n=32). The changes in millimeters of the distances between the femur and tibia were measured with ultrasound sonographer at three stages. The first stage was performed on ten (n=10) healthy men at five different sitting and upright positions. In the second and third experimental model stages the lower limbs loading was on 22 participants. Our hypothesis which was confirmed, was that as a result of increasing extraloads on the participants back (2, 5, 10, 15, 17, 20 kg), a intra-articular decrease in the femur-tibia cartilage surface distance wiil be observed. The accuracy of the created experimental model was improved over its three stages from 30% to 9%. Quantitative model data can help to create a mathematical model for the mechanical effects during deformation of the knee joint bone cartilage, as well as to outlines the some future tasks: increasing loading weights; enlarge participant groups; comparison men and women; healthy and pathology comparison.

Premortem clinical diagnoses and postmortem autopsy findings do not match throughout history. These clinicopathological discrepancies are expected to be raised during the coronavirus disease 2019 (COVID-19) pandemic due to increased pressure on healthcare. At the same time, autopsies and clinicopathological discrepancies accurately display the quality of the healthcare system. To assess that, we examined the relevant works of literature according to the PRISMA-based protocol. As discrepancy rate changes in the correlation to the length of stay in the hospital, we also checked whether studies with patients from the intensive care unit (ICU) differed in discrepancies significantly. We found overall risk differences pretty much alike in "pre-COVID" and "during the pandemic" groups of studies. Based on that, we concluded that healthcare quality did not drop significantly during the pandemic. Be it as it may, the pandemic exposed some shortcomings in mortem healthcare regarding consensus to the autopsy, organ retention, burial, and the postponed burial or the digitalization of post mortem healthcare. All of these issues should be addressed in the future.

During geomagnetic storms, which are a result of solar wind interaction with the Earth’s magnetosphere, geomagnetically induced currents (GICs) begin to flow in the long-distance high-voltage power grids on the Earth’s surface. It causes a number of negative phenomena that affect the normal operation of the entire electric power system. To investigate the nature of the phenomenon and its possible effects on transformers, a GIC monitoring system was created in 2011, the devices of which were installed at five substations of the Kola-Karelian power transit in northwestern Russia. Over 12 years of operating the system a large amount of data has been accumulated, which cannot be analyzed manually within a reasonable amount of time. To analyze the constantly growing volume of recorded data effectively, a method for automatic classification of GIC in autotransformer neutral was proposed. The method is based on a continuous wavelet transform of the neutral current data combined with a convolutional neural network (CNN) to classify the obtained scalogram images. As the result of comparing four CNNs with different architectures, a model that showed excellent GIC classification performance on the validation set (100.00% accuracy and loss of 0.0115) was chosen.

Calculating a minimum-time trajectory requires the solving of a boundary value problem resulting from invocation of necessary conditions of optimality to set up a set of ordinary differential equations to solve the trajectory between the initial position and desired ending position with set constraints on the path between the two. This manuscript expresses the minimum time optimum trajectory between a satellite in a geosynchronous orbit and a target set on earth’s surface utilizing a non-rotating earth centric coordinate system. Expressing motion in coordinates of rotating reference frames necessitates transformation between reference frames, and one such transformation is embodied in the Direction Cosine Matrices (DCM) formed by a sequence of three successive frame rotations. Rotation about the local wing of an aerospace vehicle is almost never the pitch angle, yet modern application of kinematics often assumes such (with accompanying angular error). The same assertion is usually true about the nature of roll and yaw angles. This manuscript evaluates which sequence is the most advantageous for an object starting in space and then travels through the atmosphere to a target on the Earth’s surface. Simulation precision (validated by the quaternion normalization condition) reveals the so-called 132 rotation is the most accurate with an average error of 0.14° and a computational time of 0.013 seconds: resulting in a 97.95% increase in accuracy over the ubiquitous 321 “aerospace” rotation sequence and a 99.84% increase over the so-called 313 “orbital” rotation sequence. Utilizing the proposed optimal trajectory candidate yields a total flight time of 2 hours, 34 minutes and 46 seconds, or an average velocity of 3.85 kilometers per second, while impacting the target with a velocity of 11.54 kilometers per second.

To address the challenges associated with the difficult electromagnetic (EM) scattering computations of anisotropic dielectric-coated metallic composite targets, we proposed an efficient hybrid algorithm for simulating the EM scattering of complex targets with anisotropic dielectric coatings. This method, based on Impedance Boundary Condition (IBC), utilizes surface impedance vectors to describe the EM properties of the dielectric. It fully leverages the respective advantages of the low-frequency Method of Moments (MoM) and the high-frequency Physical Optics (PO) to achieve high-precision and rapid EM simulation of anisotropic dielectric-coated metallic composite targets. Employing boundary conditions and equivalent principles, we equivalently transform the EM scattering problem of targets with thin dielectric coatings into the radiation problem of equivalent EM current on impedance surfaces. This enables the high-precision and rapid calculation of Radar Cross Sections (RCS) for complex targets with anisotropic dielectric coatings. Using examples such as a square plate structure, a simplified aircraft, and a complex satellite model, the simulation results exhibit a high degree of agreement with full-wave numerical solutions and demonstrate a significant advantage in computational resources. This research convincingly demonstrates the accuracy and effectiveness of the proposed method.

Risk management strategies protect the company as a whole as well as employees from unforeseen financial impacts. As in the case of personal finance, preparing for certain scenarios helps to face any difficulties that the company may encounter and allows it to get out of this impasse.For any project to be successful, the way the project executing agency will deal with potential risks must be determined so that it can identify, mitigate or avoid problems when it needs to do so. Successful project managers realize that risk management is important, because the achievement of project objectives depends on planning, preparation, results and evaluation that contribute to the achievement of strategic goals, especially the sustainable development of societies.Risk management strategies work to protect the company as a whole as well as employees from unexpected financial effects, and as is the case in personal finance, preparing for certain scenarios helps to face any difficulties that the company may face and allows it to get out of this impasse.To ensure the success of your project, determine how you will handle potential risks so that you can identify, mitigate or avoid problems when you need to do so. Successful project managers understand that risk management is important, because the achievement of project objectives depends on planning, preparation, results, and evaluation that contribute to the achievement of strategic objectives.

Summary: PURPOSE. Development of a drainless energy-saving technology for the processing of high-moisture iron-containing sludge from metallurgical production. RESEARCH METHOD. The regularities of the combined process of chemical dehydration of high-moisture iron-containing sludge by powdered waste of lime and dolomite, hardening and agglomeration by pressing in a single technological cycle on the developed experimental plant were studied. In the course of laboratory studies, the temperature of the mass, the rate of dehydration, the chemical composition of the mixtures, the appearance of the resulting briquettes, the weight loss during agglomeration-humidity of the mixtures, and mechanical strength of the briquettes were measured. RESULTS. New patterns have been established that have made it possible to develop a nonfiring method for producing iron-containing materials and self-healing briquettes. The essence of his method, which is one of the main provisions of scientific novel provisions, is to combine dehydration and self-hardening of the mixture with the process of shaping by applying external pressure to the hardening mixture in molds to obtain agglomerated material in the form of briquettes in a single technological cycle. The proposed technology does not require drying or firing, and a set of strength properties occurs as the material is cooled in air during the day. A new energy-efficient and drainless method for the production of iron-containing briquettes has been developed, which combines the processes of chemical dehydration and agglomeration in one technological cycle. CONCLUSION. The proposed project and technology will allow organization of production for the processing of high-moisture iron-containing sludge and the production a complex iron-containing material as a secondary metal-containing raw material for metallurgical plants for the production of steel and rolled metal. and dolomite dust from dry gas cleaning as dehydrating and binding materials, as well as screening of coke and coal as a reducing agents. The proposed technology also solves the problems of environmental pollution and land acquisition for the storage of production waste.

Microplastics and nanoplastics (MP/NPs) have been found everywhere they have been searched. On the top of Everest, in the Mariana Trench, on the clouds e recently, microplastics have been discovered in the human placenta, meconium and babies’ feces. In this review we explain what the consequences of the presence of these pollutants in fetuses and newborns are, with particular attention to human breastfeeding. Finally, we outline the possible political and social solutions to the problem of plastic overproduction that characterizes the modern world.

OSI model used to be common network model for years. In the case of ad hoc networks with dynamic topology and difficult radio communications conditions, gradual departure is happening from the classical kind of OSI network model with a clear delineation of layers (physical, channel, network, transport, application) to the cross-layer approach. The layers of the network model in ad hoc networks strongly influence each other. Thus, the cross-layer approach can improve the performance of an ad hoc network by jointly developing protocols using interaction and collaborative optimisation of multiple layers. The existing cross-layer methods classification is too complicated, because it’s based on the whole manifold of network model layers combinations, regardless their importance. In this work, we review ad hoc networks cross-layer methods, propose the new useful classification of cross-layer methods, and show future research directions in ad hoc networks cross-layer methods development. The proposed classification can help to simplify the goal-oriented cross-layer protocol development.

This paper considers the direction of arrival (DOA) estimation problem of phase ambiguity for unfolded coprime linear array (UCLA). The existing most common stacking subarray-based method can tackle the phase ambiguity problem. However, the method is not always true. For a given DOA, it has its corresponding steering vector, but if there are two DOAs which have the same steering vectors with the given DOA for different subarrays, the phase ambiguity problem still arises. A modified method, which defines a decision variable and uses the classic beamforming technique to estimate the DOAs is proposed. However, this method needs additional algorithm to distinguish the true DOAs besides multiple signal classification (MUSIC) spectrum. And sometimes this method is not reliable if the decision variable is not chosen appropriately. Therefore, based on the UCLA, we reconstruct the array to design an improved UCLA called IUCLA. With moving the reference element, the linear relationship among the directional vectors can be broken. In this way, we can directly utilize the MUSIC algorithm to estimate with no additional algorithm. The proposed method can solve the phase ambiguity problem and it does not demand other technique to decrease the complexity. Moreover, the Cramer-Rao Bound (CRB), as the lower bound of the unbiased estimation, is provided and numerical simulations are given to demonstrate the effectiveness and superiority of the proposed method.

This paper investigated reliability modeling for systems subject to dependent competing risks considering that the variation of failure threshold is not considered in most studies on competing failure reliability. Firstly, the variation of degradation quantity under shocks was analyzed, and the variation of threshold was considered on this basis. Secondly, the cumulative degradation under the influence of the random shock process was analyzed. The attractive property of copula is symmetry. Then, A linear Wiener process model is applied to model performance degradation failure, and a multi-performance-degradation correlated-competition model based on a Copula function is constructed, which considers the correlated competition between multiperformance degradation failures. Lastly, the micromotor system is used to analyze the applicability of the proposed model for bivariate instances. demonstrating the rationality and effectiveness of the proposed model.

Participating in collaborative scientific research through citizen science, a component of open science holds significance for both citizen scientists and professional researchers. Yet, the ad-vantages for those orchestrating citizen science initiatives are often overlooked. Organizers en-compass a diverse range, including governmental entities, non-governmental organizations, corporations, universities, and institutions like libraries. For libraries, citizen science holds im-portance by fostering heightened civic and research interests, promoting scientific publishing, and contributing to overall scientific progress. This paper aims to provide a comprehensive understanding of the specific ways in which citizen science can benefit libraries and how libraries can effectively utilize citizen science to achieve their goals. The paper is based on a systematic review of peer-reviewed articles that discuss the direct benefits of citizen science on libraries. A list of the main benefits of citizen science for libraries has been compiled from the literature. Additionally, the reasons why it is crucial for libraries to communicate the benefits of citizen science for their operations have been highlighted, particu-larly in terms of encouraging other libraries to actively engage in citizen science projects.

Indigo leaves form various plant species are sources of dyes/pigments, not fully exploited for making sustainable textiles. Blue indigo vat dye extracted from indigo leaves, yields high wash colorfastness but fades slowly with light, and is not easily used for direct printing. Indigo leaves can be used to produce textiles of various color shades, while light resistant Mayan-inspired hybrid pigments have not yet been used for textile coloring. Using blue indigo dyes from 3 plant species, with exhaustion dyeing, intense wash resistant blue colored textiles are produced, and in the case of Indigofera Persicaria tinctoria, textiles have antibacterial activity against S. Epidermis and E. Coli.100% Natural Mayan-inspired blue indigo pigment, made from Sepiolite clay and indigo dye, was used both in powdered and paste forms to perform pigment textile dyeing by pad cure process, and direct screen printing on textiles. A water-based bio-binder (40%) was used efficiently for both padding and printing. Bio-based Na Alginate thickener allowed color fast printing on both polyester and cotton fabrics, while bio-based glycerin allowed good print color fastness on polyester only, yielding prints with excellent color fastness to wash (5/5), to dry and wet rubbing (5/5) and light (7/7).

In the face of geopolitical threats in Artsakh, the preservation of Armenia's epigraphic heritage has become a mission of both historical and cultural urgency. This project delves deep into Armenian inscriptions, employing advanced digital tools and strategies like the Oxygen text editor and EpiDoc guidelines to efficiently catalogue, analyze, and present these historical treasures. Amidst the adversities posed by Azerbaijan's stance towards Armenian heritage in Artsakh, the digital documentation and preservation of these inscriptions have become a beacon of cultural resilience. The XML-based database ensures consistent data, promoting scholarly research and broadening accessibility. Integrating the Grabar Armenian dictionary addressed linguistic challenges, enhancing data accuracy. This initiative goes beyond merely preserving stone and text; it is a testament to the stories, hopes, and enduring spirit of the Armenian people in the face of external threats. Through a harmonious blend of technology and traditional knowledge, the project stands as a vanguard in the fight to ensure that Armenia's rich epigraphic legacy and the narratives they enshrine remain undiminished for future generations.

Ebstein anomaly, a congenital heart condition, can manifest across a broad age spectrum, including adulthood. We present a unique case of a 67-year-old woman with no significant medical history who sought medical attention for severe headaches, vomiting, and respiratory distress, accompanied by elevated blood pressure and rapid pulse. Initial investigations, including troponin T levels, yielded unremarkable results. However, an electrocardiogram unveiled a right bundle branch block (RBBB) pattern, prompting further assessment. A subsequent chest X-ray disclosed an enlarged heart, indicating cardiomegaly, prompting echocardiography. The echocardiogram confirmed the diagnosis of Ebstein anomaly, revealing a 26 mm apical displacement of the tricuspid valve (TV). The patient was managed conservatively with supplemental oxygen and exhibited gradual improvement. This case underscores the infrequent occurrence of Ebstein anomaly in adulthood and underscores the necessity for thorough evaluation in cases of unexplained cardiopulmonary symptoms.

The circular economy is based on maintaining a circular flow of resources. Policymakers face difficulties in balancing national security and circular economy aspects in the field of mineral resources policy. With a uniquely expanded input-output table, this study estimates the final destination of several critical minerals (lithium, cobalt, yttrium, lanthanum, cerium, neodymium and dysprosium) and base metals (iron, copper and aluminum) in the Japanese economy for 2015. Our model shows quite a good similarity between the estimated composition and the actual data of products. The results reveal a detailed distribution of critical minerals and indicate prioritized implementation for creating and maintaining a circular flow of critical minerals. Developed decision flow guidance provides a comprehensive approach to national security and circular economy aspects for policymakers. For further actions, inclusive indicator development is required for policymakers to support the determination of implementation possibilities from social and technological aspects.

Abstract: Background: The main aim of the study was to assess the intensity and frequency of cervical spine pain in young people with temporomandibular disorders (TMD). Methods: The pilot study was conducted from June to July 2023. Inclusion criteria were: age (18-30 years), cervical spine pain (for at least 1 month) and consent to participate in the study. The study was conducted based on a physiotherapeutic examination and an original questionnaire. The pain level was assessed using the Visual Analogue Scale (VAS). Among 95 people with cervical spine pain, 51 people (53.7%) constituted the control group (without a history of temporomandibular disorders), while 44 (46.3%) people constituted the study group. Results: The mean age of people participating in the study was 22.2±2.2 years in the study group and 22.5±3.1 years in the control group. The largest group were people aged 21-25 (n=51 people, 53.7%). Patients from the study group more often experienced pain in the stomatognathic system during palpation (both in the muscle, joint and musculoskeletal groups) and had reduced mobility of the temporomandibular joints in every movement (p<0.001). People from the study group were characterized by also less mobility of the cervical spine (p<0.05), apart from extension movement (p>0.05). There was a significant relationship between temporomandibular disorders and cervical spine pain (p<0.05, chi2=10.118, df=1, rc=0.31). The level of back pain was significantly higher in people from the study group (p<0.001, chi2=45.765, df=4, rc=0.57). Conclusions: Our research has shown that the causes of cervical spine pain at a young age may be temporomandibular disorders, which are generally not recognized and properly treated.

In this study, we investigated the surface modification of LiNi1/3Co1/3Mn1/3O2 cathode material by coating it with ZnO and examined the changes in surface composition using X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) analysis. Furthermore, we investigated the electrochemical properties, including discharge capacity and initial irreversible capacity, of the modified materials. The results revealed that ZnO predominantly existed on the material surface, exerting influence on both surface composition and electrochemical characteristics. As the ZnO coating amount increased, the nickel and manganese content on the material surface also increased, and heat treatment at 400 °C resulted in the formation of composite oxides of transition metals and zinc on the material surface. The bonding energy of transition metals increased, and ZnO coating at a mass fraction of 2 % effectively suppressed irreversible reactions around 3.6 V at 55 °C, thereby improving initial coulombic efficiency. Battery materials coated with 2% ZnO exhibited optimal discharge capacity and cycle life at 55 °C/0.5 C.

This paper identifies preschool teachers' sources of stress, the times they experience high stress, and their ways of coping with stress levels. The study was conducted using a phenomenological design, one of the qualitative research models. The data were collected through semi-structured interviews with 36 preschool teachers working with children aged 0-6 in state and private schools. As a result of the content analysis, stressors were identified primarily at both interpersonal (positive, and effective interactions), and organizational levels (school management, and leadership style). It was also found that intense stress was experienced when children were difficult to control, such as during sleeping, eating, and cleaning. Finally, these results confirmed that the teachers used active/active behavioral, and passive/avoidant coping strategies. However, it was understood that preschool teachers perceived stress negatively, and did not see stress as a personal development situation. These results are discussed in terms of their ramifications for preschool education.

This study examines the dynamics of failure development in marginalized communities, investigating the interplay of socioeconomic, environmental, and community engagement factors. The research aims to uncover underlying causes, provide policy recommendations, and elucidate the challenges faced by these communities. However, limitations include a restricted focus on marginalized areas, data limitations, and an exclusive emphasis on socioeconomic factors. The analysis reveals gaps in addressing political influences, limited coverage of success stories, and potential biases in the methodology. The conclusion emphasizes the transformative power of community-led initiatives to address challenges, foster inclusivity, and create sustainable change. These initiatives prioritize capacity building, social cohesion, economic development, and access to education and healthcare. Implications for policy and practice underscore the need for comprehensive interventions, collaboration, empowerment, and sustainable development. Future research directions include exploring the long-term impact of historical failures, intersectionality, the role of technology, mental health implications, and comparative analysis.

Fractional calculus is defined by expanded integer order integration and differentiation. In this paper, multiple mathematical models of a nonlinear dual tank device are precisely formulated by fractional calculus. Using the accurate model, multivariable Fractional-Order Controller is designed for the nonlinear device. The merits of the fractional-order design include: 1) Control of multivariable nonlinearities, 2) Compensation of uncertainties, 3) Elimination of coupling effects. Simulations and experiments are conducted to verify the precision of the fractional order models and the effectiveness of the multivariable fractional-order control design.

Burden of diseases measured as disability-adjusted life years per 100,000 people can be mined from public domain data, when they are made available by population health surveillance systems. This can be analysed to allow insightful comparisons with the national average, and to understand differences in trends between the sexes, age groups, time periods, geographic regions and sub-regions. In this illustrative case study, we have analysed the Scottish burden of disease database to understand what ailed the population of the Grampian region before the COVID-19 pandemic. We have identified selected cancers, ischaemic heart disease, Alzheimer’s disease and other dementias amongst the highest contributors to the burden; that drug use disorders and colorectal cancer are showing worsening trends and require health promotion and disease prevention measures from ages 15 and 25 respectively, especially in Aberdeen City; and that males are more vulnerable to atrial fibrillation and flutter, diabetes mellitus and oesophageal cancer, while females are to cerebrovascular disease. We demonstrate the usefulness of our analysis and methodology for the wider health system, allowing targeted medical research investments and coordinated response from public health and health service delivery. We also show the need for up-to-date surveillance data, forecasts and evidence on the impact of interventions to be made available widely.

The Konya Closed Basin (Quaternary, Central Turkey) is a graben basin which expands toward the east-west and it is controlled by faults on three sides: The Konya fault zone in the west, the Divanlar fault zone in the east and the Karaömerler fault zone in the north. Calcretes developed in relation to fault systems in the Konya region are concentrated in areas where faults cut Quaternary aged terrestrial deposits. In this study, it is aimed to elucidate the deposition conditions, geochemistry and age (with ESR method) of the calcareous deposits associated with faults in the Konya Closed Basin. Calcretes in the region existing as coatings, dust, nodules and layers are in the form of dolocrete and clayey calcrete. Dolocretes were deposited in the Quaternary terrestrial sediments on the ophiolitic rocks and geochemical data point to an ultramafic source. Bacterial community, clay, quartz minerals and calcite cement are observed in the calcretes formed in areas with limestone basement. According to the results of ICP-MS analysis of samples taken from Konya calcretes, the %MgO contents are between 0.99 and 7.7; CaO%: between 34.71 and 50.71; %SiO2 between 3.22 and 20.59. %MgO in dolocretes are between 11.65 and 21.01; %CaO between 8.44 and 29.57; %SiO2 values between 4.48 and 9.17 The δ13C and δ18O isotope values of calcretes range from -3.87 to -7.62 and from -3.62 to -7.45 respectfully. Average δ13C values indicate that calcrete formation took place under pedogenic condition or in shallow groundwater. The calcretes deposited in 3 locations around the city of Konya (on the Konya fault zone) were dated by using the Electron Spin Resonance (ESR) method and ages between 217.47 and 389.85 ky were obtained. The calcrete samples taken from the fault planes (dip-slip normal fault bordering the Upper Cretaceous Ophiolitic Mélange and the Quaternary Karahüyük Formation) gave a relative age for faulting as being 292.86 ky. This first dating study conducted in the Konya Fault Zone has provided important clues to elucidate the formation history of Konya Closed Basin (KCB) and the paleo-seismological past of Konya.

As governments in various countries and regions issue tourism-friendly policies in the post-pandemic period, the voices for tourism consumption recovery and innovative transformation have attracted great attention. Many scholars, experts and industry professionals in the field of festivals are actively exploring efficient solutions for festival marketing and sustainability. It is worth rethinking tourists’ consumption psychology and perceived image toward exiting festival products as well as the antecedents that affect festival loyalty. The Qingdao International Beer Festival, as one of the most influential festivals in China, was selected as the research case for this study. The main goal of this study was to investigate festival consumption promotion mechanism by proposing a conceptual framework in which the associations from destination familiarity and product familiarity to loyal intentions (re-patronage and recommendation) were examined, with mediators of overall festival image, perceived value and overall satisfaction. Furthermore, the moderating role of visitor involvement in the proposed framework was also adequately demonstrated. The research findings are expected to provide a significant reference for the recovery and competitiveness improvement of the entire festival industry.

Research is scarce regarding antimicrobial use and antimicrobial resistance (AMR) for specific localities in Northern Ireland (NI). Additionally, the effects of COVID-19 on antimicrobial pre-scribing patterns and AMR are unknown. Between the European Union (EU) and United States (US), AMR causes approximately 68,000 deaths annually. This study will provide a better understanding of antimicrobial use and prescribing patterns in Belfast and link with AMR. An electronic survey was developed and distributed to eighty-five community pharmacists in Belfast. Yearly and monthly prescription data was gathered from the Business Services Organisation and COVID-19 statistics from Gov.uk. All data was analysed on Microsoft Office Excel® and IBM® SPSS® Statistics 25. Overall response rate was 46%. Most pharmacists (82%) failed to address prescriber non-compliance with guidelines and antimicrobial dosing errors (59%). The most common in-dication for antibiotics was upper respiratory tract infections (URTIs). Overprescribing of anti-biotics was perceived as the leading cause of AMR, therefore 69% of pharmacists indicated in-creased General Practitioner (GP) compliance with guidelines would reduce AMR. Pharmacists’ are in an ideal position to reduce AMR through patient education however, it is demonstrated that pharmacists failed to adequately counsel patients on antibiotic use. All GP practices demonstrated inappropriate antibiotic use, especially for URTIs which suggests antibiotic appropriateness should be reviewed. Many patients avoided contact with GP’s during COVID-19 which may have resulted in reduced antibiotic use. This research established amoxicillin as the most commonly prescribed antibiotic, which is contributing to increased AMR with its broad-spectrum activity and has recognised a decrease in antibiotic prescribing during COVID-19. Based on the results found and a critical review of the literature it is recommended antimicrobial guidelines should be re-viewed and improved, enhanced training should be provided to pharmacists and the antibiotic guardian (AG) campaign should be reenergised.

This paper aims to contribute to refining the e-values for testing precise hypotheses, especially when dealing with nuisance parameters, leveraging the effectiveness of asymptotic expansions of the posterior. The proposed approach offers the advantage of bypassing the need for elicitation of priors and reference functions for the nuisance parameters and the multidimensional integration step. For this purpose, starting from a Laplace approximation, a posterior distribution for the parameter of interest only is considered and then a suitable objective matching prior is introduced, ensuring that the posterior mode aligns with an equivariant frequentist estimator. Consequently, both Highest Probability Density credible sets and the e-value remain invariant. Some targeted and challenging examples are discussed.

The aim of this research was to undertake laboratory testing to investigate the beneficial effects of epoxy resin grouts on the physical and mechanical properties of sands with a wide range of granulometric characteristics. Six sands, of different particle size and uniformity coefficients, were grouted using epoxy resin solutions with three ratios of epoxy resin to water (3.0, 2.0 and 1.5). A set of unconfined compressive strength tests were conducted on grouted samples at different curing periods and a set of long-term unconfined compressive creep tests in dry and wet conditions after 180 days of curing were also carried out, in order to evaluate the development of the mechanical properties of the sands, as well as, the impact of water on them. The findings of the investigation showed that epoxy resin resulted in appreciable strength values in the specimens, especially those of fine sands, grouted with the different epoxy resin grouts. In general, the compressive strength varied between 0.68 - 5.60 MPa and the modulus of elasticity between 75 - 480 MPa, after a curing period of 180 days. In terms of physical properties, the permeability and porosity (before and after the grouting process) were estimated. Grouts with an epoxy resin to water ratio of 3 decreased permeability by up to four orders of magnitude. Using laboratory results and regression analysis, three mathematical equations were developed that relate each of the dependent variables; compressive strength, elastic modulus, and coefficient of permeability, with particular explanatory variables.

Hong Kong was under the direct hit of Severe Typhoon Koinu (2314) on 8 and 9 October 2023, necessitating the issuance of the Increasing Gale or Storm Signal, No. 9. Koinu was a very challenging case for TC forecasting and warning services due to its compact size and erratic movement over the northern part of the South China Sea. This paper reviews the difficulties and challenges on the forecasting aspect of the severe typhoon. The predicted tropical cyclone track and intensity from both conventional models and emerging artificial intelligence models are examined, as well as local wind and rainfall forecast. Experience in this case study showed that while deterministic global models only performed moderately and were not able to adequately support early warning, a regional model and AI models could more effectively support decision making for operational tropical cyclone warning service.

The systems for automated monitoring of a human’s personal carbon footprint and CO2-equivalent emissions at industrial enterprises were developed in the article. The personal carbon footprint monitoring system includes data collection subsystems based on energy consumption metering devices, data storage and transmission, and calculation subsystems. To measure the consumption of water, electricity, thermal energy, IoT control sensors were selected. The calculation of the individual carbon footprint of a person is proposed. The system for automated monitoring of the carbon footprint of an enterprise includes a subsystem of devices for monitoring the use of energy resources, a subsystem for data transmission, calculation and prompt display of the carbon footprint. Selected devices for monitoring the consumption of water, energy and heat resources with data transfer to the SCADA system. An algorithm for calculating the carbon footprint of an enterprise is proposed. Structural schemes for automated carbon footprint control have been developed.

In our recent report, we clarified the direct interaction between excitatory amino acid transporter (EAAT) 1/2 and polyunsaturated fatty acids (PUFAs) by applying electrophysiological and molecular biological techniques to Xenopus oocytes. Xenopus oocytes have a long history of use in the scientific field, but they are still attractive experimental systems for neuropharmacological studies. We will therefore summarize the pharmacological significance, advantages, (especially in the study of EAAT2), and experimental techniques that can be applied to Xenopus oocytes; our new findings concerning L-glutamate (L-Glu) transporters and PUFAs; and the significant outcomes of our data. The data obtained from electrophysiological and molecular biological studies of Xenopus oocytes have provided us with further important questions, such as whether or not some PUFAs can modulate EAATs as allosteric modulators and to what extent docosahexaenoic acid (DHA) affects neurotransmission and thereby affects brain functions. By combining Xenopus oocyte experiments and more translational approaches, we can clarify the functions of proteins that are difficult to examine using cultured cells and the physiological roles of these proteins in brain functions. These approaches can lead to the development of the new central nervous system (CNS) drugs targeting molecules and investigations of their effectiveness.

SDG target 12.3 calls for halving food waste at retail, food service, and household by 2030. The food waste index for this purpose includes parts attached to food that are usually removed intentionally ("unavoidable food waste") and allows counting the conversion to animal feed and utilisation as biomaterial as means of reduction. In Japan, the "Food Waste Recycling Law" which has been in effect since 2001, promotes the recycling of food waste generated from businesses, designating feed conversion as top priority. On the other hand, based on the more recent "Food Loss Reduction Promotion Act" of 2019, the government is currently promoting the reduction of avoidable food waste, as to meet the SDG target. Based on statistical sources and interviews with Ministry officers, this paper explains the history and achievements of Japan's 23-year policy based on the Food Recycling Law, as well as the tension between the two legislations.

Despite recent improvements in the methods used to eradicate and minimize mosquito populations, they still pose severe threats to human health. This study aimed to investigate the Larvicidal potentials of silver nanoparticles of Ocimum gratissimum on wild Anopheles larvae from Lagos. The plant used in this study was collected from the southeastern part of Nigeria, Ibite-Olo in Ezeagu Local Government Area of Enugu State. Wild Anopheles mosquito larvae were collected from a field at Kosofe Local Government Area of Lagos State, Nigeria where resistant Anopheline populations have been reported in and around Lagos State were brought to the laboratory and kept under standard insectary conditions (25–29 °C;78–82% relative humidity). Aqueous extract of Ocimum gratissimum was made and subsequently into the silver nanoparticles. A bioassay test was performed according to WHO guidelines, with six different concentrations to assess the larvicidal activity and values obtained were subjected to log prohibit regression analysis to obtain LC₅₀ and values with 95% confidence limit. The results of the larvicidal activities of the silver nanoparticles of Ocimum gratissimum showed that the mortality rate was dose-dependent with the percentage mortality increasing at a direct proportional rate as with dose and time of exposure. Ocimum gratissimum gave LC₅₀ at 0.5 ppm and LC₉₅ at 2.5 ppm respectively. The biosynthesized silver nanoparticles augmented the larvicidal activity of the silver nanoparticles of Ocimum gratissimum on wild Anopheles larvae from Lagos. Therefore, this study showed that the silver nanoparticles of Ocimum gratissimum have the potency to be used against an insecticide-resistant mosquito vector and are a suitable candidate for the development of novel natural insecticides.

This research looks into the evolving dynamics of ransomware, shifting from conventional encryption-based attacks to sophisticated data exfiltration strategies. Employing the Bidirectional Encoder Representations from Transformers (BERT) model, the study analyzes network traffic patterns to detect ransomware activities, offering new insights into their covert operations. The findings emphasize the need for advanced AI tools in cybersecurity, highlighting the significance of adapting and innovating defense strategies to counter the changing landscape of ransomware threats. The study contributes to a deeper understanding of ransomware evolution and underscores the importance of integrating AI in cybersecurity practices.

A formulation of the Density Functional Theory (DFT) is constructed as an application of the method of maximum entropy for an inhomogeneous fluid in thermal equilibrium. The use of entropy as a systematic method to generate optimal approximations is extended from the classical to the quantum domain. This process introduces a family of trial density operators that are parametrized by the particle density. The optimal density operator is that which maximizes the quantum entropy relative to the exact canonical density operator. This approach reproduces the variational principle of DFT and allows a simple proof of the Hohenberg-Kohn theorem at finite temperature. Finally, as an illustration, we discuss the Kohn-Sham approximation scheme at finite temperature

Physical properties like shape, volume and size affect the dynamics of biological systems. Along these lines, we focus on the topological properties of biological fluids and their biochemical and physiological outcomes. We take as a paradigmatic example the salivary fluid and describe how its topological features may affect the physiopathology of the oral cavity. Topological approaches assess the general properties of saliva, ignoring small-scale physical details such as density, flow rate, stiffness, viscosity. Specifically, the mucin aggregates scattered in the salivary fluid can be tackled in terms of topological holes, i.e., vortical clusters that modify the direction, flow, impulse, local rate-of-change and velocity of saliva. While the current methodological approaches are inclined to remove the effects of impurities assessing systems as homogeneous structures, we argue that the occurrence of mucins breaks up the salivary fluid’s homogeneity, leading to unexpected biophysical modifications. We suggest that every collected salivary sample is not reliable for accurate clinical and experimental investigation, since it displays highly local as well as variable chemical, physical and biological features, not reflecting the current physiological state of the oral cavity. Therefore, the assessment of a single salivary sample is not fully reproducible and cannot provide information about the biophysical, enzymatic and microbiological content of the whole saliva. In sum, the very topological features of the saliva - such as volume, shape, antipodal cells, vortex area, whirling fluid mass, segmentation, discretization, triangulation, node numbering - produce unnoticed biological consequences and network connectivity features with intriguing operational implications.

The paper presents the results of soil research in the Prinevskaya lowland within the boundaries of St. Petersburg. The study of the direction and rate of change in the properties of fallow lands, aimed at understanding the process of post-agrogenic transformation of soils, as well as the development of a monitoring system for changes in the parameters and properties of fallow soils will contribute to the optimization of the soil-ecological state of soils excluded from agricultural turnover in St. Petersburg and the Leningrad region.

The objectives of this article are to examine whether the application of digitalization in enterprise budgeting affects the fulfilment of budgeting functions and their qualitative characteristics, and to investigate whether the realization of budgeting functions brings benefits. The research was conducted from the perspective of contingency theory, both internal and external conditions. The study used an online survey targeting company budgeting staff. Structural Equation Modelling was utilized to validate the structural model (PLS-SEM technique). The conclusions confirm that the application of digitalization, which particularly pertains to ERP, Business Intelligence systems and accounting systems with budgeting solutions, positively impacts the fulfilment of budgeting functions and most of their qualitative characteristics, while Blockchain makes a minor contribution. Our research suggests that contingency variables, particularly internal ones such as company size, the quality of the organizational structure, and support for competitive strategy, continue to affect budgeting implementation even with the participation of digitalization in budgeting. Budgeting functions and their qualitative aspects are notably correlated with the advantages derived from budgeting, including financial performance, sustainable development and budget task execution.

The article presents a hybrid method for calculating the chemical composition of steel with the required hardness after cooling from the austenitizing temperature. Artificial neural networks and genetic algorithms were used to develop the model. Based on 550 diagrams of continuous cooling transformation (CCT) of structural steels available in the literature, a dataset of experimental data was created. Artificial neural networks were used to develop a hardness model describing the relationship between the chemical composition of the steel, the austenitizing temperature, and the hardness of the steel after cooling. A genetic algorithm was used to identify the chemical composition of the steel with the required hardness. The value of the objective function was calculated using the neural network model. The developed method for identifying the chemical composition was implemented in a computer application. Examples of calculations of mass concentrations of steel elements with the required hardness after cooling from the austenitizing temperature are presented. The model proposed in this study can be a valuable tool to support chemical composition design by reducing the number of experiments and minimizing research costs.

Correlations between the Neoproterozoic belts surrounding the West African Craton and northern Brazilian cratons have long been a subject of interest and controversies. Due to the splitting of African and South American continents by the Atlantic oceanic domains, no direct links are preserved, requiring relying on various geological or geophysical characteristics to propose such correlations. In addition to the opening of the Atlantic oceanic domains, another difficulty arises from the covering of northern Brazilian belts by upper Paleozoic and Mesozoic basins, making these correlations speculative. Recently, four orogens have been evidenced in the Neoproterozoic belts of the western margin of the West Africa Craton, while the belts on the eastern side underwent only one orogeny. Similarities with the Pan-African I (900-650 Ma) and with the Pan-African II (650-480 Ma) orogenic events have been evidence in the western Brazilian belts (Araguay and Paraguay). The two first orogens on the western margin (Pan-African I and Pan-African II) can thus be extended to the western Brazilian belts and can be considered as parts of a single geodynamic system running from the Mauritania to the Paraguay including the “Gurupi rift” as an aulacogen connected to the NNW-SSE Panafrican I and II oceanic domains. Consequently, the eastern Brazilian belt should rather be linked the Eastern Trans-Saharan belts.

Chert rock is a by-product of sand quarrying (about 40% in the geological section). All attempts to use ordinary technologies for aggregate production from chert have been economically unsuccessful, resulting in significant chert "waste" accumulation covering vast quarry areas. This paper presents the study results of the effect of microwave irradiation on the mechanical properties of chert gravel, which is mineralogically relatively homogenous and consists of fine quartz grains. The results show that an increase in irradiation time decreases the strength of chert gravel (by a factor of 4-6 for the 2.5 min of irradiation), while the quenching changes the fractional content of the samples after the crushing test, decreasing the Gravel-to-Sand ratio.

When the skin is afflicted by disease such as cancer, these essential functions are disrupted, putting the entire person at risk. While the American Cancer Society lists 6 major cancer types, the National Institute of Arthritis and Musculoskeletal and Skin Diseases identifies 13 significant benign skin disorders, reflecting the diversity of skin conditions in dermatology. This topical review aims to provide an overview of the pathophysiology of these major skin cancers and disorders and summarize conventional diagnostic methods and current treatment approaches.

This last decade, chimeric antigen receptor (CAR) T-cell therapy has become a real treatment option for patients with B-cell malignancies, while multiple efforts are being made to extend this therapy to other malignancies and broader patient populations. However, several limitations remain, including those associated with the time-consuming and highly personalized manufacturing of autologous CAR-Ts. Technologies to establish “off-the-shelf” allogeneic CAR-Ts with low alloreactivity are currently being developed, with a strong focus on gene editing technologies. Although these technologies have many advantages, they have also strong limitations including double-strand breaks in the DNA with associated multiple safety risks as well as the lack of modulation. As an alternative, non-gene editing technologies provide an interesting approach to support the development of allogeneic CAR-Ts in the future, with possibilities of fine-tuning gene expression and easy development. Here we will review the different ways allogeneic CAR-Ts can be manufactured and discuss which technologies are currently used. The biggest hurdles for successful therapy of allogeneic CAR-Ts will be summarized and finally an overview of the current clinical evidence for allogeneic CAR-Ts in comparison to its autologous counterpart will be given.

Today, specific CNN models assigned to specific tasks are often used. In this article, the authors have investigated three models MobileNet, EfficientNetB0 and InceptionV3. Artificial intelligence methods for deep networks will be presented but implemented in a limited computer resource. Three types of training bases were investigated, starting with a simple base verifying five colors, followed by recognition of two different orthogonal elements, and then more complex images discriminating between elements. The research aimed to demonstrate the models' capabilities based on training base parameters such as the number of images and epoch types. The architectures proposed by the authors in these cases were chosen based on simulation studies conducted on a virtual machine with limited hardware parameters. The proposals present the advantages and disadvantages of different models based on TensorFlow, Keras libraries in the Jupiter environment written based on the Python language. The authors' proposal of the selected AI model enables further work on e.g. image classification, but in a limited computer resource for industrial implementation e.g. on a PLC.

The loss or dysfunction of skeletal tissue often necessitates surgical intervention, particularly in cases involving trauma, tumors, or abnormal development leading to critical-sized defects. Despite autografts being considered the gold standard for bone grafts, their limitations and complications prompt the exploration of alternative approaches for bone repair and regeneration. Current advancements in bone tissue engineering have led to innovative strategies aiming to regenerate injured bone structures, providing viable alternatives to traditional autografts or allografts. Among these strategies, Hydrogel Microparticles (HMPs) have emerged as promising scaffolds due to their notable characteristics, including high porosity and mechanical tunability. HMPs play an important role in facilitating vasculature formation, mineral deposition, and overall bone tissue regeneration. HMPs, fabricated through various techniques, exhibit versatility in functions such as drug and cell delivery, structural scaffolding, and bioinks for 3D printing. In addition, these microgels can be injected for minimally invasive delivery and can display modular properties with different designs and configurations. This review exclusively focuses on the advancements in HMPs for bone regeneration, delving into synthesis and functionalization techniques while highlighting their diverse applications documented in the literature. Our aim is to shed light on the unique benefits and potential of HMPs in the intricate field of engineering bone tissue.

Robots in space are necessarily extremely light and lack structural stiffness resulting in natural frequencies of resonance so low as to reside inside the attitude controller’s bandwidth. A variety of input trajectories can be used to drive a controller’s attempt to ameliorate the control-structural interactions where feedback is provided by low-quality, noisy sensors. Traditionally, step functions are used as the ideal input trajectory. However, step functions are not ideal in many applications, as they are discontinuous. Alternative input trajectories are explored in this manuscript and applied to an example system that includes a flexible appendage attached to a rigid main body. The main body is controlled by a reaction wheel. The equations of motion of the flexible appendage, rigid body, and reaction wheel are derived. A feedback controller is developed to account for the rigid body modes. Additional filters are added to compensate for the system’s flexible modes. Sinusoidal trajectories are autonomously generated to feed the controller. Whiplash compensation is additionally implemented for comparison. The control method without random errors with the smallest error is the sinusoidal trajectory method, which showed a 97.39% improvement when compared to the baseline response when step trajectories were commanded, while the sinusoidal method was inferior to traditional step trajectories when sensor noise and random errors were present.

Increasing groundwater levels (GWL) may become one of the most serious issues for Odessa City, Ukraine. This study investigated the spatial distribution characteristics and multifractal scaling behaviour of groundwater level/depth fluctuation for a Quaternary aquifer in Odessa City using a geostatistical approach and a Multifractal Detrended Fluctuation Analysis (MF-DFA). These two methods were applied to monthly GWL fluctuation time series from 1970 to 2020 to monitor 72 hydrogeological wells situated in different parts of Odessa City. The spatial distribution of GWL revealed an overall trend of decline and recovery from 1970 to 2020 in the study area, except for most of the southern region, where a persistent recovery of groundwater depth was observed. The MF-DFA results suggest that the dynamics of GWL fluctuations have multifractal characteristics in the Odessa City area. In addition, both long-range correlation and fat-tail probability distribution contribute to multifractality. However, long-range correlations among fluctuations made a major contribution to the observed multifractality of the GWL fluctuations time series. The generalized Hurst exponent shows a wide range of change (0.20 &lt; h(q) &lt; 2.85), indicating the sensitivity of GWL fluctuations to changes in small scale factors and large-scale factors. Regarding the long range correlations of GWL depth, the Hurst exponents (q = 2) demonstrated the positive persistence of groundwater depth recovery in the southern region and the persistence of groundwater depth variation in the other regions of the study area. The dynamic changes in GWL depth in the Odessa City area may be affected by both natural structural and anthropogenic factors.

The first paper of this two-part series paper discussed the development of a novel lightweight 3D wood dowel-reinforced glass epoxy hybrid composite material (3DdrFRP) and its manufacturing procedures. It also experimentally compared the performance of scaled utility poles made from conventional 2D E-glass epoxy and 3DdrFRP materials. In the second part, we developed robust finite element (FE) models in LS-DYNA, calibrated them based on experimental results, and used them to simulate the performance of equivalent 2D and 3D poles, proving the integrity of the numerical model. Additionally, we developed a simplified analytical calculation method for engi-neers to determine the stiffness of 3D-DrFRP poles accurately and quickly.

Autoimmune hepatitis (AIH) is a chronic, relapsing and remitting, immune mediated liver disease which progresses to cirrhosis if left untreated. A significant number of patients may present with acute hepatitis or acute liver failure, which are often misdiagnosed as toxic liver injury. AIH shows a preponderance for young women but may be seen in children and elderly. Diagnosis requires integration of clinical, biochemical and serologic parameters along with supportive liver histology and exclusion of other causes of liver disease. Liver biopsy is a pre-requisite for diagnosis of AIH, to assess severity and stage of disease, exclude other entities and recognize any concurrent morbidities. No single biomarker or histologic feature is pathognomonic for AIH. The diagnostic and histologic criteria have undergone several modifications since the Original Scoring system proposed by the International Autoimmune Hepatitis Group (IAIHG) in 1993. Recently, IAIHG has proposed consensus recommendations for histologic criteria, relevant for both acute and chronic AIH. This review article will describe the evolving diagnostic criteria for AIH with their limitations and utility, with an emphasis on the role of liver histology in diagnosis and management of AIH.

Modern electrical power systems integrate renewable generation, with solar generation being one of the pioneers worldwide. In Latin America, the greatest potential and development of solar generation is found in Chile through the National Electric System. However, its energy matrix faces a crisis of drought and reduction of emissions that limits hydroelectric generation and involves the definitive withdrawal of coal generation. The dispatch of these plants is carried out by the system operator, who uses a simplified mechanism, called “economic merit list” and which does not reflect the real costs of the plants to the damage of the operating and marginal cost of the system. This inefficient dispatch scheme fails to optimize the availability of stored gas and its use over time. Therefore, a real-time redispatch model is proposed that minimizes the operation cost function of the power plants, integrating the variable generation cost as a polynomial function of the net specific fuel consumption, adding gas volume stock restrictions and water reservoirs. In addition, the redispatch model uses an innovative "maximum dispatch power" restriction, which depends on the demand associated with the automatic load disconnection scheme due to low frequency. Finally, by testing real simulation cases, the redispatch model manages to optimize the operation and dispatch costs of power plants, allowing the technical barriers of the market to be broken down with the aim of integrating ancillary services in the short term, using the power reserves in primary (PFC), secondary (SCF), and tertiary (TCF) frequency control.

The purpose of this study was to explore and develop high-resolution infrared thermal (HRIT) imaging for screening toddler’s fracture. A Toddler’s fracture is a common tibial fracture of children younger than 6 years old. Initial x-ray radiographs may not show the fracture and another x-ray during a follow-on visit is usually required. The study included 39 participants admitted to an emergency department with a suspected toddler’s fracture. X-ray confirmed 8 cases with a toddler’s fracture (20.5%). Infrared images of participants were recorded on their index visit, focusing on region-of-interests on the injured and the contralateral (uninjured) legs. The uninjured leg acted as a thermal reference. Nine statistical measures were extracted from the images: maximum, mini-mum, mean, standard deviation, median, mode, interquartile range, skewness, and kurtosis. Wilcoxon rank sum test indicated that maximum, mean, standard deviation, median, and inter quartile range temperature measures were significantly different (p<0.05) when comparing fractured and non-fractured legs. Principal component analysis of these measures highlighted distinct separation of toddler’s fracture and non-fracture cases. Similarly, plots of the statistical measures further confirmed clustering of toddler’s fracture cases. The study demonstrated that HRIT imaging can be a valuable tool for screening for toddler’s fracture.

When we are asleep we lose the ability to promptly respond to external stimuli and yet we spend many hours every day in this inherently risky behavioral state. This simple fact strongly suggests that sleep must serve essential functions that rely on the brain going offline, on a daily basis, and for long periods of time. If these functions did not require partial sensory disconnection, it would be difficult to explain why they are not performed during waking. Paradoxically, despite its central role in defining sleep and what sleep does, sensory disconnection during sleep remains a mystery. We have a limited understanding of how it is implemented along the sensory pathways, we do not know whether the same mechanisms apply to all sensory modalities, nor do we know to which extent these mechanisms are shared between non-rapid eye movement (NREM) sleep and REM sleep. The main goal of this contribution is to review some knowns and unknowns about sensory disconnection during sleep as a first step to fill this gap.

Background: This study aimed to investigate how external perturbations caused by the treadmill belt's acceleration (Acc) and deceleration (Dec) during the Initial Contact (Initial), Mid Stance (Mid) and Pre-Swing (ToeOff) phase affect gait regularity in young adults. Methods: Twenty-one healthy young females walked on a treadmill in a virtual environment (Grail, Motek), where four unexpected perturbations were applied to the left belt at Initial, Mid, and ToeOff. Sample Entropy (SampEn) was calculated for the center of mass (CoM) displacements, for six perturbation scenarios in three directions: anterior-posterior (AP), medial-lateral (ML), and vertical (vert), with SampEn vector lengths (m) ranging from 2 to 10. Results: The CoM displacement exhibited its highest regularity (low SampEn values) in the AP and vert-directions during Dec_ToeOff, across all m values. Similarly, this pattern was observed in the ML-direction, but exclusively for m = 2 and 4. The least regular CoM trajectories (high SampEn values) were for Dec_Mid in the AP-direction, across all m values. This trend persisted in the ML-direction, only for m = 2 and 4. However, the most irregular CoM displacements in the ML-direction occurred during Dec_ToeOff for the remaining m values. Vertical CoM displacements exhibited the highest irregularities during Dec_Initial for m ≥ 4. Conclusions: Evaluating the regularity of CoM displacements using SampEn can be a useful tool for assessing how gait perturbations are handled.

The importance of oxygen role during aging process of wine has been long known. Many articles evaluating oxygen inlet for different wine stoppers have been published. However, none of these have studied the impact of the natural cork stoppers production process over oxygen inlet. At the moment, a standardized methodology widely accepted for measuring the oxygen transfer rate (OTR) and/or oxygen permeability of the stopper does not exist. Thus, this article is focused on the aging process (the final phase of the winemaking) and aims to test how some production process of natural cork stoppers impact on the stoppers permeability using chemiluminescence methodology and how also this affects wine ageing. In this study it has been seen that some of its processes such as the application of a surface treatment modify the permeability of the stopper. Surface plays an important role in the corks stoppers production and allows an easier insertion and extraction of the stopper into the bottle, avoiding leaks and homogenizing the stoppers. It was shown that the cork stoppers sample with surface treatment 1 had three times higher oxygen transfer rate than the cork stoppers sample with surface treatment 2 after one year of evolution. The two groups of stoppers had the same in terms of dimensions, density, visual class, batch and manufacture, the only difference between them was the surface treatment used. A red wine was corked with these two types of cork stoppers and its evolution was monitored up to 30 months of ageing. Differences were observed in the evolution of the wines both in certain oenological parameters such as the free SO2, the colour and the evolution of the polyphenols as well as at the sensory level. The wine corked with the stoppers of treatment 1 presented a faster evolution and a higher valuation in the sensory tastes of months 12th, while from the 18th month it presented an over evolution, and the score was below that of the wine with the corks of treatment 2.The data collected in this study shows that the differences observed with the chemiluminescence methodology of cork permeability test at a laboratory level are transferred to wine at the cellar. Therefore, it paves the way to standardize chemiluminescence as a methodology for permeability testing of cork stoppers. This opens a new field for the regulation of the permeability of natural cork stoppers by type of surface treatment applied.

The main issue in this work is to study limit functions necessary for the reliability assessment of the structural steel with the use of the relative entropy apparatus. This would be done using a few different mathematical theories relevant to this relative entropy, namely those proposed by Bhattacharyya, Kullback-Leibler, Jeffreys, and Hellinger. Probabilistic analysis in the presence of uncertainty in material characteristics would be delivered using three different numerical strategies – Monte-Carlo simulation, stochastic perturbation method as well as the semi-analytical approach. All these methods are based on the Weighted Least Squares Method approximations of the structural response functions versus the given uncertainty source and they would allow efficient determination of the first two probabilistic moments of the structural responses including stresses, displacements, and strains. The entire computational implementation would be delivered using the Finite Element Method system ABAQUS and computer algebra program MAPLE, where relative entropies, as well as polynomial response functions, would be determined. This study would demonstrate that the relative entropies may be efficiently used in reliability assessment close to the widely engaged First Order Reliability Method (FORM).

We study the back-reaction of fermion fields on the kink solution in one space and one time dimension. We employ a variational procedure to determine an upper limit for the minimum of the total energy. This energy has three contributions: the classical kink energy, the energy of valence fermions and the fermion vacuum polarization energy. The latter arises from the interaction of the kink with the Dirac sea and is required for consistency of the semi-classical expansion for the fermions. Earlier studies only considered the valence part and observed a substantial back-reaction. This was reflected by a sizable distortion of the kink profile. We find that this distortion is strongly mitigated when the Dirac sea is properly accounted for. As a result the back-reaction merely produces a slight squeeze or stretch of the kink profile.

The occurrence rate of occupational accidents caused by slipping and falling is 50% worldwide. Determining the slip safety risk is necessary to minimize the accidents caused by slipping in pedestrian walking areas. By on-site testing, this study aims to determine the slip risks of floor coverings used in walking areas with many pedestrians in public service buildings (PSB). For this purpose, on-site measurements were performed in two environments and six locations in PSB using portable GMG 200 and pendulum testers operating according to DIN 51131 and TS EN 14231 standards. These tests were performed on four-floor coverings with polished surface treatment in PSB. Since the floor coverings measured have a polished surface, it can be seen that the dynamic friction coefficients (DCOF) values are very low, and the slip risks are high. By statistically analyzing the slip test data using the K-means method, a new safety classification was made according to the usage areas of floor coverings. To minimize the risk of slip safety, especially for students, patients, and employees in PSB, it is recommended to use floor coverings with high DCOF values and low slip risk.

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

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

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

Chronological frameworks based on artefact typologies are essential for interpreting the archaeological record, but they inadvertently treat transitions between phases as abrupt events and disregard the temporality of transformation processes within and between individual phases. This study presents an absolute chronological investigation of a dynamic material culture from Early Iron Age urnfields in Denmark. The chronological framework of Early Iron Age in Southern Scandinavia is largely unconstrained by absolute dating, primarily due to it coinciding with the so-called ‘Hallstatt calibration plateau’ (c.750 to 400 cal BC), and it is difficult to correlate it with Central European chronologies due to a lack of imported artefacts. This study applies recent methodological advances in radiocarbon dating and Bayesian chronological modelling, specifically a statistical model for wood-age offsets in cremated bone and presents the first large-scale radiocarbon investigation of regional material culture from Early Iron Age in Southern Jutland, Denmark. Dated material is primarily cremated bone from 111 cremation burials from three urnfields. The study presents absolute date ranges for 16 types of pottery and 15 types of metalwork, which include most of the recognised metalwork types from the period. This provides new insights into gradual change in material culture, when certain artefact types were in production and primary use, how quickly types were taken up and later abandoned, and distinguishing periods of faster and slower change. The study also provides the first absolute chronology for the period, enabling correlation with chronologies from other regions. Urnfields were introduced at the Bronze-Iron Age transformation, which is often assumed to have occurred c.530-500 BC. We demonstrate that this transformation took place in the 7^th century BC, however, which revives the discussion of whether the final Bronze Age period VI should be interpreted as a transitional phase to the Iron Age.

Modelling and presenting mathematical relationships for human behaviour is one of the most complex issues that researchers have always dealt with. In this article, a bottom-up framework for calculating agricultural needs is presented using the socioeconomic characteristics of farmers (such as education level, age, and dependence on income on agriculture) and how their lands are located concerning each other (interactions between neighbours). The objective function of this framework is to maximize the profit of individual farmers based on the amount of water received. Two scenarios, ABM1 (not considering neighbourhood effects) and ABM2 (all cases of farmers' placement and feeling neighbourhood effects), were investigated. In the first scenario (ABM1), there was a noteworthy reduction in water deficit volumes by approximately 35%, accompanied by a 20% increment in farmers' profits. Interestingly, higher risk-taking tendencies correlated with reduced profit margins. The second scenario (ABM2) underscored the significant role of neighborhood dynamics in cultivating diverse behavioral patterns among farmers, subsequently affecting their profitability. A granular examination revealed that farmers with a higher propensity for risk-taking generally accrued lower profits. Additionally, the study facilitated the calculation of total annual profits and average water consumption for each farmer, offering valuable insights for optimizing water resource management and allocation strategies. These findings are instrumental for planners and water resource managers aiming to promote sustainable agricultural practices and efficient water use.

In this paper, we obtain the existence and uniqueness theorem for solutions of Caputo type fractional stochastic delay differential systems (FSDDSs) with Poisson jumps by utilizing delayed perturbation of Mittag-Leffler function. Moreover, by using Burkholder-Davis-Gundy's inequality, Doob's martingale inequality and Holder inequality, we prove that the solution of the averaged FSDDSs converges to that of the standard FSDDSs in the sense of Lp. Some known results in the literature are extended.

Using the projection evolution (PEv) approach, time can be included in the quantum mechanics as an observable. Having the time operator, it is possible to explore the temporal structure of various quantum events. In the present paper we discuss the possibility of constructing a quantum clock, which advances in time during its quantum evolution, in each step having some probability to localize itself on the time axis in the new position. We propose a working two-state model as the simplest example of such a clock.

Every subset S of a Cartesian spaces Rd, endowed with differen- tial structure C∞(S) generated by restrictions to S of functions in C∞(Rd), has a canonical partition M(S) by manifolds, which are or- bits of the family X(S) of all derivations of C∞(S) that generate local one-parameter groups of local diffeomorphisms of S. This partition satisfies the frontier condition, Whitney’s conditions A and B. If M(S) is locally finite, then it satisfies all definitions of stratification of S. This result extends to Hausdorff locally Euclidean differential spaces.

Recruitment is a fundamental aspect of Human Resource Management to drive organizational performance. Traditional recruitment processes, with manual stages, are time-consuming and inefficient. Artificial Intelligence (AI), which demonstrates its potential in various sectors such as healthcare, education and notable cases of ChatGPT, is currently reshaping recruitment by automating tasks to improve efficiency. However, in Thailand, where there is a growing demand for talents, the application of AI in recruitment remains relatively limited. This research focuses on human resources (HR) and recruitment professionals in Thailand, aiming to understand their perspectives on the integration of AI in recruitment. It extended the Unified Theory for Acceptance and Use of Technology (UTAUT) model, customized to suit the specific requirements of Thai recruitment practices. The study explores the factors influencing users' intention to adopt AI in recruitment. Survey questionnaire items were created based on prior literatures and refined with insights from HR and recruitment experts to ensure applicability in the context of recruitment in Thailand. A survey involving 364 HR and recruiting professionals in Bangkok metropolitan area supplied comprehensive responses. The research reveals that several factors, including Perceived Value, Perceived Autonomy, Effort Expectancy, and Facilitating Conditions, significantly impact the intention to adopt AI for recruitment. While Social Influence and Trust in AI Technology do not have a direct influence on intention, Social Influence directly affects Perceived Value. Trust in AI Technology positively influences Effort Expectancy. This study provides valuable benefits for HR and recruitment professionals, organizations and AI developers by offering insights into AI adoption and sustainability, enhancing recruitment processes and promoting the effective use of AI tools in this sector.

Flavin-dependent monooxygenases (FMOs) have made substantial influence as catalysts for monooxygenation reactions, impacting diverse field such as drug metabolism, environmental studies, and natural product synthesis. Their application in biocatalysis boasts several advantages over conventional chemical catalysis, such as heightened selectivity, safety, sustainability, and eco-friendliness. In the realm of biomedicine, FMOs are pivotal in antibiotic research, modulating natural products, antimicrobial agents, and pathways involved in drug synthesis. They're also underscored as potential pharmaceutical targets, pivotal in disease progression and viable for therapeutic intervention. Additionally, FMOs play a substantial role in environmental science, especially in pesticide processing and plant vitality. Their involvement in biosynthesizing compounds like polyethers, tropolones, and ω-hydroxy fatty acids, with remarkable regio- and stereoselectivity, renders them indispensable in drug discovery and development. As our comprehension of FMOs' catalytic mechanisms and structures advances, coupled with cutting-edge biotechnologies like computational design and directed evolution, FMOs are poised to occupy an increasingly significant role in both scientific exploration and industrial applications.

This study examined the effect of the media usage environment, particularly TV and SNS devices, on advertisement acceptance, lifestyle, and psychological satisfaction. Hypothesis pathways and comparative structural mediating effects were analyzed. Media and Consumer Research public data were used for empirical analysis. A total of 6,640 people who participated in sports activities were included in the study. The results demonstrated that TV and SNS device usage environments had similar effects on advertisement acceptance. While TV did not influence the pursuit of personal life, SNS device use environments affected the pursuit of personal life. SNS device use environments had a greater effect on individual psychological satisfaction than TV. Adoption had a mediating effect on the influence of media usage environments on the pursuit of personal life. The pursuit of a personal life had a significant mediating effect on the influence of media use environments on psychological stability. This study revealed no differences in the effects of new and traditional media on advertisement acceptance, while new media had a greater influence on lifestyle and psychological satisfaction.

This research presents a novel approach to film analysis, leveraging word vectors to objectively evaluate movie critiques. Focusing on Director Chanwook Park’s award-winning film, ’Decision to Leave’, the study employs word vectors derived from the movie’s script of Korean text. Traditional critiques often emphasize contrasting elements and themes, but their subjective nature poses challenges in objective validation. To address this, we trained a language model using LSTM on the film’s script, obtaining word vectors that capture the essence of the narrative. These vectors were then used to perform various text analyses, including similarity and analogy operation for the keywords suggested by the critiques. By comparing the semantic relationships in the critiques with those derived from the word vectors, we could objectively validate the critiques’ assertions. Furthermore, we visualized the word vectors in a two-dimensional space, confirming the spatial relationships of key terms highlighted in critiques. The study underscores the potential of word vectors in providing a more objective lens for film analysis, bridging the gap between traditional film criticism and data-driven insights.

Epigenetic changes are changes in gene expression that do not involve alterations to the basic DNA sequence. These changes lead to establishing a so-called epigenetic code that dictates which and when genes are activated, thus orchestrating gene regulation and playing a central role in development, health, and disease. The brain, being for the most formed by cells that do not undergo a renewal process through life, is highly prone to the risk of alterations leading to neuronal death and neurodegenerative disorders, mainly at late age. Here we review the main epigenetic modifications that have been described in the brain, with particular attention to those related to the onset of developmental anomalies or neurodegenerative conditions and/or occurring in old age. DNA methylation and several types of histone modifications (acetylation, methylation, phosphorylation, ubiquitination, sumoylation, lactylation, and crotonylation) are major players in these processes. They are directly or indirectly involved in the onset of neurodegeneration in Alzheimer’s or Parkinson’s disease. Therefore, this review briefly describes the role of these epigenetic changes in the mechanisms of brain development, maturation, and aging and some of the most important factors dynamically regulating or contributing to these changes such as oxidative stress, inflammation, and mitochondrial dysfunction.

Acid mine drainage (AMD) contamination is the primary environmental issue in industrial areas and where geological mining occurs. The oxidative dissolution of sulphide minerals causes AMD, natural ecosystems depend on microbial diversity and functioning at their best. This review presents the long-term effects of AMD water such as pollution from heavy metals (HM) on humans and plants, and the solution to the problem of heavy metal pollution by microbes metal interactions.

The practical application of a pH-responsive Nanoparticle Drug Delivery System (NDDS) in cancer treatment is often hampered by several issues such as the protection of therapeutic molecules from external stresses, inefficient targeted delivery, sustained drug release, and poor efficacy. This study presents an effective design strategy for the synthesis of a pH-sensitive controlled hydrophobic drug delivery method based on the formulation of chitosan (CS)-coated mesoporous silica nanoparticles (MSNs) through the sol-gel method, where hydrolysis takes place in the acidic medium followed by polycondensation of the hydrolyzed products. For this purpose, NH2 modified-MSNs were prepared by using tetraethyl orthosilicate (TEOS) as precursor and cetyltrimethylammonium bromide (CTAB) as a template, and 3-aminopropyltriethoxysilane (APTES) for amine modification, followed by hydrophobic drug loading and CS coating of various concentrations. Camptothecin (CPT) was used as a model drug. Fabricated monodispersed functionalized nanoparticles had sizes ranging from 200nm to 245nm with an encapsulation efficiency as high as 90%. The highest encapsulation efficiency was found for 1% CS coating, which released 50% drug in 120h at pH 6.4 and 20% at pH 7.4 respectively. These nanoformulations exhibited pH-responsive release patterns of CPT under two different pH values (pH=7.4 and pH=6.4). These results contribute to the optimization of NDDS, with potential implications for nanoformulations designed for controlled and sustained drug release particularly to tumors without affecting healthy cells owing to differences in the pH of the tumor microenvironment and the normal physiological environment of cells.

In this work, the analytical treatment of Fourth order pd equations has been discussed with the variational iteration algorithm with an auxiliary parameter. The technique has the capability of reducing the size of computational work and easily overcomes the difficulty of the perturbation method or Adomian polynomials. Comparison with the classic variational iteration algorithm- is carried out, showing that the modification is more efficient and reliable.

Text classification is one of the most important task in natural language processing, In this research, we carried out several experimental research on three (3) of the most popular Text classification NLP classifier in Convolutional Neural Network (CNN), Multinomial Naive Bayes (MNB), and Support Vector Machine (SVN). In the presence of enough training data, Deep Learning CNN works best in all parameters for evaluation with 77% accuracy, followed by SVM with accuracy of 76%, and multinomial Bayes with least performance of 69% accuracy. CNN has the best performance in the presence of large enough training dataset because of the presence of filter/ kernels which help to indentify patterns in text data regardless of their position in the sentence. We repeated the training again with just one-third of our data, at this point SVM comes with the best performance, the performance of CNN noticeably drops but still better than Multinomial Naive Bayes, the reason why SVM works best when we reduce the training data was because of its ability to look for a hyper-plane that creates a boundary between different classes of data so as to properly classify them, so we believed that getting the hyper-plane was more efficient when we reduce the dataset, hence reason for the good performance. Multinomial Naive Bayes have the least performance which we attributed to its assumption of independency between the features which sometimes does not hold true. We concluded that availability of data should be an important factor when choosing classifier for Natural Language Processing Text Classification task. CNN should be use in the presence of enough dataset, and SVM should be use when data is not enough. Multinomial Naive Bayes must not be trusted with state of the art NLP task due to its assumption of independency between the features.

Experimental measurement of porous polypropylene (PP) using the DTC-25 TA laboratory equipment and hot box test has been compared. The thermal conductivity of materials indicates the insulation capability of building materials. Excellent building materials will have a lower thermal conductivities value as well as other building insulator performance metrics. While results show that increasing the volume fraction of fluid in the porous PP has an inverse association with the thermal conductivity of the material as predicted by porous media theories, there is a marked difference in the measured values of the thermal conductivity using the two methods. The thermal conductivity values of porous from DTC-25 and hot box test were 0.21 and 0.0033 W/mK, respectively. The difference in the thermal conductivity values was due to the misapplication of the Fourier’s guarded heat flow model in the DTC-25 device to a convective fluid porous medium material.

The orbital elactronic structure of Rare Earth Elements (REEs) contains many unpaired electrons which render them capable of storing large amount of magnetic energy in addition to being critical for hitech applications. Geological deposits are their conventional sources, and the current supply chain relies on production from these deposits. However, given their critical roles in the anticipated global energy transition, there is the need to explore other viable sources to supplement current and future supplies chains. REEs occur in coal as accessory minerals and their concentration in coal ash to levels that rival those of geological deposits has been estab;ished by sophisticated analytical chemical methods. Conmventional hydrometallurgical processes rely on acid leaching, using tioxic mineral acids. Meanwhile, organosulfonic acids have pKa values that rival those of conventional minerals acid and can, therefore, be used in hydrometallurgy but their uses in this regard are not well documented in the literature. In this extensive review, we have covered geological sources of REEs exaustively in addition to showing the potential of organosulfonic acids as environmentally benign lixiviants for REEs extraction from coal ash. We have also shown how process optimization can be achieved using advance technologies while using organisulfonic acids. Moreover, we have shown current and future global market trends regarding the production of select organosulfonic acids, and the anticipated global increase in their production motivates the use of organosulfonic acids as viable lixiviants for REEs extraction from caol ash deposits.

Gadolinium-based contrast agents (GBCA) are complexes, highly stable in vivo, used in Magnetic Resonance Imaging (MRI), administered in patients and then eliminated via renal, passing through wastewater treatment plants (WWTP) before being discarded in the receiving medium, without apparent removal. In this study, it was studied if different exposure periods to several environmental parameters (solar radiation, different salinities, temperatures and pH) will influence the stability of these complexes, namely, the Gd-DOTA. Gd-DOTA solutions were processed in a seaFAST-pico saline matrix pre-concentration and elimination system and Gd concentrations were determined by ICP-MS. Results showed that the complex remained stable in fresh, brackish and saline water environments, even when exposed to extreme temperatures (40ºC) or slightly acidic to basic conditions (6-10), for an exposure period of 96h. A small increase in the free Gd concentration was observed after 18 days when exposed to pH&lt;4, in all tested salinities (0, 18 and 36 PSU), with a degradation increase of up to 29%, after 5 weeks of exposure in freshwater. When exposed to direct solar radiation a low Gd-DOTA degradation (4%) was observed after 24h at salinity 18 PSU and remained constant until the end of the exposure period (96h), while the remaining salinities showed negligible values.

High concentrations of sodium (Na+), chloride (Cl-), calcium (Ca2+), and sulphate (SO42-) are fre-quently found in saline soils. Crop plants cannot successfully develop and produce because salt stress impairs the uptake of calcium, potassium, and water into plant cells. Different intracellular and extracellular ionic concentration changes by salinity, including those of calcium, potassium, and protons. These cations serve as stress signaling molecules in addition to being essential for ionic homeostasis and nutrition. Maintaining an appropriate K+: Na+ ratio is one crucial plant mechanism for salt tolerance, which is a complicated trait. Another important mechanism is the ability for fast extrusion of Na+ from the cytosol. Calcium is established as a ubiquitous secondary messenger, which transmits various stress signals into metabolic alterations that cause adaptive responses. When plants are under stress, the cytosolic-free Ca2+ concentration can rise to 10 times or more from its resting level of 50-100 nanomolar. Reactive oxygen species (ROS) are linked to the calcium alterations, and are produced by stress. Depending on the type, frequency and intensity of the stress, the cytosolic calcium signals oscillate, are transient, or persist for a longer period and exhibit specific "signatures". Both the input and efflux of Ca2+ from the cytosol affect the length and amplitude of the signal. According to several reports, under stress calcium alterations can occur not only in the cytoplasm of the cell but also in the cell walls, nucleus and other cell organelles and the calcium waves propagate through the whole plant. Here, we will focus on how wheat and other important crops absorb Na+, K+ and Cl- when plants are under salt stress, as well as how calcium, potassium, and pH cause intracellular signaling and homeostasis. Similar mechanisms in the model plant Arabidopsis will also be considered.

Finnish government's carbon neutrality goal by 2035 requires integration of renewable energy sources into the power grid. Considering the stochasticity of these resources, additional sources of flexibility are necessary to balance supply and demand in the power grid. District heating network (DHN) operators in Finland plan to shut down fossil-fuel-based combined heat and power plants and electrify heating systems by deploying heat pumps (HPs) and electric boilers. Techno-economic analysis and optimal operation of DHN-connected HPs and electric boilers in providing ancillary balancing services considering the 15-minute granularity in the balancing markets in Finland were investigated. The objective was to maximize the potential revenue for DHN operators gained from the day-ahead electricity market and frequency containment reserve (FCR) balancing markets. Three inter-connected DHNs in the Helsinki metropolitan area were optimized considering the reference year 2019 and each operator's decarbonization strategies for 2025. HPs could gain the highest profit from FCR-D up-regulation market, while the electric boiler may gain considerable profits from FCR-D down-regulation market. Compared to other balancing markets studied, the FCR-N market had a limited profit margin. Sensitivity analysis indicated that spot electricity prices and CO2 emission allowance prices have a significant impact on the profit from balancing markets.

The treasury of a DAO is purported to uphold the value of the DAO-issued token, and this study represents a pioneering effort to delve into these realms. We explore the relationship between the treasury and market capitalization in two DAO projects, namely Olympus DAO and KlimaDAO. Employing Granger Causality tests, we scrutinize the relationship between market capitalization and the treasuries of these DAOs. Furthermore, we use an EGARCH model to investigate the in-fluence of carbon offset tokens on KlimaDAO’s market capitalization, incorporating this variable into the model's conditional mean equation. The findings reveal a significant relationship between market capitalization and the treasuries of the DAOs, indicating a potential impact of market capitalization on treasuries. Additionally, the well-specified EGARCH model highlights the sig-nificance of carbon offset tokens, suggesting their potential to influence the overall market capi-talization of a DAO project and support its value.

The BP neural network and PSO algorithm are applied into analyzing the reliability of long-span Concrete Filled Steel Tubular (CFST) arch bridges. Firstly, using BP neural network to fit the structural performance function. And then the PSO method was used to calculate the reliability index. A long-span Concrete Filled Steel Tubular arch bridges reliability indices were calculated whether considering the geometric nonlinearity or not. The calculation and analysis results showed that the BP neural network and PSO algorithm compensated the deficiency of the traditional reliability analysis methods, improved the calculation accuracy, provided a new thought and means for the research on the reliability of long-span bridge structure, and well applied to the reliability analysis of long-span Concrete Filled Steel Tubular arch bridges. Additionally, the reliability analysis of long-span Concrete Filled Steel Tubular arch bridges on service limit state must consider the geometric nonlinearity effect, or the results will tend to be unsafe.

Despite significant strides in prevention, diagnosis, and treatment, cardiovascular diseases remain the number one cause of mortality in the United States, with rates climbing at an alarming rate in the developing world. Targeted delivery of therapeutics to the heart has been a lofty goal to achieve with strategies ranging from direct intra-cardiac or intra-pericardial delivery, intra-coronary infusion, to adeno-associated viral vectors which have preference, if not complete cardio-selectivity, for cardiac tissue. Cell penetrating peptides (CPP) are 5-30 amino acid long peptides that are able to breach cell membrane barriers while carrying cargoes up to several times their size, in an intact functional form. Identified nearly three decades ago, the first of these CPPs came from the HIV coat protein transactivator of transcription. Although a highly efficient CPP, its clinical utility is limited by its robust ability to cross any cell membrane barrier, including crossing the blood-brain barrier and transducing neuronal tissue non-specifically. Several strategies have been utilized to identify cell or tissue specific CPPs, one of which is phage display. Using this latter technique, we identified a cardiomyocyte targeting peptide (CTP) more than a decade ago, a finding that has been corroborated by several independent labs across the world that have utilized CTP for myriad different purposes in pre-clinical animal models. The goal of this publication is to provide a comprehensive review of the identification, validation, and application of CTP, and outlining its potential in diagnostic and therapeutic applications especially in the field of targeted RNA interference.

Organic electrochemical transistors (OECTs) based on conducting polymers have attracted significant attention in the field of biosensors. PEDOT:PSS and polyaniline (PANI) are representative conducting polymers used for OECTs. While there are many studies on PEDOT:PSS, there are not so many reports on PANI-based OECTs, and a detailed study to compare these two polymers has been desired. In this study, we investigated the fabrication conditions to produce the best performance in the OECTs using the above-mentioned two types of conducting polymers. Two main parameters were film thickness and film surface roughness. For PEDOT:PSS, the optimal conditions for fabricating thin films were a spin-coating rate of 3000 rpm and DI water immersion time of 18 hours. For PANI, the optimal conditions were a spin-coating rate of 3000 rpm and DI water immersion time of 5 seconds, and adding dodecylbenzenesulfonic acid (DBSA) was found to provide better OECT performances. The OECT performances based on PEDOT:PSS were superior to those based on PANI in terms of conductivity and transconductance, but PANI showed excellence in terms of film thickness and surface smoothness, leading to the good reproducibility of OECT performances.

This article presents a novel sustainable business management technique, emphasizing description and estimation over the outdated profit metric. Due to the intricacies and challenges of implementing the 2019 capital management method based on capital valuation (implemented in 2020–2022), a simpler approach became essential. While it is plausible for organizations to implement capital management based on their valuation, undertaking it with no outside help presents a challenge. The new descriptive method is fundamentally distinct in that detailed monetary valuations of capitals are omitted in favor of description and estimation. This paper establishes the groundwork for applying the new approach in several stages and introduces three new management indicators—the overall accomplishment of management goals index (evaluating management efficacy), the capital level index, and the adjustment (compliance) index—replacing the profit metric. Noteworthy advantages include separating the assessment of management outcomes from the organization's condition, including human and social capital into efficiency evaluations, and removing the profit indicator for management purposes, which prevents resource waste and enhances company efficiency and effectiveness.