3D/4D printing technologies are currently among the fastest growing, cutting edge fabrication technologies. The scale of their applications is vast and applicable to nearly all industries. 3D printing technologies are particularly popular in robotics, and especially in advanced design innovative solutions for areas such as manufacturing, space technology and medicine. The development of robotics, and in particular of the precision of manufactured components, such as actuators, pneumatic muscles, power transmission units, etc., means that new prototypes are still being made, where the use of 3D printers reduces the production time severalfold and allows for completing the necessary simulations and tests. In addition, the use of 3D printers allows for the production of thin-walled and cellular structures, which is a great advantage compared to conventional fabrication technologies. In the range of 3D printers available on the market, only a few selected technologies allow for actual use in the construction of advanced robot elements (muscles, vibration dampers, etc.). In the era of rapid growth of the precision of the available 3D printers and modern materials, 3D printing may soon become a major tool in robotics. This article presents an overview of 3D printing technologies and materials in terms of their application in robotics and provides examples of the use of 3D and 4D printing in prototyping and fabrication of robotic elements with particular emphasis on the current state of the art. The study considered the possibilities of using 3D/4D printing in robotics with the use of polymeric materials. The review of the literature and the research work currently being carried out in this area is very promising and it seems that 3D/4D printing in robotics is widely used and is still developing, which allows to conclude that in the near future the number of research works in this field will increase rapidly.

Tributyltin (TBT) is an environmental contaminant present on all continents, including Antarctica, with a potent biocidal action. Its use began to be intensified during the 1970s, being effectively banned in 2003, but remaining in the environment to this day due to several factors that increase its half-life and misuse despite the bans. In addition to the endocrine disrupting effect of TBT, that may lead to imposex induction in some invertebrate species, there are several studies that demonstrated that TBT also has an immunotoxic effect. The immunotoxic effects that have been observed experimentally in vertebrates using in vitro and in vivo models involve different mechanisms, but mainly alterations in the expression and/or secretion of cytokines. In this review, we summarize and update the literature on the impacts of TBT on the immune system, as well as discuss what still needs to be done to fill the knowledge gaps regarding the impact of this endocrine disrupting-chemical on immune system homeostasis.

Chronic gastroduodenal symptoms are prevalent worldwide, and there is a need for new diagnostic and treatment approaches. Several overlapping processes may contribute to these symptoms, including gastric dysmotility, hypersensitivity, gut-brain axis disorders, gastric outflow resistance, and duodenal inflammation. Gastric Alimetry® (Alimetry, New Zealand) is a non-invasive test for evaluating gastric function that combines body surface gastric mapping (high-resolution electrophysiology) with validated symptom profiling. Together, these complementary data streams enable important new clinical insights into gastric disorders and their symptom correlations, with emerging therapeutic implications. A comprehensive database has been established, currently comprising >2,000 Gastric Alimetry tests, including both controls and patients with various gastroduodenal disorders. From studies employing this database, this pa-per presents a systematic methodology for Gastric Alimetry test interpretation, together with an extensive supporting literature review. Reporting is grouped into four sections: Test Quality, Spectral Analysis, Symptoms, and Conclusions. This review compiles, assesses, and evaluates each of these aspects of test assessment, with discussion of relevant evidence, example cases, limitations, and areas for future work. The resultant interpretation methodology is recommended for use in clinical practice and research to assist clinicians in their use of Gastric Alimetry as a diagnostic aid, and is expected to continue to evolve with further development.

Reading is a complex cognitive task involving processes from different systems. The present work aims to identify some points of divergence reported in the reading literature and discuss them in a new experimental paradigm framework. Inspired by the paradigms of perceptual identification and rapid parallel presentation (RPVP), we emphasize that the originality of our experimental paradigm lies in the recruitment of multi-stable Arabic percepts within the region where low-level processing occurs (i.e., the visual span area). With good flexibility, the current paradigm has reached higher-order processing levels. In agreement with previous works highlighting the parafoveal-on-foveal effect, results suggest parallel word processing. Furthermore, they suggest a rapid extraction of syntactic and semantic information from words in sentences while attributing an advantage to semantic processing in the emergence of the sentence superiority effect.

Many parameters and complex boundaries are involved in the spatial arrangement of an under-ground powerhouse for a hydropower station, which requires reference to many relevant cases and specifications. However, in practical applications, retrieving relevant cases or specifications is difficult, and there is a lack of knowledge of cascading logic among design parameters. For this question, a targeted knowledge graph based on knowledge graph management technology is established to support subsequent applications. This paper proposes a new concept of con-structing a knowledge graph for building information modeling (BIM) underground power-houses of hydropower stations. Firstly, the ontology skeleton of hydropower station spatial ar-rangement design, which represents the knowledge organization structure of the knowledge graph, is reconstructed by carefully analyzing the requirements for intelligent modeling of un-derground powerhouses. A large amount of unstructured data is identified based on optical character recognition (OCR) technology and is divided into words to extract correlation knowledge based on THULAC. In the next step, the knowledge triad of the spatial arrangement of the underground powerhouse is extracted based on ChatGPT and stored in a Neo4j knowledge base to build a knowledge graph. Finally, the knowledge graph is serviced to realize the query of knowledge and parameter recommendation to assist the digital intelligent design of spatial arrangement of an underground powerhouse of pumped storage hydropower stations.

Electroencephalography (EEG) is essential for tracking brain activity and identifying seizure effects. However, epileptic behaviour can only be detected after a specialist has carefully analysed all EEG recordings along with a proper history of the patient. A skilled physician is required for the right epilepsy diagnosis and therapy. But most of the time, patients visit the clinician in the interictal stage with no proper history documented. Therefore, it was essential to the automatic prediction of stages of seizure. K nearest neighbours (KNN) and random forest (RF) models using raw EEG signals, preictal, ictal, postictal, and interictal stages were identified in this study. The possibility of these characteristics is explored by examining how well time-domain signals work in the prediction of epileptic stages using intracranial EEG datasets from Freiburg Hospital (FH), Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT), and Temple University Hospital (TUHEEG). To test the viability of this approach, two different types of simulations were carried out on three binary classifications (interictal vs. preictal, interictal vs. ictal, preictal vs. postictal, and interictal vs. postictal), and one four-class problem (interictal vs. preictal vs. ictal vs. postictal) was performed for each model. The average accuracy when using time-domain signals in the FH database was 90.5% and 75.0%; CHB-MIT was 92.87% and 75.9%; and TUHEEG was 94.46% and 76.8%, respectively, for the KNN and RF models.

Waste management is an unavoidable technological operation in the process of raw material extraction. The main characteristic of this technological operation is the handling of large quantities of waste material, which can amount to several hundred million cubic metres. Working with this amount of material usually requires high-capacity systems for excavation and loading, a large fleet of trucks for haulage, construction, and maintenance of a complex roads network, use of a significant area of land in order to achieve the required capacities, etc. At the same time, this operation must comply with all administrative and environmental standards. Therefore, optimising waste rock management (particularly haulage and dumping) has the potential to significantly improve the overall value of the project. This paper presents a hybrid model for the optimisation of waste dump design and site selection. The model is based on different mathematical methods (genetic algorithm, analytic hierarchy process and heuristic methods) adapted to different aspects of the problem. The main objective of the model is to provide a solution (in analytical and graphical form) for the draft waste dump design, on the basis of which the final waste dump design can be defined.

This paper discusses the mathematical modelling of exothermic explosions in a slab. This model is based on a nonlinear equation containing a nonlinear term related to Arrhenius, bimolecular, and sensitised laws of reaction kinetics. The absolute temperature can be obtained by solving the nonlinear equation using Akbari-Ganji’s method. The influence of the parameters Frank-Kamenetskii, activation energy and numerical exponent on temperature is discussed. The analytical results are compared with previous available analytical and numerical results ( Matlab). A satisfactory agreement is noted.

Surfactants are amphiphilic molecules and one of the most versatile products of the chemical industry. They can be absorbed at the air-water interface and can align themselves so that the hydrophobic part is in the air while the hydrophilic part is in water. This alignment lowers the surface or interfacial tension. Gemini surfactants are a modern variety of surfactants with unique properties and a very wide range of potential applications. Hexamethylene-1,6-bis(N-dodecyl-N,N-dimethylammonium bromide) is one such representative compound that is a better alternative to a single analogue. It shows excellent surface, antimicrobial, and anticorrosion properties. With a highly efficient synthetic method and a good ecological profile, it is a potential candidate for numerous applications, including biomedical applications.

Some evidence suggests that personality types are a useful construct to understand stress and coping. However, further research is needed, especially on academic stress. Our aim was to explore how personality types and gender relate to coping strategies for academic stress and perceived coping efficacy. A total of 810 university psychology students completed the NEO-FFI Inventory and the Coping Strategies Inventory. Post-hoc tests for MANOVA and ANOVA were performed, where personality types and gender were treated as predictors and use of coping strategies and perceived coping efficacy as criteria. Finally, a one-way ANOVA followed by post hoc comparisons was performed to analyse the associations between personality types and perceived coping efficacy. Those with personality types combining low neuroticism with high conscientiousness chose the most adaptive coping strategies and showed the highest levels of perceived coping efficacy, while those whose personality types combined high neuroticism with low conscientiousness opted for maladaptive coping strategies and presented the lowest level of perceived coping efficacy. As for gender, women chose emotional expression more frequently. The personality type classification provided useful information on individual differences in coping with academic stress, which can help guide specific strategies to manage it.

We previously showed that feeding mice a diet containing 1% mantle tissue decreased food consumption, leading to death. We also isolated and identified toxic substances in the mantle tissue. In the present study, we investigated the characteristics and stability of mantle tissue toxicity. Treatment of mantle tissue with 1 mM HCl, 1 mM NaOH, 1 mM dithiothreitol, and 1 mM H2O2 and heating did not reduce the toxicity of mantle tissue in mice. These results suggest that mantle toxins are stable in tissues, particularly when exposed to acidic and digestive enzymes. We examined whether mantle tissue exhibited acute toxicity. Diets containing 1% and 20% mantle extract showed similar levels of toxicity, demonstrating that feeding of mantle tissue does not lead to acute toxicity. Finally, we examined the toxicity of the mantle tissue against small intestinal tissue. Chronic feeding of mantle tissue to mice changed the color of the small intestine. Real-time PCR analysis showed that mantle tissue feeding caused changes of inflammation and endoplasmic reticulum stress markers in the small intestine. These results suggest that feeding of mantle tissue causes toxicity after causing initial damage to the small intestinal tissue.

The response of plasmonic metal particles to an electromagnetic wave undergoes significant features at the nanoscale level. Different properties of the internal composition of a metal, such as its ionic background and the free electron gas, begin to manifest more prominently. As the dimensions of the nanostructures decrease, the classical local theory gradually becomes inadequate. Therefore, Maxwellʹs equations need to be supplemented with a relationship determining the dynamics of current density which is the essence of nonlocal plasmonic models. In this field of physics, the standard (linearized) hydrodynamic model (HDM) has been widely adopted with great success, serving as the basis for a variety of simulation methods. However, ongoing efforts are also being made to expand and refine it. Recently, the GNOR (general nonlocal optical response) modification of the HDM has been used, with the intention of incorporating the influence of electron gas diffusion. Clearly, from the classical description of fluid dynamics, a close relationship between viscosive damping and diffusion arises. This offers a relevant motivation for introducing the GNOR modification in an alternative manner. The standard HDM and its existing GNOR modification also do not include the influence of interband electron transitions in the conduction band and other phenomena that are part of many refining modifications of the Drude‐Lorentz and other models of metal permittivity. In this article, we present a modified version of GNOR‐HDM that incorporates the viscosive damping of the electron gas and a generalized Drude‐Lorentz term. In the selected simulations, we also introduce Landau damping which corrects the magnitude of the standard damping constant of the electron gas based on the size of the nanoparticle. We have chosen a spherical particle as a suitable object for testing and comparing HD models and their modifications because it allows finding precise analytical solutions for the interaction and, simultaneously, it is a relatively easily fabricable nanostructure in practice. Our contribution also includes our own analytical method for solving the HDM interaction of a plane wave with a spherical particle. This method forms the core of calculations of the characteristic quantities, such as the extinction cross‐sections and the corresponding components of electric fields and current densities.

Extracellular vesicles (EVs) are emerging mediators of intracellular and inter-organ communications in cardiovascular diseases (CVDs), especially in the pathogenesis of heart failure through the transference of EV-containing bioactive substances. microRNAs (miRNAs) are contained in EV cargo and are involved in the progression of heart failure. Over the past several years, a growing body of evidence has suggested that the biogenesis of miRNAs and EVs are tightly regulated, and the sorting of miRNAs into EVs is highly selective and tightly controlled. Extracellular miRNAs, in particular circulating EV-miRNAs, have shown promising potential as prognostic and diagnostic biomarkers for heart failure and as therapeutic targets. In this review, we summarize the latest progress concerning the role of EV-miRNAs in HF and their application in a therapeutic strategy development for heart failure.

A new study for CH4 reforming to hydrogen and hydrogen storage was performed using magnesium-based alloy. MgH2-12Ni (with the composition of 88 wt% MgH2 + 12 wt% Ni) was prepared in a planetary ball mill by milling in hydrogen atmosphere (reaction-involved milling). X-ray diffraction (XRD) analyses were performed for the samples after reaction-involved milling and after reactions with CH4. The variation of adsorbed or desorbed gas with time was measured by a Sieverts’ type high-pressure apparatus at 773 K. The microstructures of the powders were observed using scanning transmission microscope (STEM) with energy-dispersive X-ray spectroscopy (EDS). The synthesized samples were also characterized using Fourier Transform Infrared (FT-IR) spectroscopy. XRD pattern of MgH2-12Ni after reaction with CH4 of 12 bar at 773 K and decomposition under 1.0 bar at 773 K exhibited phases of MgH2 and Mg2NiH4. This shows that reforming of CH4 was occurred, hydrogen produced after reforming of CH4 was then adsorbed on the particles, and hydrides were formed during cooling to room temperature. Ni and Mg2Ni formed during heating up to 773 K are believed to have brought about catalytic effects for reforming CH4. MgH2-12Ni adsorbed 0.8 wt% reformed CH4 within 1 min in a reaction with CH4 of 12 bar at 773 K and then desorbed 0.8 wt% reformed CH4 (hydrogen-containing mixture) within 1 min under 1 bar at 773 K. Attenuated total reflectance FT-IR spectroscopy (ATR-FTIR) spectra of MgH2-12Ni after reactions under 12 bar CH4 at 723 K and 773 K showed peaks of C-H bending, C=C stretching, O-H stretching, O-H bending, and C-O stretching.

Age-related macular degeneration (AMD) is a leading cause of irreversible blindness world-wide. We recently reported that polyethylene glycol (PEG) can activate the alternative pathway of the complement system and induce choroidal neovascularization (CNV) in mice. Currently, no other investigator has demonstrated CNV after PEG injection in the mouse eye. The aim of this article is twofold: we review the histologic changes in mouse retina and retinal pigmented epithelium (RPE) after treatment with PEG, and we summarize a model of wet and dry AMD pathogenesis in mice through subretinal PEG treatment of RPE cells and retinal layers. We injected (subretinal) male C57BL/6 mice with 2 μL of solution containing 0.5 mg and 1.0 mg of PEG or PBS in control groups. Eyes were harvested at day 1, 3 and 5 after injection and processed for analysis. Sections were immunohistochemically stained for complement component C3, mem-brane attack complex (MAC), and cytokeratin 18. Light and laser confocal microscopy was used for image capturing. PEG increased deposition of C3 and MAC on RPE cells and on all retinal layers after 1.0 mg injection. PEG induced loss of cellular contacts between RPE cells and migration of RPE cells in the subretinal space at day 1 after PEG injection. After 0.5 mg PEG injection, increased size of RPE cells was detected at day 3 and 5. Apoptotic bodies were observed in outer nuclear layer at day 3 and 5 after 0.5 mg PEG treatment. RPE cells with dark cytoplasm and condensed chromatin were observed. Higher doses of PEG induce CNV, encouraged RPE cell proliferation and death, and damage photoreceptors in mice. This simple and fast model may be useful to explore the pathogenesis of both dry and wet AMD.

Building Information Modelling (BIM) methodology have been optimizing the construction activity in all sectors: multidisciplinary designs development; construction planning and monitoring; building management and maintenance. A BIM environment aggregates several disciplines and different skillsets and in order to control and improve the quality of a BIM project, a BIM manager is required. The BIM manager has the responsibility to coordinate all tasks involved in a building design and associated activities usually workout over the project documents. The professional can access to various discipline models, located in a shared board, and request for amendments if inconsistencies are detected. The present study issue is illustrated with three building cases were distinct specific projects, disciplines and tasks were elaborated: collaboration between disciplines (architecture, structures and construction); structural analyses and reinforcement details; quantity take-off of materials and cost estimation; construction scheduling and simulation. Although there are limitations in the implementation of BIM methodology in all sectors and stages, within the construction industry, BIM have been bringing an important improvement in the quality of a building design, reflected in the quality of the final product. BIM methodology is a current demand in the construction industry supported on advanced technology and in an adequate management of projects, were the BIM manager has an important role.

Nanoparticles (NPs) have uniform chemical composition, size, and morphology. Microorganisms are of great interest in Nanoparticle synthesis. The green production of nanomaterials occurs either intracellularly or extracellularly. Gold and silver nanoparticles are mostly synthesised by the enzymatic degradation of metal ions. The produced NPs are characterized by different instruments such as ultraviolet visible, dynamic light scattering, x-ray diffraction, scanning electron microscope, transmission electron microscope, etc. Our review discusses the various biomedical applications of gold and silver nanoparticles synthesized by microbes via intracellular and extracellular mechanisms.

The surrounding rock during the coal mine excavation is prone to significant engineering disasters such as considerable deformation and rockbursts. Pressure release can improve the stress field of a deep rock mass and prevent the occurrence of dangers such as roadway collapse and coal and gas outbursts. This paper uses the ANSYS/LS-DYNA finite element software to simulate the crush area and fracture zone of a detonation charge with different diameters under in-situ stress. The stability of the surrounding rock was analyzed based on the impact stress and velocity, and was verified by field tests. The research results show that the blasting load primarily affects the damaged area near the borehole, while the in-situ stress affects the far-field crack propagation. The crack propagates in the direction of high surrounding rock pressure. When the uncoupling index is 1.5, the impact pressure of the 60 mm diameter cartridge is 8 times that of the 20 mm diameter cartridge. The impact speed can reach 2 times that of the 20 mm diameter cartridge. The high-energy event of the roof is transferred to the front of the working face, the distribution is no longer concentrated, and a better blasting pressure relief effect is achieved. The research results can help guide the prevention and control measures of rock bursts and other mining disasters.

This study examines the geopolitical dynamics of water conflicts in Central Asia, with a specific focus on Uzbekistan and its neighbors. Drawing upon a mixed methods approach within the framework of political geography, the research investigates the interactions among regional nations and the implications of population growth, agricultural industrialization, and economic competition, which heavily rely on shared irrigation systems and watersheds. The study establishes clear research objectives aimed at evaluating the water crisis in the region, addressing challenges in water management, and analyzing contentious issues. By uncovering historical and contemporary factors influencing water conflicts, regional power dynamics, and the complexities of water governance, the study highlights the potential for conflict, regional instability, and disruptions to peace resulting from population growth and economic competition within shared watersheds. The study concludes by providing recommendations to enhance regional cooperation, promote sustainable water management, and foster peacebuilding efforts. These recommendations draw on “soft power theory” and advocate for collaborative approaches. The findings of this research offer valuable insights for policymakers, researchers, and stakeholders involved in water management and regional cooperation amid evolving geopolitical challenges. By contributing to informed decision-making and promoting strategies for sustainable development in the region, this study aims to support efforts toward effective water resource management and long-term stability in Central Asia. The implications of this research extend beyond the immediate region, serving as a reference for other areas facing similar water-related conflicts and providing a foundation for future studies in the field of geography.

In this research, we investigate the healthcare expenditure patterns in Uzbekistan, analyze their economic implications, and provide policy recommendations. The study focuses on the time frame from 2000 to 2019, employing quantitative data analysis, theoretical frameworks such as Wagner’s Law, and an economic geography perspective. Our objective is to gain insights into the relationship between economic development and healthcare spending, identify spatial disparities, and forecast future trends. The findings reveal fluctuations in per capita healthcare spending, emphasizing the necessity for sustainable financing mechanisms and preventive measures. Ultimately, our study underscores the significance of aligning healthcare expenditure decisions with economic objectives while prioritizing the well-being of the population.

Background: The adoption of self-care behaviors among patients with arterial hypertension (AH) plays an important role in the management of their health condition. However, a lack of scales assessing self-care is observed. We aimed to develop and validate the Hippocratic hypertension self-care scale. Methods: From a pool of questions derived from a literature review, 18 items were included in the scale and reviewed by a committee of experts. Participants indicate the frequency at which they follow the self-behavior prescribed in each statement on a five-point Likert scale. Data were collected between April 2019 and December 2019. Re-sults: 202 consecutive adult patients with AH were enrolled in the study. The internal consistency of the scale was found to be 0.807, using Cronbach’s alpha coefficient. An exploratory factor analysis identified two do-mains that accounted for 92.94% of the variance of the scale items; however, each sub-scale could not be used as an independent scale. Finally, the test- retest of the scale showed a significant strong correlation (r=0.0095, p<0.001). Conclusion: Our data indicate that the scale is a reliable and valid tool for assessing self-behaviors in patients with AH. Health professionals can use it in their clinical practice to improve the management of patients’ health condition.

Paraffin wax stores energy in the form of latent heat at a nearly constant temperature during melting and releases this energy during solidification. This effect is used in industrial energy storage. An unusual change in the shape of a melted droplet of paraffin wax placed on a relatively cold glass plate is studied. As the droplet solidifies, its upper surface becomes nearly flat and a dimple is formed in the center of this surface, making the droplet look like a fruit (pumpkins are more commonly shaped like this, but the authors prefer apples). A series of experiments, as well as physical and numerical modeling of the droplet's thermal state, taking into account the formation of a mushy zone between liquidus and solidus, made it possible to understand the role of gravity and gradual increase in viscosity and density of paraffin wax on changing the droplet shape and, in particular, to clarify the mechanism of formation of the dimple on its upper.

This paper pioneers a novel exploration of environmental impacts in livestock farming, with a focus on pig farming's intersection with climate change and sustainability. It emphasizes the transformative potential of data-driven Artificial Intelligence (AI) methodologies, specifically the Internet of Things (IoT) and multimodal data analysis, in promoting equitable and sustainable food systems. The study observes five pigs, aged 86 to 108 days, using a tripartite sensor that records heart rate, respiration rate, and accelerometer data. The unique experimental design alternates between periods of isolation during feeding and subsequent pairing, enabling the investigation of stress-induced changes. Key inquiries include discerning patterns in heart rate data during isolation versus paired settings, fluctuations in respiration rates, and behavioral shifts induced by isolation or pairing. The study also explores potential detection of gait abnormalities, correlations between pigs' age and their gait or activity patterns, and the evolution of pigs' walking abilities with age. The paper scrutinizes accelerometer data to detect activity changes when pigs are paired, potentially indicating increased stress or aggression. It also examines the adaptation of pigs to alternating isolation and pairing over time, and how their heart rate, respiration rate, and activity data reflect this process. The study considers other significant variables, such as time of day and isolation duration, affecting the pigs' physiological parameters. Sensor data is further utilized to identify behavioral patterns during periods of feeding, isolation, or pairing. In conclusion, this study harnesses IoT and multimodal data analysis in a groundbreaking approach to pig welfare research. It underscores the compelling potential of technology to inform about overall pig welfare, particularly stress levels and gait quality, and the power of data-driven insights in fostering equitable, healthy, and environmentally conscious livestock production systems.

A modified Nambu{Jona-Lasinio Model with lattice structure is very instructive. It shows several similar problems and their solutions as the Lattice QCD. We study the limits of the large box size, small cell size and realistic pion mass. In particular, we study the relation of the discrete (bound state) solutions to the physical scattering states, for example the pion-pion scattering.

Bee products have a millennial tradition in human use due to their numerous heal-ing properties. The paper presents the chemical characterization, antioxidant, anti-microbial and anti-inflammatory potential of royal jelly, apilarnil and propolis. These were obtained in the Banat area, Romania, in 2022. Royal jelly and apilarnil were analyzed in pure and lyophilized form and propolis in pure form and tincture. The percentage of moisture, dry matter, pH, acidity, content of impurities, sugars, proteins, ash, macro and micro minerals, total amino acids, polyphenols and flavo-noids were studied. The samples analyzed by us have a very well developed antiox-idant and according to the analysis of the mineral content of beekeeping products, an increased variability of macro and microminerals was determined, but also the lack of Pb in their composition. The flavonoid content of the samples was between 2.61519 mg QE/g sample for commercial pure apilarnil and 279.56115 mg QE/g sample for propolis harvested in 2021, and that of polyphenols between 0.63507 mg QE/g sample for natural royal jelly and 42.82186 mg QE/g sample in propolis with harvest in 2021. Propolis acts as a good antimicrobial and antiinflammatory agent, a fact that deserves to be researched in detail and exploited as a product with an ap-itherapeutic role for various microbial and inflammatory conditions.

Purpose: Social responsibility has been accepted as a core value of nursing profession, particularly in the area of health disparity, but it seems to be difficult to understand for what is meant by social responsibility. The purpose of this study was to explore ways to define the concept of social responsibility of nursing in order to understand the meaning of social responsibility in the field of nursing profession. Methods: The concept analysis process by Walker and Avant was used to clarify the meaning of social responsibility of nursing. Results: Defining attributes of social responsibility of nursing included praxis, as approach to strategizing for social and structural change of inequity, care for an oppressed group which is under social suffering caused by the privilege and power, and action for health policy change in social and political unequal contexts. The antecedents of social responsibility of nursing included reflectivities in identifying personal characteristics, taking seriously the perspective of other vulnerable population, recognizing social environmental status quo (‘fair or unfair’), developing competences in ethical and moral reasoning with social issues. Consequences of social responsibility of nursing were achieving social justice, as equal access to basic human health need in societal level, equal access to effective nursing practice delivery system and development of health promotion policy for world health administrative practices (“health for all”) in nursing. Conclusion: This study provides a guidance to direct future studies through the procedure of identifying conceptual attributes in the context of social responsibility of nursing. Future studies are suggested to develop instruments for social responsibility as well as development of educational programs to promote social responsibility competences in nursing students and nurses.

GI endoscopy forms an important part in a daily practice of a gastroenterologist. Musculoskeletal injuries related to GI endoscopy are on the rise. Observational studies and surveys depict the importance of proper ergonomical environment when performing GI endoscopy. Our aim is to outline preventive measures in gastrointestinal (GI) endoscopy in reducing possibility for occupational injury. We review most relevant studies that outline the gravity of the problem. A detailed analysis of proposed ergonomical recommendations is performed, outlining crucial steps in injury prevention. Proper ergonomical education is a key-step in preventing occupational injury. Robotics and other mechanical solutions offer a variety of approaches tackling the ergonomical challenge. Implementing proper ergonomical education and mechanical solutions lowers the possibility if occupational injury. Strategies and appliances presented are beneficial to all GI endoscopy practitioners.

In this paper, we present a new stress calculation method for flexible structures, particularly, the tensile armors, and apply it to flexible riser fatigue analysis. The method is based on a 3-dimensional curved bar theory. First, the tensile armor center line was described as a cylindrical helix curve, its bended curve length and bending migration length were derived and studied under different friction scenarios. Second, the tensile and bending stiffness was given with consideration of frictional hysteretic effect, and verified through FEA analysis results. Third, we presented the stress calculation formula for tensile armor under tension and bending load. All stress components are considered, including tensile, bending and shear stresses. Fourth, the method was benchmarked with published experimental results on a flexible prototype tension and bending tests, and comparisons showed general agreements. Fifth, the method is further applied to a 8” flexible riser for fatigue assessment and lifetime extension evaluation, and showed the flexible riser has sufficient remaining fatigue life, and is suitable to continue its service under the current operating conditions. Last, conclusions are drawn. It concluded that the presented tensile armor stress calculation method and modelling techniques are valid for flexible riser fatigue analysis. This method is time efficient, and can be implemented into other multi-scale models for riser dynamic analysis. It is also applicable to other similar helix structure stress analysis, such as wire ropes, submarine hoses, and subsea umbilicals.

An airfoil is the geometric shape of a cross-section of a wing. When it is exposed to the flow of a fluid over its surface, it generates both lift and drag forces through a pressure distribution. Designing an efficient airfoil for aerodynamic applications is a complex challenge in the field of aerodynamic engineering, with the aim of achieving an optimal lift-to-drag ratio. The success of airfoil design hinges on the effective reduction of drag force under specific conditions, while simultaneously attaining the desired lift without encountering significant flow separation, such as boundary layer shedding. Furthermore, the design must adhere to lifting force limitations and meet structural requirements. In the field of airfoil design and optimization, literature review articles provide a valuable resource by offering an overview of the latest advancements in specific areas. These areas encompass a wide range of topics including the design and testing of adaptive geometry wings, such as morphing wing technology as well as the application of shape optimization techniques to enhance airfoil performance. Our goal is to provide researchers with an in-depth review of relevant articles published to date, examining the applied approaches utilized to tackle the complex problem of airfoil design and explore the methodology employed to address it, from a broad perspective on the topic.

The purpose was to reflect on the sustainability of artisanal and informal mining in the Peruvian Andean zone by 2022. The type of research was basic, non-experimental design, ex post facto scope. The sample consisted of: statistics on crime prevention due to socio-environmental conflicts from the National Prosecutor's Office and the Ombudsman's Office, reports of interventions targeted at artisanal and informal miners. The procedure focused on gathering secondary information for a documentary review analysis that is based on proven and disseminated past facts. Artisanal and informal mining is strengthened in the Peruvian Andean zone by incidence and force: 1) the social license and agreements by community assembly, 2) the flexibility in compliance with the formalization, preventive and environmental protection laws, 3) the 50% increase in socio-environmental conflict due to mining activity, 4) a 25% progressive increase in the production costs of agricultural and livestock activities. The direct consequences on environmental sustainability are: 1) the delimited reconversion of the change in agricultural land use in a third of the communal territories in basin headwaters; 2) displacement of environmentally friendly economic activity by 20% in basin headwaters; 3) the impossibility of modification or intervention in water surfaces, bofedales by communal agreements.

Earth Observation (EO) techniques have significantly evolved over time, covering a wide range of applications in different domains. The scope of this study is to review the research conducted on EO in the Eastern Mediterranean, Middle East, and North Africa (EMMENA) region and to identify the main knowledge gaps. We searched through the Web of Science database for papers published between 2018 and 2022 for EO studies in the EMMENA. We categorized the papers in the following thematic areas: Atmosphere, Water, Agriculture, Land, Disaster Risk Reduction (DRR), Cultural Heritage, Energy, Marine Safety and Security (MSS) and Big Earth Data (BED); 6647 papers were found with the highest number of publications in the thematic areas of BED (27%) and Land (22%). Most of the EMMENA countries are surrounded by sea, yet there was a very small number of studies on MSS (0.9% of total number of papers). This study detected a gap in fundamental research in the BED thematic area. Other future needs identified by this study are the limited availability of very high resolution and near real time remote sensing data, the lack of harmonized methodologies and the need for further development of models, algorithms, early warning systems and services.

Floating Offshore Wind Turbine (FOWT) is an innovative technology with little industry guidance for its hull design. Various FOWT floaters with different hull shapes claim to support the same turbines. Structural integrity and material expense analyses of different pontoon shapes were conducted, and it was found that some configurations, such as those with every two columns connected by both pontoon and bracing, have advantages over others. However, it is important to note that the choice of pontoon shape should be based on the wave loading conditions the floater will be exposed to. While a T-shaped pontoon provides a cost-effective solution under certain wave loading scenarios, it may not be the best option for all conditions. Specifically, ring pontoon designs with full bracing were found to be necessary for withstanding certain wave loads. Therefore, it is important to consider different Dominant Load Parameters (DLP) and ensure that a FOWT floater can withstand all applicable DLPs. An uneven hexahedral column shape, which combines the best attributes of square and round shapes, is proposed as a better alternative to cylindrical columns. It offers ease of manufacture and reasonably low drag. Bracing is found to be necessary for withstanding the wind turbine’s incurred moment and forces. The conclusion is that platform design should prioritize manufacturing costs and strength over maximizing hydrodynamic performance.

: An innovative and stable probiotics-containing mucoadhesive gel (AL0020), integrated with botanical extracts, has been developed to rebalance the dysbiosis associated with periodontal diseases. Tau-Marin gel was tested against some pathogenic bacteria, belonging to the so-called "red complex", recognized as the most important pathogens in plaque specimens, adherent to the epithelial lining of periodontal pockets. A detailed physico-chemical profile of AL0020 and its in vitro efficacy in protecting activity against pathogenic bacteria as well as soothing or irritative effect on gingival epithelium were reported. Moreover, a clinical-dermatological trial on 20 volunteers using the product once a day for 30 days was also performed.

The magnetic properties of RCo3B2 compounds, with heavy rare earths, are investigated by using magnetic measurements and electronic structure calculations. The cobalt sublattice magnetizations are very small and antiparallel oriented to rare earths moments. Contributions of cobalt moments to the Curie constants were also shown. The cobalt magnetic behavior has been analyzed in spin fluctuations model. The presence of short-range order above the Curie temperatures in RCo3B2 compounds with R=Tb, Dy, and Ho has been attributed to reminiscent R5d-Co3d interactions.

Our ability to cure common diseases is still in danger due to the creation and spread of bacteria and fungi that are resistant to drugs and has developed new resistance mechanisms. The increasing global expansion of multi- and pan-resistant bacteria commonly referred to as "superbugs," which cause diseases that cannot be treated with current antimicrobial medications like antibiotics, is particularly concerning. Indirect and direct risks to public health are posed by microorganisms that are resistant to antibiotics in food. Food can get contaminated via cross-contamination, intentionally introducing resistance genes during food preparation, and antibiotic-resistant bacteria in food. Consuming unprocessed or unpreserved food products increases the danger of transferring antimicrobial resistance to people and other animals. Stressed cells in food can have an impact on food quality, safety, and security. They can also contribute to the development of resistance and afterwards spread it to unintended organisms in the food chain. These reviews look at a variety of topics to address the question of how antimicrobial resistance mechanisms work. The various types of bacteria that make up infections are examined, as well as the usage of antimicrobial agents and the requirement for alternative antimicrobial agents that will discourage the use of synthetic antimicrobial agents. Additionally, specific details are provided regarding the uniqueness, interdependence, and phylogenicity of organisms as well as their interactions with various ecological media. Thus, it is clear why it is important to work with food producers and handlers to stop the spread of pathogenic organisms.

Visual impairment and blindness are a growing public health problem, as they reduce the quality of life of millions of people. The management and treatment of these diseases represent a scientific and therapeutic challenge, since the different cellular and molecular actors involved in the pathophysiology are still being identified. The visual system components, particularly the retinal cells, are extremely sensitive to genetic or metabolic alterations, and immune cells activated by insults contribute to biological events that culminate with vision loss and irreversible blindness. Several ocular diseases are linked to retinal cell loss, and diseases such as retinitis pigmentosa, age-related macular degeneration, glaucoma and diabetic retinopathy are characterized by pathophysiological hallmarks that represent possibilities to study and develop novel treatments for retinal cells degeneration. Here, we present a compilation of revisited information on retinal degeneration, including pathophysiologic and molecular features, biochemical hallmarks and possible directions for novel treatments, aiming to assist as a guide for innovative research. The expansion of knowledge of the mechanistic bases of the pathobiology of eye diseases, including information on the complex interactions of genetic predisposition, chronic inflammation, and environmental and aging-related factors will allow the identification of new therapeutic strategies.

Air pollution is related to the development of people's livelihood. As one of the main pollutants in the air, formaldehyde affects people's physical and mental health. In order to remove formaldehyde and better protect the health of residents, it is very necessary to develop efficient adsorption materials. In this study, a cellulose composite aerogel Microcrystalline Cellulose/ N-(2- aminoethyl) -3- aminopropyl methyl dimethoxysilane (MCC/APMDS) modified by APMDS was explored. The pore volume and specific surface area of the modified aerogel decreased, the average pore diameter increased, and the adsorption capacity of formaldehyde was stronger. The adsorption experiment shows that the sample prepared under the conditions of APMDS dosage of 6 wt%, reaction time of 4 h and reaction temperature of 90℃ has the largest average pore size (14.56 nm) and the largest formaldehyde adsorption capacity (9.52 mg/g). The excellent adsorption of the composite aerogel is due to high porosity and rich active amino groups on the surface. This study provides valuable information for the preparation of adsorption materials with high formaldehyde adsorption capacity for air purification.

The straightness error of guideway is one of the key indicators of ultra-precision machine, which plays an important role in the machining accuracy of work-piece. In order to measure straightness error of long distance ultra-precision guideway accurately, a splicing measurement for straightness error of guideway using high-precision flat mirror and displacement sensor was proposed in this paper, and the data splicing processing algorithm based on coordinate transformation was studied. Then comparative experiments on splicing measurement and direct measurement of straightness error were carried out on a hydrostatic guideway grinder. The maximum difference between the two measurements was about 0.3μm, which was far less than the straightness error of 5.8μm. The experiment demonstrated the correctness of the proposed splicing measurement method and data processing algorithm. To suppress the influence of straightness error on machining accuracy, a straightness error compensation algorithm based on error rotation transformation and vertical axis position correction was proposed, and the grinding experiment of a plane optics with size of 1400mm×500mm was carried out, whose flatness error after grinding was about 2.98μm. The straightness error of the grinding machine had been well suppressed.

World health is increasingly threatened by the growing number of spice-related food hazards. Further development of reliable methods for rapid, non-targeted identification of counterfeit ingredients within the supply chain is needed. ENEA has developed a portable, user-friendly photoacoustic laser system for food fraud detection, based on a quantum cascade laser and multivariate calibration. Following a study on the authenticity of saffron, the instrument was challenged with a more elusive adulterant, olive leaves in oregano. The results show that the reported method of laser sensing and chemometric analysis was able to detect adulterants at mass ratios of at least 20% in less than five minutes.

Second-level hospitals face peculiarities that hinder the implementation of the hearing rescreening protocol, which are not uncommon in other settings. This study analyzes the hearing rescreening process in this kind of hospital. A total of 1130 individuals were included. In this cohort, 61.07% were newborns in the hospital who failed their first otoemission test after birth (n=679) or were unable to have the test performed (n=11), then being referred to outpatient clinic. The remaining 38.93% were individuals who were born in another hospital with their first test conducted in the outpatient clinic (n=440). A high amount of rescreenings were made outside the recommended time frame, mainly in children referred from another hospital. There was a high rate of lost to follow-up especially with otolaryngologist referrals. Neonatal Hearing screening in second level hospitals is difficult because of the staffing and time constraints. This results in longer than recommended turnaround times and interferes with the timely detection of hearing loss. This is particularly serious in outpatients. Referral of children with impaired screening to out-of-town centers leads to unacceptable loss of follow-up. A legislative support for all these rescreening issues is necessary. We discuss these findings and propose some solutions.

This paper begins with an introduction to porcelain tiles. A review of the major scientific and technological features of the mullite−based porcelain tile (MPT) and anorthite−based porcelain tile (APT), focusing primarily on the raw material, processing, phase evolution and mechanical behavior, is then presented. Based on the porcelain tile firing behavior and a series of physical and chemical changes that can occur, a comprehensive comparison is described. In the last part, the prospects for further developments related to MPT and APT are discussed.

Due to the special characteristics of the shooting distance and angle of remote sensing satellites, the pixel area ratio of ship targets is small and the feature expression is insufficient, which leads to unsatisfactory ship detection performance and even situations such as missed detection and false detection. In this study, we propose an improved-YOLOv5 algorithm. The improvement strategies mainly include: (1) Add the Convolutional Block Attention Module (CBAM) into the Backbone to enhance the extraction of target-adaptive optimal features; (2) Introduce cross-layer connection channel and lightweight GSConv structure into the Neck to achieve higher-level multi-scale feature fusion and reduce the number of model parameters; (3) The Wise-IoU loss function is used to cal-culate the localization loss in the Output, and assign reasonable gradient gains to cope with dif-ferences in image quality. In addition, during the preprocessing stage of experimental data, a me-dian and bilateral filter method is used for noise reduction to reduce interference from ripples and waves and highlight the information of ship features. The experimental results show that Im-proved-YOLOv5 has a significant improvement in recognition accuracy compared to various mainstream target detection algorithms; Compared to the original YOLOv5s, the mean Average Precision (mAP) has improved by 3.2% and the Frames Per Second (FPN) has accelerated by 8.7%.

The relationship between child psychology and the widespread usage of mobile devices in the modern day is examined in "The Mobile Dilemma: Child Psychology and the Era of Technological Dependence." The abstract serves as a brief synopsis of the work, highlighting its important ideas and arguments. Concerns concerning the effects of excessive time spent on mobile devices on children's mental health and development have arisen in this age of technology dependency. The essay opens by pointing out the importance of investigating the psychological effects of kids' exposure to mobile gadgets. The effects of mobile phone addiction on learning, memory, and social and emotional health are investigated. The neurodevelopmental implications are explored further in the abstract, with a focus on the impact of mobile technology on brain plasticity and the formation of the developing brain. It offers advice on how to establish appropriate limits for children's screen time, encourages the development of digital literacy, and promotes responsible behavior.The pros and cons of using mobile devices in the classroom are also examined, along with their effects on students' ability to study and the risks and difficulties that could arise from implementing such a strategy. The emotional and social impacts of mobile device addiction are discussed in the abstract. This includes the impact on one's social life, empathy, ability to communicate, and sense of self-worth. The abstract also stresses the importance of interdisciplinary efforts involving parents, teachers, psychologists, and legislators to combat mobile device addiction through intervention and preventative techniques. Future directions are highlighted, with a focus on topics such as mobile technology development, digital well-being, privacy protection, mental health implications, screen time limits, digital literacy, and the impact of cultural and socioeconomic variables.

Atopic dermatitis (AD) is a chronic inflammatory skin disease characterized by itching, impaired epidermal barrier function and unbalanced inflammatory response. The pathophysiology involves immune dysregulation, with a predominance of T-helper 2 cells. AD is triggered by many known and unknown factors, including oxidative stress. Reactive oxygen species (ROS) contribute to AD pathogenesis by causing cellular damage and inflammation. Moreover, increased oxidative stress in AD leads to hyperactivation of the MAP kinase pathway, extracellular signal-regulated kinase (ERK) and p38, with DNA damage and subsequent skin barrier dysfunction. This narrative review provides a comprehensive overview of the role of natural antioxidant compounds, highlighting their potential therapeutic value in AD management. They include vitamin D, vitamin E, pyridoxine (vitamin B6), Vitamin C, carotenoids and melatonin, in AD. Despite some studies have shown an association between vitamin D, vitamin E, vitamin C and carotenoids levels and AD course, conflicting results exist. Pyridoxine supplementation has shown mixed results, and melatonin has demonstrated antioxidant and anti-inflammatory properties in AD; in fact, melatonin treatment resulted in a decrease in symptoms in patients with AD, although no significant correlation with changes in sleep latency was reported. In addition, iron and zinc (Zn) supplementation can also improve AD symptoms. Further research is needed to elucidate the optimal use of these natural antioxidants in AD treatment

Much evidence reveals an important link between gut microbiota and the heart. In particular, the gut microbiota plays a key role in the onset of cardiovascular (CV) disease, including heart failure (HF). In HF, splanchnic hypoperfusion causes intestinal ischemia resulting in the translocation of bacteria and their metabolites into the blood circulation. Among these, the most important is the Trimethylamine N-Oxide (TMAO), which is responsible through various mechanisms for pathological processes in different organs and tissues. In this review, we summarise the complex interaction between gut microbiota and CV disease, particularly with HF, and the possible strategies to influence its composition and function. Finally, we highlight the potential role of TMAO as a novel prognostic marker and new therapeutic target of HF.

On-stream inspections are the most appropriate method for routine inspections during plant operation without going through production downtime. Ultrasonic inspection, one of the on-stream inspection methods, faces challenges when performed at high temperatures exceeding the recommended 52°C. This study aims to determine the ultrasonic velocity and attenuation with the known material grade, thickness, and temperatures by comparing theory calculation versus experiment with temperatures ranging between 30°C to 250°C on low carbon steel covering most petrochemical equipment material and working conditions. The theoretical analysis was to obtain Young's modulus, Poisson's ratio, and longitudinal velocity at different temperatures. The experiments validated the predicted results of ultrasonic change due to temperature increase and showed a maximum error of 3%. The experimental data of velocity and decibel change from the temperature range provide a reference for the future when dealing with unknown materials information on site that require a quick corrosion status determination.

Alberta Cancer Exercise (ACE) is an exercise oncology program that transitioned from in-person to online delivery during COVID-19. The purpose of this work was to understand participants’ experiences in both delivery modes. Specifically, survivors' exercise facilitators and barriers, delivery mode preference, and experience with program elements targeting behaviour change were gathered. A retrospective cohort design using explanatory sequential mixed methods was used. 57 participants completed a survey, and 19 subsequent, optional interviews were conducted. Most participants indicated preferring in-person programs (58%), followed by online (32%), and no preference (10%). There were significantly fewer barriers (i.e., commute time) (p<0.01), but also fewer facilitators (i.e., social support) (p<0.01), to exercising online. Four themes were generated from the qualitative data surrounding participant experiences in both delivery modes. Key differences in barriers and facilitators highlighted a more convenient experience online relative to a more socially supportive environment in-person. For future work that includes solely online, focusing on building social support and a sense of community will be critical to optimizing program benefits. Beyond the COVID-19 pandemic, results of this research will remain relevant as we aim to increase the reach of online exercise oncology programming to more underserved populations of individuals living with cancer.

Psoriatic arthritis (PsA) is a persistent, inflammatory disease that affects individuals with psoriasis, arthritis, and enthesitis. Research has demonstrated that inflammatory cytokines such as tumor necrosis factor-alpha (TNF-α), interleukin-23 (IL-23), and interleukin-17 (IL-17) play a pivotal role in both the onset and progression of PsA. These cytokines are generated by activated immune cells and stimulate the attraction of inflammatory cells to the synovium and joint tissues, resulting in the deterioration of cartilage and bone. The blocking of these cytokines has become a successful treatment strategy for PsA, as biological drugs that inhibit TNF-α, IL-23, and IL-17 have demonstrated notable clinical benefits. The association between PsA and other types of inflammatory cytokines or chemokines, excluding TNF-α, IL-23, and IL-17, has been extensively investigated in numerous studies. These findings may provide a chance for the discovery of novel therapeutic agents targeting other molecules, distinct from the currently approved biologics and targeted synthetic disease-modifying antirheumatic drugs. In this review, we discuss the current understanding of the role of inflammatory cytokines in PsA pathogenesis and clinical implications of targeting these cytokines for PsA treatment.

Gliomas, which arise from glial cells in the brain, remain a significant challenge due to their location and resistance to traditional treatments. Despite research efforts and advancements in healthcare, the incidence of gliomas has risen dramatically over the past two decades. The dysregulation of microRNAs (miRNAs) has prompted the creation of therapeutic agents that specially target them. However, it has been reported that they are involved in complex signaling pathways that contribute to the loss of expression of tumor suppressor genes and the upregulating of the expression of oncogenes. In addition, numerous miRNAs promote the development, progression, and recurrence of gliomas by targeting crucial proteins and enzymes involved in metabolic pathways such as glycolysis and oxidative phosphorylation. However, the complex interplay among these pathways and other obstacles hinder the ability to apply miRNA targeting in clinical practice. This underscores the importance of pinpointing miRNAs to be targeted for therapy and having a complete understanding of the diverse pathways they are involved in. Therefore, the aim of this review is to provide an overview on the role of miRNAs in the progression and prognosis of gliomas, emphasizing the different pathways involved and identifying potential therapeutic targets.

Feedback trading theory is one of the most primitive theories about financial market. But for a long time，researches and modelings on this topic are rarely seen. The model in this paper shows the effects of sentiment shocks on asset prices in a market characterized by feedback trading in the long run. We find that，generally，feedback trading will lead to cognitive bias effect and trading inducement effect. Cognitive bias effect increases with the feedback trading parameter ( FTP) . In our model，the abnormal volatility of asset prices is captured by cognitive bias effect，sentiment shock effect and trading inducement effect．

Since the 20th century, Japan has experienced a period of very rapid urbanization. Cities have experienced substantial densification and expansion, resulting in gradually elevated flood risk. Urban flooding has also occurred in most large cities in Japan, particularly in Tokyo. In response to this growing problem, much effort and resources have been spent on research and development aimed at understanding, simulating, and managing urban flood risk in Japan. The objective of this review is to summarize, discuss and share key outputs from some of the main research directions in this field, significant parts of which have been uniquely developed in Japan and only published in Japanese. After a general introduction to urban runoff modelling, in the next section, key historical works in Japan are summarized, followed by a description of the situation in Japan with respect to observations of precipitation and water level. Then, the storage function model approach is reviewed, including an extension to urban basins, as well as recent experiments with AI-based emulation in Japanese basins. Subsequently, we review the prospects of detailed hydrodynamic modelling involving high-resolution, vector-based Geographical Information System (GIS) data for the optimal description of the urban environment with applications in Tokyo. We conclude the paper with some future prospects related to urban flood risk modelling and assessment in Japan.

The 2022-2023 Chilean summer showed increased temperatures and similar burned area, compared to the 2016-2017 season, where more than 500,000 hectares were compromised, mainly in the rural areas. After a brief review, it is revealed that the effects of forest fires on soil and hydrological properties are barely debated in Chile. Here, we showed a climatological analysis where temperature records in the 2016-2017 season were unusual, as well as another unexpected increase in the summer of 2022-2023, resulting in high-severity fires known as ‘mega-fires’ or “storm-fires”. Mega-fires affect forest plantations and native forests mainly from 33º S (Maule Region) to 39º S (Los Ríos Region) and they are expected to become frequent due to climate change, moving from the north to the south. We present an overview of the influence of wildfires on soil components in the most affected areas (inland, Coastal, and Andes ranges), their hydrological impacts, and potential erosion risk due to high winter precipitation. We propose several management practices that could help to prevent or mitigate these events, including pre-and post-fire interventions, such as afforestation and seeding, selective logging, mulching, erosion barriers, soil preparation, and dam monitoring. We argue that any effective plan in fire-prone and affected areas should include a combination of actions taken at the hillslope scale at integral ecosystem management, whose effectiveness should be monitored and verified regionally at the watershed scale.

Construction productivity entails a wide range of work combinations. When human resources are scarce, it is critical to replace manpower with machinery, and calculating machinery productivity is crucial. Traditional labor productivity methods, however, cannot address dredging complex multi-attribute decision-making (MADM) problems. Aiming to address the limitations of the traditional labor productivity method, this paper extends the data envelopment analysis (DEA) and proposes a new dredging productivity evaluation method. The proposed method can solve the problem of evaluating various combinations of factors (single-input, multiple-input, sin-gle-output, and multiple-output) and the problem suggesting that the efficiency of the DEA method'scalculation results is equal to 1. The effectiveness of the proposed method was verified using reservoir dredging examples. The simulation results show that the proposed method has broad applicability, can accurately evaluate the related dredging performance issues, and provide directions for construction managers to improve labor productivity.

Adult T-cell leukemia (ATL) is an aggressive hematologic disease caused by human T-cell leukemia virus type 1 (HTLV-1) infection. Various animal models of HTLV-1 infection/ATL have been established to elucidate the pathogenesis of ATL and develop appropriate treatments. For analyses employing murine models, transgenic and immunodeficient mice are used because of the low infectivity of HTLV-1 in mice. HTLV-1 Tax and HBZ transgenic mice spontaneously develop tumors, and roles for both Tax and HBZ in cell transformation and tumor growth have been established. Severely immunodeficient mice were able to engraft ATL cell lines and have been used in preclinical studies of candidate molecules for the treatment of ATL. HTLV-1-infected humanized mice with an established human immune system are a suitable model to characterize cells in the early stages of HTLV-1 infection. This review outlines the characteristics of mouse models of HTLV-1 infection/ATL and describes progress made in elucidating the pathogenesis of ATL and developing related therapies using these mice.

Jatropha curcas is a potential energy crop and has been identified as a significant resource for biodiesel. Retrotransposons occupy the plant genome in a large proportion, so the specific retrotransposon characterization will help improve understanding of the Jatropha genome evolution and organization. This research aimed to characterize and classify Ty1-copia retrotransposons in J. curcas using specific gene sequence and to detect the distribution of Ty1-copia in J. curcas and J. integerrima chromosomes using florescence in situ hybridization (FISH) method. Ty1-copia sequences from J. curcas were isolated using three degenerate primer sets specific to the conserved Ty1-copia reverse transcriptase gene for polymerase chain reaction (PCR). FISH technique using the Ty1-copia probes was used to map physically on J. curcas and J. integerrima chromosomes. Altogether, 164 Ty1-copia sequences were obtained to use for the phylogenetic analysis and were classified into the four families of TAR, Angela, Ale and Bianca. Physical map using FISH method of Angela and Ale families on J. curcas and J. integerrima chromosomes exhibited biases for specific regions around the centromeres or at the chromosome terminal regions. The study indicates the high variation of the Ty1-copia elements in the genome of Jatropha. These results will enhance understanding of retrotransposon chromosomal distribution and evolution of the J. curcas genome and also promotion of retrotransposon possible utilization in J. curcas improvement projects using retrotransposon-based markers.

This article explores the behavioral geography of the Hajj pilgrimage, focusing on the impact of the physical environment on pilgrims' behavior. Using qualitative research and analyzing religious literature and online publications, the study reveals significant findings. The spatial arrangement of the Grand Mosque, including the central courtyard and pillars, influences pilgrims' behavior during the Tawaf ritual. Environmental factors such as crowds and noise affect pilgrims' experiences, evoking anxiety while enhancing the ceremony's spiritual significance. Cultural and religious beliefs also shape pilgrims' behavior during the circumambulation. This study provides valuable insights into the multifaceted factors shaping pilgrims' behavior during the Hajj, including spatial organization, cultural influences, and social interactions. The findings can inform improvements in infrastructure, crowd management, and services to enhance the overall pilgrimage experience.

Acoustic metasurface are artificial structures which could manipulate the wavefront in sub-wavelength dimensions and the previous proposed acoustic metasurface were mostly realized with single materials. An acoustic metasurface with composite structure is proposed for underwater acoustic stealth considering both wavefront manipulation and sound absorption. The unit cells of the metasurface are composed by metallic supporting lattice, interconnecting polymer materials and mass balancing columns. With the gradual modulations of equivalent physical properties along the horizontal direction of metasurface, the incident acoustic wave is reflected to other directions. Meanwhile, the polymer material inside the unit cells would dissipate the acoustic wave energy due to inherent damping properties. With the simultaneous modulations of reflected wave direction and scattering acoustic amplitude, significant improvement of underwater stealth effect is achieved. Compared with single-phase metasurface, the Far-Field Sound Pressure Level (FFSPL) of the multiphase metasurface decreased by 4.82 dB within the frequency range of 3kHz~30kHz. Under a hydrostatic pressure of 5MPa, the linearized mean stress for multiphase metasurface is only 1/3 of that of single-phase metasurface due to much thicker struts and much more uniform stress distribution. The proposed composite structure possesses potential applications due to acceptable thickness (80mm) and low equivalent density (1100 kg/m3).

Peptidases of the papain family play a key role in protein degradation, regulated proteolysis, and the host-pathogen arms race. Although the papain family has been the subject of many studies, knowledge about its diversity, origin, and evolution in Eukaryota, Bacteria, and Archaea is limited; thus, we aimed to answer these long-standing questions. We traced the origin and expansion of the papain family through phylogenomic analysis, using sequence data from numerous prokaryotic and eukaryotic proteomes, transcriptomes, and genomes. We identified the full complement of the papain family in all prokaryotic and eukaryotic lineages. Analysis of the papain family provided strong evidence for its early diversification in the ancestor of eukaryotes. We found that the papain family has undergone complex and dynamic evolution through numerous gene duplications, which produced eight eukaryotic ancestral paralogous C1A lineages during eukaryogenesis. Different evolutionary forces operated on C1A peptidases, including gene duplication, horizontal gene transfer, and gene loss. This study challenges the current understanding of the origin and evolution of the papain family and provides valuable insights into their early diversification. The findings of this comprehensive study provide guidelines for future structural and functional studies of the papain family.

This article traces the origination, distribution, kinematics, function, and nature of alternative lateral horse gaits, i.e. intermediate speed lateral-sequence gaits involving the synchronization of ipsilateral limbs in the swing phase. Such alternative lateral horse gaits (namely, the running walk, rack, broken pace, hard pace, and broken trot) have been prized by equestrians for their comfort, and have been found in select horse breeds for hundreds of years and even exhibited in fossil equid trackways. After exploring the evolution and development of alternative lateral gaits via fossil equid trackways, human art and historical writings, and the genetics and history of modern horse breeds, functional and biomechanical reasons are offered for the genesis of these gaits. The article concludes by tracing similarities and differences between and within the expression of these alternative lateral gaits by various horse breeds. Fast and low-swinging hard pacing gaits are common in several horse breeds of East and North Asia, high-stepping rack and running walk gaits are often displayed in European and North and South American breeds, the broken pace is found in breeds of Central Asia, Southeast Asia, West Asia, Western North America, and Brazil in South American, and the broken trot occurs in breeds of North Asia, South Asia, and the Southern United States, and Brazil South America.

The utilization of wind energy has become increasingly popular in the United States and many European countries due to its abundant natural source and optimized design. While existing wind turbines are predominantly large-scale and not suitable for standalone or distributed power production, Lubbock County in West Texas offers a diverse range of renewable energy options to meet its energy needs. The region relies heavily on utility-scale wind energy sources to supply power to the Texas Grid, replacing conventional fossil fuel-based systems. Currently, standalone solar PV systems are the preferred choice for renewable energy generation. However, West Texas possesses an ample supply of wind energy that can be harnessed to establish a microgrid and provide standalone power to rural communities. By employing the latest technology and optimizing efficiency, even in low-scale generation, a 6 kW permanent magnet alternator-based distributed wind turbine has been designed. This paper focuses on analyzing the techno-economic aspects of implementing this wind turbine in a real-world scenario, taking into account wind attributes such as velocity and available power at the specific location.

Diabetes may cause an increase blood levels of cytokines inducing a rising of C reactive protein (PCR) and fibrinogen stimulating a subclinical inflammation which lead to adhesive molecules expression and to endothelial disfunction. A comprehensive panel of type 1 diabetes mellitus (T1DM) interleukins polymorphisms is not provided yet. As chronic periodontitis (CP) is considered the sixth complication of DM, a clarification is needed about the inflammatory role managed by single nucleotides polymorphisms (SNPs). The goal of this review is to focus on the significant diversity of SNPs in T1DM patients with and without CP. After a digital search on PubMed and Scopus with reference to the last 5 years, 21 items were enrolled. Several ILs were analyzed. T1DM still needs to be thoroughly explored regarding the ILs polymorphisms panel, however the last 5 years have led to the increased independence of this condition, causing autonomous inflammatory effects which requires further investigations. CP and T1DM association in children and adolescents represents a severe gap in literature that should be filled, the scarce presence of studies also about adults serves as a motivation for ulterior clinical researches

This article presents a comprehensive review of the relationship in sustainable tourism and blockchain technology. The aim of this research is to explore the potential of blockchain to promote sustainable tourism, as well as to evaluate the current state of research and practical implementations in this field. The findings demonstrate the potential of blockchain in enhancing sustainability practices in tourism, while also highlighting the challenges and limitations. The study provides valuable insights for policymakers, industry practitioners, and researchers, and proposes future research directions to further advance the field.

Flexibility is perceived as a primary reason for working as a gig worker. However, there are not enough studies that investigate gig workers' motivations. Hence, this study aims to examine the motivation of white-collar gig workers using a sample size of 327 gig workers in Mongolia, a developing country’s labor market. The purpose of this study is to investigate intrinsic and extrinsic motivation factors for white-collar gig workers and their impact on behavioral intentions such as those of remote workers, freelancers, and any representatives of digital gig workers, not location-based gig workers. The primary data used in this study were collected through questionnaires from an online platform that attracts white-collar gig workers. The characteristics of this group are analyzed using Smart PLS4.0 software through the PLS-SEM technique to test the hypothesized relationships. Overall, the study contributes to an extension of current literature by understanding the white-collar digital gig workforce’s motivations and reasons behind it.

This paper presents an in-depth contextualized tutorial on Agricultural IoT (Agri-IoT), covering the fundamental concepts, assessment of routing architectures and protocols, and performance optimization techniques via systematic survey and synthesis of related literature. The negative impacts of climate change and the increasing global population on food security and unemployment threats have motivated the adoption of the wireless sensor network (WSN)-based Agri-IoT as an indispensable underlying technology in precision agriculture and greenhouses to improve food production capacities and quality. However, most related Agri-IoT testbed solutions have failed to achieve their performance expectations due to the lack of an in-depth and contextualized reference tutorial that provides a holistic overview of communication technologies, routing architectures, and performance optimization modalities based on users’ expectations. Thus, although IoT applications are founded on a common idea, each use case (e.g., Agri-IoT) varies based on specific performance and users expectations as well as its technological, architectural, and deployment requirements. Likewise, the agricultural setting is a unique and hostile area where conventional IoT technologies do not apply, hence the need for this tutorial. Consequently, this tutorial addresses these via the following contributions: (1) a systematic overview of the fundamental concepts, technologies, and architectural standards of WSN-based Agri-IoT, (2) an evaluation of the technical design requirements of a robust, location-independent, and affordable Agri-IoT, (3) a comprehensive survey of the benchmarking fault tolerance techniques, communication standards, routing and medium access control (MAC) protocols, and WSN-based Agri-IoT testbed solutions, and (4) an in-depth case study on how to design a self-healing, energy-efficient, affordable, adaptive, stable, autonomous, and cluster-based WSN-specific Agri-IoT from a proposed taxonomy of multi-objective optimization (MOO) metrics that can guarantee an optimized network performance. Furthermore, this tutorial established new taxonomies of faults, architectural layers, and MOO metrics for cluster-based Agri-IoT (CA-IoT) networks and a 3-tier objective framework with remedial measures for designing an efficient associated supervisory protocol for cluster-based Agri-IoT networks.

Non-alcoholic steatohepatitis (NASH) is a clinically serious stage of non-alcoholic fatty liver disease (NAFLD). Histologically characterized by hepatocyte ballooning, immune cell infiltration and fibrosis, NASH at a molecular level involves lipid induced hepatocyte death and cytokine production. Currently, there are very few diagnostic biomarkers available to screen NASH, and no pharmacological intervention is available for its treatment. In this study, we show that hepatocyte damage by lipotoxicity results in the release of extracellular RNAs (eRNAs) which serve as damage-associated molecular patterns (DAMPs) that stimulate the expression of pro-apoptotic and pro-inflammatory cytokines, aggravating inflammation, and cell death in HepG2 cells. Furthermore, the inhibition of eRNA activity by RNase 1 significantly increased cellular viability and reduced NF-kB mediated cytokine production. Similarly, RNase 1 administration significantly improved hepatic steatosis, inflammatory and injury markers in a murine NASH model. This study, therefore, for the first time, underscores the therapeutic potential of inhibiting eRNA action as a novel strategy for NASH treatment.

Microplastics are widespread in freshwater environments and could impact these ecosystems. Bivalves are freshwater organisms that are particularly exposed to microplastic contamination. Therefore, in this preliminary study, the accumulation of microplastics, plasticizers, and additives in the freshwater bivalves Anodonta cygnea through active biomonitoring was investigated. Specimens commercially bought were exposed in three rivers in Central Italy for different exposure times: short (1 month) and long (3 months). The gills and the gastrointestinal tract (GIT) were analyzed separately to evaluate the possible uptake and ingestion of particles via Micro-FTIR. For the first time, small microplastics (SMPs, 5-100 µm), plasticizers, additives, and other micro-litter components, e.g., natural and non-plastic synthetic fibers (APFs) were identified in the bivalve A. cygnea. The most abundant polymer in the gills (94.4%), and GITs (66.1%) was polyamide, which had the highest concentration in each river. A decrease in SMPs' abundance was observed over time in the gills in each river, while the abundance in GIT increased. Compared to polymers, a greater variety of APFs was observed in rivers. The APFs changed during the time of exposure and between different rivers more evidently than polymers, allowing a clearer identification of the possible sources. These results highlighted plastic pollution by SMPs using freshwater bivalves as sentinel organisms and the need to investigate further the additives that can be proxies of the presence of microplastics in the environment and biota.

(1) Background: Heart failure (HF) is the final stage of multiple cardiac diseases, which has now become a severe public health problem worldwide. β-Adrenergic receptor (β-AR) overactivation is a major pathological factor associated with multiple cardiac diseases and mediates cardiac fibrosis and inflammation. Previous study has demonstrated that Bruton's tyrosine kinase (BTK) mediated cardiac fibrosis by TGF-β related signal pathways, indicating that BTK was a potential drug target for cardiac fibrosis. Zanubrutinib, a second-generation BTK inhibitor, has shown anti-fibrosis effects in previous research. However, it is unclear whether Zanubrutinib can alleviate cardiac fibrosis induced by β-AR overactivation;(2) Methods: In vivo: Male C57BL/6J mice were treated with or without the β-AR agonist isoproterenol (ISO) to establish cardiac fibrosis animal model. Here, results showed that BTK inhibitor Zanubrutinib (ZB) had a great effect on cardiac fibrosis and inflammation induced by β-AR. In vitro: Results showed that ZB alleviated β-AR-induced cardiac fibroblast activation and macrophage proinflammatory cytokine production. Further mechanism studies demonstrated that ZB inhibited β-AR-induced cardiac fibrosis and inflammation by BTK、STAT3、NF-κB and PI3K/Akt signal pathways both in vivo and in vitro; (4) Conclusions: our research provides evidence that ZB ameliorates β-AR-induced cardiac fibrosis and inflammation.

Togo is one of the countries characterized by the highest deforestation rate in the world, caused mainly by the overexploitation of domestic biomass energy. Uapaca togoensis being one of the species appreciated for its strong calorific power, is increasingly overexploited, and its rarefaction in the Togolese forest landscapes becomes worrying hence the need to conduct this study to evaluate the possibilities of its vegetative reproduction. This study contributes to the sustainable development of natural resources by determining the optimal conditions for assisted regeneration of Uapaca togoensis. The approach consisted in conducting a series of nursery trials to determine the impact of the substrate, size of cuttings, sunlight, and apical tip coverage of the plastic film on its germination and budburst capacity. The lower calorific value is determined from samples in dry wood slices of 350g to 500g in five diameter classes. After 33 days, only one unscarred seed germinated in the compost. Substrate type, diameter of cuttings, sunlight, and plastic film significantly influenced the budburst rate and delay. More than 70% of the medium-diameter segments budded compared to 60% and 50% for small and large-diameter segments. More than 80% of the segments exposed to sunlight budded compared to 60% for the shaded segments. The average lower calorific value of dry wood of Uapaca togoensis varies between 7.35 Mj/Kg and 12.12 Mj/Kg depending on the humidity rate and the diameter.

The main question proposed in this research is if different types of organizational approach, adapted from rapidly changing disciplines — such as IT industry, and software engineering in particular — could help overcome this gap by shortening the response time needed to analyze advanced solutions in accordance with changed circumstances, thus allowing for architectural programming to obtain different positions in the timeline of project planning and realization. We propose a novel methodology of architectural design as a self-reliant instrument inspired by Agile Manifesto and some of its instantiations, most notably by the Scrum Framework.

Several sun models suggest the radioactive balance where the concentration of greenhouse gases and the albedo effect are related to the Earth's surface temperature. There is a considerable increment of greenhouse gases due to anthropogenic activities. Climate change correlates with this alteration in the atmosphere and an increase in surface temperature. Efficient forecasting of climate change and its impacts of 1.5°C global warming above pre-industrial levels could be helpful to respond to the threat of c.c. and develop sustainably. Many studies have predicted the temperature change in the coming years. The global community has to create a model that can realize good predictions to ensure the best way to deal with the warming. Thus, we propose a finite-time thermodynamic (FTT) approach in the present work. The FTT can solve problems such as the faint young sun paradox. In addition, we use different machine learning models to evaluate our method and compare the experimental prediction and results.

Wild artisanal cultures, such as SCOBY-based membranes (Symbiotic Culture of Bacteria and Yeasts) and water kefir grains (WKG), are complex consortia of microorganisms comprising yeasts, lactic and acetic acid bacteria, with a large strains’ diversity and abundance. The fermented products (FPs) obtained by the microbiome’s contribution can be included into functional products due to their metabiotics (pre-, pro-, post-, and paraprobiotics) as a result of the complex and synergistic association as well as due to the metabolic functionality. In this study, both consortia of SCOBY and WKG were involved in the co-fermentation of a new formulated substrate, that was further analysed aiming at increasing of the postbiotic composition of the FPs. Plackett-Burman (PB) and Response Surface Methodology (RSM) techniques were used for the experimental designs to select and optimize the most important parameters that influence the freeze-dried starter cultures of SCOBY and WKG activity as a multiple inoculum. The tea concentration (1-3%), sugar concentration (5-10%), raisins concentration (3-6%), SCOBY lyophilized culture concentration (0.2-0.5%), WKG lyophilized culture concentration (0.2-0.5%), and fermentation time (5-7 days), were considered the independent variables for mathematical analysis and fermentation conditions’ optimization. The pH, total acidity (TA), antioxidant activity (DPPH), and antimicrobial activity against Escherichia coli ATCC 25922, Bacillus subtilis MIUG B1, Staphylococcus aureus ATCC 25923, and Aspergillus niger MIUG M5 were evaluated as responses. The rich postbiotic bioactive composition of the FP obtained in optimized biotechnological conditions highlighted the usefulness of the artisanal co-cultures, through their symbiotic metabolic interactions for the improvement of bioactive potential.

Background: Cell-free plasma DNA (cfDNA) is composed of circulating extracellular DNA originating from apoptosis or cell necrosis. It is generally present in healthy individuals, but its levels increase in different clinical conditions, such as kidney disease, sepsis, myocardial infarction, trauma and cancer. Caspase-3 plays a central role in apoptosis, a mechanism of programmed cell death involved in the pathogenesis of chronic kidney disease (CKD). Methods: We compared cfDNA and caspase-3 levels in 25 CKD patients and in 10 healthy subjects, evaluating the modification of their concentrations according to CKD stage. We also analyzed the correlation between cfDNA and caspase-3 levels in CKD patients and the correlation between cfDNA and caspase-3 levels and creatinine and urea. Results: CfDNA and caspase-3 levels were higher in CKD patients compared to healthy subjects, in particular in patients with advanced renal disease. A positive correlation between cfDNA and caspase-3 levels and between cfDNA and caspase-3 and creatinine and urea was also observed. Conclusion: Patients with chronic kidney disease present higher levels of cfDNA and caspase-3 levels compared with healthy subjects. The worsening of renal damage and the increase in uremic toxin concentration are associated to higher levels of cfDNA and caspase-3 levels, thus reflecting a central role of apoptosis in the pathogenesis of CKD.

In practical applications, the detection of objects with various sizes is a common requirement for most detectors. The feature pyramid network (FPN) is widely adopted as a framework to address this challenge. The field is witnessing an increasing number of transformer-based target detectors due to the widespread adoption of transformer technology. This paper initially examines the design flaws in FPN and transformer-based target detectors, followed by the introduction of a new transformer-based approach called Texturized Instance Guidance (TIG-DETR) to address these issues. Specifically, TIG-DETR comprises a backbone network, a new pyramidal structure known as Texture-Enhanced FPN (TE-FPN), and an enhanced DETR detector.The TE-FPN is composed of three components: a bottom-up pathway for enhancing texture information in the feature map, a lightweight attention module to address confounding effects resulting from cross-scale fusion, and a standard attention module to enhance the final output features.The improved DETR detector utilizes Shifted Window based Self-Attention to replace the multi-headed self-attention module in DETR, thereby accelerating model convergence. Moreover, it incorporates an Instance Based Advanced Guidance Module to enhance instance perception in the image by employing a pre-local self-attentive mechanism for recognizing larger instances. By employing TE-FPN instead of FPN in Faster RCNN with Resnet-50 as the backbone network, we achieve a 1.9% improvement in average accuracy. TIG-DETR achieves an average accuracy of 44.1 with Resnet-50 as the backbone network.

A chronically stable electrode material with low impedance for recording neural activity and high charge-injection capacity for functional electro-stimulation is desirable for the fabrication of implantable microelectrode arrays that aims to restore impaired or lost neurological functions in humans. For this purpose, we have investigated the electrochemical properties of sputtered ruthenium oxide (RuOx) electrode coatings, deposited on planar microelectrode arrays, using an inorganic model of interstitial fluid (model-ISF) at 37o C as the electrolyte. Through a combination of cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) modelling study we have established the contribution of faradaic reaction as the major charge-injection contributor within the safe neural stimulation potential window of 0.6 V vs Ag|AgCl. We have also established the reversibility of the charge-injection process for sputtered RuOx film by applying constant charge-per-phase current stimulations at different pulse widths and by comparing the magnitudes of leading and trailing access voltages during voltage transient measurements. Finally, the impedance of the sputtered RuOx film was found to be reasonably comparable in both its oxidized and reduced states, although electronic contribution from capacitive double-layer was found to be slightly higher for the completely oxidized film around 0.6 V than its reduced counterpart around -0.6V.

Fracture and failure performance of foamed concrete materials were conducted using three methods, i.e., inverse analysis, digital image correlation (DIC) and finite element modelling (FEM) from tested normalized notched beams under three-point bending. From this study, several characteristics both experimental and FEM are discussed. However inverse analysis is only well applicable for series GF-30. The bilinear softening of the testing beam was estimated to identify fracture energy (GF), critical crack length (ac) and elastic modulus (E) with values of 0.015 N/mm, 54.5 mm, and 13 GPa, respectively. Additionally, fracture toughness was calculated by adopting double-K (initiation fracture of 6.907 MPa.mm0.5, unstable fracture of 23.186 MPa.mm0.5 and cohesive fracture of 16.278 MPa.mm0.5). Two-dimensional FEA Modelling of fracture was carried out using a Traction Separation Law (TSL), incorporating extended finite element method (XFEM) and cohesive zone (CZM) techniques. A sensitivity study was carried out, global mesh size of two and damage stabilization cohesive with the value of 1 × 10-5 showed good convergence and were used in other models. Furthermore, by comparing experimental observation using DIC, reliability FEM was validated and showed good acceptance to simulating the crack propagation.

This article examines the wavelet transforms and the machine learning methods in accelerating large eddy simulations of turbulent flows. An overarching challenge of large eddy simulations is to accurately represent the cascade of kinetic energy across the cut-off length scale. Taylor hypothesis suggests that the energy cascade occurs through the process of vortex stretching. However, Richardson hypothesis assumes the self-amplification of the strain field and a hierarchical break down of large eddies lead the energy cascade. The large eddy simulations typically employs the self-amplification of the strain in formulating subgrid models. However, several studies also proposed subgrid models based on vortex stretching. The wavelet-based coherent vortex simulation of turbulence directly accounts for vortex stretching in overall forward scatter of energy, while allowing local backscatter. The wavelet-based large eddy simulation adapts the grid to capture the creation of small-scale eddies, while adopting subgrid models based on the self-amplification of strain. The advancement of artificial intelligence in turbulence modelling is currently evolving around accelerating the numerical simulations of turbulent flow. However, there is a clear connection between the application of wavelet transfroms and neural networks for directly solving the Navier-Stokes equation, indicating some potential benefits of wavelet methods over the neural networks.

The cytoskeleton is a master organizer of cell cortex, organelles positioning and membrane trafficking. Therefore, playing a decisive role in establishment of apico-basal polarity. Septins are critical cytoskeleton components which function in apico-basal polarity remain weakly investigated. Here, using 3D culture system, we demonstrate that septin9 localizes at basolateral membrane (BM). Its depletion induces an inverted polarity phenotype, decreasing -catenin at BM and increasing the expression of the transforming growth factor (TGF) and the epithelial-to-mesenchymal transition (EMT) markers. Similar effects were observed upon deleting its two polybasic domains, and the mutant become cytoplasmic and apical. The cysts with an inverted polarity phenotype display an invasive phenotype, with src and cortactin accumulating at the peripheric membrane. Inhibition of TGF-receptor and RhoA rescues the polarized phenotype. Although the cysts from overexpressed-septin 9, overgrowth and present a filled lumen. Both phenotypes correspond to tumor features. This suggests that septin 9 expression and assembly through the two PB domains are essential for establishing and maintaining apico-basal polarity against tumor development through a mechanism involving TGF-dependent EMT and RhoA activity.

Natural cellulose hydrogels have been widely used to enhance mechanical properties. However, existing natural fiber composite hydrogels are not reusable, limiting their potential applications. To address this issue, we designed and prepared a polyvinyl alcohol/glycerol /bamboo microfibril double network tough hydrogel using a simple method. The bamboo microfibril and polyvinyl alcohol form a tight and rigid network through hydrogen bonding, improving mechanical properties. The prepared polyvinyl alcohol/glycerol/bamboo microfibril double network tough hydrogel has the advantages of reusability and fatigue resistance. Furthermore, both the elastic modulus and toughness of the hydrogel increase with increasing bamboo microfibril content. We also demonstrated that the hydrogel can be recast after cyclic compression, maintaining its recyclability, stability, and certain stiffness and toughness. Our study highlights the potential of hydrogels for controllable mechanical properties, fatigue resistance and shows that polyvinyl alcohol/glycerol/bamboo microfibril hydrogel has broad value for plasticity and reuse.

Integrating artificial intelligence (AI) and natural language processing (NLP) technologies with project-based learning experiences in Science,Technology, Reading, Engineering, Arts, and Mathematics (STREAM) education offers the potential to enhance student engagement, critical thinking,problem-solving, and interdisciplinary learning. This paper presents a comprehensive approach to implementing AI and NLP technologies, such as ChatGPT, in STREAM project-based learning experiences, highlighting the potential advantages and challenges of this innovative educational approach. The proposed method encompasses personalized learning pathways, AI-powered research assistance, collaborative AI tools, real-time feedback, virtual mentoring, advanced simulation, and objective assessment. We also discuss the implications of this integration for educators, institutions, and students, along with recommendations for future research and development in this emerging field.

Background and objective: Acinetobacter baumannii (A. baumannii) is an important nosocomial pathogen that possesses not only intrinsic resistance to many classes of antibiotics, but also is capable to rapidly develop antimicrobial resistance during treatment. The aim of our study was to determine the production of different types of β-lactamases (AmpC, ESBL, KPC) in A. baumannii strains, to evaluate its association with antimicrobial resistance, and to identify the changes in these characteristics after 5 years. Materials and methods: A total of 233 A. baumannii strains were isolated from different clinical specimens of patients treated at the Hospital of Lithuanian University of Health Sciences in 2016–2017 and 2021–2022. All clinical cultures positive for A. baumannii were analyzed. The type of β-lactamase was detected by phenotypic methods using ESBL plus AmpC screen disk tests and the combination meropenem disk test. Results: In 2016–2017 and 2021–2022, all A. baumannii strains were resistant to ciprofloxacin; more than 80% were resistant to carbapenems, piperacillin/tazobactam, gentamicin, and tobramycin. Comparison of two different period showed that the production of two different types of β-lactamases increased more than 5-fold (from 17.7% to 94.2%, p < 0.001), and the production of all three types of β-lactamases, more than 4-fold (from 1.3% to 5.8%, p < 0.001). A. baumannii strains producing two or three types of β-lactamases were more often resistant to tigecycline, tetracycline, and doxycycline than strains producing one type of β-lactamases (p < 0.001). Conclusions: The frequency of isolation of A. baumannii strains producing two or three β-lactamases types and the resistance rates to ampicillin/sulbactam, tigecycline, tetracycline, and doxycycline increased in 2020–2021 as compared with 2016–2017. The production of two or three types of β-lactamases by A. baumannii strains was associated with higher resistance rates to tetracyclines.

During the last few years, several approaches have been proposed to improve early warning systems for reducing rock-fall risk. In this regard, this paper introduces a Deep learning-and (IoT) based Framework for Rock-fall Early Warning, devoted to reducing the rock-fall risk with high accuracy. In this framework, the prediction accuracy was augmented by eliminating the uncertainties and confusion plaguing the prediction model. In order to achieve augmented prediction accuracy, this framework fused the prediction model-based deep learning with a detection model-based Internet of Things. In order to determine the framework’s performance, this study adopted parameters, namely overall prediction performance measures, based on a confusion matrix and the ability to reduce the risk. The result indicates an increase in prediction model accuracy from 86% to 98.8%. In addition, a framework reduced the risk probability from (1.51 ×10-3) to (8.57 ×10-9). Our results indicate the framework’s high prediction accuracy; it also provides a robust decision-making process for delivering early warning and lowering the rock-fall risk probability.

An algorithm for the treatment of images affected by both blurring and salt&pepper noise is proposed with a cost only proportional to the number of pixels. The methodology uses a discretization scheme for the Laplace operator multiplied by a suitable nonlinear term depending on the gradient. Even if this approach resembles a diffusion type algorithm, only one step of the procedure is applied, leading to significant time savings. The procedure is successfully tested on some standard black&white natural images.

The global warming our generation is experiencing is just one of the great environmental crises of the Anthropocene, a geological period that began with the use of fossil fuels and that, in merely one century and a few decades of industrial activity, has altered ecosystemic processes that sustain human health and well-being. Beyond the loss of the “intrinsic value of nature”, changes in the magnitude and direction of biogeochemical cycles and increases in temperature are phenomena that not only accompany the loss of habitats and species but impair resilience by ultimately generating greater and more complex numbers and types of exposures that constitute a danger to human health. In this study, we attempted to offer some notes about the margin, understood as that space with the greatest inequity and therefore the fastest growth of risk: the collision area where deprivation marks the social determinants of health and where the greatest interaction with causes of disease occur.

Crack inspection is important to monitor the structural health of pavement structures and to facilitate an easier rehabilitation process. Currently, pavement crack inspection is conducted manually, which is inefficient and costly at the same time. For solving the problem, this work has developed a robotic system for automated data collection and analysis in real-time. The robotic system navigates on the pavement and collects visual images from the surface. A deep learning-based semantic segmentation framework named RCDNet was proposed and implemented on the onboard computer of the robot to identify cracks from the visual images. Simulation results show that the deep learning model obtained 96.29% accuracy for predicting the images. The proposed robotic system was tested on both indoor and outdoor environments and was observed that it can complete inspecting a 3m × 2m grid within 10 minutes and a 2.5m × 1m grid within 6 minutes. This outcome shows that the proposed robotic method can drastically reduce the time of manual inspection. Furthermore, a severity map based on the results from visual images was also generated to provide an idea of which locations should be paid more attention to repair in a test grid.

In this non-exhaustive review, we discuss the importance of invariant vectors in atomic physics, such as the Laplace-Runge-Lenz vector, the Redmond vector in the presence of an electric field, the Landau-Avron-Sivardière vector when the system is subject to a magnetic field, and the supergeneralized Runge-Lenz vector for the two-center problem. Application to Stark and Zeeman effects are outlined. The existence of constants of motion in the charge-dyon system is also briefly mentioned.

Urban environments are frequently populated by different insect species. Some of them are very beautiful and appealing to the people around them, such as ladybugs and butterflies, while some others are molestants and even dangerous to public health. Mosquitoes often inhabit urban environments by staying close to their hosts (humans, birds, etc.), while phytophagous species such as stinkbugs find hosts among ornamental plants and shelters during the winter around humans. This article describes the early discoveries and distribution of two invasive mosquito species, Aedes albopictus, and Ae. japonicus (Diptera: Culicidae), which were recorded in Serbia in 2009 and 2018, respectively. Both species are important for human health, due to their nuisance behavior and because they are vectors of many viruses. On the other hand, in 2015 and 2008, two invasive stinkbug species, Halyomorpha halys and Nezara viridula (Hemiptera: Pentatomidae) were observed to spread, respectively. Since then, these species have disrupted human population in urban areas, but also damaged a range of crops and ornamental plants. All species have been monitored in the territory of Serbia, and establishment and distribution have been confirmed so far.

The spatiotemporal variations of rainfall erosivity in the Hengduan Mountains, charac-terized by rugged terrain and high potential soil erosion risks, over the past 30 years was exam-ined. The changing trends of rainfall erosivity for 2025-2040 was also be investigated under the comprehensive scenario of moderate socio-economic development (SSP2-4.5) combined with me-dium-low radiative forcing, using four global climate models (GCMs) based on CMIP6. The results indicated that: (1) The annual distribution of rainfall erosivity in the Hengduan Mountains exhib-ited significant seasonal variations, with the order of erosivity being summer > autumn > spring > winter on a seasonal scale. (2) Over the past 30 years, there has been a slight decrease in annual precipitation and a slight increase in rainfall erosivity, with periodic extreme values occurring every 6-8 years. (3) Rainfall erosivity showed a decreasing gradient from southeast to northwest in terms of spatial distribution. There was a significant positive correlation between rainfall ero-sivity and precipitation, while a significant negative correlation existed with elevation in the ver-tical direction. Moreover, there was an increasing trend of rainfall erosivity in the northeastern part of the Hengduan Mountains and a decreasing trend in the southern region. (4) Under the joint driving forces of increased precipitation and erosive rainfall events, rainfall erosivity in the future is expected to significantly increase, posing a more severe risk of soil erosion in the Heng-duan Mountains.

When the minimal length approach emerging from noncommutative Heisenberg algebra, generalized uncertainty principle (GUP), and thereby integrating gravitational fields to this fundamental theory of quantum mechanics (QM) is thoughtfully extended to Einstein field equations, the possible deformation of the metric tensor could be suggested. This is a complementary term combining the effects of QM and general relativity (GR) and comprising noncommutative algebra together with maximal spacelike four–acceleration. This deformation compiles with GR as curvature in relativistic eight–dimensional spacetime tangent bundle, generalization of Riemannian spacetime, is the recipe applied to derive the deformed metric tensor. This dictates how the affine connection on Riemannian manifold is straightforwardly deformed. We have discussed the symmetric property of deformed metric tensor and affine connection. Also, we have evaluated the dependence of a parallel transported tangent vector on the spacelike four–acceleration given in units of L, where L = rℏcG3 is a universal constant, c is speed of light, and ℏ is Planck constant, and G is Newton’s gravitational constant.

In this paper is shown the dynamic modeling and design of a passivity based controller for the RV-3SB robot. Firstly, the dynamic modeling of the of the Mitsubishi Rv-3SB robot is done by the Euler-Lagrange formulation in order to obtain a decoupled dynamic model considering the actuators orientation besides the position of this analyzed robot. It is important to remark that the dynamic model of the RV-3SB robot is done based in the kinematic model obtention in which is developed by the implementation of screw theory. Then the passivity based controller is obtained by separating the end effector variables and the actuator variables by making an appropriate coordinate transformation. The passivity based controller is obtained by selecting an appropriate storage function and by the Lyapunov theory the passivity based control law is obtained in order to drive the error variaable, which is the difference between the measured end effector position variable and the end effector desired position variable. The passivity based controller makes that the error variable reach the origin in finite time taking into consideration the dissipation properties of the proposed controller in order to stabilizes the desired end effector position. A numerical simulation experiement is performed in order to validate the theoretical results obtained in this research study. It is verified by numerical experimentation that the proposed control strategy is efficient and effective in order to drive the error variable to the origin in comparison with other modified techniques found in the literature. Finally, the appropriate discussion and conclusion of this research study are provided.

3D metal nanostructures are often the basis of several applications such as in catalysis, plasmonics, medical diagnosis, therapy, drug screening, ophthalmologic, and biomedical applications. Porous gold nanoparticles (PGNs) are intensively investigated due to their outstanding morphological as well as advantageous optical properties. Unfortunately, the thermal stability of these open-porous structures is poor, i.e. even as a result of low-temperature annealing (150$^\circ$C in air), their porosity disappears and they lose their favorable optical properties. In order to preserve their beneficial properties, a thin metal oxide coating can be applied. Changing the coating's thickness and/or composition, the optical response of the PGNs can also be tuned in a wide wavelength region. Moreover, these nanoparticles can be synthesized also in support-free form, which makes them more attractive from an application point of view. This review article summarizes some of the preparation modes of these complex nanostructures (fixed and support-free), as well as their thermal stability and optical responses.

In recent years, intelligent identification and prediction of ore deposits based on deep learning algorithm and image processing technology has gradually become one of the research frontiers in the field of geological and metallogenic prediction. However, this method also has many problems that need to be solved. For example, (1) very few trainable image samples containing mineral point labels; (2) The geological image features are small and irregular, and the image similarity is high; (3) It is difficult to calculate the influence of different geological prospecting factors on ore mineralization. Based on this, this paper constructs a deep learning network model Multiscale Feature Attention Framework (MFAF) based on geo-image data. The results show that MFCA-Net module in MFAF model can solve the problem of scarce mine label images to a certain extent. In addition, the channel attention mechanism SE-Net module can quantify the difference of influence of different source factors on mineralization. The prediction map is obtained by applying the MFAF model in the study of deposit identification and prediction in the research area of the southern section of Qin-hang metallogenic Belt. In the forecast map, many regions have high metallogenic potential. Through observation, it is found that the above predicted area covers 100% of the known ore deposits at present, which has a good prediction effect. Later, we can find out the specific reasons through field verification. The multi-scale feature fusion and attention mechanism MFA Framework in this paper can provide a new way of thinking for geologists in mineral exploration. The research of this paper also provides resource guarantee and technical support for the sustainable exploitation of mineral resources and the sustainable growth of society and economy.

Leadership and sustainability have been researched and examined concurrently. We know much about sustainable, sustainability and environmental leadership as separate areas of research and the leadership behaviours and practices that facilitate achievement of sustainability outcomes. Whilst these research streams have developed alongside each other, we know little about the similarities and differences of each of these three leadership approaches. The purpose of this paper is to review and compare which sustainable, sustainability and environmental leadership approaches are predictive of improved organizational performance with a view to understanding leadership towards sustainability. Through a comprehensive review of the extant literature, we integrate the three leadership approaches and highlight areas of similarity and difference. From a theoretical perspective, this paper seeks to make a significant contribution to the scholarly literature by building on current knowledge and developing a unified framework that combines our findings on leadership practices and behaviours in terms of the types of leadership required for achieving sustainability outcomes. By unifying existing frameworks and clarifying points of integration and differentiation under the umbrella of ‘leadership towards sustainability’, this paper seeks to advance research on leadership approaches. From a practical perspective, a cohesive set of leadership behaviours and practices will be emphasized so that leaders can adapt these to suit the context of their organization, thus helping leaders make sense of the literature to inform their practice and reach sustainability goals. Thus, the main goal of this paper is to identify a range of leadership behaviours and practices that are required to improve the performance of sustainability in organizations thus informing the broader leadership field.

In this work the author utilizes the quantum geometrization of spacetime for describing the gravitational interaction within the framework of quantum theory. This approach allows for the development of an equation of gravity that is mathematically connected to the fermion and boson fields. This achievement is accomplished by incorporating two fundamental principles: covariance of the quantum field equations and the principle of least action. By considering these principles, a theory is established that enables the calculation of gravitational corrections to Quantum Electrodynamics, and potentially, to the standard model of particle physics as well. The theory also provides an explanation for two phenomena: the existence of a cosmological pressure density similar to quintessence, that is compatible with the small value of the observed cosmological constant, and the breaking of matter-antimatter symmetry at high energies offering insights into why there is an imbalance between the two in the early universe. In the cosmological modeling of the theory, there exists a proposal to account for the formation of supermassive black holes that are accompanied by their own surrounding galaxies, without relying on the process of mass accretion. The model, in accordance with recent observations conducted by the James Webb Space Telescope, supports the notion that galactic configurations were established relatively early in the history of the universe, shortly after the occurrence of the Big Bang.

Perovskite solar cells are an evolving technology owing to self-assembling and highly tunable bandgap properties of materials. In this context, thin films of perovskites have attracted immense attention and witnessed great advancement because of their low manufacturing cost. The key development in these devices is the conversion efficiency, which rose from 3.8% to 28%. The formulation of innovative materials with the proper replacement of lead in perovskites is imperative to mitigate lead toxicity. Here, we analyzed the challenges like material and structural stability, device stability under high temperature and humidity conditions, lifetime, manufacturing cost, etc. faced in the commercialization of perovskite devices. This review shows that challenges such as device engineering, performance stability against the harsh environment, cost-effectiveness, and environmental concern should be taken into consideration for the widespread acceptance of perovskite-based solar devices. In conclusion, we suggested that an enormous scope exists for exploring high-performance and long-lasting perovskites for energy applications.

Voice cloning, an emerging field in the speech processing area, aims to generate synthetic utterances that closely resemble the voices of specific individuals. In this study, we investigate the impact of various techniques on improving the quality of voice cloning, specifically focusing on a low-quality dataset. To contrast our findings, we also use two high-quality corpora for comparative analysis. We conduct exhaustive evaluations of the quality of the gathered corpora in order to select the most suitable audios for the training of a Voice Cloning system. Following these measurements, we conduct a series of ablations by removing audios with lower SNR and higher variability in utterance speed from the corpora in order to decrease their heterogeneity. Furthermore, we introduce a novel algorithm that calculates the fraction of aligned input characters by exploiting the attention matrix of the Tacotron 2 Text-to-Speech (TTS) system. This algorithm provides a valuable metric for evaluating the alignment quality during the voice cloning process. We present the results of our experiments, demonstrating that the performed ablations significantly increase the quality of synthesised audios for the challenging low-quality corpus. Notably, our findings indicate that models trained on a 3-hour corpus from a pre-trained model exhibit comparable audio quality to models trained from scratch using significantly larger amounts of data.

Chronic wounds are associated with considerable patient morbidity and present a significant economic burden to the healthcare system. Often, chronic wounds are in a state of persistent in-flammation and unable to progress to the next phase of wound healing. Placental-derived bio-materials are recognized for their biocompatibility, biodegradability, angiogenic, an-ti-inflammatory, anti-microbial, anti-fibrotic, immunomodulatory, and immune privileged prop-erties. As such, placental-derived biomaterials have been used in wound management for more than a century. Placental-derived scaffolds are composed of an extracellular matrix (ECM) that can mimic the native tissue, creating a reparative environment to promote ECM remodeling, cell migration, proliferation, and differentiation. Reliable evidence exists throughout the literature to support the safety and effectiveness of placental-derived biomaterials in wound healing. How-ever, differences in source (i.e., anatomical regions of the placenta), preservation techniques, decellularization status, design, and clinical application have not been fully evaluated. This re-view provides an overview of wound healing and placental-derived biomaterials, summarizes the clinical results of placental-derived scaffolds in wound healing, and suggests directions for future work.

Familial dysbetalipoproteinemia (FD) is a highly atherogenic genetically-based lipid disorder with the underestimated actual prevalence. In the recent years, several biochemical algorithms have been developed to diagnose FD using available laboratory tests. However, there is not enough data on their use in real-world clinical implementation. We studied the applicability of the most accessible biochemical algorithms to diagnose FD in clinical practice. We also investi-gated the prevalence of FD in one of the European regions of Russia based on a population sample. In this study there was detected a high prevalence of FD: 1 in 151. We demonstrated that the diagnostic algorithms of FD including a diagnostic apoB levels require correction, taking into account the characteristics of the distribution of apoB levels in the population. At the same time a triglycerides cutoff ≥1.5 mmol/L may be a useful tool in identifying subjects with FD. We also analyzed the presence and pathogenicity of APOE variants associated with the autosomal dominant FD in a large research sample.

Huge-scale video surveillance systems have become essential in crime prevention and situation recording. Traditional surveillance systems relied on human monitoring of video streams, which often led to errors and difficulties in understanding events. Furthermore, locating specific scenes within recorded videos required extensive human investigation. To overcome these challenges of inefficiency, inconvenience, and potential risks, we propose an intelligent analysis scheme that utilizes abnormal behavior recognition and metadata retrieval algorithms to replace human monitoring. The proposed method consists of three stages: i) metadata generation through object detection and tracking, ii) abnormal behavior recognition, and iii) SQL-based metadata retrieval. By incorporating specific information such as object color and aspect ratio, our technique enhances the usability of retrieval. Moreover, our abnormal behavior recognition module demonstrates robust classification capabilities for activities such as pushing, violence, falling, and crossing barriers. The proposed method can be seamlessly deployed on both edge cameras and analysis servers, making it adaptable to various surveillance setups. This approach revolutionizes the traditional surveillance paradigm, enabling more efficient, reliable, and secure video monitoring and analysis.

Organic wastes and by-products from several activities, including food industries, farming, and animal husbandry, are a hygiene threat when aerobically decomposed. Therefore, their manage-ment is crucial for public health. In this direction, anaerobic digestion (AD) systems may be the solution by transforming waste into energy, which may decrease the environmental impact. However, their efficacy should be carefully examined. In this innovative study, we evaluated the physicochemical and microbial characteristics of liquid digestate (LD) retrieved from organic animal wastes in northern Greece using nanofiltration. Using treatment technologies including physical (solid-liquid separation, microfiltration and nanofiltration) and biological (anaerobic digestion), heavy metals and microbial (i.e., Salmonella spp., Escherichia coli, Enterococcus faecalis) concentrations reduced and nutrients were recovered. This work sets the basis for the efficient management of liquid digestate. Our method may enable the use of treated liquid digestate for unlimited irrigation water and other industrial applications of water. Apart from the sanitation process, the recovery of nutrients for soil fertilization seems to be a more sustainable way for fu-ture agricultural practices.

With the exponential growth of machine learning and development of Artificial Neural Network (ANNs) in recent years, there is great opportunity to leverage this approach and accelarate bio-logical discoveries through applications on the analysis of bioinformatics data. Various types of datasets including for example protein or gene interaction networks, molecular structures and cellular signalling pathways, have already been used for machine learning by training ANNs for inference and pattern classification. However, unlike regular data structures that are commonly used in the computer science and engineering fields, bioinformatics datasets present challenges that require unique algorithmic approaches. The recent development of the geometric and deep learning approach within the machine learning field, is very promising towards accelerating analysis complex bioinformatics datasets. The principles of ANNs and their importance for bio-informatics machine learning is demonstrated herein, through presentation of the undelying mathematical and statistical foundations from group theory, symmetry, linear algebra. Further-more, the structure and functions of ANN algorithms that form the core principles of artificial intelligence are explained, in relation to the bioinformatics data domain. Overall, the manuscript provides guidance for researchers to understand the principles required for practicing machine learning and artificial intelligence, with the special considerations towards bioinformatics applications.