Multidrug resistance (MDR) among gram-negative bacteria is a global public health threat because it has exhausted all standard therapeutic options. This has necessitated clinicians to reconsider colistin, an “old sort” antibiotic which was deemed toxic for clinical use. Unfortunately, swift resistance towards colistin by K. pneumoniae has been reported in different parts of the world. The study aimed at investigating the genetic determinants of colistin resistance in K. pneumoniae isolated from patients admitted in a tertiary care hospital in Kampala, Uganda. 31 archived multidrug resistant K. pneumoniae isolates obtained from rectal swabs of patients admitted to the Mulago Hospital ICU were retrieved. From this collection, we selected 7 colistin resistant K. pneumoniae isolates for whole genome sequencing and molecular profile analysis. In silico sequence data analyses were performed using established web-based bioinformatics tools. The sequence analysis of the genes involved in colistin resistance revealed several non-synonymous mutations in nucleotide sequences of pmrA, pmrB, phoP, phoQ and mgrB genes. Insertion transposase genes for the insertion sequences IS1 and IS5 which are highly implicated in colistin resistance via modification or inactivation of mgrB gene were identified in all isolates and were located in the chromosomal DNA at different genomic positions. No plasmid-borne mcr genes were detected. More so, the strains harbored numerous multidrug resistant genes. This study underscores the need of genomic surveillance of K. pneumoniae strains to limit further spread of colistin resistance genes to avert the potential risk of pandrug resistance. And high throughput sequencing is imperative.

As a new logistics system, Physical Internet (PI) provides a solution to cope with the continuous rise of urban logistics demand by exploring same-level and cross-level paths and flattening. This research suggests a PI-based urban logistics distribution cost minimization model based on the examination of the primary elements influencing PI distribution, intending to maintain the logistic transportation process' integrity. This proposed model enhances the flexibility of goods operation and reduces the global cost of logistics distribution using the interconnected and open PI logistics distribution mode. The experimental results show that the distribution cost of the PI logistics model is significantly better than that of a traditional logistics model. The elastic and cost advantages relatively grow as the infrastructure for distribution scales up and the interruptions from emergencies occur.

(Background) Phytotoxicity refers to the capacity of chemical substances or environmental factors to have a negative impact on plants. This is a crucial issue in both the context of crop cultivation and environmental protection. (Material and Methods) The research results were based on a 3-year field experiment conducted at the experimental station in Jadwisin (52°28′ N, 21°02′ E) on loamy soil. The experiment was set up using a randomized sub-block design in a split-split-plot arrangement, with three replications. The first-order factor consisted of potato cultivars, while the second-order factors were weed control methods: 1) Control – without protection; 2) mechanical weed control, extensive mechanical treatments to close rows; 3) Sencor 70 WG – pre-emergence (PRE) of potatoes; 4) Sencor 70 WG + Titus 25 WG + Trend 90 EC – PRE of potatoes; 5) Sencor 70 WG – post-emergence (POST) of potatoes; 6) Sencor 70 WG + Titus 25 WG + Trend 90 EC – POST of potatoes; 7) Sencor 70 WG + Fusilade Forte 150 EC – POST of potatoes; 8) Sencor 70 WG + Apyros 75 WG + Atpolan 80 SC – POST of potatoes. The phytotoxic effects of herbicides on potato plants and weeds were assessed every 7 days, starting from the date when the first signs of damage appeared, until they stabilized or disappeared. (Results:) Phytotoxic damage to potato and weed plants were caused by the chemical weed control methods used. The response of potato plants to herbicides was significantly related to the genetic traits of the cultivars and meteorological conditions in the years of research. (Conclusion:) Phytotoxicity is an important aspect in both agriculture and environmental protection. Research on its mechanisms and impact will enable the development of effective plant protection strategies and the preservation of ecosystem balance.

Background: Migraine is one of the most common health conditions in the reproductive male and female population. Premenstrual syndrome (PMS) is a common condition that affects many women during their menstrual cycle. around 50 to 60% have menstrual headaches among the migraineur women. The symptoms in the majority were mild, but 5–8% may suffer moderate to severe symptoms, accompanied by considerable distress or functional dysfunction. Premenstrual migraine (PMM) refers to migraines that occur with the menstrual cycle. It affects approximately 50% of women with migraine and can be debilitating in terms of both frequency and severity of symptoms. This information is important for medical professionals in Saudi Arabia to be aware of so, as to provide better medical care and support which can significantly improve the person's quality of life of women who suffer from PMS and menstrual migraines. Objectives: To estimate the prevalence of menstrual migraines in women, to evaluate the severity and frequency of menstrual migraines in women with PMS, and to identify potential risk factors aggravating menstrual migraines in women with PMS. Methodology: A cross-sectional community-based study was conducted on reproductive age (18-50Years) women who have regular menstrual cycles with experience migraine headaches and are diagnosed with PMS and menstrual migraine, using a self-administered questionnaire between December 2022 to May 2023 in Saudi Arabia. Results: Out of 2130 women participants 397 were suffering from migraine which is 18.6%. Of the total 397(18.6%) Migraineurs individuals 230 (57.9%) were suffering from menstrual migraine and 167 (42.1%) were non-menstrual migraineurs, in general, reproductive women menstrual migraine is 10.7% and non-menstrual migraine is 7.8%. The BMI is increasing the incidence of menstrual migraines is increasing. Migraine Disability Around one-third of the participants were suffering from III–moderate disability 134 (33.8) Most of the menstrual migraine victims at least 3 days in the last three months were absent from their duties due to their menstrual migraines. Conclusions: Migraine attacks during the menstrual cycle cause the impairment of their social and physical ability to perform their routine household, and academic activities and unable to fulfill their professional commitments. To better understand the Menstrual Migraine and Non-menstrual migraine large prospective studies are required to plan the best management methods.

Currently, peptic ulcers are widely studied as an infectious disease caused by Helicobacter pylori primarily due to 3 supporting evidences, and this etiology may explain the other 3 observations, but cannot confront the challenges of the 15 major characteristics and the other 75 observations/phenomena of peptic ulcers. To address the challenges, a recently published Complex Causal Relationship with its accompanying methodologies was applied to analyze existing data. Peptic ulcers are identified as a psychosomatic disease triggered by psychological stress, where Helicobacter pylori plays a secondary role in only the late phase of ulceration. This new etiology elucidated all the 15 major characteristics and 81 observations/phenomena of peptic ulcers in a series of 6 articles. This sixth article focuses exclusively on the controversies surrounding the role of Helicobacter pylori in peptic ulcers. In-depth analyses find that all the 3 evidences supporting “peptic ulcers are an infectious disease caused by Helicobacter pylori” are deceiving, and 2 of the 3 explainable observations may have been misinterpreted. Meanwhile, the definitions of ‘etiological factor’ and ‘causality’ do not support ‘H. pylori infection is an etiological factor of peptic ulcers’, and existing literatures have presented a controversial view on the role of Helicobacter pylori in peptic ulcers. Interestingly, if “peptic ulcers are an infectious disease caused by Helicobacter pylori” is considered an illusion, all the characteristics of the disease, along with all the clinical, epidemiological, and laboratory observations/phenomena, can be fully understood. This illusion has misguided peptic ulcer research over the past 36 years with little progress in the field, and that may represent a widespread situation in modern medical research, resulting in a direct interference with the true understanding of disease. Evidently, keeping the concept “illusion” in mind may help remove a huge obstacle that impedes medical advance, thereby facilitating the in-depth study of disease.

Hemoglobin is one of the proteins that are more susceptible to S-glutathionylation and the levels of its modified form, glutathionyl hemoglobin, increase in several human pathological conditions. The scope of the present review is to provide knowledge about how hemoglobin is subjected to be S-glutathionylated and how this modification affects its functionality. The different diseases that showed increased levels of glutathionyl hemoglobin and the methods used for its quantification in clinical investigations will be also outlined. Since there is a growing need for precise and reliable methods of markers of oxidative stress in human blood, this review highlights how glutathionyl hemoglobin is more and more emerging as a good indicator of severe oxidative stress but also as a key pathogenic factor in several diseases.

Our recent work has focused on the application of infinite group theory and related algebraic geometric tools in the context of transcription factors and microRNAs. We were able to differentiate between “healthy" nucleotide sequences and disrupted sequences that may be associated with various diseases. In this paper, we extend our efforts to the study of messenger RNA metabolism, showcasing the power of our approach. We investigate (i) mRNA translation in prokaryotes and eukaryotes, (ii) polyadenylation in eukaryotes, which is crucial for nuclear export, translation, stability, and splicing of mRNA, (iii) miRNAs involved in RNA silencing and post-transcriptional regulation of gene expression, and (iv) the identification of disrupted sequences that could lead to potential illnesses. To achieve this, we employ (a) infinite (finitely generated) groups fp, with generators representing the r+1 distinct nucleotides and a relation between them [e.g., the consensus sequence in the mRNA translation (i), the poly(A) tail in item (ii), and the miRNA seed in item (iii)], (b) aperiodicity theory, which connects “healthy groups" fp to free groups Fr of rank r and their profinite completion F^r, and (c) the representation theory of groups fp over the space-time-spin group SL2(C), highlighting the role of surfaces with isolated singularities in the character variety. Our approach could potentially contribute to the understanding of the molecular mechanisms underlying various diseases and help develop new diagnostic or therapeutic strategies.

A Bacille Calmette-Guérin (BCG) is still the only licensed vaccine for the prevention of tuberculosis, providing limited protection against Mycobacterium tuberculosis infection in adulthood. New advances in delivery of DNA vaccines by electroporation have been made in the past decade. We evaluated the safety and immunogenicity of DNA-hsp65 vaccine administered by intramuscular electroporation (EP) in cynomolgus macaques. Animals received three doses of DNA-hsp65 at 30-days intervals. We demonstrated that intramuscular electroporated DNA-hsp65 vaccine immunization of cynomolgus macaques was safe, and there were no vaccine-related effects on hematological, renal, or hepatic profiles, compared to the pre-vaccination parameters. No tuberculin skin test conversion nor lung X-ray alteration was identified. Further, low, and transient peripheral cellular immune response and cytokine expression were observed, primarily after the third dose of the DNA-hsp65 vaccine. Electroporated DNA-hsp65 vaccination is safe but provided limited enhancement of peripheral cellular immune responses. Preclinical vaccine trials with DNA-hsp65 delivered via EP may include a combination of plasmid cytokine adjuvant and/or protein prime-boost regimen, to help the induction of a stronger cellular immune response.

Personal Information Management Systems (PIMS) are acquiring a prominent role in the data economy by promoting services that help individuals to have more control over the processing of their personal data, in line with the European data protection law. One of the highlighted solutions in this area is Solid, a new protocol that is decentralizing the storage of data, through the usage of interoperable Web standards and semantic vocabularies, to empower its users to have more control over the processing of data by agents and applications. However, to fulfill this vision and gather widespread adoption, Solid needs to be aligned with the law governing the processing of personal data in Europe, the main piece of legislation being the General Data Protection Regulation (GDPR). To assist with this process, we analyze the current efforts to introduce a policy layer in the Solid ecosystem, in particular, related to the challenge of obtaining consent for processing personal data, focusing on the GDPR. Furthermore, we investigate if, in the context of using personal data for biomedical research, consent can be expressed in advance, discuss the conditions for valid consent and how it can be obtained in this decentralized setting, namely through the matching of privacy preferences, set by the user, with requests for data and whether this can signify informed consent. Finally, we discuss the technical challenges of an implementation that caters to the previously-identified legal requirements.

Extensive damage to peripheral nerves is a health problem with few therapeutic alternatives. In this context, the development of tissue engineering seeks to obtain materials that can help recreate environments conducive to cellular development and functional repair of peripheral nerves. Different hydrogels have been studied and presented as alternatives for future treatments to emulate the morphological characteristics of nerves. Along with this, other research proposes the need to incorporate electrical stimuli into treatments as agents that promote cell growth and differentiation; however, no precedent correlates the simultaneous effects of the types of hydrogel and electrical stimuli. In this research, the neural differentiation of PC12 cells we are evaluated, relating the effect of collagen, alginate, GelMA, and PEGDA hydrogels with electrical stimulation modulated in four different ways. Our results show significant correlations for different culture conditions, allowing us to develop new experimental schemes for new materials in peripheral nerve engineering.

The dynamic interaction between carbon nanodots (CNDs) and cannabidiol (CBD) has captured significant attention as an innovative avenue for redefining drug delivery and amplifying therapeutic effectiveness. This in-depth review delves into the intricate synergy between these two elements, unveiling their profound potential in medicine. Commencing with an examination of the unique characteristics of CNDs and the techniques governing their synthesis, we discuss their versatility as drug carriers, highlighting their invaluable role in advancing CBD delivery. Cannabidiol, a non-psychoactive compound sourced from cannabis, has emerged as a focal point for its diverse therapeutic attributes. Nevertheless, the limitations posed by its restricted bioavailability and susceptibility to degradation pose substantial hindrances to realizing its full potential. Here, we elucidate how the amalgamation of CBD with CNDs transcends these challenges. We delve into the mechanisms that underlie this synergy, such as the augmentation of solubility and the safeguarding of CBD against premature breakdown, providing an intricate analysis. We will also journey you through a comprehensive exploration of diverse CBD loading techniques onto CNDs, dissecting the realms of physical encapsulation, covalent bonding, and adsorption processes. In summation, the combination of CNDs and CBD presents an extraordinary opportunity to elevate therapeutic outcomes. This synergetic paradigm masterfully tackles pivotal challenges in drug delivery, thereby paving the path for pioneering medical solutions.

The transportation of feed pellets via pneumatic conveying plays an improtant role in feed industry. In recent years, many efforts are made both exprimentally and numerically to gain a better understanding of the underlying mechanism for pneumatic conveying. Though few of those research is directly related to feed pellets, it can be beneficial to draw a full picture of rencent development in pneumatic conveying, with emphasis on aspects extendable to feed transportation. This paper reviews first the major factors concerning feed pellets pneumatic conveying, such as particle breakage, pipe wear and electrostatic. Building on that, new advancement including emerging new technologies in experiments and simulations are discussed, with a focus on the experimental measurements and mathematical models, repectively. The needs for future research and the analogy to feed pellets tranportation is given lastly.

Balo’s concentric sclerosis is a rare disease and a subtype of multiple sclerosis. A 38-year-old male patient presented to the hospital with the complaint of numbness in the left-sided upper and lower limb, slurring of speech and left-sided headache for 15 days. Further investigation was done and in ECG ‘Delta wave’ was identified along with tachycardia. Diagnosis of Wolff Parkinson White syndrome was made. The patient’s MRI Brain has shown a non-enhancing intra-axial altered signal intensity lesion at the callose-septal interface adjacent to both lateral ventricles, which was identified as Balo’s concentric sclerosis.

The World Meteorological Organization (WMO) recommends that the most recent 30-year period, i.e. 1991-2020, shall be used to compute climate normals of geophysical variables. A unique aspect this recent 30-year period is that the satellite-based observations of many different essential climate variables are available during this period, thus opening up new possibilities to provide a robust, global basis for the 30-year reference period in order to allow climate monitoring and climate change studies. Here, using the satellite-based climate data record of cloud and radiation properties, CLARA-A3, for the month of January between 1981 to 2020, we illustrate the difference between climate normal, as defined by guidelines from WMO on calculations of 30-yr climate normals, and climatology. It is shown that this difference is strongly dependent on the climate variable in question. We discuss the impacts of the nature and availability of satellite observations, variable definition, retrieval algorithm and programmatic configuration. It is shown that the satellite-based climate data records show enormous promise in providing climate normal for the recent 30-year period (1991-2020) globally. We finally argue that the holistic perspectives from the global satellite community should be increasingly considered while formulating the future WMO guidelines on computing climate normals.

The Jeryak, a hybrid offspring of Gannan yak and Jersey cattle, exhibits evident hybrid advantages over the Gannan yak in terms of production performance and other various aspects. The small non-coding RNAs known as miRNAs exert a significant regulatory influence on gene expression post-transcriptionally. However, the regulatory mechanism of miRNA associated with muscle development in Jeryak remains elusive. To elucidate the regulatory role of miRNAs in orches-trating the skeletal muscle development in Jeryak, we selected dorsal longissimus muscle tissues from Gannan yak and Jeryak for transcriptome sequencing analysis. A total of 230 (DE)miRNAs and 1819 differentially expressed mRNAs (DEMs) were identified in the longest dorsal muscle of Gannan yak and Jeryak. The functional enrichment analysis revealed a significantly enrichment of target genes from differentially expressed (DE)miRNAs and DEMs in signaling pathways associ-ated with muscle growth, such as the Ras signaling pathway and the MAPK signaling pathway. The network of interactions between miRNA and mRNA suggested that some differentially ex-pressed miRNAs, including miR-2478-z, miR-339-x, novel-m0036-3p and novel-m0037-3p, played a pivotal role in facilitating muscle development. These findings help us to deepen our under-standing of the hybrid dominance of Jeryaks and provide a theoretical basis for further research on the regulatory mechanisms of miRNAs associated with Jeryak muscle growth and development.

Excessive use of antibiotics to control colibacillosis on poultry farms in Morocco contributes to the development of multiresistant avian pathogenic E. coli. Autogenous vaccines are an alternative to antibiotic usage; the main goal of this study was to assess the efficacy of this approach to control recurrent outbreaks of colibacillosis in a large broiler production flow. A tetravalent autogenous vaccine (serotypes O78, O88, O91, and O185) was produced from E. coli strains isolated from clinical lesions in breeding hens and used on two farms (65,000 breeding hens in total). On each farm, contemporaneous groups were included: groups vaccinated twice (12 and 18 weeks of age) and unvaccinated control groups. The performances of these flocks, as well as the performances of broilers hatched from these breeders (12 farms, over 600,000 broilers in total), were recorded. A significant reduction in lesion scores, mortality rate and a significant increase in the number of saleable day-old chicks were observed among vaccinated hens. In broilers, body weight at slaughter, lesion scores, food conversion ratio, mortality and condemnation rates were significantly improved. This is the first field observation of a lasting effect of breeder hens immunization with an autogenous vaccine against E. coli on their offspring.

This article explores the relationship between green energy and cryptocurrencies in the sustainable energy finance sector. The research findings contribute to our understanding of the application of green economy practice, enabling investors in financial markets, policymakers, and stakeholders to make informed decisions and develop specific strategies. Adopting the green economy paradigm makes it possible to promote collaboration and innovation by integrating ethical and responsible principles that can improve the overall quality of processes and boost sustainable growth. Cryptocurrencies have been widely used as financial instruments over the last decade. Given the development of the cryptocurrency market and the growing awareness of greener and more energy-efficient tokens, the green economy has become a popular topic for understanding economic and political issues. However, the literature still lacks clear evidence on how cryptocurrencies interact with green energies. Therefore, this study examines the long- and short-term relationships between dirty cryptocurrencies such as Bitcoin (BTC), Ethereum (ETH), clean cryptocurrencies such as Cardano (ADA), Ripple (XRP), Stellar (XLM), and green energies such as ISE Clean Edge Global Wind Energy, S&P Global Clean Energy, S&P TSX Renewable Energy and Clean Technology, Solactive China Clean Energy, in the period from January 2020 to September 2023. The results show that diversification is key, with clean cryptocurrencies such as ADA, XLM and XRP offering diversification opportunities alongside "dirty" cryptocurrencies such as BTC and ETH. Although sustainable energy indices show mixed evidence in the long and short term, they remain relevant for those who focus on clean energy investments. It is also becoming increasingly relevant for investors in sustainable portfolios to assess their environmental impact, especially for energy-intensive cryptocurrencies, and it is advisable to explore sustainable blockchain technologies.

Hearing loss stands as the most prevalent sensory deficit among humans, posing a significant global health challenge. Projections indicate that by 2050, approximately 10% of the world's population will grapple with disabling hearing impairment. While approximately half of these cases have a genetic etiology, traditional interventions such as hearing aids and cochlear implants do not completely restore normal hearing. The absence of biological treatment has prompted significant efforts in recent years, with a strong focus on gene therapy to address hereditary hearing loss. Although several studies have exhibited promising recovery of common forms of genetic deafness in mouse models, existing challenges must be overcome to make gene therapy applicable in the near future. Herein, we summarize the primary gene therapy strategies employed over past years, provide an overview of the recent achievements in the preclinical studies for genetic hearing loss, and outline the current key obstacles to cochlear gene therapy.

This work focuses on addressing the dynamic positioning and trajectory tracking problem for a 4 degree-of-freedom (DOF) unmanned underwater vehicle (UUV) in the presence of nonlinear dynamics, parametric uncertainties, system constraints, and time-varying external disturbances. To tackle this problem, a disturbance observer-based control (DOBC) scheme is proposed. The scheme is structured around the model predictive control (MPC) method integrated with an extended active observer (EAOB). Compared to the conventional disturbance observer, the EAOB has the unique ability to handle both external disturbances and system/measurement noises simultaneously. The EAOB leverages a combination of sensor measurements and a system dynamic model to estimate disturbances in real-time, which allows continuous estimation and compensation of time-varying disturbances back to the controller. The proposed disturbance observer-based MPC (DOBMPC) is implemented by feeding the estimated disturbances back into the MPC’s prediction model, which forms a robust adaptive controller with a parameter-varying model. The proposed control strategy is validated through simulations in a Gazebo and Robot Operating System (ROS) environment. The results show that it can effectively reject unpredictable disturbances and improve the UUV’s control performance.

The formation and functioning of membrane-less organelles (MLOs) is one of the main driving forces in the molecular life of the cell. These processes are based on the separation of biopolymers into phases regulated by multiple specific and nonspecific inter- and intramolecular interactions. Among the realm of MLOs, a special place is taken by the promyelocytic leukemia nuclear bodies (PML-NBs or PML bodies), which are the intranuclear compartments involved in the regulation of cellular metabolism, transcription, maintenance of genome stability, response to viral infection, apoptosis, and tumor suppression. According to the accepted models, specific interactions, such as SUMO/SIM, formation of disulfide bonds, etc., play a decisive role in the biogenesis of PML bodies. In this work, a number of bioinformatics approaches were used to study proteins found in the proteome of PML-bodies for their tendency to spontaneous liquid-liquid phase separation (LLPS), which is usually caused by weak nonspecific interactions. 205 proteins found in PML bodies have been identified. It has been suggested that UBC9, P53, HIPK2, and SUMO1 can be considered as the scaffold proteins of PML bodies. It was shown that more than half of the proteins in the analyzed proteome are capable of spontaneous LLPS, with 85% of the analyzed proteins being intrinsically disordered proteins (IDPs), and remaining 15% being proteins with intrinsically disordered protein regions (IDPRs). About 44% of all proteins analyzed in this study contain SUMO binding sites and can potentially be SOMYylated. These data suggest that weak nonspecific interactions play a significantly larger role in the formation and biogenesis of PML bodies than previously expected.

Introduction: Intrauterine fetal death (IFD) is death of fetus after the 20th week of gestation. Despite regular monitoring, the incidence of IFD remains high. This study aims to assess the incidence and risk factors for IFD in term pregnancies for better prevention and reduction of neonatal morbidity and mortality. Materials and Methods: A retrospective cohort study was conducted with term pregnant women diagnosed with IFD. The analysis included the number of deliveries, live births, and stillbirths. Statistical analysis involves descriptive and analytical statistical methods. Results: Average age was 30 years. Most patients had intermediate and high education, and one-third of patients had regular pregnancy monitoring. 53.33% were primiparous, and pregnancies occurred spontaneously. IFD mainly occurred in the 39th week of gestation. The average birth weight was approximately 3000g. 38.3% had one to two associated diseases, 5% more than three, and 56.7% were healthy. Recurrence of IFD was reported by 10% of patients, while 8.33% had a history of spontaneous abortion. Over 80% of placental histopathological findings indicated some pathology (infarction, infections, abruptio placenta). Conclusion: The most significant risk factors were pregnancy-induced hypertensive disorders, obesity, and diabetes, followed by hypothyroidism, maternal tachycardia, and anemia.

Gentiopicroside (GPS) is a leading component of several plant species from Gentianaceae botanical family. As a compound with plenty biological activities and a component that is often consumed in dietary supplements and herbal drugs, GPS has an important role in the regulation of physiological processes in humans. Recent studies on the type 2 receptors shed new light on GPS applications showing its agonistic properties that could be meaningful in the future therapeutic strategies of Parkinson’s disease, thyroid disorders or cancer states. This review aims to collect previously published reports on the biological properties of GPS as a single compound that were confirmed by in vitro and in vivo studies, and to draw attention at the newly discovered role of this bitter-tasting secoiridoid as a type 2 receptor agonist. Thanks to these properties, the research on this substance could be revisited.

This study aimed to investigate the potential correlations and differences between patients with Acute Coronary Syndrome (ACS) and controls. Emphasis was placed on examining the relationship between arterial blood gas PH value and arterial blood gas lactate value as well as assessing the utility of the Peripheral Perfusion Index (PI) in ACS management. Materials and Methods: A prospective observational study was conducted between January 1, 2023, and July 1, 2023, involving 60 ACS patients and 30 control subjects in an emergency department. The diagnosis of ACS was confirmed by experienced emergency physicians, and various parameters, such as peripheral perfusion index, blood gas values, and cardiac biomarker values, were collected. The statistical analyses included Pearson’s chi-square test, Mann-Whitney U test, Student’s t-test, and others, using SPSS version 18.0. There were significant differences in the mean age, perfusion index, and lactate levels between the patient and control groups. A robust negative correlation was found between age and PI, and a moderate negative correlation was observed between pH and lactate levels (r = -0.301, p=0.004). The perfusion index in the patient group was significantly lower, indicating its potential diagnostic utility. The findings demonstrate the importance of arterial blood gas pH and lactate values in understanding ACS patient profiles, emphasizing the potential of PI as a noninvasive diagnostic method. The negative correlation between pH and lactate levels may offer valuable insights into risk stratification and treatment strategies for patients with ACS.

Alzheimer's disease (AD) is a progressive and evolving neurodegenerative disease with an insidious onset that can lead to memory loss and cognitive impairment. There is no effective treatment for this disease. However, early diagnosis plays an important role in treatment planning to slow down its progression, as treatment has the greatest impact in the early stages of the disease. Neurological images obtained through different imaging techniques provide powerful information and help diagnose the disease. With the wide application of deep learning techniques in disease diagnosis, especially the prominence of Convolutional Neural Networks (CNNs) in computer vision and image processing, more and more studies are proposing the use of this algorithm for the diagnosis of AD. In this paper, we first systematically introduce the impact of AD on people, detailing the biomarkers, early clinical symptoms, and risk factors of this disease. Secondly, it goes on to detail the development of CNNs, their form, and methods to help diagnose AD. It is proposed that CNNs can help diagnose AD by analyzing medical imaging data, particularly structural brain scans such as magnetic resonance imaging (MRI) and functional scans such as positron emission tomography (PET). Finally, it is concluded that CNNs are of great importance for the diagnosis of AD and that they are likely to play an increasingly important role in the early detection of the disease, the understanding of disease mechanisms, and ultimately, in the development of effective AD therapies and interventions. CNNs are playing an increasingly important role in the Their potential impact on healthcare emphasizes the importance of continued research and innovation in neural networks and medical imaging.

Neutral facial expression recognition is of great importance in various domains and applications. This study introduces a data-centric approach for neutral facial expression recognition, presenting a comprehensive study that explores different methodologies, techniques, and challenges in the field to foster a deeper understanding. The results show that data augmentation plays a crucial role in improving dataset performance. Additionally, the study investigates different model architectures and training techniques to identify the most effective approach, with the InceptionV3 model achieving the highest accuracy of 72%. Furthermore, the research examines the influence of preprocessing methods on the performance of both InceptionV3 and a simplified CNN model. Interestingly, the results indicate that preprocessing techniques positively affect the performance of the simpler CNN model but negatively impact the InceptionV3 model. The implemented system, used to evaluate the findings, demonstrates promising results, correctly classifying 77% of neutral expressions. However, there are still areas for improvement. Creating a specialized dataset that includes both neutral and non-neutral expressions would greatly enhance the accuracy of the system. By addressing limitations and implementing suggested improvements, neutral facial expression recognition can be significantly enhanced, leading to more effective and accurate results.

Disassembly is a pivotal technology to enable the circularity of electric vehicle batteries by applying circular economy strategies that extend the life cycle of their components, like remanufacturing and repurposing, or by using efficient recycling to reintegrate the gained materials in producing new battery systems. This paper aims to develop a multi-method self-configuring simulation model for investigating disassembly scenarios while considering the battery design as well as the configuration and layout of the disassembly station. We demonstrate the developed model in a case study using a battery of Mercedes-Benz and the automated disassembly station of the project DeMoBat at Fraunhofer IPA. Furthermore, we introduce two disassembly scenarios, the component-oriented and the accessibility-oriented disassembly, and compare them using the simulation model to determine several indicators, such as the frequency of tool change, the number and distribution of robot routes, the tool utilization, and the disassembly time.

This study investigates the application of Light Detection and Ranging (LiDAR) sensor technology for data collection at signalized intersections characterized by a high rate of traffic crashes. The research aims to provide valuable insights into the potential of LiDAR-based data analysis to enhance road safety and traffic management at signalized intersections. The research methodology involved the deployment of LiDAR sensors at Marlboro Pike & Brooks Dr. signalized intersection in Coral Hills, Maryland. Two LiDAR sensors installed in this intersection to collect high-resolution, three-dimensional data of the intersection area from June, 1^st to July, 7^th 2023. The data included information on vehicle trajectories, speeds, and behaviors, as well as pedestrian and cyclist movement patterns. Concurrently, historical traffic crashes recorded and traffic flow data were obtained for the same intersection.The analysis of LiDAR data involved several key aspects including LiDAR data allowed for a precise evaluation of traffic flow patterns, including congestion points, traffic volume fluctuations, and peak-hour behavior. This information provided insights into potential factors contributing to crashes. By analyzing LiDAR data, the study identified near-miss incidents, which are often precursors to actual crashes. This proactive approach could assist in identifying crash-prone areas within the intersection. The LiDAR data analysis also focused on pedestrian and cyclist movements, including jaywalking and bike lane usage. The aim was to identify areas where infrastructure improvements could enhance safety for vulnerable road users. LiDAR data was compared with historical crash data to identify specific locations within the intersection that exhibited a high frequency of crashes. This information can guide targeted safety interventions. Last but not least, the study explored opportunities to optimize traffic signal timings based on real-time traffic data from LiDAR. Adaptive signal control could help mitigate congestion and reduce the risk of crashes.The results of this study demonstrated the potential of LiDAR sensor technology in collecting detailed data for traffic analysis in signalized intersections. By combining LiDAR data with historical crash records and traffic flow data, traffic engineers and urban planners can develop evidence-based strategies to reduce the frequency and severity of crashes in high-risk areas. Ultimately, this research contributes to a comprehensive understanding of how LiDAR technology can be employed to enhance road safety and traffic management, providing valuable insights for traffic engineers, urban planners, and policymakers seeking to improve the safety and efficiency of signalized intersections with a history of high traffic crashes.

Vulvovaginitis is a common and potentially serious gynecological condition that can have a significant impact on the physical, emotional, and social well-being of young women and adolescents. The condition is caused by a variety of factors, including bacterial, viral, and fungal infections, as well as hormonal changes and other underlying conditions. The symptoms of vulvovaginitis can include itching, burning, pain, discharge, and bleeding, which can impact the quality of life of affected individuals. This article examines the effect of Vulvovaginitis on Nigerian students residing in dormitories, highlighting the causes, symptoms, complications, and treatment options. The study emphasizes the need for improved sanitation, education on personal hygiene, and easy access to effective treatment to mitigate the spread of this infection.

Traffic signal control plays a key role in managing urban traffic flow, enhancing safety, and minimizing congestion and conflicts. Effective green time allocation is a critical element of this control process. This research explores the utilization of LiDAR sensor technology in the optimization of green time allocation for one phase of a traffic signal at a signalized intersection. LiDAR sensors provide precise and real-time data on vehicle presence and traffic patterns, enabling a data-driven approach to traffic signal control. The study begins with an analysis of the limitations of traditional traffic signal control strategies, which often rely on fixed-time plans or rudimentary vehicle detection systems. These approaches can lead to suboptimal green time allocation, resulting in inefficient traffic management and increased vehicle delays.The integration of LiDAR sensors provides detailed information on vehicle queues, arrival rates, and vehicle types. The research presents a practical framework for green time allocation optimization, considering factors such as intersection geometry, traffic volumes, and signal coordination. An intelligent control algorithm was developed that uses LiDAR data to determine the optimal green time for a specific phase, thereby reducing unnecessary waiting times and enhancing intersection efficiency. The effectiveness of the proposed LiDAR-based green time allocation strategy is demonstrated through extensive field tests. The results indicate significant improvements in intersection throughput, reduced delays, and enhanced traffic safety. In conclusion, this research highlights the transformative potential of LiDAR sensor technology in traffic signal control, specifically in the context of optimizing green time allocation. The findings support the notion that adaptive and data-driven strategies, when integrated with LiDAR sensors, can contribute to more efficient, sustainable, and safe urban traffic management. This research aims to provide valuable insights for transportation engineers, policymakers, and researchers seeking innovative solutions for modern urban traffic control.

Traffic congestion is a persistent and challenging problem in urban areas, leading to increased travel times, fuel consumption, and environmental pollution. Signalized intersections play a pivotal role in regulating traffic flow, and their efficiency has a direct impact on the overall traffic performance of a city. This study investigates the effect of traffic signal in managing traffic volume and reducing congestion and delays at signalized intersections through a comprehensive analysis of existing research, data collection, and simulations.The research begins by analyzing the traffic characteristics by an installed LiDAR sensor at E Cold Spring Ln – Hillen Rd intersection in Baltimore City, MD. When the signal at this intersection stopped working for some hours during a working day in September 2023, the LiDAR recorded vehicle and pedestrian counts, vehicle-vehicle and vehicle-pedestrian conflicts, and jaywalking events conflicts. The research aims to assess the impact of traffic signal failures on traffic flow, congestion, safety (V2V and V2P conflicts), and the frequency of jaywalking events before, during, and after improper performance of the traffic signal. Furthermore, this study explores the factors influencing traffic signal performance, including traffic demand, geometric layout, pedestrian interactions, and the integration of emerging technologies. The analysis results highlighted the importance of signal control systems existence at this intersection that can adjust signal timing in response to changing the real-time traffic conditions.Reduced congestion, minimized delays, and enhanced traffic flow are observed outcomes, contributing to a more sustainable and efficient urban transportation system. However, it is crucial to consider the trade-offs and challenges associated with traffic signal optimization, such as the potential for increased travel times for certain modes of transportation and the need for ongoing maintenance and updates. In conclusion, this study underscores the pivotal role of traffic signals in managing traffic volume and reducing congestion and delays at signalized intersections. Through evidence-based analysis and innovative signal control strategies, urban planners and transportation authorities can work towards creating more efficient, sustainable, and less congested transportation networks. The insights derived from this research can inform policy decisions and guide the development of future traffic management solutions, ultimately leading to improved quality of life in urban areas.

The $k$-set tree connectivity, as a natural extension of classical connectivity, is a very important index to evaluate the fault-tolerance of interconnection networks. Let $G=(V, E)$ be a connected graph and a subset $S\subseteq V$, an $S$-tree of graph $G$ is a tree $T=(V',E')$ that contains all the vertices of $S$. Two $S$-trees $T$ and $T'$ are internally disjoint if and only if $E(T)\cap E(T')=\varnothing$ and $V(T)\cap V(T')=S$. The cardinality of maximum internally disjoint $S$-trees is defined as $\kappa_{G}(S)$, and the $k$-set tree connectivity is defined by $\kappa_{k}(G)=\min\{\kappa_{G}(S)|S\subseteq V(G)\ \text{and} \ |S|=k\}$. In this paper, we show that the $k$-set tree connectivity of hierarchical folded hypercube when $k=4$, that is, $\kappa_{4}(HFQ_{n})=n+1$, where $HFQ_{n}$ is hierarchical folded hypercube for $n\geq 7$.

This paper introduces in general the conservation work of the Nara Palace Site in Japan carried out by Japanese conservation experts. Concerning conservation theory, this paper focused on the international conventions in which the 1994 Nara Document on Authenticity plays an important role in contributing to Japanese cultural heritage conservation achievements with the expansion of Cultural diversity and Heritage diversity, the Values and Authenticity conceptions which proposed a new orientation in terms of awareness and openness broader vision in identifying architectural heritage values. Regarding, based on the 1994 Nara Document on Authenticity, the 1964 Venice Charter, and the 1999 Bura Charter, we try to propose a new concept of the so-called “Architectural Heritage DNA” and its potential structure, providing a simple formula for the authentic values appraisal of the heritage conservation works. In addition, we also try to supplement the concept of Inheritance between Conservation and Development which is the lack of international conventions of cultural heritage conservation. The viewpoints expressed in this paper are based on the most common concepts of international conventions but interpreted in a new-understandable, practical, and highly applicable way possible to the current socio-political situation and in the future, as well.

Rammed earth in a built environment has vapor diffusion characteristics and humidity control ability each of which are respectively attributed to the porous structures and the hydrophilic properties. Indeed, these structures and properties, which allows easily absorbing water parti-cles, hence, affecting the durability of a rammed earth wall. This paper presents the water repel-lency method for rammed earth walls which synthesizes siloxane copolymers containing fluo-rine. The water-repellent properties are investigated by measuring the contact angle, water ab-sorption rate, and compressive strength after spray coating with the synthesized siloxane co-polymers on the surface of the rammed earth specimens under study. The water contact angle of the specimen coated with a siloxane copolymer containing 10 mol.% of a silane monomer with a fluorine group is about 140o. The water absorption of the specimen obtained after immersing in water for 24 hours is low at about 3.5 wt.%. In addition, the compressive strength is remained more than 80% of the corresponding strength of the specimen which is not immersed into water. It is confirmed that the use of a 10% by volume of the siloxane copolymer containing the fluo-rine group may assure the water-repellent performance and the economic competitiveness.

Prescriptions for fuels management are universally applied across forest types in British Columbia, Canada, to reduce fire behaviour potential in the wildland-urban interface. Fuel thinning treatments are assumed to reduce the potential for sustained ignition and crown fire initiation by reducing surface fuel loading. We hypothesized that these prescriptions are not appropriate for the coastal wet forests in the Whistler region of the province. Our study measured the efficacy of fuel thinning treatments in four stands located in the Whistler community forest. We examined several in-stand microclimate variables during snow melt in the spring and at the height of fire danger in late summer, at thinned and unthinned locations paired using GIS- analysis. We found that thinning increased the wildfire risk based on the differences between unthinned and thinned areas in the same forest stand.

Morphine-induced antinociception is partially reduced in interleukin-31 (IL-31) receptor A (IL-31RA)-deficient mice, indicating that IL-31RA is crucial for morphine-induced peripheral antinociception. Herein, we examined the combined effects of IL-31 and morphine on antinociceptive activity and itch-associated scratching behavior (LLS) in mice, and elucidated the regulatory mechanisms. A hot-plate test was used to assess antinociception. LLS was automatically detected and recorded via computer. IL-31RA mRNA expression was assessed using real-time polymerase chain reaction. Repeated pre-treatment with IL-31 resulted in significant antinociceptive activity. Repeated administration of morphine decreased the morphine-induced antinociceptive activity, LLS counts, and regular dose, and inhibited IL-31-induced LLS. These results suggested that repeated administration of morphine depleted inter-neuronal IL-31RA levels, preventing morphine-induced antinociception. Therefore, IL-31 may be helpful as an adjunct analgesic to morphine. To explore the benefits of IL-31, its influence on morphine-induced antinociceptive tolerance in mice was examined. IL-31 and morphine combination increased analgesic action which increased the expression of DRG neuronal IL-31RA, elucidating the site of peripheral antinociception of morphine. This site may induce exocytosis of IL-31RA in the sensory nervous system. Collectively, the suppressive effect of IL-31 on morphine-induced antinociceptive tolerance may result from IL-31RA supplementation in sensory nerves.

This paper presents a deep learning-based multi-guidance line detection approach, enabling an autonomous four-wheeled agricultural robot to navigate strip farmland. The integration of Proportional-Integral-Derivative (PID) and Fuzzy Logic Control (FLC) systems optimizes the velocity and heading angle of robot, facilitating smooth navigation along identified guidance line. Enhance cornering maneuverability with real-time kinematics (RTK)-assisted Global Navigation Satellite System (GNSS) (RTK-GNSS) positioning. Additionally, the spraying system combined with deep learning can effectively identify weeds and crop nutrient deficiencies to achieve precise spraying. The guidance system prioritizes irrigation lines for navigation, with additional guidance from crop and furrow lines. Trigonometric analysis determines the angular deviation between the identified guidance line and the vertical line of the top view image. Experiments under diverse weather conditions demonstrate the stable navigation of robot at 12.5 cm/s, achieving up to 90% accuracy in weed and nutrient deficiency identification. The spraying accuracy for weeds and deficiencies averages 87% and 73%, respectively, underscoring the system's contribution to sustainable and precision horticulture practices.

We study different aspects of an exactly solvable master equation (ME). Its simplicity allows one direct access to the details of its workings, highlighting significant features and peculiarities. The existence of phase transitions is unveiled.

The aim of this study was to evaluate the clinical and radiographic outcomes of the All-on-4 technique in fully edentulous maxilla using R2GATE software for flapless, computer-guided surgery and immediate loading. Ten adult patients with fully edentulous maxilla, aged between 35 and 60 years, were included in the study between April 2021 and April 2022. The surgical procedure was performed under local anesthesia and followed the All-on-4 approach with immediate loading of implants using a screw-retained provisional acrylic resin prosthesis on the same day. Final prosthesis was delivered four months after the surgery. Clinical and radiographic outcomes were evaluated at four- and twelve-months post-operation. The study reported a 95% implant survival rate using the All-on-4 technique. The mean marginal bone level was recorded at 0.35 mm and 0.66 mm during the 4 and 12-month follow-up periods, respectively. Fixed provisional prosthesis fracture, abutment, and prosthesis screw loosening were the most frequent mechanical complications reported. Within the limitations of this study, the use of computer-guided surgery in the All-on-4 technique seemed to be a promising treatment option with high implant survival rates that may help reduce post-surgical discomfort and mechanical complications in the rehabilitation of the edentulous maxilla.

Many ethical issues arise when robots are introduced into elder-care settings. When ethically charged situations occur, robots ought to be able to handle them appropriately. Some experimental approaches use (top-down) moral generalist approaches, like Deontology and Utilitarianism, to implement ethical decision-making. Others have advocated the use of bottom-up approaches, such as learning algorithms, to learn ethical patterns from human behaviour. Both approaches have their shortcomings when it comes to real-world implementations. Human beings have been observed to use a hybrid form of ethical reasoning called Pro-Social Rule Bending, where top-down rules and constraints broadly apply, but in particular situations, certain rules are temporarily bent. This paper reports on implementing such a hybrid ethical reasoning approach in elder-care robots. We show through simulation studies that it leads to better upholding of human values such as autonomy, whilst not sacrificing beneficence.

This paper makes a theoretical contribution by exploring the integration of sustainability principles into project management. It compares two recent methodologies, PM² and PRiSM^TM, and provides a practical contribution by advocating for the adoption of these sustainability-driven practices among practitioners. Sustainability remains relatively unknown in the realm of project management, and this research aims to bridge that gap. The study follows an interpretivist philosophy and employs a combination of interviews and archival data analysis. PM², created by the European Commission, provides a project management methodology free to organizations and includes best practices from other bodies of knowledge. However, it doesn't include sustainability, because it aims to be generic. PRiSM^TM, based on the P5™, aims to make the project management process more sustainable. PRiSM^TM has P5 Impact Analysis and Sustainability Management Plan as the main differentiating deliverables and is an extension of the Triple Bottom Line, also including product and process. The PM² Alliance CEO believes that PM² aims to be generic, so a focus on sustainability would remove the methodology's "elasticity". However, users wishing to use PM² and consider sustainability can include it in the additional objectives and use PRiSM^TM differentiating deliverables.

Accurate prediction of the degree of airport delays under the influence of convective weather is crucial for collaborative traffic management implementation and improving the efficiency of airport operations. However, existing studies usually only consider numerical-type quantitative features of weather-affected traffic in their models, and lack the introduction of spatial information to comprehensively portray the traffic operation scenarios under the influence of weather. In order to overcome this problem, this paper firstly designs a new image representation of weather-affected air traffic, and constructs a multi-channel traffic and weather scene image (MTWSI) by populating the airspace two-dimensional grid with traffic and meteorological information to represent the overall traffic operation situation in the terminal area under the influence of convective weather; then, a deep convolutional neural network-based airport delay prediction model ( ADLCNN), which takes MTWSI images as input and uses a specific CNN model to extract the deep features that affect traffic operation in it to input into the subsequent classification algorithm to predict the flight delay level; finally, a series of comparative experiments are carried out on the operational data of Guangzhou Baiyun Airport, and the experimental validation shows that, compared with the traditional machine learning methods, the proposed CNN-based airport delay prediction The experimental validation shows that the proposed CNN-based airport delay prediction model has satisfactory prediction performance compared with the traditional machine learning methods, which also proves that the proposed MTWSI method can more comprehensively respond to the real traffic conditions.

The residue of chestnut processing generates a large amount of waste material, a resource not adequately exploited. The phenolic composition of water extracts from discarded pericarp of four (MURG, LOCG, ILDP and COEV) chestnut accessions and one marron variety belonging to the Sardinian biodiversity was studied. The antioxidant capacity of cold and hot water extracts was determined by DPPH, ABTS and cyclic voltammetry tests. The antiproliferative effect on normal cells (fibroblasts), and colon (RKO and SW48), breast (MCF7) and melanoma (B16F10) cancer cells, was evaluated by biological assays. MTT test demonstrated that temperature and different extraction times significantly influenced the growth of cells, both normal and tumor. The fibroblast viability was significantly reduced by moderate doses of cold extracts, but only by doses greater than 250 µg/ml of hot extracts, regardless of the accession or cultivar. An even more marked effect was observed when RKO and SW48 were treated with cold extracts, while treatments on B16F10 melanoma cells resulted less effective. Differently, the cold extracts of all accessions induced a significant increase in MCF7 cell viability starting from moderate doses (50 µg/ml), whereas hot extracts had a similar, but less evident, effect compared to reference fibroblasts.

(1) Background: The synthesis of core-shell magnetic mesoporous nanoparticles (MMSN) from phase transfer process is usually performed at 100-250 mg scale. At the gram scale, nanoparticles without core or with multicore systems are observed. (2) Methods: Iron oxide core nanoparticles (IO) were synthesized through thermal decomposition procedure of -FeO in oleic acid. Phase transfer from chloroform to water was then performed in order to wrap IO with mesoporous silica shell through the sol-gel procedure. MMSN were then functionalized with DTPA, and used for the separation of metal ions. Their toxicity was evaluated (3) Results: The phase transfer pro-cedure was crucial to obtained MMSN at large scale. Three synthesis parameters were rigorously controlled: temperature, time and glassware. Homogeneous dispersion of MMSN at the gram scale was successfully obtained. After functionalization with DTPA, the MMSN-DTPA were shown to have a strong affinity for Ni ions. Furthermore toxicity was evaluated in cells, zebrafish and through seahorse metabolic assays, and the nanoparticles were found nontoxic. (4) Conclusions: We developed a method of preparation of MMSN at the gram scale. After function-alization with DTPA, the nanoparticles were efficient in metal ion removal and separation, fur-thermore, no toxicity was noticed up to 125 µg.mL-1 in zebrafish.

The permeability of the oral or nasal mucosa is higher than that of the skin. Mucosa permeability depends mainly on the thickness and keratinization degree of the tissues. Their permeability barrier is conditioned by the presence of certain lipids. This work has the main aim of reinforcing the barrier effect of oral mucosa with a series of formulations. Sixty-three initial formulations were evaluated for transmembrane water loss, with 16 formulations selected to test on sublingual mucosa. In vitro release tests of caffeine, ibuprofen, dexamethasone and ivermectin were carried out on porcine skin, mucosa and modified mucosa in order to compare the effectiveness of the formulations. A similar permeation profile was obtained in the different membranes: caffeine > ibuprofen ~ dexamethasone > ivermectin. The most efficient formulation was a liposomal formulation composed of lipids that are present in the skin stratum corneum. Impermeability provided by this formulation was really notable mainly for the low molecular weight compounds, decreasing their permeability coefficient between 40-80%. The reinforcement of the barrier function of mucosa provides a reduction or prevention of the permeation of different actives such as viruses, contaminants, toxins, etc.

This research paper investigates ultra-wideband (UWB) localization systems by focusing on the use of average filter (AVG), Kalman filter (KF), and extended Kalman filter (EKF) algorithms, as well as a novel integrated filtering method that incorporates low-pass filter (LPF) into AVG, KF, and EKF. The study aims to improve localization loss in indoor environments using a TurtleBot robot equipped with a camera to observe ground truth positions. To evaluate the effectiveness of the proposed algorithms, a comprehensive comparison of the raw and filtered data with the camera-based ground truth observations is performed. Quantitative analyses of the results, including max, min, max-min, and mean error, are performed to evaluate the localization performance of the algorithms and the integrated filtering method. The results reveal that the integrated filtering method has performed better accuracy in comparison with existing methods.

Gibberella ear rot (GER) caused by Fusarium graminearum (teleomorph Gibberella zeae) is one of the most destructive diseases in maize that severely reduces grain yield and contaminates several potential mycotoxins. However, few efforts had been devoted to dissect the genetic basis of maize GER resistance. In the present study, a genome-wide association study (GWAS) was conducted in a maize association panel consisting of 303 diverse inbred lines. The phenotypes of GER severity were evaluated using kernel bioassay across multiple time points in the laboratory. Then, three models including fixed and random model circulating probability unification model (FarmCPU), general linear model (GLM) and mixed linear model (MLM), were conducted simultaneously in GWAS to identify single-nucleotide polymorphisms (SNPs) significantly associated with GER resistance. A total of four individual significant association SNPs with the phenotypic variation explained (PVE) ranging from 3.51 to 6.42% were obtained. Interestingly, the peak SNP (PUT-163a-71443302-3341) with the greatest PVE value, was co-localized in all models. Subsequently, 12 putative genes were captured from the peak SNP that several of these genes were directly or indirectly involved in disease resistance. Overall, these findings contribute to understand the complex plant-pathogen interactions in maize GER resistance. The regions and genes identified herein provide a list of candidate targets for further investigation, in addition to the kernel bioassay that can be used for evaluating and selecting elite germplasm resources with GER resistance in maize.

Water pollution is regarded as a dangerous problem that needs to be resolved right away. This is largely due to the positive correlation between the increase in global population and waste production, especially food waste. Hydrogel beads based on sodium alginate (Alg) and pomegranate fruit peels (PP) were developed for the adsorption of Safranin O dye (SO) in aqueous solutions. The obtained Alg-PP beads were widely characterized. The effects of the contact time (0-180 min) and initial concentration (10-300 mg/l), the initial pH (2-10), the adsorbent dosage (1-40 g/l) and the temperature (293-333 K) were investigated through batch tests. The data proved that the adsorption kinetics of SO reached equilibrium within 30 min and up to 180 min. The adsorption data of SO onto synthesized beads follow the pseudo second-order model. The experimental data fitted very well to both Freundlich and Langmuir models. The maximum adsorption capacity of Alg-PP could reach 8.99 mg/g at 293 K. Calculation of Gibbs free energy and enthalpy indicated that adsorption of SO onto Alg-PP is spontaneous and endothermic. Finally, analysis of diffusion and mass transport phenomena were presented. The reported results revealed that the Alg-PP beads could be used as a novel natural adsorbent for the removal of cationic dye pollutants from aqueous environments.

Ferroptosis is a recent form of non-apoptotic cell death, which occurs due to imbalance of iron homeostasis (iron overload). Oxidative stress due to the impairment of the antioxidant system is a major pathophysiology during ferroptosis, which eventually results in lipid peroxidation. The cellular and physiological biomarker of ferroptotic cell death includes major alteration in the glutathione peroxidase 4 (GPX4) antioxidant system and lipid peroxidation induced loss of plasma membrane integrity. This review elaborates the mechanism of oxidative stress which triggers ferroptosis.

Abstract—Online learning platforms provide diverse course resources, but this often result in the issue of information overload. Learners always want to learn courses that are appropriate for their knowledge level and preferences quickly and accurately. Effective course recommendation plays a key role in helping learners select appropriate courses and improving the efficiency of online learning. However, when a user is enrolled in multiple courses, Existing course recommendation methods face the challenge in accurately recommending the target course that is most relevant to the user, because of the noise courses. In this paper, we propose a novel reinforcement learning model named Actor-Critic Hierarchical Reinforcement Learning (ACHRL). The model incorporates the Actor-Critic method to construct the profile reviser. This can remove noise courses and make personalized course recommendation effectively. Furthermore, we propose a policy gradient based on temporal difference error to reduce the variance in the training process, to speed up the convergence of the model, and improves the accuracy of the recommendation. We evaluate the proposed model on two real datasets, and the experimental results show that the proposed model is significantly outperforms the existing recommendation models (improving 3.77% to 13.66% in terms of HR@5).

Forests, as a form of natural resource, play a significant role in the social, ecological, and economic aspects of community life. One of the communities that live in the forest and dependent on the forest is Orang Rimba in Jambi. The objectives of this research are to investigate changes in ownership and access systems of natural resources within the Orang Rimba community, the factors driving these changes, and the impacts of changes in access and control over natural resources on the socio-cultural conditions of the Orang Rimba community. This research was conducted using a qualitative approach. The result of this research shows that the Orang Rimba community has experienced changes in access and control of forest resources. Many factors contribute to these changes, mainly from the Government and market forces. Moreover, these changes bring about some fundamental changes in Orang Rimba’s livelihood and even their live in general.

Several factors impact the durability of concrete bridge decks, including traffic loads, fatigue, temperature changes, environmental stress, and maintenance activities. Detecting problems such as corrosion, delamination, or concrete degradation early on can lower maintenance costs. Nondestructive evaluation (NDE) techniques can detect these issues at early stages. Each NDE method, meanwhile, has limitations that reduce the accuracy of the assessment. In this study, multiple NDE technologies were combined with machine learning algorithms to improve the interpretation of half-cell potential (HCP) and electrical resistivity (ER) measurements. A parametric study was performed to analyze the influence of five parameters on HCP and ER measurements, such as degree of saturation, corrosion length, delamination depth, concrete cover, and moisture condition of delamination. The results were obtained through finite element simulations and used to build two machine learning algorithms, a classification algorithm and a regression algorithm, based on the Random Forest methodology. The algorithms were tested using data collected from a bridge deck in the BEAST® facility. Both machine learning algorithms were effective in improving the interpretation of ER and HCP measurements using data from multiple NDE technologies.

In this work, we propose an approach for the autonomous navigation of mobile robots using fusion of sensor data by a Double Deep Q-Network with collision avoidance by detecting moving people via computer vision techniques. We evaluate two data fusion methods for the proposed autonomous navigation approach: Interactive and Late fusion strategy. Both are used to integrate mobile robot sensors through the following sensors: GPS, IMU and, an RGB-D camera. The proposed collision avoidance module is implemented along with the sensor fusion architecture in order to prevent the autonomous mobile robot from colliding with moving people. The simulation results indicate a significant impact on the success of completing the proposed mission by the mobile robot with the fusion of sensors, indicating a performance increase (success rate) of 27% in relation to navigation without sensor fusion. With the addition of moving people in the environment, deploying the people detection and collision avoidance security module has improved about 14% the success rate when compared to that of the autonomous navigation approach without the security module. Video was developed with robot navigation using the DDQN-Late Fusion https://www.loom.com/share/684afa6a5b0148afadc9a200ab9f3483.

In August 2020, the World Health Assembly launched a global initiative to eliminate cervical cancer by 2030, setting three primary targets. One key goal is to achieve a 70% screening coverage rate for cervical cancer, primarily relying on the precise analysis of Papanicolaou (Pap) or digital Pap smears. However, the responsibility of reviewing Pap smear samples to identify potentially cancerous cells primarily falls on pathologists, a task known to be exceptionally challenging and time-consuming. This paper proposes a solution to address the shortage of pathologists for cervical cancer screening. It leverages the OpenAI-GYM API to create a deep reinforcement learning environment utilizing liquid-based Pap smear images. By employing the Proximal Policy Optimization algorithm, autonomous agents navigate Pap smear images, identifying cells with the aid of rewards, penalties, and accumulated experiences. Furthermore, the use of a pre-trained convolutional neuronal network like Res-Net54 enhances the classification of detected cells based on their potential for malignancy. The ultimate goal of this study is to develop a highly efficient, automated Papanicolaou analysis system, ultimately reducing the need for human intervention in regions with limited pathologists.

The rising number of unknown-type attacks on the Internet emphasizes the significance of developing efficient intrusion detection systems, even if machine learning-based techniques can detect unknown types of attacks. The necessity for innovative techniques is highlighted by the possibility that traditional machine learning techniques will not be sufficient for identifying these unknown types of attacks. In this research, we address this difficulty by proposing a deep learning-based solution: the log-cosh variational autoencoder (LVAE). When it comes to understanding intricate data distributions and creating freshly reconstructed data, LVAE inherits the strong modeling skills of the variational autoencoder (VAE). To better imitate discrete features of actual attacks and generate unknown types of attacks, this study develops an effective reconstruction loss term employing the logarithmic hyperbolic cosine (log-cosh) function in the log-cosh variational autoencoder (LVAE). When compared to conventional VAEs, LVAE exhibits promising potential for effectively generating data that closely resembles an unknown attack, a crucial capability for increasing the unknown attack detection rate. To categorize the generated unknown-type data, eight feature extraction and classification techniques were used. Using the most recent CICIDS2017 dataset, numerous experiments were carried out, training under varying amounts of real and unknown-type attacks. Our optimal experimental results outperformed several state-of-the-art techniques with accuracy and average F1 scores of 99.89% and 99.83%, respectively. Outstanding results were also shown by the suggested LVAE strategy for producing unknown attack data. In general, our work sets a strong basis for the accurate and efficient identification of unknown types of attacks and contributes to the development of intrusion detection techniques.

(1) Background: Bronchial artery embolization has been shown to be effective in the management of neoplastic hemoptysis. However, knowledge of pulmonary artery embolization is lacking. To evaluate safety and efficacy of pulmonary artery embolization in patients presenting with hemoptysis related to lung tumors. (2) Methods: This retrospective study reviewed all consecutive patients with cancer and at least one episode of hemoptysis that required pulmonary artery embolization from December 2008 to December 2020. The endpoints of the study were technical success, clinical success, recurrence of hemoptysis and complications. (3) Results: A total of 92 patients were treated with pulmonary artery embolization (63.1 years ± 9.9; 70 men). Most patients had stage III or IV advanced disease. Pulmonary artery embolization was technically successful in 82 (89%) patients and clinically successful in 77 (84%) patients. Recurrence occurred in 49% of patients. Infectious complications occurred in 15 patients (16%). The 30-days mortality rate was 31%. At 3 years, survival rate was 3.6%. Tumor size, tumor cavitation and necrosis and pulmonary artery pseudo-aneurysm were significantly associated with recurrence and higher mortality. (4) Conclusions: Pulmonary artery embolization is an effective treatment to initially control hemoptysis in patient with lung carcinoma but recurrence rate remains high and overall survival remains poor.

The use of nitrogen fertilizers can be a source of environmental pollution; the use of or-ganomineral fertilizers can become a nutritional source for crops, ensuring sustainability in the production system. Another alternative approach is through the inoculation and co-inoculation of microorganisms. The objective was to evaluate the development, nutrition, and agronomic yield of common bean through fertilization with organomineral formula "FMO" derived from sewage sludge biosolids, combined with Rhizobium tropici inoculation and co-inoculation with Azospirillum brasilense techniques. Three bean cultivars from different commercial groups, Pérola, BRS Esteio, and BRS Pitanga, were tested. They were subjected to organomineral fertilizer application, orga-nomineral fertilizer application combined with seed inoculation with R. tropici and re-inoculation; seed co-inoculation with R. tropici + A. brasilense prior to sowing, and foliar re-inoculation with R. tropici + A. brasilense. Seed inoculation, combined with foliar re-inoculation at the V4 stage, resulted in higher productivity of common bean. The combination of R. tropici with co-inoculation with A. brasilense generally led to increased productivity compared to mineral nitrogen fertilization. The use of organomineral fertilizer alone enabled gains in development, as well as productivity. The Pérola bean cultivar showed better adaptation to the applied treatments.

Gold nanoparticles (AuNPs) have been used in a broad range of applications conferring to bio-molecules diverse proprieties such as deliver, stabilization and reduction of adverse effects of drugs or plant ex-tracts. Polyphenolic compounds from Bacopa procumbens (BP) are able to modulate proliferation, adhesion, migration and cell differentiation, reducing artificial scratch area in fibroblast cultures and promoting wound healing in in vivo model. Here, chemically synthetized AuNPs conjugated with BP (AuNP-BP) were characterized by Uv-Vis, ATR-FTIR, DLS and zeta-potential. Results showed over-lapping FTIR spectra of polyphenolic compounds from B. procumbens capping the AuNPs, stable size by the DLS and zeta potential, AuNP-BP was 44.58 nm, the zeta-potential of AuNPs was -36.3±12.3 mV after conjugation with the BP; - (AuNP-BP), the zeta-potential was reduced to -18-2±7.02 mV. Enhancement of wound healing effect were evaluated by morphometric, histochemical and FTIR changes in rat wound excision model. Results showed that the nanoconjugation process reduced 100 folds BP concentrations to have the same wound healing effect of BP alone. Besides histological and FTIR spec-troscopy analyses, demonstrated that AuNP-BP treatment displayed better macroscopical performance; the reduction on inflammatory cells, and the increased synthesis and better organization of collagen fibers.

The study of coordination practices in health policy and, especially in emergency situations is a central aspect. The COVID-19 pandemic has highlighted the need for further research on such practices, especially those that are deployed in complex and unforeseen situations to respond quickly while minimising errors. These dialogic coordination practices (DP) have been identified through case studies but have not been validated. The purpose of this study is to develop and validate a DP questionnaire for healthcare teams. The development of the items was based on a literature review and the content validation was carried out by means of a Delphi study. A total of 10 experts assessed the clarity and appropriateness of the items and their corresponding measurement scales. Consensus was reached after the second round, with a percentage of agreement greater than or equal to 90% for all items. The validation of these items constitutes a methodological innovation that responds to the call in the literature to open up new avenues for comparative studies, the possibility of generalising the findings obtained and the possibility of bringing together different approaches to the problem of coordination, key in health policy.

This study employs the FLACS code to analyze hydrogen leakage, vapor dispersion, and subsequent explosions. Utilizing pseudo-source models, a liquid pool model, and a hybrid model combining both, we investigate dispersion processes for varying leak mass flow rates (0.225 kg/s and 0.73 kg/s) in a large open space. We also evaluate explosion hazards based on overpressure and impulse effects on humans. The computational results, compared with experimental data, demonstrated reasonable hydrogen vapor cloud concentration predictions, especially aligned with the wind direction. For higher mass flow rate of 0.73 kg/s, the pseudo-source model and hybrid model proved appropriate, while the liquid pool model was more suitable for lower mass flow rate of 0.225 kg/s. Regarding explosion analyses using overpressure-impulse diagram, higher mass flow rates leaded to potentially fatal overpressure and impulse effects on humans. However, lower mass flow rates may cause severe eardrum damage at the maximum overpressure point.

Self-selecting the intensity of aerobic training is a perspective that allows practitioners to develop autonomy (choice of pace), improve physical fitness and achieve weight loss. To compare the effect of four aerobic training protocols on cardiometabolic and psychophysiological responses in physically inactive adult men and women. The sample consisted of 11 individuals aged 56 ± 10 years and BMI 29.2 ± 2.4 kg/m2 performed four different treadmill aerobic training protocols, including: 1-individual with self-selected intensity (ISS), 2-individual with prescribed intensity (IPI) (64-76% of HR max), 3-small group with self-select. selected intensity (SGS) and 4-small group prescribed intensity (SGP) (64-76% of HR max). Heart rate, lactate, perceived exertion, affective response, activation scale, enjoyment, intention to repeat the session, treadmill speed and total distance from the protocol were analyzed. Statistical analysis used ANOVA with Tukey's post hoc test (p<0.05). Heart rate, lactate, perceived exertion, activation scale, enjoyment, average speed and total distance analyzes did not show significant differences between protocols. The response affective showed a smaller decline in the ISS protocol (p<0.05), and the intention to repeat the training session was greater in the ISS protocol (p<0.05). Conclusion: The data allow us to conclude that the ISS training protocol produced superior results in affective response and intention to repeat the session.

This paper provides a data set collected with an underground shaft mobile mapping system equipped with rotated Velodyne VLP-16, Velodyne Ultra Puck VLP-32c, Livox Tele-15, and IMU Xsens MTi-30. The ground truth data was acquired with a geodetic survey including 15 ground control points and 6 Faro Focus 3D Terrestrial Laser Scanner stations of a total 273,784,932 of 3D measurement points. The aim of the paper is to describe the data set of a mining shaft. Obtained mobile mapping data can be the basis for detailed analyzes of the technical condition of the shaft. This data set provides an end-user case study of realistic applications in mobile mapping technology. It provides ground truth data, mobile mapping data and software tools for manipulation and visualization. The project is released and maintained at https://michalpelka.github.io/mine-mapping-dataset/.

As the oil industry increasingly turns to unconventional low-permeability and low-porosity reservoirs, precise post-fracture production prediction is a pivotal instrument in investment de-cision-making, formulation of energy policies, and promotion of environmental assessments. Nevertheless, despite extensive research spanning decades, the precise post-fracture production prediction based on logging parameters remains an intricate task. In this study, we gathered ex-tensive logging data and segmented the post-frac gas production during well testing on the first day to enrich the dataset. Nine pipelines were then architected using various techniques of data preprocessing, feature extraction, and advanced machine learning models. Hyperparameter op-timization was executed via the GridsearchCV. To assess the efficacy of diverse models, metrics including the coefficient of determination (R2), standard deviation (SD), and root mean square error (RMSE) were invoked. Among the several pipelines explored, the PS-NN exhibited excellent predictive capability in specific reservoir contexts (an R2 value of 0.94 and an RMSE of 48.15). In essence, integrating machine learning with logging parameters effectively assesses reservoir productivity at multi-meter formation scales. This strategy not only mitigates uncertainties en-demic to reservoir exploration but also equips petroleum engineers with monitoring on reservoir dynamics, thereby facilitating reservoir development. Additionally, this approach provides res-ervoir engineers with an efficient way of reservoir performance oversight.

The design of water Vessel fender system can minimize impact energy, which could result in severe vessel or offshore structure damage during collision. In order to protect Offshore structures and vessels from damage after impact, a Fender design approach is proposed which uses Soft materials like rubber, sand, inflated rubber tube, etc. to reduce damage on impacted vessels as well as offshore structures like wind turbines, bridges, oil drilling platforms in water etc. The fender is designed in such a way that it can handle vessels made of different material, sizes, and weights.The proposed solution is a fender consisting of a number of layers of soft sandwich materials, each layer getting softer as it moves away from the structure i.e. Hard-Soft fender design which can absorb impact energy upon collision. To handle lighter vessels made of soft or brittle materials, the outer layer is made of inflatable or Very soft foam rubber; however, the inner layer covering the offshore structure is made of hard material to handle heavy vessels made of hard material such as steel. Furthermore, the use of sand as a natural fender along waterways such as narrow channels is also proposed to reduce the cost of fender installation and catastrophic vessel impact damage on rocky ground since it produces less deformation just like rubber fender as demonstrated in the simulation. Finite Element Analysis using ANSYS software, Explicit Dynamic Autodyn, was performed. The results showed a considerable decrease in the total deformation and internal energy of the vessel and fended structure when collision occurs. Furthermore, the result showed that Hard-Soft fender layer performs much better than Soft-Hard-Soft followed by Soft-Hard Fender layer design.

Target detection of defense technology is being rapidly upgraded with modern surveillance technologies. The latest techniques of surveillance are already being implemented for defense applications. Self-protection and hiding from opposing forces are the key principle for protection of special team in defense. Camouflage textiles aims to create confusing objects for target detection of military personnel. These textiles are applied for military protection such as clothing, weapon, vehicle and location hiding nets/tents, etc. The urgent need of camouflage textiles have been formulated with a technical solution and implementation of right camouflage materials for concealment of defense target signature against dry leaves, green leaves, tree bark-woodland combat background; water-marine combat background; sand-desertland combat background; stone-stoneland combat background; snow-snowland combat background; sky combat background and ice-iceland combat background, concrete-concreteland combat background (DGTWSICB) in ultraviolet-visible-infrared (UV-Vis-IR) spectrums. This hypothesis of optical & surveillance engineering has been coalesced for advancement of UV-Vis-IR-DGTWSICB camouflage textiles technology. The principle of camouflage engineering has been approached by broader spectrum probe in UV-Vis-IR rather than Vis ranges only. Furthermore, single formulation of camouflage textiles has been proposed for multidimensional CBs-DGTWSICB. Electromagnetic spectrum, reflection, electron energy, photonic signal and imaging mechanism in UV-Vis-IR have been presented for optical engineering of concealment, detection, recognition and identification of target signature against DGTWSICB. Spectrum relationship of camouflage materials and DGTWSICB materials have been illustrated and compared in UV-Vis-IR spectrums. Camouflage material design, method design & spectral design; adaptive camouflage; techniques for camouflage textile assessment for digital camera and hyperspectral camera imaging; image processing techniques and a hierarchical model have been demonstrated for augmentation of camouflage textiles in UV-Vis-IR illumination. Therefore, anticipated design of camouflage textiles may enhance high-performance innovation for modern surveillance of military protection related to digital camera, hyperspectral camera and radar. This hypothesis includes advance guideline for camouflage textiles design for CBs-DGTWSICB.

Geospatial knowledge in massive academic papers can provide knowledge services such as location-based research hotspot analysis, spatio-temporal data aggregation, research results recommendation, etc. However, geospatial knowledge often exists implicitly in literature resources in unstructured form, which is difficult to be directly accessed and mined and utilized for rapid production of massive thematic maps. In this paper, we take the geospatial knowledge of the area studied as an example and introduce its extraction method in detail. An integrated feature template matching and random forest classification algorithm is proposed for accurately identifying research areas from the abstract texts of academic papers and producing thematic maps. Firstly, the precise recognition of geographical names is achieved step by step based on BiLSTM-CRF algorithm and improved heuristic disambiguation method; then, the area studied is extracted by the designed integrated feature recognition template of area studied using random forest classification algorithm, and a fast thematic map is designed for the knowledge of area studied, topic and literature. The experimental results show that the area studied recognition accuracy can reach 97%, the F-value is 96%, and the recall rate reaches 96%, achieving high accuracy and high efficiency of area studied extraction in text. Based on the geospatial knowledge, the thematic map can achieve the effect of fast map formation and accurate expression.

This paper proposes an upper bound for mine productivity and also a simple truck dispatch rule that demonstrates how tight the upper bound can be using simulation. It also proposes a greedy search to approximate the productivity upper bound, which is faster and often exact. Uncertainty is added to the simulation in order to verify how the productivity responds to it. Typically, the productivity upper bound is less tight close to its saturation point as a function of the number of trucks, where adding more trucks only increases queues. Furthermore, more uncertainty in the model typically leads to a less tight upper bound. The results are conducted using real data from an open pit mine in Brazil.

In the FCC conversion of heavy petroleum fractions as atmospheric residues, the main challenge for refiners to achieve the quantity and quality of various commercial products depends essentially on the catalyst used in the process. A deep characterization of the catalyst at different steps of the process (fresh, regenerated, and spent catalyst) was investigated to study the catalyst's behavior including the physicochemical evolution, the deactivation factor, and kinetic-thermodynamic parameters. All samples have been characterized by various spectroscopy methods such as N2 adsorption-desorption, UV-visible spectroscopy, Raman spectroscopy, LECO carbon analysis, Scanning electron microscopy (SEM), X-ray diffraction (XRD), X‐ray fluorescence (XRF), nuclear magnetic resonance spectroscopy (NMR13C) analysis, and Thermogravimetric analysis. The results of N2 adsorption-desorption, UV-vis, Raman, LECO carbon, and SEM images showed that the main causes of catalyst deactivation and coking were the deposition of carbon species that covered the active sites and clogged the pores, and the attrition factor due to thermal conditions and poisonous metals. The XRD and XRF results showed the catalyst’s physicochemical evolution during the process and the different interlinks between catalyst and feedstock (Nickel, Vanadium, Sulfur, and Iron) elements which should be responsible for the coking and catalyst attrition factor. It has been found that, in addition to the temperature, the residence time of the catalyst in the process also has an influence on catalyst structure transformation. NMR13C analysis revealed that polyaromatic hydrocarbon is the main component in the deposited coke of the spent catalyst. Thermogravimetric analysis showed that the order of catalyst mass loss was fresh > regenerated > spent catalyst due to the progressive losses of the hydroxyl bonds (OH) and the structure change along the catalyst thermal treatment. Moreover, the kinetic and thermodynamic parameters showed that all zones are non-spontaneous endothermic reactions.

Lung cancer (LC) stands as the foremost cause of cancer-related fatality rates worldwide. Early diagnosis significantly enhances patient survival rate. Nowadays, low dose computed tomography (LDCT) is widely employed on chest as a tool for large-scale lung cancer screening. Nonetheless, a large amount of chest radiographs causes an onerous burden on radiologists. Some computer-aided diagnostic (CAD) tools can provide insights to medical images for diagnosis and augmenting diagnostic speed. However, due to variation in parameter settings across different patients, substantial discrepancies in image voxels persist. We find different voxel-size causing a compromise between model generalization and diagnostic efficacy. This study investigates the performance disparities of diagnostic models trained on original images and LDCT images reconstructed to different voxel-sizes but isotropic. The application is to differentiate a nodule to be benign or malignant. Using 11 features, a support vector machine (SVM) is trained on LDCT images with an isotropic voxel having side-length of 1.5 mm for 225 patients in house. The result yields a favorable model performance with an accuracy of 0.9596 and an area under the receiver operating characteristic curve (ROC/AUC) of 0.9855. In addition to furnish CAD tools for clinical applications, future research is encouraged to include LDCT images from multi-centers.

Underwater wireless sensor networks (UWSNs) represent a specialized category of WSNs with versatile applications including acoustic monitoring, oil and gas exploration, and military surveillance. UWSNs face formidable challenges such as limited energy resources, extended propagation delays, and harsh conditions. Existing clustering and multi-hop routing protocols often unevenly distribute nodes geographically, causing network fragmentation and disproportionately draining the battery life of nodes near the sink due to higher data transmission demands. In this paper, we introduce an Energy-efficient Artificial Fish Swarm-based Clustering Protocol (EAFSCP), inspired by the collective behavior of fish swarms. EAFSCP is a decentralized clustering algorithm designed for acoustic monitoring in UWSNs. Its decentralized nature makes it particularly well-suited for large-scale UWSNs, where centralized algorithms may not be feasible. Through comprehensive comparisons with existing cluster-based routing protocols, our findings indicate that EAFSCP consistently outperforms them across multiple key performance metrics, including network lifetime, energy consumption, packet delivery ratio, packet loss rate, and throughput. According to the results, EAFSCP represents an effective clustering algorithm that enhances network performance, prolongs network lifespan by reducing energy consumption, promotes scalability, and provides valuable guidance for emergency response efforts.

Understanding the dynamic interaction between piles and surrounding soil under vehicular impacts is essential for effectively designing and optimizing soil-embedded vehicle barrier systems. The complex behavior of pile-soil systems under impact loading, attributed to the soil’s nonlinear behavior and large deformation experienced by both components, presents significant simulation challenges. Popular computation techniques, such as the Updated Lagrangian Finite Element Method (UL-FEM), encounter difficulties in scenarios marked by large soil deformation, e.g., impacts involving rigid piles. While mesh-free particle and discrete element methods offer another option, their computational demands for field-scale pile-soil impact simulations are considerable. We introduce the erosion method to bridge this gap by integrating UL-FEM with an erosion algorithm designed for simulating large soil deformations during vehicular impacts. Validation against established physical impact tests confirmed the method’s effectiveness for flexible and rigid pile failure mechanisms. Additionally, this method was used to investigate the effects of soil mesh density, soil domain sizes, and boundary conditions on the dynamic impact response of pile-soil systems. Our findings provide guidelines for optimal soil domain size, mesh density, and boundary conditions. This investigation sets the stage for improved, computationally efficient techniques for the pile-soil impact problem, leading to better pile designs for vehicular impacts.

The importance of utilizing an optimal and efficient braking system is emphasized in this study. Braking system optimization and efficiency were practically determined through successive tests on the brake dynamometer, according to road safety regulations. Subsequently, the results were correlated with practical tests involving consecutive braking at different speeds, tracking both the time and distance of braking. The coefficient of friction (COF) was established for each braking instance by utilizing the braking force measured on the brake dynamometer. This paper aims to highlight the genuine impact of the braking system by measuring and establishing its braking efficiency depending on the car’s speed, time, and distance of braking.

The usage of biotechnological molecules and processes is an indispensable part of the resource technology research. The development of novel biomolecules therefore needs to be adapted to the existing applicational conditions and biological processes are to be examined. Novel biosorbents may not only contribute to future applications but can be of further used, e.g. to better understand the interaction of known metal- and metalloid-interacting biological molecules and materials. This review highlights biotechnological approaches published so far for bioremediation as well as metal recovery with a special spotlight on cobalt, nickel and arsenic.

Osteoarthritis (OA) is a prevalent disease and the leading cause of pain, disability, and quality of life deterioration. Our study sought to evaluate the image quality and dose of cone-beam com-puted tomography arthrography (CBCT-A) and compare them to digital radiography (DR) for OA diagnosis. Overall, 32 cases of CBCT-A and DR with OA met inclusion criteria and were prospectively analyzed. The Kellgren and Lawrence classification (KLC) stage, sclerosis, osteo-phytes, erosions, and mean joint width (MJW) were compared between CBCT-A and DR. Image quality was excellent in all CBCT-As, with excellent inter-observer agreement. OA un-der-classification was noticed with DR for MJW (p=0.02), osteophyte detection (<0.0001), and KLC (P<0.0001). The HU values obtained for the CBCT did not correspond to the values for MDCT, with a greater mean deviation obtained with the MDCT HU for MBIR1 than MBIR2. CBCT-A has been found to be more reliable for OA diagnosis than DR as revealed by our results using three-point rating scale for the qualitative image analysis, with higher quality and an ac-ceptable dose. Moreover, the use of this imaging technique permits the preoperative assessment of extremities in OA diagnosis, the upright position and bone microarchitecture analysis being two other advantages of CBCT-A.

The presence of heavy metals in industrial effluents has recently become a source of concern for human health and the environment. Efficient removal of metal ions and wastewater treatment is essential for protecting public health and the environment. In this study, we present an eco-friendly, green synthesis of reactive and fully dispersed zerovalent iron nanoparticles (nZVI) in carbon nanofibers via an electrospinning technique. In this novel study, green tea (GT) was used as environmentally friendly, polyvinyl alcohol (PVA) was used for the stabilization and reduction of nZVI, and tetraethyl orthosilicate (TEOS) was added to provide flexibility and to increase the specific surface area of the nZVI based nanofibers. GT contains polyphenols, which act as reducing agents, converting iron ions into nZVI and the particles can then serve as the building blocks for the carbon nanofibers. TEOS can also contribute to the stability of the nZVI by coating their surfaces with a silica layer. This silica layer helps prevent the oxidation of the nZVI, thereby reducing their catalytic activity. The nZVI-based composite (∼ 400 nm) / carbonized (∼ 200 nm) nanofibrous mats were fully characterized by scanning electron microscopy. The average size of the nZVI embedded in the composite and carbonized nanofibers can range from 50 nm to 100 nm. The x-ray diffraction (XRD) analysis of nZVI-based carbon nanofibers showed that there is no crystallinity and a single-phase cubic structure. Both energy-dispersive X-ray spectroscopy (EDX) and Fourier transform infrared (FTIR) analysis also confirmed the formation of single-phase nZVI-based composite / carbonized nanofibers. The high intensity of the peaks in the FTIR spectrum indicates the formation of nZVI in the nanofibers structure. The electrospun nZVI-based carbon nanofibers have a higher surface area and better reactivity due to small particle size and large surface area-to-volume ratio. They can provide excellent water stability and dispersibility in water compared to bulk nZVI, which tend to agglomerate and settle quickly. Additionally, nanofiber morphology can enhance the mechanical strength and durability of the composite material. Due to low-cost synthesis and their high efficiency in removing pollutants, these nanofibers could be used as nano-filters for wastewater treatment.

The concentrations and fluxes of arsenic (As) and cadmium (Cd) were examined in the hydrological cycle (bulk, throughfall deposition and percolation water), litterfall and soils in a maquis broadleaved evergreen forest stand in western Greece. It was found that the enrichment of As in the atmosphere was both due to suspended geogenic material and long range transfer, whereas for Cd the long range transfer was the predominant way for deposition in the ecosystem. Three models were assessed to find the volumes of percolation water and therefore the fluxes of As and Cd in the water that leave the ecosystem permanently. When calculating the total amounts of the heavy metals in soils, the statistical uncertainty derived from every soil layer has to be taken into account.

Public parks are a community resource with an important role in improving liveability, physical, and mental wellbeing. However, exercise facilities that are suitable for people with disabilities typically have been neglected in public park design. As such, people with disabilities often are unable to independently or safely use the park. To address this shortcoming, the objective of this paper was to employ a pragmatic research through designing process in developing the design for an inclusive park. We used a mixed-methods approach in the research that included review of previous studies, semi-structured interviews, and questionnaire surveys with stakeholders were applied as design integration. Persons with disabilities specifically were consulted to express their views on all matters of inclusive park design.

Cognitive reserve is the adaptability of cognitive processes in the face of brain aging and pathology. This study aimed to validate the Arabic version of the Cognitive Reserve Index Questionnaire (CRIq) in a healthy Lebanese sample. CRIq assesses cognitive reserve through three domains: education, working activity, and leisure time. Statistical measures, including descriptive and regression analysis along with structural equation modeling, were utilized to investigate the convergent and discriminant validity of CRIq, incorporating fluid intelligence (Gf) and measures of cognitive function, long-term memory encoding and retrieval (Glr), and processing speed (Gs). Results from 174 participants revealed that the activities assessed by CRIq-Arabic were comparable to the original CRIq study, with slight cultural differences. The internal consistency of CRIq-Arabic was good (Cronbach's α = 0.88), indicating reliability. Convergent validity was confirmed, with moderate to high loadings on the cognitive reserve latent construct. Discriminant validity was supported as correlations between cognitive reserve variables and non-target constructs (Gf, Glr, Gs) were less than 1. The findings provide an initial psychometric validation of the CRIq-Arabic. Further research in clinical samples is needed to enhance its utility in neuropsychological practice.

This work deals with a systematic review of literature data concerning the theme of the integrated approach to occupational health and safety management, with particular reference to the programming of assistance plans, which guide the company's organizational choices also by aiming at the principles of the Total Worker Health. In the current regulatory framework on this issue, the UNI ISO 45001: 2018 standard assumes particular relevance, which defines the dynamic approach to occupational health and safety management systems, paying particular attention to external contextual factors that may influence corporate organizational decisions. The adoption of these systems is not mandatory, but allows companies to fulfill their duties in terms of health and safety at work, through an organizational approach aimed at awareness, involvement and participation of all subjects of the company prevention system, overcoming the phase of the mere technological and prescriptive approach, towards a holistic vision of prevention, which places the person at the center of preventive actions. In this context, the role of institutional networks and socio-economic partnerships assumes particular importance, in the activation of territorial assistance interventions to support companies for the improvement of risk management levels. To this end, the importance of verifying the effectiveness of assistance interventions emerges from the scientific debate, through the use of indicators such as quantitative ones for measuring the performance of all phases of the intervention with particular attention to the effects in terms of improved solutions developed.

By the end of 2023, biowaste must be completely separated or recycled at source based on the EU legislation. Separate biowaste collection and valorisation towards biofuels could play an essential role in the biobased circular economy. In this context, the principal goal of this paper was to demonstrate in pilot scale the technological solution of bioethanol production via the utilisation of urban source-separated biowaste within the city context of Athens, Greece. More specifically, the main aim was the demonstration of a pilot system in continuous operation (over 10 operating cycles) with real feedstock – wet separately collected biowaste. From the 11 pilot trials performed with wet feedstock, the mean starch and cellulose degradation of the pilot trials amounted up to 80.69±16.27% and 79.41±10.37% respectively, while the bioethanol yield was 74.05±6.82%. The latter was comparable to that of more intensive pretreatment methods. Homogenization and shredding that was applied in this study, stand as promising and cost-effective pretreatment methods for bioethanol production from wet feedstock. Further research is needed to optimize conditions and evaluate scalability. Nevertheless, pilot scale testing is a crucial step in the development and deployment of this technology since it serves as a bridge between laboratory research and full-scale implementation, offering a practical and controlled environment to validate and optimize the technology while minimizing risks and uncertainties.

Hafnium is a metal with rare properties, such as a low superconducting transition temperature slightly above 100 mK, which makes it attractive for a lot of applications, especially for design and fabrication of microcalorimeters with high energy resolution. In this paper we describe the results of fabrication and experimental investigation of superconducting properties of hafnium thin films in a dilution refrigerator. The considered Hf films, whose thickness is in the range from 60 to 115 nm, are deposited on substrates by electron beam evaporation. The combinations with thin layers of normal metals to decrease the critical temperature of superconducting hafnium films by proximity effect, are also considered. The critical temperature of the studied films varies from 56 to 302 mK. Also, significant increase of the critical temperature of some films over time was observed and investigated.

ABSTRACT Objectives: Typical Diagnostic Reference Levels (DRL) in terms of Computed Tomography Dose Index (CTDI) and patient dose in terms of Effective Dose (ED ) and Size Specific Dose Estimate (SSDE) were estimated in Computed Tomography (CT) guided biopsy procedures. Materials and Methods: A total of 226 CT biopsy procedures - Iliac bone, liver, lung, mediastinum and para-aortic tissue - were retrospectively analyzed and Typical DRL extracted based on ICRP 135 instructions. Results: For helical mode acquisitions, DRLs in terms of CTDIvol were 9.7 mGy for Iliac bone, 8.9 mGy for liver, 8.8 mGy for lung, 7.9 mGy for mediastinal mass and 9 mGy for para-aortic lymph nodes biopsy procedures. For biopsy acquisitions, DRL values were 7.3 mGy, 7.7 mGy, 5.6 mGy, 5.6 mGy and 7.4 mGy respectively. Also, SSDE median values ranged from 7.6 mGy to 10 mGy for biopsy acquisitions and 11,3 mGy to 12,6 mGy for helical acquisitions, as well as the median values for effective dose ranged from 1.6 mSv to 5,7 mSv for biopsy scans and 3.9 to 9.3 mSv for helical scans. Conclusions: The use of DLR as an optimization tool for CT-guided biopsy procedures revealed that helical scans across the entire anatomical region greatly affect radiation dose compared to biopsy acquisitions.

Inflammation is natural protective response of the body tissue caused by various stimuli. Macrophages start and control the inflammatory response. Microalgae have high value of ingredients including carotenoids which are well known for anti-inflammatory properties and used for various products in functional food industries. A green microalgal, Tetraselmis species contains a various type of carotenoids such as lutein, violaxanthin, astaxanthin, fucoxanthin, α-carotene and β-carotene. Therefore, we studied whether carotenoids isolated from Tetraselmis sp. with different culture conditions in Raw 264.7 cells and zebrafish (Danio rerio) have an anti -inflammatory effect. Carotenoid extracts of natural seawater (NS) and magma seawater (MS) showed inhibitory activity of nitric oxide (NO) overproduction without toxicity. In addition, carotenoid extracts of NS and MS inhibited pro-inflammatory cytokines including tumor necrosis factor (TNF)-α, interleukin (IL)- 1β and IL-6. Inducible nitric oxide synthase (iNOS) and cyclooxygenase (COX)-2, which are inflammatory mediators also decreased by pretreatment of NS and MS. Carotenoid extracts of NS and MS pretreatment also reduced phosphorylation of mitogen-activated protein kinases (MAPKs) and nuclear factor-kB (NF-kB). In conclusion, the carotenoid extract of Tetraselmis sp. has an anti -inflammatory effect and can be potential industrial ingredient.

Biofilm matrix is akin to bacterial abodes, primarily composed of proteins, polysaccharides, extracellular DNA, and lipids, providing essential structural support to bacteria. While some biofilm matrix offers significant benefits, such as engineered biofilm reactors that assist in water pollutant removal, others pose risks to human health, potentially leading to conditions like lung infections. Realizing the potential of advantageous biofilm matrix and mitigating the harmful effects of detrimental ones necessitates a comprehensive and systematic exploration of this intricate domain. To facilitate this examination, our study leveraged a dataset of the 1000 most pivotal papers in the field and conducted an exhaustive bibliographic review. This paper serves as a valuable resource for understanding the current progress in biofilm matrix research and delving into vital avenues for future exploration in this dynamic field.

Currently, in a context of biorefinery and bioeconomy, lignocellulosic biomass is increasingly used to produce biofuels, biochemicals and value-added products. Microwaves and ultrasounds are emerging techniques that enable efficient and environmentally more sustainable routes in the transformation of lignocellulosic biomass. This review is divided into four parts. In Part I, the theoretical foundations of microwaves and ultrasounds are revisited. Dielectric constants for biomass, factors that influence pre-treatment, are some of the subjects addressed. In Part II, the effects that these technologies have on lignocellulosic biomass (on the size and surface area of the particle; on the content of lignin, hemicellulose and cellulose; on the crystallinity index of cellulose; on the effect of solubilization of organic matter; on hydrolysis and reduction of sugars) are analyzed. In Part III, emphasis is given on how microwaves and ultrasounds can contribute to the achievement of value-added products. In this context, several examples of liquefactions and extractions are presented. Part IV describes examples of sonocatalysis of lignocellulosic biomass to obtain value-added products such as for instancethe production of furfural, which is significantly reduced by ultrasound.

This paper discusses the theoretical and experimental correlations between fatigue and static strength statistical distributions. We use a two-parameter residual strength model that obeys the qualitative Strenght-Life Equal-Rank (SLERA) assumption for guidance. The modeling approach consists of recovering the model's parameters by best fitting the constant amplitude (CA) fatigue data at a given stress ratio, R, and the experimental Weibull parameters of the static strength distribution function. Once the model's parameters are fixed, its capabilities, potential, and limits are discussed by comparing its predictions with residual strength and fatigue data obtained at different stress ratios, R. Moreover, from a preliminary analysis, the theoretical extension of the model's capabilities to variable amplitude loadings is conceptualized. The application of Miner's rule is also discussed and compared with a new damage rule to analyze the fatigue responses under variable amplitude loadings.

Algal-bacterial granular sludge, a new biological technology, has been widely recognized due to its highly effective pollutant treatment and energy efficiency. This study investigated the effects of environmental concentrations of Cr(VI) (0.5-2.5 mg/L) on the performance of algal-bacterial gran-ular sludge and self-defensive responses after 90 days of cultivation. The results showed that Cr(VI) affected chemical oxygen demand (COD), ammonia-N and phosphate removal with different trends being apparent. A linear decline in COD removal was observed, whereas an initial de-creasing and then increasing ammonia-N and phosphate removal took place. Algal-bacterial granular sludge effectively removed Cr(VI) from wastewater through biological adsorption and reduction, showing the potential to treat Cr(VI)-contaminated wastewater. Cr(VI) affected the community abundance of the algal-bacterial granular sludge, in which Chlorophyceae and cya-nobacteria were vulnerable under Cr(VI)-induced stress. To reduce the toxicity of Cr(VI), over-produced EPS-PN and antioxidant enzymes (MDA, SOD and CAT) acted as self-defensive responses to resist oxidative damage. This study showed that algal-bacterial granular sludge can remove 00.5 mg/L of Cr(VI) without performance loss. It is hoped that this study can provide useful information for improved engineering feasibility of algal-bacterial granular sludge.

Xaa-Pro dipeptidase (XPD, EC 3.4.13.9; also known as prolidase) catalyzes the hydrolysis of iminopeptide bond in the trans Xaa-Pro dipeptides (Xaa represents any amino acid except proline), which makes it find wide applications in food, medical and environmental protection fields. In the present study, a novel Xaa-Pro dipeptidase from Aspergillus phoenicis ATCC 14332 (ApXPD) was molecularly and biochemically characterized. Reclassification based on phylogenetic analysis and version 12.5 MEROPS database showed that this enzyme was the only fungal XPD in the unassigned subfamily which shared the highest sequence similarity with Xanthomonas campestris prolidase but not with that from the more related fungal species A. niudulans. As compared with other prolidases, ApXPD also contained an N-terminal tail (residues 81-89) and an additional region (PAPARLREKL), and used a different arginine residue for dipeptide selectivity. After heterologous expression and partial purification, recombinant ApXPD was highly active and stable over the alkaline range from 8.5 to 10.0, with a maximum activity at pH 9.0 and more than 80% activity retained after 1-h incubation at pHs of 8.5-10.0 (55oC). It also had an apparent optimum temperature of 55oC and remained stable at 20-30oC. Moreover, this enzyme was a cobalt dependent prolidase that only cleaved dipeptides Lys-Pro, Gly-Pro and Ala-Pro rather than other dipeptides, tripeptides and tetrapeptides. All these distinct features make A. phoenicis ATCC 14332 XPD unique among currently known prolidases, thus defining a novel Xaa-Pro dipeptidase subfamily.

The healthcare domain is increasingly adopting IoT and Electronic Health Record (EHR) systems, generating vast volumes of healthcare data. This shift is driven by the growing need of delivering the right information to the right individuals, at the right time. The latter underscores the importance of adopting a comprehensive strategy for efficiently collecting, utilizing, and analyzing health-related data to not only enhance overall healthcare management but also for the provision of timely and personalized prevention strategies. The latter is of highest importance especially in scenarios where lack of effective treatments or poor survival rates (such in pancreatic cancer) renders typical healthcare strategies ineffective. In this article, we introduce an innovative and integrated platform that is specifically designed and developed for accessing, processing, and analyzing data in challenging healthcare scenarios, such as dealing with pancreatic cancer. This platform, called iHelp, combines multidisciplinary technologies and provides healthcare professionals reliable risk modelling, analysis, and prediction techniques so that individuals (at risk of developing pancreatic cancer) can be provided with timely, reliable, and personalized prevention and intervention measures. A key innovation in the iHelp platform is the standardized data management approach called Holistic Health Records (HHRs) that facilitate the capturing of all health determinants in a standardized and well-structured way for processing towards the provision of health risk detection and personalized healthcare decision support. In the development of iHelp platform, the HHRs are evaluated through different real-world healthcare datasets, including datasets coming from hospital systems, data from wearables, questionnaires, and mobile applications.

This paper explores the application of wavelet analysis, a multiscale approach for enhancing visual clarity, in the context of image denoising, which reduces the impact of noisy pixels, caused by various factors such as electronic sensor limitations, low-light conditions, or transmission errors in digital imaging systems. This paper introduces some common noise types like Gaussian noise and processes of image denoising, eliciting the strength of wavelet analysis. As a powerful image denoising technology, wavelet analysis needs five steps to process the image, and the key step is thresholding. There are many kinds of wavelet, and each wavelet has different advantages and functions, which makes it suitable for different applications. Hence, wavelet analysis also makes a contribution in various fields beyond signal processing and data analysis, such as Biomedical Imaging and Geophysics and Seismology, where preserving image quality is essential for accurate analysis and interpretation. In short, this research highlights the promise of wavelet analysis, emphasizing the use of high- quality image data.

This study investigates the magnetization of Cobalt (Co) nanoparticles with two different crystal structures: a centered cubic (fcc) and an hexagonal close packed (hcp), under the magnetic field of the Earth. For that reason, the hysteresis loops of the two material samples are exported and compared with the corresponding value by experimental procedure in the laboratory under the Earth’s magnetization. For both samples, the nanoparticle number variation and the nearest neighbor distance effect, in the Co hysteresis loop are investigated, structural information that is useful for the sample preparation. For the simulations the Finite Element Method (FEM) was used, while experiments are conducted using a measurement set-up based on fluxgate magnetometers. From the simulation, it is proven that, for both samples, the nanoparticle number effect does not change the hysteresis loop. In contrast, when the distance between the nanoparticles increases, the magnetization obtains smaller value. This study aims to build a novel, simple and economical measurement arrangement enabling in situ magnetic measurements for ferromagnetic nano-material characterization. As the need for continuous knowledge of the condition and the phase of ferromagnetic nanoparticles that is crucial in many applications, like catalytic processes, this work aims to introduce an alternative approach that will add another dimension to conventional chemical reaction engineering this of the magnetic state of the material resolved in time and space and to contribute in the field of the monitoring and the early fault diagnosis of nanoparticle materials.

Here in it is described a new genetic microvascular obstructive disease causing progressive hypo-perfusion of human brain, heart and kidney. Since the age of 30 years a male patient developed recurrent angina with normal coronary epicardial vessels but remarkable slow flow at angiography causing cardiac micro-aneurysms that at endomyocardial biopsy were associated to obstructive microvascular dysplasia. His history was followed in the seven decade by micro-hematuria characterized at kidney biopsy by renal microvascular dysplasia and frequent cerebral ischemic attacks with preserved structure of main brain arteries. Analysis of 5,600 genetic disease-causing genes revealed mutation of ABCC6, MMP2 and XYLT1 genes.

Although adults and children differ in self-versus-other perception, the developmental perspective on this discriminative ability is missing. We compared neural activation of self-vs-others in 39 participants of 4 different age groups (4 yo. to adulthood). Two brain regions, the MCC and right postcentral gyrus, exhibited respectively non-linear and gradual gains in discriminative abilities for self-vs-others stimuli. These regions play critical roles in self-referential processing, empathy, and social cognition. Nine brain regions showed linear increase for others-vs-self stimuli. These regions are associated with multisensory processing, somatosensory skills, complex visual stimuli, self-awareness, empathy, theory of mind, and social recognition. Understanding the neural basis of self-vs-others discrimination during development can inform when and how social contexts support learning processes during childhood and adolescence.

End-stage heart failure (ESHF) leads to hypoperfusion and edema formation in the whole body and is accompanied by neurohormonal and immunological alterations. Orthotopic heart transplantation (HTX) has been used as a beneficial option for ESHF. Due to the shortage of donor hearts, the ideal matching and timing of donors and recipients has become more important. Our aim was to explore the relationship between the clinical outcome of HTX and the cytokine and apolipoprotein profiles of the recipient pericardial fluid obtained at transplantation after opening the pericardial sac. The clinical data and the interleukin, adipokine and lipoprotein levels in the pericardial fluid of twenty recipients were investigated. Outcome variables included primer graft dysfunction (PGD), need for posttransplantation mechanical cardiac support (MCS), International Society for Heart and Lung Transplantation grade ≥ 2R rejection and mortality. Recipient risk scores were also investigated. Leptin levels were significantly lower in patients with PGD than in those without PGD (median: 6.36 [IQR: 5.55-6.62]; versus 7.54 [IQR=6.71-10.44]; p = 0.029). Higher ApoCII levels (median: 14.91 [IQR: 11.55-21.30] versus 10.31 [IQR=10.02-13.07]; p = 0.042) and ApoCIII levels (median: 60.32 [IQR: 43.00-81.66] versus 22.84 [IQR=15.84-33.39]; p=0.005) were found in patients (n=5) who died in the first 5 years after HTX. In patients who had rejection (n=4) in the first month after transplantation, the levels of adiponectin (median: 74.48 [IQR: 35.51-131.70] versus 29.96 [IQR: 19.86-42.28]; p=0.039), ApoCII (median: 20.11 [IQR: 13.06-23.54] versus 10.32 [IQR: 10.02-12.84]; p=0.007) and ApoCIII (median: 70.97 [IQR: 34.72-82.22] versus 26.33 [IQR: 17.18-40.17; p=0.029) were higher than those in the nonrejection group. Moreover, the pericardial thyroxine (T4) levels (median: 3.96 [IQR: 3.49-4.46] versus 4.69 [IQR: 4.23-5.77]; p=0.022) were lower in patients with rejection than in patients who did not develop rejection. Our results indicate that apolipoproteins can facilitate the monitoring of rejection and could be a useful tool in the forecast of early and late complications.

Saccharomyces cerevisiae fermentation products (SCFP) can potentially promote gastrointestinal growth and immunity in young livestock. However, reports within the existing literature on the effects of SCFP supplements on calves have been inconsistent; therefore, we perform the following experiments to resolve the inconsistencies. A total of 22 Holstein calves [10 d after birth, BW = 48.93 ± 3.99 kg (mean ± SD)] were assigned randomly into two groups, namely the control group (CON) and SCFP group, each having 11 replicas. The calves in the CON were fed a basal diet, while the SCFP group was fed the basal diet supplemented with 5g/head/d SCFP (NutriTek, Diamond V, Cedar Rapids, IA52404, United States) incorporated into feed. All the calves were regularly fed thrice daily at 08:00, 14:30, and 21:00 and had free access to water. A 5-day adaptation phase was followed by a 45-day experimental period. The results showed that compared to the CON, at the end of the d-45 trial, the body weight was significantly greater in the SCFP group (p < 0.05), and during the 1-45 days, the ADG was higher (p < 0.05). The FCR in the 30-45 days SCFP group was higher (p < 0.05). Furthermore, the apparent digestibility of DM, CP, EE, ADF, Ca, and P were significantly increased in the SCFP group, except for NDF (p < 0.05). The concentration of GH and IGF-1 in serum showed a tremendous increase (p < 0.05) with SCFP supplementation on d 15 and d 45. On d 15, SCFP supplementation significantly increased the serum IgA contents (p < 0.05). Notably, on d 15 and d 45, the serum concentrations of IL-1β, IL-6, and TNF-α reduced (p < 0.001). Moreover, the Actinobacteriota in the SCFP group were significantly lower than those in the CON group (p = 0.034). SCFP significantly increased the abundance of Butyricimonas, Parabacteroides, and Ruminococcus. The differences among sob, Chao1, and PD-tree groups were statistically significant (p < 0.05). In conclusion, these results demonstrate that SCFP supplementation improved ADG, apparent digestibility and serum hormone, enhanced immunity, and regulated gut microbiota, thereby jointly promoting the growth of pre-weaning calves.

The study is devoted to analyzing the economic sustainability of the town of Amherst, MA. The city's top employer and core enterprise is the University of Massachusetts Amherst, with over 32,000 students and almost 2,000 staff members. Based on a literature review, a hypothesis was put forward that a university city should have a high level of economic sustainability. To assess economic sustainability, the USCESI Index was developed. It evaluates sustainability in three groups of parameters: society, economy, and ecology. The first group includes the level of racial diversity, the level of education of the population, and the access to medical services. The second group consists of the Gini coefficient by income level, the median cost of housing, and the unemployment rate. The environmental situation is assessed according to the Air Quality Index developed by the US Environmental Protection Agency. For comparison, the town of Braintree, MA, was taken. The USCESI was calculated for both locations. The analysis showed that both Amherst and Braintree have a high degree of economic sustainability. However, it was revealed that proximity to a significant economic center has a more powerful positive impact on economic sustainability than the location of a large university.

In regenerated oak forests, weeds are present throughout the year, the ones appearing in early spring representing a major problem. Hence, the aim of this study was to examine herbicides for early spring broadleaved weed control in the regenerated oak forests while the seedlings are in a dormant stage. During 2019 and 2020 two experiments were set up in regenerated pedunculate oak forests with 2-yar and 3-year-old seedlings and two herbicides were applied in two doses: fluroxypyr at dose 360 g a.i. ha-1 and 540 g a.i. ha-1 and clopyralid at dose 100 g a.i. ha-1 and 120 g a.i. ha-1. The results from the two-year investigations showed that fluroxypyr and clopyralid significantly reduced early spring broadleaved weeds in the regenerated pedunculate oak forests but both doses of fluroxypyr provided greater control of presented weeds than the applied doses of clopyralid. The manual weeding reduced broadleaved weeds in experiments, but that method did not have a long-term effect on the reduction of weeds. Applied doses of herbicides fluroxypyr and clopyralid did not cause phytotoxicity symptoms in dormant oak seedlings. All investigated treatments significantly reduced fresh broadleaved weed biomass compared to the control. Generally, it can be concluded that fluroxypyr and clopyralid can be successfully used for control of many early spring broadleaved weeds in the regenerated pedunculate oak forests, but oak seedlings must be in the dormant stage.

The interplay between Diffuse Idiopathic Skeletal Hyperostosis (DISH) and the gut microbiota represents a compelling area of research, offering insights into the relationship between spinal degenerative diseases and the gut's microbial inhabitants. This comprehensive review seeks to unravel the complex connection, shedding light on its implications for human health and potential therapeutic avenues. A crucial section dives into the world of gut microbiota (GM), exploring its impact on human health, featuring its defining characteristics, and highlighting its role in metabolism, immunomodulation, host interaction, and how its composition changes over time. The subsequent portion delves into the relationship between microbiome composition and pathological bone development, including the link between Intervertebral Disc Degeneration (IDD) and gut inflammation, emphasizing how gut inflammation and GM dysbiosis play pivotal roles. Further dissecting the interconnections, various axes of influence, including the gut-spine axis, gut-bone axis, gut-joint axis, gut-disc axis (specific to DISH), gut-ligament axis, and gut-muscle axis, are discussed. Of particular interest is the section on the impact of GM on DISH-derived pain, addressing a critical aspect of the condition's manifestation. The review discusses the potential of GM modulation as a treatment for DISH, providing hope for therapeutic advancements. Additionally, it highlights the positive impact of lifestyle interventions, such as dietary modifications, sleep optimization, and exercise regimens, in mitigating GM dysbiosis and potentially improving DISH outcomes. Lastly, the intriguing prospect of fecal microbiome transplant and its implications for DISH management is examined, opening new avenues for research and therapeutic interventions. In conclusion, this comprehensive review underscores the intricate interplay between DISH and the gut microbiota, offering a fresh perspective on the impact of GM on spinal degenerative diseases. It emphasizes the potential for innovative treatments, such as GM modulation and lifestyle interventions, and presents fecal microbiome transplant as an exciting area for future exploration.

We previously developed a highly sensitive and specific anti-PDPN mAb, LpMab-23 (mouse IgG1, kappa). In this study, we produced a humanized IgG1 version (humLpMab-23) and its defucosylated form (humLpMab-23-f) of an anti‑PDPN mAb to potentiate the ADCC activity. The humLpMab-23 could recognize PDPN‑overexpressed Chinese hamster ovary (CHO)-K1 (CHO/PDPN) and PDPN-positive PC-10 and LN319 cells by flow cytometry. Furthermore, we found that humLpMab-23-f exerted ADCC and complement-dependent cytotoxicity against CHO/PDPN, PC-10 and LN319 cells in vitro and exhibited potent antitumor activities in the xenograft models. These results indicated that humLpMab-23-f could be useful for an antibody treatment regimen for PDPN-positive human cancers.

The Cav3.2 T-type calcium channel is implicated in various pathological conditions, including cardiac hypertrophy, epilepsy, autism, and chronic pain. Phosphorylation of Cav3.2 by multiple kinases plays a pivotal role in regulating its calcium channel function. The calcium/calmodulin-dependent serine/threonine phosphatase, calcineurin, interacts physically with Cav3.2 and modulates its activity. However, it remains unclear whether calcineurin dephosphorylates Cav3.2, the specific spatial regions on Cav3.2 involved, and the extent of the quantitative impact. In this study, we elucidated the serine/threonine residues on Cav3.2 targeted by calcineurin using quantitative mass spectrometry. We identified six serine residues in the N-terminus, II-III loop, and C-terminus of Cav3.2 that were dephosphorylated by calcineurin. Notably, a higher level of dephosphorylation was observed in the Cav3.2 C-terminus, where calcineurin binds to this channel. Additionally, a previously known CaMKII-phosphorylated site, S1198, was found to be dephosphorylated by calcineurin. Furthermore, we also discovered that a novel CaMKII-phosphorylated site, S2137, underwent dephosphorylation by calcineurin. In CAD cells, a mouse central nervous system cell line, membrane depolarization led to an increase in the phosphorylation of endogenous Cav3.2 at S2137. Mutation of S2137 affected the calcium channel function of Cav3.2. Our findings advance the understanding of Cav3.2 regulation not only through kinase phosphorylation but also via calcineurin phosphatase dephosphorylation.

Abstract: The transforming growth factor beta (TGFβ) and Hippo signaling pathways are evolutionarily conserved pathways that play a critical role in cardiac fibroblasts during embryonic development, tissue repair, and fibrosis. TGFβ and Hippo signaling is also important for cardiac cushion remodeling and septation during embryonic development. Loss of TGFβ2 in mice causes cardiac cushion remodeling defects resulting in congenital heart disease. In this study, we used in vitro molecular and pharmacologic approaches in the cushion mesenchymal cell line (tsA58-AVM) and investigated if Hippo pathway acts as a mediator of TGFβ2 signaling. Immunofluorescence staining showed that TGFβ2 induced nuclear translocation of activated SMAD3 in the cushion mesenchymal cells. In addition, the results indicated increased nuclear localization of Yes associated protein 1 (YAP1) following a similar treatment of TGFβ2. In collagen lattice formation assays, TGFβ2 treatment of cushion cells resulted in an enhanced collagen contraction compared to the untreated cushion cells. Interestingly, verteporfin, a YAP1 inhibitor, significantly blocked the ability of cushion cells to contract collagen gel in absence or presence of by exogenously added TGFβ2. To confirm the molecular mechanisms of verteporfin induced inhibition of TGFβ2-dependent extra-cellular matrix (ECM) reorganization we performed gene expression analysis of key mesenchymal genes involved in ECM remodeling in heart development and disease. Our results confirmed that verteporfin significantly decreased the expression of α-smooth muscle actin (Acta2), collagen 1a1 (Col1a1), Ccn1 (i.e., Cyr61), and Ccn2 (i.e., Ctgf). Western blot analysis indicated that verteporfin treatment significantly blocked TGFβ2-induced activation of SMAD2/3 in cushion mesenchymal cells. Collectively, these results indicate that TGFβ2 regulation of cushion mesenchymal cell be-havior and ECM remodeling is mediated by YAP1. Thus, TGFβ2 and Hippo pathway integration represents an important step in understanding the etiology of congenital heart disease.