Claims arising frequently in the Architecture, Engineering and Construction (AEC) industry usually result in disputes, leading to all sorts of negative implications for a project. Claims need to be managed efficiently, and in case they evolve into disputes, they need to be resolved as soon as possible so that the construction process can resume. In this paper, a bibliometric review is carried out to explore the existing literature regarding construction claims and dispute resolution methods employed in construction projects. Using VOSviewer and the Scopus database, relevant literature is retrieved and analyzed using keyword searches, including "construction claim” and "construction management". The detected research themes provide future researchers with potential research directions. A gap in the research regarding the emergence of terms such as “blockchain”, “smart contracts”, and "building information modelling (BIM)" appearing only recently after 2020 in the literature regarding the construction claims and disputes research area was determined. Therefore, a content analysis of the most recent publications employing these and other novel technologies is conveyed. Ultimately, the main research trends and potential research directions for assisting researchers and construction professionals in their efforts to address construction claims and disputes in sustainable and efficient ways are discussed.

In recent years, e-commerce platforms have replaced conventional marketplaces. People are rapidly adopting internet shopping due to the convenience of making purchases from the comfort of their homes. Online review sites allow customers to share their thoughts on products and services. Customers and businesses are increasingly relying on online reviews to assess and improve the quality of products. Existing literature uses Natural language processing (NLP) to analyze customer reviews for different applications. Due to the growing importance of NLP for online customer reviews, this study attempts to provide a taxonomy of NLP applications based on existing literature. This study also examined emerging methods, data sources, and research challenges by reviewing 154 publications from 2013 to 2023 that explore state-of-the-art approaches for diverse applications. Based on existing research, the taxonomy of applications divides literature into five categories: sentiment analysis, review analysis, customer feedback and satisfaction, user profiling, and marketing and reputation management. It is interesting to note that the majority of existing research relies on Amazon user reviews. Additionally, recent research has encouraged the use of advanced techniques like Bidirectional Encoder Representations from Transformers (BERT), Long Short-Term Memory (LSTM), and ensemble classifiers. The rising number of articles published each year indicates increasing interest of researchers and continued growth. This survey additionally addresses open issues, providing future directions in online customer review analysis.

Herpes simplex virus type 1 (HSV-1) is a lifelong pathogen characterized by asymptomatic latent infection in the trigeminal ganglia (TG) with periodic outbreaks of cold sores caused by virus reactivation in the TG and subsequent replication in the oral mucosa. While antiviral therapies can provide relief from cold sores, they are unable to eliminate HSV-1. We provide experimental results that highlight non-thermal plasma (NTP) as a new alternative therapy for HSV-1 infection that would resolve cold sores faster and reduce the establishment of latent infection in the TG. Additionally, this study is the first to explore the use of NTP as a therapy that can both treat and prevent human viral infections. We investigated the antiviral effect of NTP using an in vitro model for HSV-1 cold sores, involving the application of NTP from two separate devices to cell-free HSV-1, HSV-1-infected cells, and uninfected cells. We found NTP reduced the infectivity of cell-free HSV-1, reduced viral replication in HSV-1-infected cells, and diminished the susceptibility of uninfected cells to HSV-1 infection. This triad of antiviral mechanisms of action suggest the potential of NTP as a therapeutic agent effective against HSV-1 infection.

The human immunodeficiency virus (HIV) continues to pose a significant global health challenge, with millions of people affected and new cases emerging each year. While various treatment and prevention methods exist, including antiretroviral therapy and non-vaccine approaches, developing an effective vaccine remains the most crucial and cost-effective solution to combat the HIV epidemic. Despite significant advancements in HIV research, the HIV vaccine field has faced numerous challenges, and only one clinical trial has demonstrated a modest level of efficacy. This review delves into the history of HIV vaccines and the current efforts in HIV prevention, emphasizing pre-clinical vaccine development using the non-human primate model (NHP) of HIV infection. NHP models offer valuable insights into potential preventive strategies for combating HIV, and they play a vital role in informing and guiding the development of novel vaccine candidates before they can proceed to human clinical trials.

Radiomics represents the science of extraction and analysis of a multitude of quantitative features from medical imaging, unrevealing quantitative potentiality of Radiologic images. This scientific review aims to provide radiologists a comprehensive understanding of radiomics, emphasizing its principles, applications, challenges, limits, and future prospects. Limits of standardization of actual scientific production are analyzed with the possible solutions proposed by some papers reported and commented. As the continuous evolution of medical images is ongoing, radiologists must be aware of new perspective to perform a central role in patients management.

This study investigates the influence of economic growth on CO2 emissions levels in three developed countries—Argentina, Equatorial Guinea, and South Korea—based on their status as high-income countries. We test the environmental Kuznets curve (EKC) hypothesis using the time series approaches to check the relationship and direction of causality among the variables over a sample spanning 1974–2020. The results show an inverted U-shaped short-run relationship in all three countries. In the long run, only South Korea supports the EKC hypothesis. Further, Granger causality results indicate the existence of causality. These long-run causal relationships between economic growth and emissions recommend one policy implication that wealthy governments must expand investments in renewable clean energy projects and R&D, with regulatory measures to suppress harmful environmental procedures and support environmentally friendly development.

With the increase of global human activities, a large number of technogenic magnetic particles (TMPs) generated by industrial activities such as coal combustion, traffic and so on enter sediments on continental shelves. However, there is currently a lack of understanding of the spatiotemporal distribution of TMPs on continental shelves, as well as the sedimentary effects they cause. This review work comprehensively analyzes the source, morphology, composition, and spatiotemporal distribution characteristics of TMPs. Then it elucidates their magnetic contribution to sedimentary environments in continental shelf seas, as well as the influence of heavy metals and active iron. At the same time, the existing problems and future development directions of TMPs on continental shelves are summarized.

In Einstein’s Special Relativity(SR), time is treated as one of the four dimensions within spacetime and is relative in nature. Typically, a photon clock serves as the illustrative device in the time dilation thought experiment, featuring a single photon bouncing between two mirrors. However, the present paper identifies a fundamental flaw in this thought experiment, hence challenging its validity. Contrary to SR, this paper asserts that time is a consequence of motion. Space and time should be treated differently as proposed by classical mechanics. Importantly, this stance does not challenge the concept of curved space in General Relativity (GR), but rather questions the idea of relative time, as employed in both SR and GR. The absence of time dilation also dispels the twin paradox, prompting a necessary reassessment of the second postulate of relativity to ensure a more precise depiction of relativistic effects.

The purpose of this study is to analyse the drivers and outcomes of the brand love derived from consumption experiences in the automobile retail sector. We examine the effects of consumers’ perceptions of perceived service quality and the trust they feel towards a car dealership (cognition) on emotions and brand love (affection), and the effects of brand love on consumers´ behavioural intentions (conation). This research provides insights into customer brand love in the automobile industry.

A thermal system in very deep Lake Tazawa (maximum depth, 423 m) was investigated by estimating the heat budget. In the heat budget estimate, the net heat input at lake surface and the heat input by river inflow and groundwater inflow were considered. Then, the heat loss by snowfall onto lake surface was taken into account. Meanwhile, lake water temperature was monitored at 0.2 m to the bottom by mooring temperature loggers for more than two years. The heat storage change of the lake from the loggers was calibrated by frequent vertical measurements of water temperature at every 0.1 m pitch by a profiler with high accuracy (± 0.01 °C). The heat storage change (W/m2) obtained by the temperature loggers reasonably accords to that from the heat budget estimate. In the heat budget, the net heat input at lake surface dominates the heat storage change, but the significant heat loss by river inflow sporadically occurred, which is caused by the relatively large discharge from a reservoir in the upper region. How deep the vertical water circulation in the lake occurs in winter was judged by the differences between water temperatures at 0.2 m depth and bottom and between vertical profiles of dissolved oxygen over winter. It is strongly suggested that the whole water circulation does not occur every winter, if any, very weak.

This work aims to study and analyze a hybrid power system for electric vehicles consisting of a dual low and high-rate lithium battery block and a fuel cell. In this configuration, the high-rate lithium battery powers the electric vehicle in high power demand processes like acceleration mode or on an uphill road; the low-rate battery operates at a low output power range, servicing the auxiliary systems and low power loads and the fuel cell supplies energy at intermediate power demand conditions, normal driving mode, constant velocity, or flat and downhill terrain. The dual power system improves global efficiency since every power unit operates optimally depending on driving conditions. Power sharing optimizes the lithium battery performance and fuel cell capacity, minimizing the size and weight of each energy system and enlarging the driving range. A comparative study between different lithium battery configurations and fuel cell shows an efficiency improvement of 31.4% for the hybrid dual battery block and fuel cell operating in low, high, and intermediate output power ranges, respectively. The study bases on a simulation process recreating current driving conditions for electric cars in urban, peripheral, and intercity routes. An alternative solution consisting of a hybrid system, fuel cell and a high rate lithium battery produces a 29 % power gain.

Single-Anastomosis Duodeno-Ileal bypass with Sleeve Gastrectomy (SADI-S) is a modification of the duodenal switch in which only one anastomosis is performed, with a longer common limb and an expected less malabsorptive effect. The present study analyzes presentation and treatment of malnutrition after SADI-S. 258 consecutive patients undergoing SADI-S between May 2007 and September 2017 were included. The common limb length was 200 cm in 50 cases, 250 cm in 156 and 300 in 52. 30 patients were admitted for severe hypoalbuminemia and 16 patients were submitted to revisional surgery and constitute the series of our study. Mean weight before reoperation was 57 kg and mean body mass index (BMI) was 21 kg/m2. Mean number of daily bowel movements was 5,6. Mean time to reoperation was 56 months. Revisional surgery consisted mainly in elongation of the common limb. Mean weight regain was 14 kg and mean final BMI was 26 kg/m2. Daily bowel movements were decreased to 1,3. Factors related to hypoalbuminemia were hypertension, poor controlled diabetes, age over 55 years and a shorter common limb. Although SADI-S is expected to be less malabsorptive than previous biliopancreatic diversions, caution has to be taken with selected patients to avoid postoperative malnutrition.

Phytoene desaturase (PDS) is a plant enzyme involved in carotenoid biosynthesis. The PDS gene has been used as a selective marker for genome editing in several plant species, including banana (Musa spp.). Its knockout promotes dwarfism and albinism, characteristics that are easily recognizable and highly favorable. In Musa spp., the A genome increases fruit production and quality, whereas the B genome is associated with tolerance to biotic and abiotic stresses. The objective of this study was to identify a molecular marker in the PDS gene to easily discriminate the A and B genomes of banana. A 2166 bp fragment for the ‘PDSMa’ marker was identified as polymorphic for the A genome (identification accuracy of 99.33%), whereas ~332 and ~225 bp fragments were detected for the ‘PDSMb’ primer with 100% accuracy using MedCalc software. To the best of our knowledge, this is the first study to use the PDS gene to determine doses of the A genome and identify the B genome in Musa spp., which will aid in evaluating the genomic constitution of banana hybrids and accessions at the seedling stage, and accelerating their classification in crop genetic improvement programs.

Voluntary carbon markets open horizons for private companies, public institutions, and individuals developing CO2 removal projects in peatlands to reduce overall carbon footprint. These steps, however, should be in line with appropriate rewetting targets. To do so, the base line information about the status of area must be assessed. Here we follow the methodology set by the carbon certification program standards which define the necessary steps for reference conditions assessment. In this study we practically test the fulfilment of necessary drained peatland baseline evaluation for paludiculture and carbon certification activities. Estimates on the greenhouse gas emission mitigation potential were summarized to define priorities and propose quantifiable measures with suggested paludiculture implementation. Our hands-on approach shows that it is possible for companies to implement rewetting strategies without large EU level project fundings when the conservation and economic aspects are met, thus boosting climate mitigation actions.

Background: Laser therapies can cause hyper- and hypopigmentation of the skin. There is little evidence in the literature of effective treatments for these types of problems in Fitzpatrick IV-VI skin phototypes. The main aim of this retrospective study is to evaluate the effects of a new therapy combining the application of electromagnetic fields and vacuum on a subject with Fitzpatrick VI skin phototype, presenting an extensive, laser-induced facial dyschromia. The secondary aim is to test the effectiveness of a free imaging software for assessing skin pigmentation. Methods: The level of improvement after the therapy was evaluated, with a 5-point Likert scale, one month after the end of the treatment by both the subject, and the doctor who performed the treatment, and by two blinded dermatologists. With the free software, a three-dimensional reconstruction of the area treated and the evaluation of colour distribution were performed. Results: Both the subject and the doctors involved in the study positively evaluated the effects of the treatment. The image analysis highlighted the homogenization of the skin colour in the treated area. Conclusions: The combination of electromagnetic fields and vacuum for dyschromia treatments appears promising. The new method of assessing melanin levels resulted particularly efficient.

Mandibular third molar is the most frequently impacted tooth. Mandibular third molar impaction bears consequences on the adjacent mandibular second molar (MSM) like bone loss. It can be identified initially using orthopantomography (OPG). The objective is to compare the changes in the bone level distal to MSM between patients with extracted and non-extracted impacted man-dibular third molars (IMTM) using OPG. In this retrospective case-control study, 160 archived (OPGs) of 80 patients visiting the Dental Hospital of the University of Barcelona (HOUB) were randomly selected. The participants were stratified into two groups. The study group involved measuring the bone level distal to the mandibular second molar before and after the extraction of the IMTM. The control group, on the other hand, had bone levels measured twice within 3–6-month period without the extraction of the IMTM. The mean ages of patients in study and control groups were 35.5 ± 15.45 and 33 ± 16.49, respectively. Study group demonstrated signifi-cant (p < 0.05) bone gain after extraction, whereas control group demonstrated significant bone loss (p < 0.0001) after follow-up. Bone improvements were observed distal to the mandibular second molar after the extraction of the IMTM compared to those in control group.

Previous studies found high but very variable levels of tetranor-PGEM and PGD-M (urine metabolites of prostaglandin (PG) E2 and PGD2, respectively) in persons with cystic fibrosis (pwCF), which correlated with the severity of the CF transmembrane receptor (CFTR) genetic alteration. This study aims to assess the potential role of cyclooxygenase (COX)-1 and COX-2 genetic polymorphisms in the variability of PG production, and determine the potential role of PG metabolites as markers of symptoms severity and imaging findings. Thirty healthy subjects and 103 pwCF were included in the study. Clinical and radiological CF severity was evaluated using clinical scoring methods and the extent of bronchiectasis and air trapping were assessed by chest computed tomography (CT). Urine metabolites were measured using liquid chromatography/tandem mass spectrometry. The presence of variants in the COX-1 gen (PTGS1 639 C>A, PTGS1 762+14delA, and COX-2 gen: PTGS2-899G>C (-765G>C) and PTGS2 (8473T>C) were analysed. PGE-M and PGD-M urine concentrations were significantly higher in pwCF than in healthy controls. There were also statistically significant differences between clinically mild and moderate disease and severe disease. Patients with bronchiectasis and/or air trapping had higher PGE-M levels than patients without these complications. The four polymorphisms did not associate with clinical severity, air trapping, bronchiectasis, or urinary PG levels. Taken together, the present study suggests that urinary PG level testing can be used as a biomarker of CF severity. We found no relationship between COX-1 and COX-2 genetic polymorphisms in the variability of PG production.

Background: Interstitial lung disease (ILD) is a frequent complication in systemic sclerosis (SSc). So, an increased awareness of this complication is a real need in the clinical setting, because it may affect the prognosis of patients. In particular, an accurate strategy is desirable in order to detect ILD in its stages. So, we investigate the validity of ultrasound (US) in detecting subclinical ILD in SSc, and to determine its potential in disease progression. Methods: 133 patients without respiratory symptoms and 133 healthy controls were included. Borg scale, Rodnan skin score (RSS), pulmonary auscultation, chest radiographs and respiratory function tests (RFT) were performed. An expert rheumatologist performed the lung US. High-resolution CT (HRCT) was also performed. After the baseline assessment, the patients were followed every 3 months for 12 months. Results: A total of 79 of 133 patients (59.4%) showed US signs of ILD in contrast to healthy controls (4.8%) (p=0.0001). The clinical and laboratory variables associated with ILD were anti-centromere antibodies (p=0.005) and RSS (p=0.004). A positive correlation was demonstrated between the US and HRCT findings (p=0.001). Sensitivity and specificity of US in detecting ILD was 91.2% and 88.6% respectively. A good inter-observer reliability was observed (k = 0.72). In the follow-up, a total of 30 patients out of 79 (37.9%) who demonstrated US signs of ILD at baseline, showed changes in the ILD score by US. Conclusions: US showed a high prevalence of subclinical ILD in SSc patients. It demonstrated to be a valid, reliable and feasible tool to detect ILD in SSc and to monitoring the disease progression.

Ni-rich layered cathodes are regarded as a potential candidate for high energy-density lithium-ion batteries, but their high sensitivity to air during storage and poor thermal stability are a vital challenge for large-scale applications. In this paper, an effective solid-solution strategy was proposed to improve the surface and structural stability of Ni-rich layered cathodes by introducing Li2MnO3. The structural analysis results indicate that the formation of Li2CO3 inert layers on Ni-rich layered cathodes during storage in air is responsible for the increased electrode interfacial impedance, thereby resulting in the severe deterioration of electrochemical performance. The introduction of Li2MnO3 can reduce the surface reactivity of Ni-rich cathode materials, playing a certain suppression effect on the formation of surface Li2CO3 layer and the deterioration of electrochemical performances. Additionally, the thermal analysis results show that the heat release of Ni-rich cathodes strongly depends on the charge of states, and Li2MnO3 can suppress oxygen release and significantly improves the thermal stability of Ni-rich layered cathodes. This work provide a method to improve the storage performance and thermal stability of Ni-rich cathode materials.

In recent years, both domestic and international research on quadruped robots has advanced towards high dynamics and agility, with a focus on high-speed locomotion as a representative motion in high-dynamic activities. Quadruped animals like cheetahs exhibit high-speed running capabilities, attributed to the indispensable role played by their flexible spines during the flight phase motion. This paper establishes dynamic models of quadruped robots with different degrees of spine flexibility, providing a parameterized description of the flight phase motion for both rigid trunks and flexible spine quadruped robots. By setting different initial values for the spine joint and calculating the flight phase results for both types of robots at various initial velocities, the study compares and analyzes the impact of a flexible spine on the flight phase motion of quadruped robots. Through comparative experiments, the research aims to validate the influence of a flexible spine during the flight phase motion, providing insights into how spine flexibility affects the flight phase motion of quadruped robots.

Reservoir computing (RC) systems can efficiently forecast chaotic time series using nonlinear dynamical properties of an artificial neural network of random connections. The versatility of RC systems has motivated further research on both hardware counterparts of traditional RC algorithms and more efficient RC-like schemes. Inspired by the nonlinear processes in a living biological brain and using solitary waves excited on the surface of a flowing liquid film, in this paper we experimentally validate a physical RC system that substitutes the effect of randomness for a nonlinear transformation of input data. Carrying out all operations using a microcontroller with a minimal computational power, we demonstrate that the so-designed RC system serves as a technically simple hardware counterpart to the `next-generation’ improvement of the traditional RC algorithm.

In response to the growing need for efficient energy conversion technologies, this pa-per introduces an innovative Tubular Thermoelectric Generator (TTEG), specifically de-signed for high-efficiency conversion of waste heat into electrical energy. Unlike conven-tional flat plate thermoelectric generators (FTEGs), the TTEG incorporates full-ring ther-moelectric elements within a tubular layout, offering a novel approach to thermal energy recovery from fluid-based systems. This design significantly enhances the heat transfer capabilities, thereby improving the efficiency of energy conversion. Comprehensive simulations and analyses form the core of this study, where the per-formance of the TTEG is rigorously compared with traditional FTEGs. These comparisons highlight the advantages of the tubular design in terms of energy conversion efficiency and practical applicability in various scenarios. The findings reveal that the TTEG not only outperforms its flat plate counterparts but also presents a scalable and adaptable so-lution for waste heat recovery in a wide range of industrial and automotive applications. This research contributes to the field of energy science and technology by presenting a detailed experimental setup, complete with reproducible procedures and results. It opens new pathways for the development of more sustainable and efficient energy conversion systems, aligning with the goal of harnessing renewable and sustainable energy sources. The potential applications of this technology in enhancing energy efficiency and reducing environmental impact are vast, making it a significant step forward in the quest for clean and sustainable energy solutions.

The pursuit of more efficient transport has led engineers to develop a wide variety of 1 aircraft configurations with the aim of reducing fuel consumption and emissions. However, these 2 innovative designs introduce significant aeroelastic couplings that can potentially lead to structural 3 failure. Consequently, aeroelastic analysis and optimization has become an integral part of modern 4 aircraft design. In addition, aeroelastic testing of scale models is a critical phase in aircraft devel- 5 opment, requiring accurate prediction of aeroelastic behaviour during scale model construction to 6 reduce costs and mitigate risks associated with full-scale flight testing. Achieving a high degree of 7 similarity between the stiffness, mass distribution and flow field characteristics of scaled models 8 and their full-scale counterparts is of paramount importance. However, achieving similarity is 9 not always straightforward due to the variety of configurations of modern lightweight aircraft, as 10 identical geometry cannot always be directly scaled down. This configuration diversity has a direct 11 impact on the aeroelastic response, necessitating the use of computational aeroelasticity tools and 12 optimization algorithms. This paper presents the development of an aeroelastic scaling framework 13 using multidisciplinary optimization. Specifically, a parametric Finite Element Model (FEM) of the 14 wing is created, incorporating parameterisation of both thickness and geometry, primarily using 15 shell elements. Aerodynamic loads are calculated using the Doublet Lattice Method (DLM) em- 16 ploying twist and camber correction factors, and aeroelastic coupling is established using infinite 17 plate splines. The aeroelastic model is then integrated within an Ant Colony optimization (ACO) 18 algorithm to achieve static and dynamic similarity between the scaled model and the reference wing. 19 A notable contribution of this work is the incorporation of internal geometry parameterisation into 20 the framework, increasing its versatility and effectiveness.

Topological states of matter have attracted significant attention due to their intrinsic wave-guiding and localization capabilities robust against disorders and defects in electronic, photonic, and phononic systems. Despite the above topological features phononic crystals share with their electronic and photonic counterparts, finite-frequency topological states in phononic crystals may not always survive. In this work, we discuss the survivability of topological states in Su-Schrieffer-Heeger models with both local and non-local interactions with larger symmetry perturbation. Although such a discussion is still about ideal mass-spring models, the insights from this study set the expectations in continuum phononic crystals, which can further instruct the applications of phononic crystals for practical purposes.

In the present work, the effects of ageing treatment on the microstructures of a near-β Ti alloy (TC18) are studied. The influence of ageing treatment on the tensile properties and failure mechanisms are systematically analyzed. It is found that the size and morphology of the primary α (αp) phases are insensitive to ageing temperature and time. Furthermore, the ageing temperature and time dramatically influence the precipitation of the secondary α (αs) phases. Massive αs phases precipitate and gradually coarsen, and finally weave together with increasing the ageing temperature or extending the ageing time. The thickness of αs phases is responsible for the material strengths, while the content of α phases can enhance the material ductility. The ductile characteristics of the alloy with coarser αs phases are more obvious than those with thinner αs phases. Therefore, the ageing treatment is helpful for the precipitation and homogeneous distribution of αs phases, which is essential for balancing the strengths and ductility of the studied Ti alloy.

Anatomy education plays a critical role in medical practice, and the level of anatomical knowledge among students and physicians significantly impacts patient care. This article presents a pilot project conducted by the University of Milan aimed at exploring the effectiveness of the Area9's Rhapsode platform, an intelligent tutoring system that uses artificial intelligence to personalize learning and collect data on mastery acquisition. The study focused on liver anatomy and employed a flipped classroom approach, incorporating adaptive learning modules and an interactive in-class session. The project's execution, outcomes and preliminary pedagogical considerations are discussed. The results demonstrated improved learning quality, positive repurposing of study time, enhanced metacognitive awareness among students, with most of students demonstrating conscious mastery of the materials and a clear understanding of their level of competence. This approach, by providing valuable insights into the potential of artificial intelligence-based adaptive learning systems in anatomy education, could address the challenges posed by limited teaching hours, shortage of anatomist and the need for individualized instruction, with recommendations for future research and the expansion of adaptive learning modules to other anatomical districts.

Collecting and recording physiological parameters and forwarding this data via telemedicine or remote surveys may significantly increase the health and safety of people working under extreme environmental conditions, like firefighters, mountain rescuers, disaster control employees, military personnel, etc. First, ruggedized systems, as small, lightweight, and flexible as possible, are needed to optimize the goal of increasing occupational health and safety of persons at risk and maximizing their performance during missions. Previous systems could only record a very limited number of parameters, and a few could forward the data online to return information to the user. Therefore, in order to record several meaningful, valid, and reliable physiological parameters synchronized, an extension of existing systems is required. This review highlights this problem and gives an overview of the historical development. The actual status of the systems available was listed and described comparatively. In the end, a proven, promising, and innovative solution is presented that can solve the problem and allow people to work more safely in extreme environments, which may represent the future.

Standard Non-Melanoma Skin Cancer (NMSC) treatment involves surgery, recently combined with chemotherapy or immunotherapy in case of advanced tumors. Exosomes, integral to carcinogenesis, are found in NMSC, releasing mediators impacting tumor progression. Nevertheless, the precise intercellular signaling role of NMSC-derived exosomes remains unclear. This review aims to elucidate their potential role in NMSC diagnosis and treatment. A systematic review encompassed literature searches in electronic databases from inception to September 2023, based on certain inclusion and exclusion criteria, addressing NMSC-derived exosomes, their molecular cargo and their implications in the diagnosis, prognosis, and treatment of NMSC. Key components were identified. Extracellular vesicle (EV) proteins and RNA emerged as diagnostic biomarkers in EV-based liquid biopsy. Circular RNA CYP24A1, known for its molecular stability, holds promise as a diagnostic biomarker. Long noncoding RNAs (lincRNA-PICSAR) and Desmoglein 2 (DSg2) are linked to drug resistance, serving as prognostic biomarkers. EV mediators are actively investigated for their potential role as drug delivery agents. In conclusion, this systematic review showed that NMSC-derived EVs display promise as therapeutic targets and diagnostic biomarkers. Further research is imperative to fully comprehend exosome mechanisms and explore their potential in cancer diagnosis and treatment.

This study investigates the emergence of ertapenem-resistant, meropenem-susceptible (ErMs) among non-carbapenemase producing (NCP) and carbapenemase producing (CP) Escherichia coli and Klebsiella pneumoniae. As mutations for ertapenem resistance establish the genetic background for non-carbapenemase meropenem resistance, there is a great need for antibiotic stewards and researchers to understand the determinants of a strain’s propensity to become resistant. Whole genome sequencing was conducted on clinical carbapenem-resistant E. coli (CREC) and K. pneumoniae (CRKP) across 5 hospitals in San Antonio, U.S. from 2012-2018. The majority of carbapenem resistant Enterobacterales (CRE) were NCP (54%; 41/76). The blaCTX-M was found to be most prevalent among NCP isolates (p = 0.02). LC-MS/MS analysis of carbapenem hydrolysis revealed that blaCTX-M-mediated carbapenem hydrolysis, indicating the need to reappraise the term, “non-carbapenemase (NCP)” for quantitatively uncharacterized CRE strains harboring blaCTX-M. Antimicrobial susceptibility results showed that 56% of all NCPE isolates had an ErMs phenotype (NCPE vs. CPE, p &lt; 0.001), with E. coli driving the phenotype (E. coli vs. K. pneumoniae, p &lt; 0.001). ErMs strains carrying blaCTX-M, had approximately 4-fold more copies of blaCTX-M than ceftriaxone-resistant but ertapenem and meropenem susceptible (EsMs) isolates (3.7 v. 0.9, p &lt; 0.001). ErMs also carried more mobile genetic elements (MGEs), particularly IS26 composite transposons, than EsMs (37 vs. 0.2, p &lt; 0.0001). Immunoblot analysis demonstrated the absence of OmpC expression in NCP-ErMs E. coli, with 92% of strains lacking full contig coverage of ompC. Overall, this work provides evidence of a collaborative effort between blaCTX-M and OmpC in NCP strains that confer resistance to ertapenem but not meropenem. To thwart potential mismanagement of CRE infected patients, future efforts should focus on understanding the mechanism(s) underlying OmpC loss, developing rapid methods to detect blaCTX-M copy number variants, and targeted antimicrobials for NCPE and ErMs strains.

Scales are widely used in many agricultural applications, ranging from weighing crops at harvest to determine crop yields to regularly weighing animals to determine growth rate. In agricultural research applications, there is a long history of measuring crop water use (evapotranspiration) using a particular type of scale called weighing lysimeters. Typically, weighing lysimeters require very accurate data logging systems that tend to be expensive. Recent developments in open-source technologies, such as micro-controllers and Internet of Things (IoT) platforms, created opportunities for developing effective and affordable ways to monitor crop water use and transmit the data to the Internet in near real-time. Therefore, this study aimed to create an affordable Internet of Things (IoT) scale system to measure crop evapotranspiration. A scale system to monitor crop evapotranspiration was developed consisting of an Arduino-compatible microcontroller with cell phone communication, electronic load cells, an Inter-Integrated Circuit (I2C) multiplexer, and analog-to-digital converters (ADC). The system was powered by a LiPo battery, charged by a small (6 W) solar panel. The IoT scale system was programmed to collect data from the load cells at regular time intervals and send the data to the ThingSpeak.com IoT platform. The system performed successfully during indoor and outdoor experiments conducted in 2023 at the Clemson University Edisto Research and Education Center, Blackville, SC. The results from the experiments showed that the IoT scale system could accurately measure crop evapotranspiration using the weighing lysimeter technique.

A synoptic compendium of the legumes of the Mimosoideae clade in northeastern Mexico is presented for the first time, including changes in their botanical nomenclature and retypification of genera. Furthermore, based on new information recently published, the taxonomic limits of several new genera segregated from Acacia (Acaciella, Mariosousa, Senegalia and Vachellia) and Prosopis (Neltuma and Strombocarpa) are clarified and included. Based on field work, collecting botanical samples during the last 30 years, a review of botanical materials and database in national and international, we have completed the diversity of legumes of the Mimosoideae clade of northeastern Mexico. Three tribes (Acacieae, Ingeae and Mimosaeae), 22 genera and 92 species, and 19 infraspecif categories were recorded. Only the genus Painteria is endemic to Mexico. Eighty-eight species are native to Mexico, and four are exotic, Acacia salicina, Neptunia prostrata, Neltuma chilensis and Albizia lebbeck. Twenty-eight species are endemic to Mexico, nine species are endemic of northeastern Mexico, and four species endemic to only one state in Mexico. The 22 registered genera represent 44% and 65% of the generic flora of the Mimosoideae clade for Mexico and the planet respectively while the 92 species registered represent 3% and 18% of the species of the Clade Mimosoideae for the planet and Mexico respectively. According to the new nomenclature of legumes, the number of genera in the Mimosoideae clade in northern Mexico has been increased from 19 to 24.

The perovskite solar cells (PSCs) have been significantly improved by utilizing inorganic hole transporting layer (HTL), such as nickel oxide. Despite the promising properties, there are still limitations due to defects. Recently, research on self-assembled monolayers (SAM) is being actively conducted, which show promise in reducing defects and enhancing device performance. In this study, we successfully engineered a p-i-n perovskite solar cell structure utilizing HC-A1 and HC-A4 molecules. These SAM molecules were found to enhance the grain morphology and uniformity of the perovskite film, which are critical factors in determining optical properties and device performance. Notably, HC-A4 demonstrated superior performance due to its distinct hydrophilic properties with a contact angle of 50.3°, attributable to its unique functional groups. Overall, the HC-A4 applied film exhibited efficient carrier extraction properties, attaining a carrier lifetime of 117.33 ns. Furthermore, HC-A4 contributed the superior device performance with its favorable band alignment, achieving the highest device efficiency of 20%.

Alginate, a biopolymer promising in food, biomedical, pharmaceutical, and electronic materials industries, is characterized by its biodegradability, biocompatibility, low toxicity, and gel-forming properties. It is most abundantly found in brown algae. However, conventional dilute acid and alkali extraction methods face limitations in commercialization due to their long processing time, low throughput, and high solvent requirements. In this study, a microwave-assisted extraction (MAE) process for sodium alginate was designed to improve extraction efficiency. Solid/liquid ratio, extraction temperature, and extraction solvent concentration were major variables affecting sodium alginate extraction from Undaria pinnatifida(sea mustard). They were then statistically optimized using response surface methodology. Under optimal conditions (13.27 g/L, 91.86 ℃, 2.51 %(w/v), and 15 min), the yield was 38.41 %, which was 93.43 % of the theoretical content of sodium alginate in Undaria pinnatifida. Our work has confirmed the productivity and industrial feasibility of efficient extraction of sodium alginate from marine biomass, and we hope that it will serve as an encouraging case for the application of biopolymers as one of the desirable options for alternative petrochemicals to construct a sustainable society.

The global energy landscape is undergoing a transformative shift, and the potential of LNG as a major energy source is a topic of intense debate. In order to meet the growing demand for sustainable energy supply, it is crucial to maximize the efficiency and environmental friendliness of the LNG supply chain. This research aims to leverage computational modeling and optimization techniques to enhance the production units involved in LNG production. By harnessing the power of advanced algorithms and simulations, we can identify and implement innovative strategies that minimize energy consumption, reduce greenhouse gas emissions, and enhance the overall sustainability of LNG. Through this study, we seek to uncover novel approaches to address the challenges faced by the LNG industry, including improving operational efficiency, optimizing liquefaction processes, and enhancing the utilization of natural resources. By integrating cutting-edge computational tools and considering environmental factors, we aspire to pave the way for a more sustainable and environmentally friendly future powered by LNG. By exploring the immense potential of computational modeling and optimization, we strive to contribute to the ongoing efforts in advancing energy sustainability and shaping the future of LNG as a crucial global energy source."In this paper, our focus is on simulating and optimizing the process of converting natural gas to LNG. Our goal is to achieve the minimum energy consumption per ton of LNG produced. Through our research, we have identified that utilizing a three-stage exchanger is the most effective approach for minimizing energy consumption in an LNG industrial production unit. Moreover, we have discovered that the outlet pressure from the compressor and the type of refrigerant in the cooling system play significant roles in determining the rate of energy conservation. By carefully considering these factors and optimizing their settings, we can further enhance the overall energy efficiency of the LNG production process. Our research aims to provide valuable insights and guidance to industry professionals and decision-makers in the LNG sector. By implementing the findings of this study, we can contribute to the sustainable development and utilization of LNG as a cleaner and more environmentally energy source. Friendly It's great to see the optimized parameters for the refrigerants and pressure settings in the liquefaction and subcooling cycles. With the mass fraction of 0.89 for methane and 0.14 for ethane in the liquefaction cycle, and 0.59 for methane and 0.3 for nitrogen in the composition for achieving energy efficiency in the LNG production subcooling cycle, The optimized outlet pressure of 650 kPa for the compressors in the liquefaction cycle and 1800 kPa for the subcooling cycle furtherr ccontribute to minimizing energy consumption. Based on your findings, the amount of consumed energy at 14.81 kW per ton of produced LNG highlights the success of the optimization efforts. Reducing the energy consumption per ton of LNG produced is a significant accomplishment towards achieving energy sustainability and environmental friendliness in the LNG industry. These results demonstrate the importance of computational modeling and optimization in identifying the best parameters for eenhancing energy efficiency in LNG production. By implementing these optimized settings, we can work towards a more sustainable future with reduced energy consumption and lower environmental impact

In response to growing industrial demands, necessitated by larger ships and increased cargo volumes, many port authorities worldwide are undertaking a significant expansion of their infrastructure to increase their capacity. Significant expansion raises challenges such as potential congestion and environmental concerns, especially for port located in urban area as the case study explored in this paper. To address these issues, the study employs a combination of scenario analysis developed in collaboration with the port authority and logistic system simulation. This approach assesses the capacity of existing access gates to handle the increased trucking traffic and optimizes the unloading process of construction trucks at a new terminal. Key findings suggest that while the current gate capacities are adequate, optimizing unloading times at the new terminal is critical to prevent road congestion in urban area before the gate and reduce negative impacts such as sound and atmospheric pollution. The study advocates for an appointment system during peak hours to manage traffic flow effectively and underscores the importance of collaboration between the city and port authorities in managing truck traffic to mitigate congestion on the city side. Nonetheless, the study recognizes certain constraints, including the incomplete evaluation of the influence of intermodal transport on truck traffic. Furthermore, the study emphasizes the need for future research to consider the correlation between vehicle numbers and service levels, aiming to effectively adjust the time in the system.

High-grade gliomas are extremely fatal tumors, marked by severe hypoxia and therapeutic resistance. Autophagy is a cellular degradative process that can be activated by hypoxia, ultimately resulting in tumor advancement and chemo-resistance. Our study aimed to examine the link between autophagy markers expression in low (LGG) and high-grade gliomas (HGG). In 39 glioma cases, we assessed protein expression of autophagy markers LC3B, p62, and DRAM by immunohistochemistry (IHC) and mRNA expression of autophagy genes; PI3K, AKT, m-TOR, PTEN, ULK1, ULK2, UVRAG, Beclin 1 and VPS34 using RT-qPCR. Livak’s method was used to analyze the relative changes in gene expression and multi-variate Anova test and Spearman's correlation tests were performed for statistical significance. LC3B, p62, and DRAM expression were positive in 64.1%, 51.3%, and 28.2% of glioma cases respectively. The expression of LC3B and p62 was notably higher in HGG compared to LGG. VPS34 exhibited a significant differential expression and increased fold change and demonstrated strong positive correlations with Beclin1 (rs=0.768), UVRAG (rs=0.802), and ULK2 (rs=0.786) in HGG compared to LGG, thus highlighting the potential link between autophagy and glioma progression. We Provide preliminary data for functional analysis of autophagy using cell culture model and to identify potential targets for therapeutic interventions

Hypertension (HTN) is the foremost contributor to cardiovascular diseases (CVD), which remain a leading cause of death. However, adherence to the properly prescribed dosage form is critical and challenging for patients with chronic diseases such as HTN to prevent illness progression and death. The study’s objective was to develop AMB-loaded subcutaneous implants to reduce the frequency of administration, thus improving patient compliance during HTN management. AMB subcutaneous implants were prepared using continuous hot melt extrusion technology using PCL and PLGA with dimensions of 7.5 cm (length) by 2 mm (diameter). The implants were characterized for thermal characteristics, drug-excipient incompatibilities, surface morphology, fracturability, in vitro release, and stability studies. DSC showed that the drug was in the crystalline state in the fabricated implants. Scanning Electron Microscopy (SEM) revealed a smooth surface. The lead formulation presented good drug content, showed an extended drug release profile over 30 days, and followed zero-order release kinetics with a mean dissolution time of 15 days. The formulation was stable over 30 days in accelerated stability conditions (the last time point was tested, 40℃/75% RH), and the release profile was similar to the initial drug release profile. The lead formulation showed good fracturability during textural analysis. Therefore, the hot melt extruded implants could be an alternative management strategy for conventional amlodipine besylate (AMB) formulation.

Abstract: Wildfires in forest ecosystems exert substantial ecological, economic, and social impacts. The effectiveness of fire management hinges on precise pre‐fire risk assessments to inform mitigation efforts. This study aims to investigate the relationship between predictions from pre‐fire risk assessments and outcomes observed through post‐fire burn severity analyses. In this study, forest fire risk was assessed with the Fuzzy Analytical Hierarchy Process, in which fire behavior factors were used as input. The degree of burn was determined using the Random Forest method using 11519 training points and 400 test points on Sentinel‐2 satellite images in three different classes. According to the results obtained from 266 selected test points located within the forest boundaries, all primary factors showed an increased effect in areas with high burn severity. Climate, in particular, emerged as the most influential factor, accounting for 52% of the overall impact. However, in cases of high fire severity, climate proved to be the most effective risk factor, ac‐counting for 67%. It followed by topography with 50% accuracy at high fire intensity. In the risk assessment is based on the FAHP method, climate was assigned the highest weight value among other factors with 32.2%. Topography emerged as the second most effective risk factor with 27 %. To evaluate the results more comprehensively both visually and statistically, two regions with different stand canopy characteristics were selected within the study area. While high burn severity had the highest accuracy in Case 1 area, moderate burn severity had the highest in Case 2 area. During the days when the fire continued, the direction of spread was obtained from MODIS images. In this way, the fire severity depending on the direction of fire progression was also interpreted. Through an analysis of various case studies and existing literature, the research underscores both the strengths and limitations inherent in predicting forest fire behavior‐based pre‐fire risk assessments. Furthermore, it emphasizes the necessity of continuous improvement to increase the success of forest fire management.

Chromosome segregation in female germ cells and early embryonic blastomeres is known to be highly prone to errors. The resulting aneuploidy is therefore the most frequent reason for termination of early development and embryo loss in mammals. And when compatible with embryonic and foetal development, aneuploidy leads into severe developmental disorders. The main surveillance mechanism, essential for protection of cells against aneuploidy, is the Spindle Assembly Checkpoint (SAC). And although all eukaryotic cells are perhaps able to mount SAC response, it is not clear, whether this pathway is active in all cell types, including blastomeres of early embryos. In this review, we will summarize and discuss the published literature with regards to mechanisms controlling chromosome segregation in early embryos. Our conclusion is that early embryos show limited capabilities to react to chromosome segregation defects, which might, at least partially, explain the widespread problem of aneuploidy during early development.

Genetic engineering and directed evolution are effective methods to address the low yield and poor industrialization level of microbial target products. The current research focus is on how to efficiently and rapidly screen beneficial mutants from constructed large-scale mutation libraries. Traditional screening methods such as plate screening and well plate screening are severely limited in their development and application due to their low efficiency and high costs. In the past decade, microfluidic technology has become an important high-throughput screening technology due to its fast speed, low cost, high automation, and high screening throughput, and it has developed rapidly. Droplet-based microfluidic high-throughput screening has been widely used in various fields such as strain/enzyme activity screening, pathogen detection, single-cell analysis, drug discovery, and chemical synthesis, and has been widely applied in industries such as materials, food, chemicals, textiles, and biomedicine. In particular, in the field of enzyme research, droplet-based microfluidic high-throughput screening has shown excellent performance in discovering enzymes with new functions, improved catalytic efficiency or stability, acid-base tolerance, etc. Currently, droplet-based microfluidic high-throughput screening technology has achieved high-throughput screening of enzymes such as glycosidase, lipase, peroxidase, protease, amylase, oxidase, and transaminase, as well as high-throughput detection of products such as riboflavin, coumarin, 3-dehydroquinate, lactic acid, and ethanol. This article reviews the application of droplet-based microfluidics in high-throughput screening, with a focus on high-throughput screening strategies based on UV, visible, and fluorescence spectroscopy, including labeled optical signal detection screening, as well as label-free electrochemical detection, mass spectrometry, Raman spectroscopy, nuclear magnetic resonance, etc. Furthermore, the research progress and development trends of droplet-based microfluidic technology in enzyme modification and strain screening are also introduced.

During fertilization, the fusion of the spermatozoa with the oocytes causes the release of calcium from the oocyte endoplasmatic reticulum. This, in turn, triggers a series of calcium ion (Ca2+) oscillations, a process known as oocyte activation. The sperm-specific factor responsible for oocyte activation is phospholipase C zeta (PLCζ). Men undergoing intracytoplasmic sperm injection (ICSI) with their spermatozoa lacking PLCζ are incapable of generating Ca2+oscillation, leading to fertilization failure. The immunofluorescence assay is the most used technique to assess the expression and localization of PLCζ and to diagnose patients with reduced/absent ability to activate the oocytes. In these patients, the use of assisted oocyte activation (AOA) technique can help to yield successful ICSI results and shorten the time of pregnancy. However, the production of a stable PLCζ recombinant protein represents a new powerful therapeutic approach to treating individuals with this condition. We aim to conduct a systematic review focusing on the expression, level, and localization of PLCζ, discussing the novel genetic mutation associated with its impairment. In addition, we highlight the benefits of AOA, looking at new and less invasive methods to diagnose and treat cases with PLCζ dysfunction ability.

Heterotopic ossification (HO) is most dramatically manifested in the rare and severely debilitating disease, fibrodysplasia ossificans progressiva (FOP), in which heterotopic bone progressively accumulates in skeletal muscles and associated soft tissues. The great majority of FOP cases are caused by a single amino acid substitution in the type 1 bone morphogenetic protein (BMP) receptor ACVR1, a mutation that imparts responsiveness to activin A. Although it is well-established that biological sex is a critical variable in a range of physiological and disease processes, the impact of sex on HO in animal models of FOP has not been explored. We show that female FOP mice exhibit both significantly greater and more variable HO responses after muscle injury. Additionally, the incidence of spontaneous HO was significantly greater in female mice. This sex dimorphism is not dependent on gonadally-derived sex hormones, and reciprocal cell transplantations indicate that apparent differences in osteogenic activity are intrinsic to the sex of the transplanted cells. By circumventing the absolute requirement for activin A using an agonist of mutant ACVR1, we show that the female-specific response to muscle injury or BMP2 implantation is dependent on activin A. These data identify sex as a critical variable in basic and preclinical studies of FOP.

Diatomite (DME) consists of natural ordered porous structures that are excellent candidates as microcontainers. However, to the best of our knowledge, the application of DME loaded with corrosion inhibitors in anti-corrosion coatings has not hitherto been reported. In this study, DME has been used as a source of microcontainers to load benzotriazole (BTA) inhibitor by an immersion method. In order to prevent unwanted early release of the small molecule BTA inhibitor from the DME microcontainers, inspired by the adhesion characteristics of catechol and amine in mussel adhesion protein, polydopamine (PDA) was coated on their surfaces to generate BTA@DME/PDA microcapsules. Because of the depolymerization characteristics of PDA at low pH, the synthesize microcapsules showed a controllable release function. The SEM morphology, chemical structure, and loading capacity of the synthesized BTA@DME/PDA microcapsules were characterized. The corrosion resistances of epoxy coatings with different contents of BTA@DME/PDA microcapsules were compared by saline immersion and electrochemical impedance tests. A scratched coating with 5wt.% BTA@DME/PDA microcapsules showed the best anti-corrosion effect.

The effect of climate change plays a significant role on groundwater level variations and crop yield. The change in climate leading to increased temperatures, decreased rainfalls and extreme drought conditions ultimately cause low groundwater level and crop yield. Judicious groundwater management technology viz., water recharge options, need based irrigation, crop selection, must be adapted for further increasing the water table level in soil ecosystem. Additionally, climate change impacts combined with changes in agricultural water use can affect groundwater dynamics. Increased irrigation demand and decreased summer precipitation can lower groundwater levels, impacting crop production. Overall, climate change affects both groundwater resources and crop yield highlighting the need for sustainable water management practices and consideration of soil properties in agricultural modelling. The authors carefully selected relevant research articles addressing the impact of climate change on ground water level in Asian countries. The review highlights the use of machine learning method to ground water level and crop yield modelling. According to the study, machine learning techniques have made significant contributions to predicting groundwater level changes and crop yield with higher accuracies, high performance and less running time.

Addressing the increasing nursing demand in the face of a limited nursing workforce, understanding job satisfaction and retention becomes critical. Our cross-sectional study, conducted among 2,572 nurses in Bavaria, Germany, uncovers a dichotomy where nurses have strong empathy for their profession yet yearn for significant improvements. The top areas identified for enhancement include (i) ensuring sufficient time for patient care, (ii) providing a reliable service organization with minimal unplanned shift changes, and (iii) streamlining nursing documentation. Moreover, the largest disparity between expectations and job satisfaction was measured in patient care time. Multivariable regression analysis further investigates factors influencing intentions to stay in the profession, including (i) demographic aspects (age, living conditions), (ii) working area, (iii) working hours, (iv) career choice satisfaction, (v) career opportunities, (vi) payment, (vii) working and rest times, and (viii) satisfaction derived from aiding individuals in challenging life situations. The findings uncover a need to change nursing conditions, and measures for younger nurses and elderly care nursing. Although there are limitations, and a potential bias due to convenience sampling, our study provides key insights into nursing conditions. Future research should broaden its scope to investigate nurse job satisfaction and retention, emphasizing potential relief tools such as digitization.

Prosthetic infections are associated with high morbidity, mortality, and relapse rates making them still a serious problem for implantology. Staphylococcus aureus is one of the most common bacterial pathogens causing prosthetic infections. In response to the increasing rate of bacterial resistance to commonly used antibiotics, the work proposed a method of combating pathogenic microorganisms by modifying the surface of synthetic polymeric biomaterials using proteolytic enzyme inhibitors (serine protease inhibitors - 4-(2-aminoethyl)benzenesulfonyl fluoride hydrochloride and puromycin). While using techniques based on immobilization of biologically active molecules, it is important to monitor changes occurring on the surface of the modified biomaterial, where spectroscopic techniques (e.g. FTIR) are ideal. The ATR-FTIR measurements demonstrated that the immobilization of both inhibitors caused large structural changes on the surface of the tested vascular prostheses (polyester or polytetrafluoroethylene) and showed that they were covalently bonded to the surface of the biomaterials. Next, the bactericidal and antibiofilm activities of the tested serine protease inhibitors were determined using the CLSM microscopic technique with fluorescent staining. During LIVE/DEAD analyses, a significant decrease in the formation of Staphylococcus aureus biofilm after exposure to selected concentrations of native inhibitors (0.02-0.06 mg/mL for puromycin and 0.2-1 mg/mL for 4-(2-aminoethyl)benzenesulfonyl fluoride hydrochloride was demonstrated.

Irrational belief is a product of complex personality traits and Machiavellianism Intelligence. The present study is conducted to trace the significance of predictive nature of personality characteristics and Machiavellianism Intelligence (Mach Intelligence) on irrational beliefs among chronically ill older people. The research method is cross-sectional with correlational design, purposive sampling with a total of 200 chronically ill older people aged between 40–60 years with disease type such as Systemic lupus erythematosus, Complicated Diabetes, Glomerulonephritis and Chronic Heart Failure. The analysis revealed that personality characteristics and irrational belief subscales such as worrying, rigidity, problem avoidance and Mach Intelligence are significantly positively correlated; however, Emotional irresponsibility has significant negative correlation with personality characteristics and Mach Intelligence. Gender differences revealed that males are high on all the subscales of personality characteristics, irrational beliefs (except emotional irresponsibility) and Mach Intelligence as com-pared to female chronically ill older people. Predictive analysis also revealed that overall personality characteristics explained a total of 67% variance in irrational beliefs. Moreover, Mach Intelligence predicts irrational beliefs. Future health related recommendations should be planned accordingly.

Nutrition is one of the most influential environmental factor in both taxonomical shifts in gut microbiota as well as development of Type 2 Diabetes Mellitus (T2DM). Emerging evidence has shown that the effects of nutrition on both these parameters is not mutually exclusive and that changes in gut microbiota and related metabolites such as short chain fatty acids (SCFA) and branched chain amino acids (BCAA) may influence systemic inflammation and signaling pathways that contribute to pathophysiological processes associated with T2DM. With this background, our review highlights the effects of macronutrients, carbohydrates, proteins and lipids, as well as micronutrients, vitamins, and minerals, on T2DM, specifically through their alterations in gut microbiota and the metabolites they produce. Additionally, we describe the influences of common food groups, which incorporate varying combinations of these macronutrients and micronutrients, on both microbiota and metabolic parameters in the context of diabetes mellitus. Overall, nutrition is one of the first line modifiable therapies in the management of T2DM and better understanding of the mechanisms by which gut microbiota influence its pathophysiology provides opportunities for optimizing dietary interventions.

The work presented in this paper makes multiple scientific contributions with a specific focus on the analysis of misinformation about COVID-19 on YouTube. First, the results of topic modeling performed on the video descriptions of YouTube videos containing misinformation about COVID-19 revealed four distinct themes or focus areas - Promotion and Outreach Efforts, Treatment for COVID-19, Conspiracy Theories regarding COVID-19, and COVID-19 and Politics. Second, the results of topic-specific sentiment analysis revealed the sentiment associated with each of these themes. For the videos belonging to the theme of Promotion and Outreach Efforts, 45.8% were neutral, 39.8% were positive, and 14.4% were negative, for the videos belonging to the theme of Treatment for COVID-19, 38.113% were positive, 31.343% were neutral, and 30.544% were negative, for the videos belonging to the theme of Conspiracy Theories regarding COVID-19, 46.9% were positive, 31.0% were neutral, and 22.1% were negative, and for the videos belonging to the theme of COVID-19 and Politics, 35.70% were positive, 32.86% were negative, and 31.44% were negative. Third, topic-specific language analysis was performed to detect the various languages in which the video descriptions per topic were published on YouTube. This analysis revealed multiple novel insights. For instance, for all the themes, English and Spanish were the most widely used and second-most widely used languages, respectively. Fourth, the patterns of sharing these videos on other social media channels such as Facebook and Twitter were also investigated. The results revealed that videos containing video descriptions in English were shared the highest number of times on Facebook and Twitter. Finally, correlation analysis was performed by taking into account multiple characteristics of these videos. The results revealed that the correlation between the length of the video title and the number of Tweets as well as the correlation between the length of the video title and the number of Facebook posts was statistically significant.

Two novel sizable multicharged cationic complexes, of the formulae [(η6-[12]CPP)[Ru(η5-Cp)]12]Χ12 and [(η6-[11]CPP)[Ru(η5-Cp)]11]Χ11, CPP= cycloparaphenylene, Cp = cyclopentadienyl, X = [PF6]-, (1), (3) and [Cl]-, (2), (4), were synthesized and characterized using NMR techniques, high-resolution mass spectrometry, and elemental analyses. The complexes, (1) and (3) were stable in acetone and acetonitrile solutions over 48 h. In contrast, the water-soluble, (2) and (4), begins to decompose in aqueous media after 1h, due to the [Cl]- tendency for nucleophilic attack on ruthenium of the {Ru(η5-Cp)} units. Fluorescence quenching experiments conducted during the stability window of (2) with the d(5′-CGCGAATTCGCG-3′)2-EtBr adducts, revealed remarkably high values for Ksv = 1.185 × 104 ± 0.025 M-1 and Kb = 3.162 × 105 ± 0.001 M-1. Furthermore, the cytotoxic activity of (2) against A2780, A2780res, and MCF-7 cancer cell lines shows that it is highly cytotoxic with IC50 values in the range of 4.76 ± 1.85 to 16 ± 0.81 μΜ.

Abstract: This study estimates consumers’ willingness to pay (WTP) for sustainability turfgrass attributes such as low-input and stress-tolerance attributes, while considering potential trade-off relationships between aesthetic attributes and sustainability attributes. To address our objectives, our study conducts a choice experiment and estimates two mixed logit models. The first model includes low-input, winter kill, and shade-tolerance attributes as predictor variables, and the second model extends the first model by adding interaction terms between aesthetic and sustainability attributes. Another choice experiment is conducted under water policies with various water rate increase and watering restriction scenarios. Results from the mixed logit models show that overall, higher low-input cost reduction, less winter-damaged, and more shade-tolerance grasses are preferred, the direct effect of aesthetic attributes on consumers’ preference is strong, but the indirect effect represented by the interaction terms are generally statistically insignificant. Our results indicate that consumers like to have a pretty lawn, but no strong consideration is given to the aesthetics of their lawn when selecting low-input and stress-tolerance turfgrasses. Our choice experiment under water policy scenarios suggests that water pricing is more effective than watering restriction in increasing consumer demand for water-conserving turfgrasses.

The Spearman rank correlation coefficient is a non-parametric (distribution-free) rank statistic proposed by Charles Spearman as a measure of the strength of the relationship between two variables. It is a measure of a monotonic relationship that is used when the distribution of the data makes Pearson's correlation coefficient undesirable or misleading. The Spearman coefficient is not a measure of the linear relationship between two variables. It assesses how well an arbitrary monotonic function can describe the relationship between two variables, without making any assumptions about the frequency distribution of the variables. Unlike Pearson's product-moment (linear) correlation coefficient, it does not require the assumption that the relationship between variables is linear, nor does it require that the variables be measured on interval scales; it can be applied to variables measured at the ordinal level. The purpose of this study is to compare the values of Pearson's product-moment correlation coefficient (treating the data in a quantitative way) and Spearman's rank correlation coefficient (treating the same data in a somewhat "qualitative" way) and their statistical significance for six Pinus sylvestris L. traits (original – for Pearson's coefficient and ranked – for Spearman's coefficient) estimated from all observations, object means (for trees) and medians. The results show that the linear and rank correlation coefficients are consistent (as to direction and strength). In cases of divergence in the direction of correlation, the correlation coefficients were not statistically significant, which does not imply consistency in decision-making. Estimation of correlation coefficients based on medians is robust to outlier observations and factors that linear correlation is then very similar to rank correlation.

Abstract：To investigate the effects of feeding the Lincomycin and faecal bacterial on weaning stress in Tibetan piglets, we divided the weaned Tibetan piglets at 30 days of age into four groups. We measured growth performance, blood physiological indexes, and metabolomics. The results showed that the Ant, Tib, and Fec groups significantly reduced the ratio of diarrhoea to feed/weight (F/G) and increased the average daily gain (ADG) compared to the Nor group (p < 0.01). The Nor group had significantly lower leukocyte counts, hemoglobin levels, and erythrocyte counts compared to the other three groups on 21d (p < 0.05). These physiological indexes tended to stabilize on 42d. We found that there were beneficial metabolites and metabolic pathways for gastrointestinal function. Specifically, the porphyrin metabolic pathway was elevated in the Ant group, and the tryptophan metabolic pathway was significantly elevated in the Tib and Fec groups compared to the Nor group (p < 0.05). In conclusion, adding faecal bacterial supernatant and fifteen-flavour black pills of Tibetan medicine to the feed reduced the rate of diarrhoea and improved the growth performance of piglets. Moreover, it had an effect on microorganisms and their metabolites and pathways in the gastrointestinal tract of the animals, which might be the main reason for influencing the diarrhoea rate of weaned Tibetan piglets and the growth and development of the piglets. This study provides a new approach for anti-stress applications in weaned Tibetan piglets and the development of substitute anti-products.

Currently the bimatoprost implant (DURYSTA) is approved for a single administration secondary to concern for progressive corneal endothelial cell (CEC) loss with intracameral administration. In order to better understand the cause of CEC loss and other adverse events (AEs) with intracameral administration, multimodal imaging of the implant utilizing optical coherence topography (OCT), robotic ultrasound and bio microscopy video recording was utilized. Inherently the anterior chamber is a non-confined space. In certain examples the implant assumed a round and spotted structure as it picked up iris pigment as it migrated around the anterior chamber. Accordingly, we explored delivery of the implant in the middle segment behind the iris and in front of the pseudophakic lens. We then evaluated the suitability of various imaging modalities to assess the implant in this location. For middle segment administration, the ArcScan Insight 100 robotic ultrasound provided resolution and repeatability sufficient to monitor the implant behind the iris. This preliminary study hypothesizes that DURYSTA migration in the anterior chamber is the main source of AEs. Through use of a confined location, the middle segment, the implant is unlikely to migrate and cause CEC loss while also delivering drug closer to its site of action, the ciliary body. Further efforts are underway to understand the suitability of the middle segment for serial DURYSTA administration to maximize intraocular pressure lowering while minimizing AEs.

Machine learning models facilitate the search for non-linear relationships when modeling hydrological processes, but they are equally effective for automation at the data preparation stage. The tasks whose automation was analyzed consisted in estimating changes in the roughness of a mountain streambed and the extent of floods from images. The Segment Anything Model (SAM) developed this year by Meta was used for this purpose. Images from many years from the Wielka Puszcza mountain stream located in the Polish Carpathians were used as the only input data. The model was not additionally trained for the described tasks. The model can be run in several modes, but the two most appropriate were used in this study. The first one is available in the form of a web application, while the second one is available in the form of a Jupyter notebook run in the Google Colab environment. Both methods do not require specialized knowledge and can be used by virtually any hydrologist. In the roughness estimation task, the average Intersection over Union (IoU) ranges from 0.55 for grass to 0.82 for shrubs/trees. Ultimately, it was possible to estimate the roughness coefficient of the mountain streambed between 0.027 and 0.059 based solely on image data. In the task of estimation of the flood extent, when selecting appropriate images, one can expect IoU at the level of at least 0.94, which seems to be an excellent result considering that SAM is a general-purpose segmentation model. It can therefore be concluded that SAM model can be a useful tool for a hydrologist.

This work studies the discontinuities features of sedimentary flysch materials in a 100 km2 area belonging to the Basque Arc. Such materials are common in this Spanish Alpine region located in the north of the Iberian Peninsula. A total of 33 outcrops are investigated by an intensive geotechnical investigation including geomechanical stations, boreholes and mechanical laboratory tests. Two flysch units are characterized: the Upper Aguinaga Formation or siliciclastic flysch, and the Lower Itziar Formation or calcareous flysch. Differences between both flysch formation are found. Joints in the siliciclastic flysch formation present an undulated roughness, with a spacing narrower and a persistence lower than in the calcareous flysch formation, which exhibits higher friction angles, although roughness is essentially planar. In addition, the potential of using Artificial Intelligence (AI) techniques, particularly Artificial Neural Networks and Support Vector Machine, to estimate the Geological Strength Index (GSI) from the Rock Quality Design (RQD) and some discontinuities features (spacing, persistence, aperture and roughness) is investigated. AI techniques are found to be satisfactory, being the Support Vector Machine with a linear kernel the technique which achieves the best performance.

The pandemic SARS-CoV-2 continues to evolve to give rise to variants of concern that can escape vaccine-induced immunity. As such, more effective vaccines are urgently needed. In this study, we evaluated virus-like particle (VLP) as a vaccine platform for SAS-CoV-2. The spike, envelope, and membrane proteins of the SARS-CoV-2 Wuhan strain were expressed by a single recombinant baculovirus BacMam and assembled into VLPs in cell culture. The morphology and size of the SARS-CoV-2 VLP as shown by transmission electron microscopy was found to be similar to the authentic SARS-CoV-2 virus particle. In a mouse trial, two intramuscular immunizations of the VLP BacMam with no adjuvant elicited spike-specific binding antibodies in both sera and bronchoalveolar lavage fluids. Importantly, BacMam VLP -vaccinated mouse sera showed neutralization activity against SARS-CoV-2 spike pseudotyped lentivirus. Our results indicated that the SARS-CoV-2 VLP BacMam stimulated spike-specific immune responses with neutralization activity.

Hepatocellular carcinoma (HCC) is characterized by uncontrolled cellular proliferation driven by aberrant signal transduction. Cells respond to potential carcinogenic signals by inducing cellular senescence (CS) as a defense mechanism. However, assessing CS levels in various tumors is challenging due to heterogeneity and the lack of universal CS markers. This study integrates single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from HCC samples to analyze gene expression profiles. HCC-specific senescence-related pathways are identified, and genes from these pathways distinguish molecular subtypes associated with senescence in HCC. These subtypes exhibit significant variations in biological and clinical attributes. A specific CS risk model is developed, revealing associations between CS scores and prognosis, clinical staging, immune infiltration, immunotherapy response, and drug sensitivity. The key gene G6PD is identified as a potential senescence-related target in liver cancer. Molecular experiments confirm the effective suppression of HepG2 cell proliferation, invasion, and migration upon G6PD knockdown. In summary, this analysis enhances our understanding of HCC-specific senescence molecular features and introduces a novel senescence-related biomarker, offering promising implications for future research.

The maritime sector, grapples with environmental challenges, but the adoption of "cold ironing" emerges as a promising solution, signifying a shift toward sustainability by providing energy to ships at port, reducing reliance on fossil fuels, and significantly lowering emissions, contributing to global climate change efforts. This transition towards renewable energy is especially crucial for islands like Lesvos, addressing challenges of high energy costs and environmental degradation resulting from reliance on imported fossil fuels, highlighting the potential for positive economic and environmental impacts. The existing literature highlights a research gap in the development of Renewable Energy Sources (RES) to support cold ironing operations, specifically due to the absence of specific data for the power demand needed in such operations and the lack of monitoring data for accurate calculations. This study's primary objective is to utilize real monitoring data from the port of Lesvos to evaluate the power demand for a potential cold ironing application. Additionally, the study aims to analyze the implementation of a wind power park to meet the energy needs of an electric port and evaluate the potential reduction in CO2 emissions. The database of Marine Traffic S.A. was utilized, while the determination of the energy used in-port per ship depended on factors such as the number of arrivals, the duration of hoteling, and the type of engine used by the ships. In addition, the software RETSCREEN was used for the energy analysis of a simulated 20 MW wind park that can support the in-port operations. The combined monthly energy demand for both main and auxiliary engines of shipping vessels at Mytilini port was assessed to be 6118 MWh and averaging a power demand equaled to 8.2 MW. The simulation analysis indicates that the annual electricity delivered to the port can be72080 MWh, with a significant portion remaining unused and exported to the grid, amounting to 14956 MWh annually. Due to demand fluctuations, in-port activities require an additional 924 MWh from the main electrical grid, which highlights the importance of additional measures like energy storage and demand-response practices for the gradual transition to 100% Renewable Energy Sources (RES) operations.

This review centers on the pivotal role of the oncoprotein FOSL1, within the dimeric AP-1 transcription factor consisting of FOS-related elements. FOSL1 emerges as a key regulator governing invasion and metastatic dissemination, therefore making it a promising target for therapeutic intervention in cancer patients. The review provides a comprehensive survey of the regulatory mechanisms that exert influence over FOSL1. These encompass a spectrum of transcriptional and post-translational modifications. Notably, we unveiled the intricate involvement of diverse non-coding RNAs, specifically microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), in the modulation of FOSL1 expression through targeted interactions with its mRNA transcripts. Furthermore, an exploration into the functional dimensions of FOSL1 unfolds, encompassing apoptosis, proliferation, and migration. This investigation is accompanied by a thorough examination of the elaborate signaling pathways that underpin these multifaced roles. Additionally, emphasis is placed on the role of FOSL1 in orchestrating the stimulation of various cytokines, including TGF-beta, and the initiation of IL-6 and VEGF production in tumor-associated macrophages (TAMs) that transverse into the tumor microenvironment. A distinct focus is dedicated to appraising the prognostic implications associated with FOSL1. Finally, insights emerge into the evolving roles of FOSL1 in the context of mechanisms governing resistance and dependency on targeted therapeutic modalities.

Real and complex analytic functions are largely studied in the field of complex analysis and are seen as very useful tools in solving problems in mathematics, physics and engineering. Real and complex numbers are a subset of semi-structured complex numbers (a new number set created to algebraically solve division by zero). Nevertheless, the properties of analytic functions made up of semi-structured complex variables (called semi-structured complex analytic functions) is yet to be explored. This limits the range of possible problems that can be resolved using analytic functions). In this regard, the aim of this paper was to expound upon the properties of semi-structured complex analytic functions and show their application in solving engineering problems. The results of this paper included (1) developing a full set of Cauchy–Riemann Equations for the semi-structured complex -space; (2) define sufficient and necessary conditions for a semi-structured complex function to be analytic; (3) determine the relationship between semi-structured complex analytic functions, Laplace’s Equations and Poisson’s Equations; and (5) provide an example of the use of these functions.

This study conducted an extensive analysis of campylobacteriosis surveillance in Portugal from 2009 to 2021, aiming to investigate demographic shifts, seasonal variations, and antimicrobial resistance (AMR) within Campylobacter isolates. Surveillance network and sentinel laboratory-based system data revealed a substantial under-notification of campylobacteriosis cases, suggesting an underestimated disease burden. A paradigm shift was observed in notification rates, with a notable prevalence among the pediatric population, particularly in children aged 1-4 years, diverging from European reports. However, the study also highlighted an emerging trend of Campylobacter infections in younger adults (15-44 years). The study unveiled a unique seasonal distribution of cases, defying typical summer peaks seen elsewhere. AMR analysis revealed extremely to very high-level resistance to ciprofloxacin and tetracycline, both in C. jejuni (93.7% and 79.2%, respectively) and in C. coli (96.5% and 93.2%, respectively), stable throughout the studied period (2013-2021). C. coli also exhibited significantly higher resistance to erythromycin, gentamicin, ampicillin, amoxicillin-clavulanic acid (decreased resistance), and ertapenem compared to C. jejuni (P&lt;0.001). In conclusion, the study highlights the need for enhanced surveillance efforts and emphasizes worrying AMR levels. The implementation of WGS-based surveillance is recommended to attain a more profound comprehension of disease patterns and the evolving landscape of AMR.

The aim of the research presented here is to assess the impact of depressive disorders on the potential of the labour markets in the countries of the European Union, with particular reference to the disparities between the 'old' and 'new' EU countries. The initial hypothesis of persistent inequalities in the system under study was verified by analysing the process of convergence in the burden of depressive disorders among people aged 20-54 that occurred in the EU-27 group of countries between 1990 and 2019. The study used data from the Global Burden of Disease Study 2019 (IHME, 2020), which examined the number of years lived with disability (YLD) due to depression in the working age population. The analysis showed that the high burden of the consequences of depressive disorders is particularly true for the highly developed economies of the EU-14. The results of the convergence assessment did not confirm the real effect of catching up over time with economies in a more favourable situation, and the inequalities observed at the beginning of the analysis period deepened..

Background: Genetic factors are considered important risk factors for the occurrence of osteoarthritis (OA), which has received extensive attention. This study examined the research on the relationship between genetic factors and the pathogenesis of OA from a bibliometric perspective. Methods: We searched Web of Science Core Collection for original and review articles on genetic factors and OA. We used R package “bibliometrix” to perform statistical and visualization analysis of countries, institutions, authors, journals, and keywords. Results: A total of 1,127 articles met the inclusion criteria, with an average citation of 20.41 per article. From 2012 to 2022, the average annual growth rate of research in this field was 7.83%. The corresponding authors of the published articles were mainly from China, the USA, and the UK. Boston University emerged as the most active and important institution, while the Osteoarthritis and Cartilage published the most articles in this field. The keywords “polymorphism”, “genetic” and “mendelian randomization” indicate the future research directions. Conclusion: This bibliometric study provides an overview of the key topics and trends in genetic factors and OA pathogenesis research. The high-frequency keywords suggest the current and potential future focus of this field, involving methods, mechanisms, and populations.

The relationship between culture and the individual is a central focus of social scientific research. This paper examines motivations that mediate between shared culture norms and individual actions. Inspired by the works of Leon Festinger and Melford Spiro, we posit that social network conformation (the perceived adherence of one’s social network with norms) and internalization of cultural norms (incorporation of cultural models with the self-schema) will differentially shape behavior (cultural consonance) depending on the domain and individual characteristics. For the domain of gender roles among Brazilian men, religious affiliation results in different configurations of the individual and culture. Our findings suggest that due to changing and competing cultural models, religious men are compelled to reflexively “think” about what masculinity means to them, rather than subconsciously conform to social (hegemonic) expectations. This study demonstrates the importance of considering the impetus of culturally informed behaviors, and in doing so, provides a methodological means for measuring and interpreting such motivations, an important factor in the relationship between culture and the individual.

In this study, tree selection/plantation DSS (Decision Support Systems) were reviewed and assessed based on essential objectives in the available literature. We reviewed existing DSS using multiple data sources and available online resources such as web interfaces. We compared the existing DSS, focusing primarily on five primary objectives in this study, which DSS may address when it comes to the tree selection, including a) Climate resilience, b) Infrastructure/Space Optimization, c) Agroforestry, d) Ecosystem services, e) Urban sustainability. Climate resilience of tree species and urban sustainability is addressed relatively less in existing systems, which can be holistically internalized in future DSS tools Based on this review, DNN (Deep Neural Networks) is recommended to address achieving trade-offs between complex objectives such as maximizing ecosystem services, climate resilience of tree species, maintaining Agroforestry, and other benefits.

Mesoporous silica nanoparticles (MSNs) can be used as carrier materials for the controlled release of pesticides while reducing their negative environmental impact. In this study, we screened an active ingredient, p-cymene (PC), with an excellent inhibitory effect on rice bacterial blight. Subsequently, the PC was successfully loaded onto MSNs via physisorption(PC@MSNs). PC@MSNs, characterized by a regular spherical shape, smooth surface, and an MSN average size of 262.9 nm, achieved an 8.6 % drug loading capacity. The release kinetics of the PC from the PC@MSNs demonstrated a sustained release (288 h) pattern influenced by drug diffusion. The efficacy of the PC@MSNs against Xanthomonas oryzae pv. Oryzae paralleled those of PC. Acute toxicity assays re-vealed that the PC@MSNs were less toxic to aquatic life (LC50=257.867 mg/L) and that the formu-lation showed no adverse effects on rice seedling growth. In summary, these results suggest that PC@MSNs can broaden PC's application scope in managing rice diseases.

Dirac's Large Number Hypothesis (LNH), proposed in 1937, has captivated the scientific community with its exploration of profound correlations between cosmic and atomic scales. This hypothesis delves into the intricate interplay between the infinitesimally small and the vastly large, offering potential insights into the fundamental nature of the universe. As we continue to uncover the mysteries of the cosmos, the LNH oscillates on the precipice of scientific acceptance—neither fully validated nor entirely dismissed. In this review paper, we embark on a comprehensive journey through Dirac's LNH, shedding light on its theoretical underpinnings, its implications for universe models, and its resonance with the Anthropic Principle. We delve into the possibilities of variable gravitational constants and continuous mass creation, inviting further exploration into the intricacies of our cosmic symphony. By embracing the ongoing quest for understanding, we endeavor to unravel the profound harmonies that connect the infinitesimal with the infinite, contributing to the symphony of knowledge in theoretical physics and cosmology.

The consequences of climate change and anthropogenic stressors, such as habitat loss and overexploitation, are threatening the subsistence of species and communities across the planet. Therefore, it is crucial to analyze the impact of environmental perturbations on the diversity, structure and function of ecosystems. In this work, in silico simulations of biodiversity loss were carried out on the marine food web of Caleta Potter (25 de Mayo Island, Antarctica) where global warming has caused critical changes in the abundance and distribution of benthic and pelagic communities during the last 30 years. We performed species removal considering their degree and trophic level and including four different thresholds on the occurrence of secondary extinctions. We examined the impact of extinctions on connectance, modularity and stability of the food web. We found different responses of these properties depending on the extinction criteria used, e.g., large increase in modularity and rapid decrease in stability when most-connected and relatively high-trophic level species were removed. Additionally, we studied the complexity-stability relationship of the food web founding two regimes: 1) high sensitivity to small perturbations suggesting that Potter Cove would be locally unstable, and 2) high persistence to long-range perturbations suggesting global stability of this ecosystem.

In obesity, white adipose tissue expresses inflammatory cytokines leading to insulin resistance. Non-physiological meta-tyrosine and ortho-tyrosine (meta-Tyr and ortho-Tyr), produced from phenylalanine by free radicals, may contribute to the development of insulin resistance. The resulting insulin resistance may have a significant impact on macrophage function. In this study we aim to investigate microscopically the effect of meta- and ortho-Tyr on insulin sensitivity and M1/M2 polarization of macrophages using Akt phosphorylation and the arginase 1/iNOS ratio. Macrophage cell lines were cultured in media containing para-, meta- or ortho-Tyr, 5 mmol/L or 25 mmol/L glucose (para25-Tyr group) and treated with insulin. Para25, meta- and ortho-Tyr increased pAkt levels and decreased the arginase 1/iNOS ratio in macrophages in the absence of insulin. In the case of physiological para-tyrosine treatment, insulin increased the amount of pAkt and decreased the arginase 1/iNOS ratio. Both meta- and ortho-Tyr treatment were able to abolish or reverse the insulin’s increasing effect on pAkt and the decreasing effect on arginase 1/iNOS ratio. Our results suggest that non-physiological tyrosine isomers may affect the insulin signaling of macrophages and influence their M1/M2 polarization.

(1) Background: Brassinosteroids (BRs) are an important hormone that participates in almost all stages of plant growth and development, and sterol dehydrogenase is a key enzyme that is involved in the biosynthesis of BRs. However, the steroid dehydrogenase gene family in Populus yunnanensis Dode (P. yunnanensis) has not been studied; (2) Methods: The PyDET2 gene family was identified and bioinformatics analyzed. Three genes were screened based on the RNA-seq of stem tip, the PyDET2e was further investigated by RT-qPCR (real-time quantitative polymerase chain reaction) and subcellular localization; (3) Results: We identified 14 DET2 family genes in P. yunnanensis that were classified into 4 groups according to sequence similarity and phylogenetic relationship, and 10 conserved protein motifs had been identified. The gene structure, chromosome distribution, collinearity, and codon preference of all PyDET2 genes identified in the genome of P. yunnanensis were analyzed. The codon of this family is biased to the end of A/U, and natural selection has a great influence on it. The expression level of PyDET2e in September was higher than in July, and it was significantly expressed in stems, stem tips, and leaves. The PyDET2e protein was localized in chloroplasts; (4) Conclusions: The PyDET2e is involved in the development of P. yunnanensis in the rapid growth stage. The systematic analysis provided a basis for the genome-wide identification of genes related to brassinolide biosynthesis processes in P. yunnanensis, and laid a foundation for the study on the mechanism of rapid growth of P. yunnanensis.

Recent years have experienced an increase in construction and demolition waste (C&amp;DW), which is the most significant solid waste stream. C&amp;DW is contributing to exceeding all planetary boundaries and presents a range of other issues. In order to better understand the existing research on C&amp;DW, a global bibliographic analysis was undertaken through seven groups of keyword searches and the results visualised using VOCviewer. The results show that C&amp;DW receives only a modest research attention compared to other areas of waste, and this is despite an exponential increase in C&amp;DW research since 2016. The analyses also show that concrete is the most researched material in terms of C&amp;DW, and that reuse, recycling, and circular economy are so far attracting only proportionally modest research attention. This signals a need for further acceleration of the C&amp;DW research, and specifically for more research on reuse, recycling, and circular economy for materials other than concrete.

Vit-106 is a promising zirconium-based alloy with high glass-forming ability and belongs to the so-called bulk metallic glasses (BMG). Workpieces with a size of around one centimeter in all three dimensions can be obtained from a BMG alloy by casting. However, further increasing the cast size decreases the cooling rate and thus induces crystallization. Selective laser melting (SLM) is a well-known technique to overcome the size limitations for BMGs because a workpiece is built by the addition of multiple melt portions where the cooling rate is kept above the critical one. Currently, BMG parts obtained by SLM suffer from partial crystallization. The present work studies the influence of SLM process parameters on partial crystallization of Vit-106 by metallography and the influence of the microstructure on mechanical properties by microhardness and wear resistance testing. Submicron crystalline inclusions are observed in an amorphous matrix of Vit-106 alloy obtained by SLM. The size and the concentration of the inclusions can be controlled by varying the laser scanning speed. It is shown that submicron crystalline inclusions formed in the amorphous matrix during SLM can favorably affect microhardness and wear resistance.

The populations of clearwing moth borers in Korea have recently exploited and severe damage on pin oaks (Quercus palustris Munchh.). We conducted the field monitoring and the molecular analyses to identify them in an integrated manner. Morphological examination and molecular analyses on COI-gene based intra-and inter-specific genetic divergences (GD) were revealed that the borers were recognized as two invasive species, Sphecodoptera sheni and Paranthrenella pinoakula sp. nov.. The maximum intraspecific GD was found to be 1.9%, whereas the minimum interspecific GD was confirmed as 8.1%, with a distinct barcoding gap. Both MJ network and NJ tree were also showed that 18 haplotypes (HAPs) were detected from the 52 COI sequences. The borers were revealed total 17 HAPs: i) H1-H7 were detected from all seven regions with S. sheni; ii) Wonju and Goyang populations of S. sheni were revealed as more than three HAPs; iii) H7 was closely connected with H8 of Chinese population of S. sheni; iv) H9-H10 were detected as the other samples from Wonju population with P. pinoakula sp. n., and closely located with congeneric species. Maximum likelihood tree also revealed that P. pinoacula sp. n. nested within the congeneric species by genetically separating from the S. sheni.

Printed Circuit Boards (PCBs) are essential to most electronic devices. Digitalization and upgradation of gadget generates lots of PCB-containing electronic waste. Conserving resources and protecting the environment requires recycling such e-waste. The present paper is focused on the recovery of metals from PCBs by physical pretreatment and hydrometallurgical processes. Initially, the waste PCBs were pre-treated to separate metallic and non-metallic fractions. The metallic concentrate was leached using nitric acid (strong oxidative agent) for dissolution of metals. The system was fully jacketed with scrubber and condenser so that no emission of toxic gases to the environment. The process parameters viz. effect of acid concentration, pulp density, temperature, time, etc. were optimized and the obtained data were scientifically validated. Kinetics leaching fitted well with the Shrinking core model, XB = kc.t for Cu, (1-(1-XB)1/2) for Ni and 1-3(1-XB)2/3 + 2(1-XB) for Pb. The optimized conditions derived from these studies will be useful for recovery of metals from waste PCBs, and tin left in the residue could be further treated for the purpose of safe disposal or the utilization in an environmentally friendly manner. The developed process provides environmental benefits and has potential to be commercialized after scale-up studies.

In this study, the extraction of rare earth elements (REEs) from chloride solutions containing mixtures of these metals with solutions of the mixtures of P507 and Cyanex 272 (1:1) of various concentrations was experimentally studied. It was shown that the distribution coefficients of all REEs decrease with increasing concentration of these metals in the initial solution, which is associated with the loading of the organic phase. The most significant improvement in the extraction is observed for heavy group of rare earth elements. The extractability of REEs enhances with increasing atomic number of the element, as is typical for the extraction of these metals with acidic organophosphorus extractants. The data obtained show that separation factors of adjacent rare earth elements mainly decrease with increasing concentration of metals in the initial aqueous solution. Increasing the concentration of the extractant mixture does not have a significant effect on the values of the adjacent REE separation factors. Analysis of the experimental results shows that two commercial products can be obtained from a concentrate of the medium-heavy group. In the first cascade, yttrium can be separated, in the second, a concentrate of dysprosium and terbium can be obtained.

Microplastics have been detected as widespread in an aquatic environment at the microscale, also known as plastic debris. They have continuously increased due to the increase in population, production of synthetic plastics and poor waste management. They are ubiquitous and slowly degrade in soil and water. They are emerging contaminants that have received attention from research communities and public audiences over the last few years. They have high stability and can absorb several other pollutants like heavy metals, pesticides, etc. After entering the environment, they can accumulate and persist for a long time. They can create a serious threat to freshwater ecosystems and human health. These particles can cause physical damage to freshwater organisms. Raman spectroscopy, Fourier-transform infrared spectroscopy, visual identification, density separation, microscopic method, chemical method, thermos-analytical method and hyperspectral imaging method are the commonly known approaches for identification and quantification of microplastics. The noticed concentration of microplastics depends on the analysis method, sampling location and technique. The authors reviewed the sources, health impact, transport and treatment of microplastics in freshwater environments in detail. This study will provide the baseline data for the researchers to do more research on microplastic pollution in the future.

In an era driven by technology and connectivity, where the sphere of learning goes beyond conventional classrooms, e-Service-Learning (e-SL) merges the possibilities of technology with the principles of experiential education in a powerful blend [1]. Service-learning (SL) is an educational proposal that has been cited by UNESCO [2] as an innovative educational tool through which to address the complex challenges of our society. The Sustainable Development Goals [3] provide a framework around which to structure the SL projects and thus develop the skills needed to act on the full range of goals. Embedding digital means open a debate on the intricate relationship between technology, education, and societal impact [4]. By analyzing two focus groups involving faculty, students and community partners, this contribution aims to explore the potential of combining SL and digital empowerment (DE). The focus group participants discussed the opportunities for innovation, the expected impact on them and the society at large, their needs and the pre-conditions needed to make SL and DE successful, and limitations. The results are presented according to the six principles of sustainability education in the university environment, highlighting the transformative potential of combining these principles within SL and DE.

Terahertz tomography is a promising method among non-destructive inspection techniques to detect faults and defects in dielectric samples. Image quality recently significantly improved through the incorporation of a priori information and off-axis data. However, this improvement has come at the cost of increased measurement time. To aim toward industrial applications, it is therefore necessary to speed up the measurement by parallelizing the data acquisition employing multi-channel setups. In this work, we present two tomographic frequency-modulated continuous wave (FMCW) systems working at a bandwidth of 230-320 GHz, equipped with an eight-channel detector array, and compare their imaging results with a single-pixel setup. While in the first system, the additional channels are used exclusively to detect radiation refracted by the sample, the second system features an f-θ lens, focusing the beam at different positions on its flat focal plane, and thus utilizing the whole detector array directly. The usage of the f-θ lens in combination with a scanning mirror eliminates the necessity of the formerly used slow translation of a single-pixel transmitter. This opens up the potential for a significant increase in acquisition speed, in our case by a factor of four to five, respectively.

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

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

In recent years, Synthetic Aperture Radar (SAR) has received attention in the Automatic Target Recognition (ATR) field due to its ability to acquire images both day and night, combined with the superior resolution offered by the latest sensors. However, despite advances, there remains a deficiency in dataset quality and quantity. This has necessitated the use of simulated data to overcome challenges associated with obtaining large quantities of high-quality images of targets and their subsequent labeling. In this study, we trained a Convolutional Neural Network (CNN) using a simulated dataset, subsequently employing it to classify real images from the MSTAR dataset. Traditional training methodologies often struggle with generalization when confronted with domain disparities between simulated and real data. To mitigate this, we exploited Margin Disparity Discrepancy (MDD), a domain adaptation technique not previously explored in SAR context. Findings from this study showcased a 13% increase in classification accuracy and improved generalization using MDD. Through Explainable AI (XAI) techniques such as t-SNE and other metrics like Kullback Leibler Divergence (KLD), we revealed a more distinct alignment of feature spaces between the two domains after domain adaptation, emphasizing MDD’s role in enhancing model accuracy and generalization.

In any forest stand, the theoretically modelled output of sawlogs (the most valuable roundwood assortments) will differ from what is actually obtained. The aim of this study was to assess whether it is possible to characterize this difference by site properties or inventory parameters of forest element for birch, black alder and as-pen. The differences in yield of sawlogs varied among soil types, and was increasing with age and average diameter of the forest element. The theoretical model for assortment grading predicted a lower yield of saw-logs compared to actually obtained yield at a lower age and at a lower average diameter, but overestimated output of sawlogs as age and diameter increase. The results highlight necessity to consider decreasing wood quality with increasing age to account for damage, such as stem rot, in assortment tables.

Post-training quantization is pivotal in deploying convolutional neural networks for mobile applications. Block-wise reconstruction with adaptive rounding, as employed in prior works like BrecQ and Qdrop, facilitates acceptable 4-bit quantization accuracy. However, adaptive rounding is time-intensive, and its constraint on weight optimization space curtails the potential for quantization performance. The optimality of block-wise reconstruction hinges on the quantization status of subsequent network blocks. In this investigation, we delve into the theoretical underpinnings of the limitations inherent in adaptive rounding and block-wise reconstruction. Our exploration leads to the development of a post-training quantization methodology, designated as AE-Qdrop. This algorithm operates in two distinct phases: block-wise reconstruction and global fine-tuning. The block-wise reconstruction phase introduces a progressive optimization strategy, superseding adaptive rounding, which not only augments quantization precision but also significantly improves quantization efficiency. To mitigate the risk of overfitting, we introduce a random weighted quantized activation mechanism. During the global fine-tuning phase, we account for interdependencies among quantized network blocks. The weight of each network block will be corrected with logit matching and feature matching. Extensive experiments validate that AE-Qdrop achieves high-precision and efficient quantization. For instance, in the case of 2-bit MobileNetV2, AE-Qdrop outperforms Qdrop by achieving a 6.26% enhancement in quantization accuracy and quintupling the quantization efficiency.

There is a need to develop enriched milk drinks with healthy and natural additives. A consumer test was conducted to compare milk (cow and camel) flavored with date syrup (Khlass and Sukkary varieties) at different percentage. The objective of the present work was to study consumers liking patterns for flavored milk drinks from dates syrup (from Khlass and Sukkary dates), at different percentages, added to milk (cow and camel) utilizing preference mapping analysis. A total of sixteen trained panelists took part in the test. The obtained data were used to develop an internal preference map for these samples. Principal component analysis (PCA) and Agglomerative hierarchical clustering (AHC) algorithms were used to construct the preference map. The first component signifies overall acceptance of taste and color, while the second focuses on texture and flavor. Consumers were grouped into five clusters based on preferences. Cluster two favored both components positively, while cluster four leaned negatively on both. A factorial ANOVA was performed and the results showed a significant effect of the main factors as well as the interactions. Panelists preferred cow's milk over Camel’s milk in all aspects. For taste, cow’s milk with 20% Khlass syrup or 10% Sukkary syrup was favored, while in flavor, it was cow’s milk with 5% Khlass syrup and Camel’s milk with 10% Sukkary syrup. Texture-wise, Camel’s milk with 5% Khlass syrup and 15% Sukkary syrup, along with cow’s milk with 10% Khlass syrup, received top marks. In color evaluation, cow’s milk with 15% Sukkary syrup was the preferred choice. Finally, for overall color score, cow’s milk with 10% Sukkary syrup led, followed by cow’s milk with 5% Sukkary syrup. This research suggests that dairy companies may have more impact if they use date syrup as a natural and healthy flavor. The preference map includes two main dimensions; the first represents overall acceptance, taste, and color while the second is related to flavor and texture attributes. The preference map can be used in product optimization and development.

Natural Fibre Composites (NFC) are eco-friendly, sustainable alternatives to synthetic polymers. However, some intrinsic natural fillers´ properties hinder their widespread implementation as re-inforcement in polymeric matrices and require further investigation. In the scope of this study, the thermal, rheologic, mechanical (tension and flexural modes), morphological properties, water ab-sorption and dimensional stability of the NF polypropylene (PP) based injection moulded compo-sites with the rice husk (rh) and olive pits (op) of 20 wt% and 30% wt%, were investigated. The results suggest that the higher content of the rice husk and olive pits led to a similar reduction of the Melt Flow Index (MFI), independent of the additive type compared to virgin polypropylene (PPv). The melting and crystallization temperatures of the PPrh and PPop composites did not change with statistical significance. The composites are stiffer than the PP matrix by up to 49% and possess higher mechanical strength in what concerns the tension mode at the expense of de-creased ductility. PPrh and PPop have superior flexural modulus in the bending mode, while the flexural strength improvement was accomplished for the PP30%rh. The dimensional stability of the composites was improved as the linear shrinkage in the flow direction was decreased by 49% for PPrh and 30% for PPop, positively correlating with an increase in the filler content and stiff-ness. PPop was less susceptible to water sorption than PPrh due to fibres' composition and larger surface-to-area volume ratios.

Disease detection and prediction have been one of the most frequent uses of machine learning models in the last decade, and Parkinson's disease is no exception. It is common for people in their old age to have one form of disease or another depending on the circumstances in which they find themselves. This study analyzed and evaluated various supervised machine learning models to detect the presence of Parkinson's disease in elderly individuals. An extreme gradient boosting model, along with other models, such as naïve Bayes, random forest, K-nearest neighbor, and support vector machine (SVM), was implemented to determine the best outcome. The extreme gradient boosting (XGBoost) model is a powerful boosting machine learning technique, particularly in terms of speed and accuracy. The results showed that the XGBoost model, which is an optimized version of the other boosting models, is capable of projecting the presence of Parkinson's disease with very high accuracy compared to other algorithms. The implemented classification algorithm extreme gradient boosting method achieved approximately 98 % accuracy, 97.5 % precision, 100.0 % recall, and 98.7% f1-score which are high compared with the results found in the existing literature.

This work is the result of a two-year research leave (French CNRS delegation) with field research in France, India and England, based on a total of 36 interviews in the three countries. The aim of this publication is to discuss how the laws of different countries deal with gender and what representations the laws reveal about gender roles in the societies they regulate through discourses. For example, France, England and India have laws that are more or less specific about gender roles in society: the language used to express the laws also fulfils gender roles while affecting people’s everyday lives. The whole issue of gender and rights is about the presumed and desired equality of rights for women and men, and the way in which this corresponds to the reality of women’s and men’s lives. Indeed, laws are necessary to regulate human relations in society. For example, anti-discrimination laws exist to protect and regulate these relationships in a common space, to regulate and combat abuse. The emphasis on gender – including gender roles – and LGBTQ+ people shows that this phenomenon is understood and experienced differently in global practice. Our examples in this publication focus on France and India.

Numerous types of oligonucleotide modifications have been developed since automated synthesis of DNA/RNA became a common instrument in the creation of synthetic oligonucleotides. Despite the growing number of types of oligonucleotide modifications under development, only a few of them, and moreover, their combinations have been studied wide enough in terms of their in-fluence on the properties of corresponding NA constructions. In the present study, a number of oligonucleotides with combinations of 3′ end lipophilic (single cholesteryl or pair of dodecyl residues) and phosphate backbone modifications were synthesized. The influence of the combi-nation of used lipophilic groups with phosphate modifications of various nature and different position on the efficiency of cell penetration was evaluated. Obtained results indicate that even a couple of phosphate modifications are able to affect a set of oligonucleotide properties in a complex manner and can remarkably change cellular uptake. These data clearly show that the strategy of using different patterns of modification combinations has great potential for the ra-tional design of oligonucleotide structures with desired predefined properties.

Triphenylphosphonium (TPP) derivatives of a decapeptide related to sequences of bactenecin 7 (Bac7) and oncocin (Onc112) were synthesized and studied as potential antimicrobial compounds using various biochemical and microbiological assays. It was shown that while the reduction of the Bac7 length to 10 a.a. residues dramatically decreases the affinity to bacterial ribosomes, the modification of peptide with alkyl-TPP moieties leads to an increase in the affinity. New analogs which structure combines a decapeptide related to Bac7 and Onc112 — Bac(1-10, R/Y) — and TPP, attached to the C-terminal amino acid residue through alkylamide linkers, inhibit translation in vitro and are found to be more selective inhibitors of bacterial translation as compared with eukaryotic translation, than Onc112 and Bac7. Triphenylphosphonium analogs of a decapeptide related to Bac7 and Onc112 suppress the growth of both gram-negative bacteria, similar to Onc112 and Bac7, and gram-positive ones as alkyl-TPP derivatives, and also act against some resistant laboratory strains. Bac(1-10, R/Y)-C2-TPP, containing a short alkylamide linker between the decapeptide and TPP, is transferred into the E. coli cells via the SbmA transporter protein. TPP derivatives of the decapeptide Bac(1-10, R/Y) containing either decylamide or ethylamide linker cause B. subtilis membrane depolarization, similar to alkyl-TPP. The Bac(1-10, R/Y)-C2-TPP analog is proved to be non-toxic for mammalian cells by MTT-test.

Thirty-six healthy 21-day-old weaned ternary piglets (Duroc × Landrace × Yorkshire) were randomly divided into 2 treatments with 18 replicates per treatment and 1 pig per replicate. The control group was fed with basal diet and the test group was fed with diets supplemented with 1 kg/t tea residue. The test period was 28 days. The results are as follows: The addition of tea residue in the diet has no significant effect on the growth performance of weaned piglets (P > 0.05), but it could significantly reduce the diarrhea rate of piglets from 1 to 7 days and 1 to 28 days (P < 0.05). Compared with the control group, the dietary supplementation of tea residue had no significant effect on nutrient apparent digestibility, plasma biochemical indexes and plasma immune indexes (P > 0.05), but increased the content of glutathione in plasma (P < 0.05). Tea residue had no significant effect on the morphology of jejunum and ileum of piglets (P > 0.05), but it could significantly reduce the content of chloride ion in feces (P < 0.05). Compared with the basal diet group, there was no significant difference in the relative expression of TMEM16A and CFTR mRNA in the colon of weaned piglets (P > 0.05). The whole-cell patch clamp recording showed that the TMEM16A and CFTR ion channels could be activated by ionomycin and forskolin, respectively. However, when the HT-29 cells transfected with TMEM16A and CFTR channels were treated with tea residue extract, it could significantly inhibit the chloride current of the TMEM16A and CFTR ion channels (P < 0.05).

Anthracnose, caused by the fungus Colletotrichum lindemuthianum, poses a significant and widespread threat to the common bean crop. The use of plant genetic resistance has proven to be the most effective strategy for managing anthracnose disease. The Amendoim Cavalo (AC) Andean cultivar has resistance against multiple races of C. lindemuthianum, which is conferred by the Co-AC gene. Fine mapping of this resistance gene to common bean chromosome Pv01 enabled the identification of Phvul.001G244300, Phvul.001G244400, and Phvul.001G244500 candidate genes for further validation. In this study, we assessed the relative expression of Co-AC candidate genes, as well as other putative genes in vicinity of this locus and known resistance genes, in the AC cultivar following inoculation with the race 73 of C. lindemuthianum. Gene expression analysis revealed significantly higher expression levels of Phvul.001G244500. Notably, Phvul.001G244500 encodes a putative Basic Helix-Loop-Helix transcription factor, suggesting its involvement in the regulation of defense responses. Furthermore, we observed a significant modulation of the expression of defense related genes PR1a, PR1b, and PR2, in a time-course experiment. These findings contribute to the development of improved strategies for breeding anthracnose-resistant common bean cultivars, thereby mitigating the impact of this pathogen on crop yields and ensuring sustainable bean production.

Background: While outcomes of chronic phase chronic myeloid leukemia (CP-CML) patients aged over 65 years have been extensively evaluated in real-life experiences, limited data exist for the very elderly population (i.e., aged ≥ 75 years), especially for next-generation tyrosine kinase inhibitors (TKIs). In this retrospective study, we sought to evaluate the safety and efficacy of TKIs in this particular setting of patients. Methods: We conducted a retrospective analysis of a multicenter cohort of 123 newly diagnosed CP-CML very elderly patients. Results: The median age at diagnosis was 80 years (range: 75-96). In the first-line, 86.1% of patients received imatinib, 7.1% dasatinib, 5.6% nilotinib, and 0.81% received bosutinib. A total of 31 patients (25.2%) switched to second-line therapy, nine patients to a third-line and one patient to a fourth line of therapy. Resistance to treatment was the primary reason for switching therapy in both the first (64.5%) and second lines (77.7%). At diagnosis, reduced doses were administered in 36.5% of patients, in 61.2% in the second line, and in all patients in subsequent lines of therapy. In first-line setting, 71.9% of patients achieved an early molecular response (EMR, i.e. 3-month BCR::ABL1 IS <10%); at 6, 12, and 24 months, MR3 was reached by 35.7%, 55.7%, and 75.0% of patients, with 16.6%, 35.7%, and 51.7% achieving DMR at the same timepoints. Treatment-free remission (TFR) was successfully attempted in 11 patients. During the follow-up period, adverse events (AEs) were observed in 78.8% of patients, including 22 cases of cardiovascular AEs. Toxicity grade ≥ 3 was more commonly observed in patients treated with standard doses of TKIs compared to reduced doses (p=0.033). Overall, median follow-up was 46.62 months (range: 1.8-206.2), and 43 patients died due to non CML related causes. Three patients died due to disease progression to advanced (n=1) and blastic (n=2) phases. The 5-year overall survival (OS) for the entire cohort was 71.9% (95% CI: 0.63-0.81), with no significant difference between patients treated with standard doses of TKI compared to those treated with reduced doses (p=0.35). Conclusions: TKIs appear to be safe and effective even in very elderly CML patients, and dose optimization strategies yield satisfactory molecular responses for adequate disease control with an improved safety profile.

Hungary's first national park was created in 1973 in the Hortobágy area to protect Europe's largest contiguous steppe area with its flora and fauna. The Hortobágy National Park - the Puszta was inscribed on the UNESCO World Heritage List as a cultural landscape in 1999. The park's outstanding importance is due to the predominantly non-arboreal steppe vegetation, home to a unique bird fauna, and the alkaline and chernozem soils with a complex, mosaic-like spatial structure. In addition, the landscape of the Hortobágy has a pastoral history stretching back thousands of years. Several hypotheses have been put forward, which suggest that the alkaline soils and the habitats that cover them were formed as a result of human activities related to river regulation that began in the second half of the 19th century. However, palaeoecological and palaeobiological studies over the last 30-40 years have pointed to the natural origin of the alkaline steppes, dating back to the end of the Ice Age. For thousands of years human activities, in particular grazing by domestic animals, hardly influenced the natural evolution of the area. Drainage of marshy and flooded areas began in the 19th century, and the introduction of more and more intensive agriculture, had a significant impact on the landscape. This paper aims to describe the past natural development of this special alkaline steppe ecosystem, with particular reference to the impacts of past and present human activities, including conservation measures.

Climate change is affecting the planet, compromising survival and altering forest ecosystems. Investigating climatic variations in all regions is important. The aim of this research was to assess such variations in the W and Pendjari Biosphere Reserves in Benin from 1985 to 2015 and predict climate up to 2045. Drought frequency was assessed by using the Standardized Precipitation and Evapotranspiration Index (SPEI) and correlation was performed between climatic variables. Then a predictive analysis was computed. From 1985 to 2015, there was change in the climate with few severe dry and wet years while no extreme climatic condition was noticed. Most of the years showed nearly normal climatic conditions. The predicted climate indicates an absence of extreme conditions up to 2045 but an increase in the annual humidity is expected. A low decrease in annual mean temperature with high confidence is expected. Decision-makers can better organize adaptation programs and sensitize people in the reserves on their role in environmental conservation and mitigation of climate change using these outputs.

Container crane has been widely used for port operation. However, the structure of port container crane is large, which always lead to crane damage under the vibration and strong wind. Therefore, a method for vibration reduction of container crane structure based on particle damping technology is proposed. In this investigation, the scale 1:80 crane model is built, the equivalent mechanical model is also established to preliminary verify the effect of vibration suppression. Furthermore, the dependence of vibration suppression effect on the key parameters of the damper, i.e., filling material, filling rate, particle size, and installation position of dampers are analyzed through experiments. The results indicate that the vibration peak of the crane structure displayed in Simulink oscilloscope is weakened and lags behind, the installation of the damper brings the effect of vibration suppression for the crane, the vibration suppression effect reaches 25%; the crane mode obtains the best vibration suppression effect under the condition that the material filled in the damper has a large density and elastic modulus, sufficient collision space and high collision frequency, and the dampers are installed far away from the crane center of gravity. The optimum parameters of the damper obtained from experiments, 12 mm lead beads, filling rate of 60%, installed in the distal ends within the strength range of the forearm of the crane. It is thus concluded that the particle damping technology has provided an effective way in wind and vibration reduction for container crane.

As the lifespan of porous asphalt pavement extends, it invariably experiences performance degradation and an increase in tire/pavement noise compared with the original surface when it is newly built. To understand the medium-term performance of porous asphalt pavement during service and reveal the influence of different pavement performance indicators on tire/pavement noise generation, a seven-year continuous observation and data analysis study was conducted. Porous asphalt with different designed material parameters was taken into account, including thin-layer porous asphalt overlay with a maximum nominal aggregate size of 10mm (PUC-10), porous asphalt with a maximum nominal aggregate size of 13mm (PAC-13), and a two-layer porous asphalt incorporating both PUC-10 and PAC-13 (PUC-10+PAC-13). Using automated pavement technology testing equipment, key performance indexes, including damage rate (DR), rut depth (RD), international roughness index (IRI), and sideway force coefficient (SFC), were measured and calculated. The on-board sound intensity (OBSI) method was used to test noise levels in three types of porous asphalt pavement structures and on a dense graded easy compact asphalt concrete (ECA) for comparison. The progressions of the medium-term performances were analyzed according to the measured results. The correlations between tire/pavement noise levels and testing speed, testing lane, pavement structure, and road condition indicators were investigated by regression. The research results revealed that the DR and SFC of the three types of porous asphalt pavement displayed more significant attenuation in the service period, while the IRI and RD showed small changes. Among them, the SFC demonstrated significant attenuation over the first 4 years, decreasing between 13.8% and 17.0%. From the 3-7 years of operation, the transverse crack disease in porous asphalt pavement progressed rapidly. The three porous asphalt pavement structures tested exhibited commendable noise reduction capabilities. Compared to ECA, the OBSI noise levels of these structures were lower by 2.09 dB, 1.53 dB, and 2.88 dB, respectively. Compared to other pavement condition indicators, RD had a more significant impact on the OBSI value of the PUC-10 porous asphalt pavement. For the PUC-10+PAC-13 porous asphalt pavement, there was a significant linear relationship between the OBSI value and SFC, mainly due to polishing of the coarse aggregate surface. It leads to a decrease of the micro-texture, which lies in increasing tire/pavement noise at high-frequency ranges and decreasing SFC. This study will have guiding significance for the research of the attenuated law and durability improvement of porous asphalt tire/pavement noise.

Fluorescent labels, especially FRET probes, are promising tools for studying a number of bio-chemical processes. In this paper, we promoted 2 important applications of FRET probes (MUTMAC-R6G and FITC-R6G): i) the formation of micelles from surfactants of various natures and polymers (chitosan – fatty acid), as well as ii) monitoring of enzymatic activity with improved parameters (increased analytical signal and improved selectivity due to shift to the long-wavelength region). The formation of micelles is accompanied by the convergence of fluorophores in the hydrophobic micelle core by a distance closer than in the buffer solution, thus r/R0 (where R0 – Foerster radius) is chosen as an analytical signal of micelle formation, including critical micelle concentration (CMC) and critical pre-micelle concentration (CPMC). The CMC values calculated using FRET probes are in a good agreement with literature data. At the same time, the r/R0 function provides valuable information about the nature and mechanism of micelle formation. With the second analytical application of FRET probes, we considered the optimization of techniques for studying enzymatic activity. The enzyme catalyses the reaction with the release of a fluorescent product, the signal from which may not be enough for detection, or it may be quenched, for example, in the reverse micelles (AOT-octane). Here we have proposed a solution – a FRET probe containing a rhodamine 6G (R6G) acceptor, which allows us to monitor the enzymatic reaction selectively (in the red region, 550-600 nm), and obtain a significantly higher fluorescence yield (potentially from 10 to 250 times). Thus, we have demonstrated a high potential for the FRET probes application as indicators of micelle formation as well as for the study of the enzyme catalytic activity. In the future, the method developed has prospects for application in the visualization of the enzyme functioning in cells due to the shift of the fluorescence signal to the long-wavelength region with an increase in the signal selectivity to suppress autofluorescence.

A cell-surface ectonucleotidase CD39 mediates the conversion of extracellular ATP into immunosuppressive adenosine with another ectonucleotidase CD73. The elevated adenosine in the tumor microenvironment (TME) attenuates antitumor immunity, which promotes tumor cell immunologic escape and progression. Anti-CD39 monoclonal antibodies (mAbs), which suppress the enzymatic activity, can be applied to antitumor therapy. Therefore, an understanding of the relationship between the inhibitory activity and epitope of mAbs is important. We previously established an anti-mouse CD39 (mCD39) mAb, C₃₉Mab-1 using the Cell-Based Immunization and Screening (CBIS) method. In this study, we determined the critical epitope of C₃₉Mab-1 using flow cytometry. We performed the PA tag (12 amino acids)-substituted analysis (named PA scanning) and RIEDL tag (5 amino acids)-substituted analysis (named RIEDL scanning) to determine the critical epitope of C₃₉Mab-1 using flow cytometry. By the combination of PA scanning and RIEDL scanning, we identified the conformational epitope, spanning three segments of 275^th to 279^th, 282^nd to 291^st, and 306^th to 323^rd amino acids of mCD39. These analyses would contribute to the identification of the conformational epitope of membrane proteins.

How crucial is big data in contemporary molecular design? In this publication we elucidate fundamental concepts and terminology in this field, critically addressing overlooked issues. We thoroughly examine the size, accessibility, quality, and structural aspects of big data alongside the primary methodologies employed for their analysis. Within chemical compounds, properties and descriptors represent two distinct data types, forming the basis for categorizing molecular big data. The primary objective of chemistry is property production, which means we are searching for novel drugs or materials rather than chemical compounds, and big data is the central issue of this philosophy. The increasing availability of data in computer-aided technology propels advancements in artificial intelligence (AI), machine learning (ML), and deep learning (DL). Accordingly, a broad chemical audience must comprehend these methods to understand data-centered chemistry. Thus, we aim to systemize big data issues through a simple illustrative framework with fundamental descriptor categories: coding, computer-generated descriptors, and property correlates. Although we employ computer-generated descriptors as big data for predictions, the measured data are irreplaceable for achieving high-quality and reliable outcomes and controlling molecular effects. The scarcity of property data remains a significant hurdle limiting comprehensive studies on the structure-property relationships within big data. Accordingly, guided by pragmatics not-so-big data is an option for drug design. We presented also a brief review of the recent big data literature.