Molnupiravir, a prodrug known for its broad antiviral activity, demonstrated efficacy in animal models of Covid-19, prompting clinical trials where initial results indicated a significant effect against the disease. However, subsequent clinical studies did not confirm these findings, leading to the rejection of molnupiravir for permanent market authorization in many countries. This report critically assessed 19 studies published in 17 reports that investigated the efficacy of molnupiravir in animal models of Covid-19 with the purpose of determining how well the design of these models informed human studies. We found that the administered doses of molnupiravir in most studies involving animal Covid-19 models were disproportionately higher than the dose rec-ommended for human use. Specifically, when adjusted for body surface area, half of the doses of molnupiravir used in the animal studies were more than twice as high as the human dose. Addi-tionally, the drug was frequently given prophylactically or shortly after SARS-CoV-2 inoculation in these models, in contrast to clinical trials where such timing is not consistently achieved. Furthermore, the recommended five-day treatment duration for humans was exceeded in several animal studies. Collectively, we suggest that these design elements in the reported animal studies contributed to a bias favoring molnupiravir, and thus inflated expectations for its efficacy against Covid-19. Addressing these elements may offer avenues to enhance the clinical efficacy of mol-nupiravir for treatment of Covid-19 that include dose increment, early treatment, and admin-istration by inhalation along with use of molnupiravir in antiviral combination therapy.

The objective of this study is to investigate the effect of the premixed ethanol ratio based on the same total heating value in-cylinder on the equivalence ratio distributions and the injected fuel droplet behavior in the cylinder of the RCCI engine. The spray simulation was conducted by dividing two-part. First, the spray validation simulations progressed to find the spray-influenced factor of the test injector. Next, the engine simulations were performed with the spray-influenced factor obtained from spray validation simulations to investigate the effect of the premixed ethanol ratio based on the same total heating value in-cylinder on the injected fuel atomization and the equivalence ratio distributions. The introduced total heating value was fixed at 595J based on the lower heating value of diesel 14mg. The heating value of the premixed ethanol ratio varied from 0% to 40% based on the same total heating value in-cylinder in steps of 10%. It was revealed that when the premixed ethanol ratio based on the same total heating value in-cylinder was increased, the spray tip penetration value was reduced from the time after 4deg of diesel injection start because of the short injection duration by the small amount of diesel fuel. The SMD value was also more enormous up to 32.58% with increasing the premixed ethanol ratio because of the low kinetic energy of the injected fuel by the short injection duration and the slow evaporation of the injected fuel by the low cylinder temperature.

Solvents are widely-used in all aspects of chemical sciences. One of the disadvantages of conventional solvents is attributed to the adverse impacts they pose on human health and ecological systems. Emerging class of solvents such as ionic liquids have been proposed to alleviate this problem. In this study, aquatic toxicity and biodegradability of two common industrial solvents are compared to those of two ionic liquids. Results from this study highlight the importance of solvent selection considering the information on the toxicity, biodegradability and fate and transport properties of selected solvents altogether.

Rett syndrome (RTT) is an X-linked neurodevelopment disorder associated with the single monogenic mutation in methyl-CpG binding protein 2 (MeCP2) in up to 95% of cases. The growing number of genome-wide association studies and incomplete concordance for autoimmune diseases in monozygotic twins concur to support the involvement of environmental factors, like infectious agents or chemicals, in the breakdown of tolerance leading to autoimmunity. In fact, the coexistence of a perturbation of the immune system in RTT patients has been previously hypothesized. We herein explored the hypothesis that an autoimmune component derived from environmental bacterial infection of non typeable Haemophilus influenzae may coexist in RTT. At this purpose we screened sera from RTT syndrome patients, non-RTT pervasive developmental disorders patients and healthy controls with the hyperglucosylated adhesin protein HMW1ct(Glc) used as a precise antigen in ELISA in order to identify specific antibodies to N-glucosylation sites. Results showed that HMW1ct(Glc) is able to significantly discriminate antibodies among RTT sera and controls. Competitive ELISA confirmed the specific interaction between antibodies characteristic of RTT syndrome and the N-glucosylation motifs of the bacterial adhesin protein HMW1ct(Glc).

The emergence of drug-resistant mycobacteria has rendered many clinical drugs and regimens ineffective, imposing significant economic and healthcare burden on individuals and society. Repurposing drugs intended for treating other diseases is a time-saving, cost-effective, and efficient approach for identifying excellent anti-mycobacterial candidates or lead compounds. This study is the first to demonstrate that rupatadine (RTD), a drug used to treat allergic rhinitis, possesses excellent activity against mycobacteria without detectable resistance, particularly Mycobacterium tuberculosis and Mycobacterium marinum, with a minimal inhibitory concentration as low as 3.13 µg/mL. Furthermore, RTD exhibited moderate activity against nonreplicating M. tuberculosis with the minimal inhibitory concentrations lower than drugs targeting the cell wall, suggesting that RTD has the great potential to be modified and used for the treatment of nonreplicating M. tuberculosis. Additionally, RTD exhibits partial synergistic effects when combined with clofazimine, pretomanid, and TB47 against M. tuberculosis, providing the theoretical foundation for the development of treatment regimens. Transcriptomic profiling leads us to speculate that eight essential genes may be the targets of RTD or may be closely associated with the mycobacterial resistance to RTD. In summary, RTD may be a promising hit for further anti-mycobacterial drug or regimen optimization, especially in case of nonreplicating mycobacteria.

Increased anthropogenic pressure on forest resources leads to deforestation and forest degradation, significantly limiting the regeneration capacity of native woody species and consequently the restoration of miombo woodlands in anthropized habitats within the rural area of Lubumbashi. This study assessed the diversity and natural regeneration capacity of miombo species through floristic inventories in three different habitats (unexploited forests, degraded forests, and post-cultivation fallows). The results reveal that for the adult’s stratum unexploited and degraded forests exhibit higher dendrometric (density, mean square diameter, basal area) and floristic parameter (taxa, genera, families) values compared to post-cultivation fallows. Furthermore, the regeneration of miombo woody species is higher in degraded forests (21 taxa; 105 juveniles/plot). However, regarding the sapling’s stratum (1 cm ≤ dbh < 10 cm), the three habitats display nearly similar situations. Additionally, the floristic composition and diversity of unexploited and degraded forests show a significantly higher similarity (76.50%) among them compared to these habitats and the post-cultivation fallows (56.00%). These findings indicate that miombo woodlands have the potential to regenerate and maintain floristic diversity. To sustain this natural regeneration capacity of miombo woody species and promote the restoration of forest mass and its floristic diversity, it is imperative to determine the rotation period after habitat exploitation and regulate anthropogenic activities and late bush fires, particularly in anthropized habitats at the village level.

Timely and accurate acquisition of information on distribution of the crop planting structure in Loess Plateau of eastern Gansu Province, one of the most important agricultural areas in western China, is crucial for promoting fine management of agriculture and ensuring food security. In this study, the Object-Based Image Classification (OBIC), the Random Forest (RF) and Convolutional Neural Network (CNN) models were employed to classify the crop planting structure of four representative test areas in Qingyang City in a precise manner. Firstly, different optimal segmentation scales for various crops were selected using the Estimation of Scale Parameter 2 (ESP2) tool and the Ratio of Mean Difference to Neighbors(ABS) to Standard Deviation (RMAS)model. The images were then segmented through multiresolution segmentation combined with the Canny Edge Detection algorithm. Secondly, the L1 regularized logistic regression model was utilized to select and optimize 39 spatial feature factors including spectral, textural, geometric, and index features, in conjunction with phenological factors. Lastly, under the multi-level classification framework, the Random Forest (RF) classifier and Convolutional Neural Network (CNN) model, combined with object-based multiresolution segmentation, was used to classify the crop planting structure. The findings show that: Thanks to the Canny Edge Detection algorithm, we can obtain a more complete boundary of the segmented objects and improve the separability. The optimal segmentation scales for corn, vegetables, and buckwheat were found to be 55, 70, and 35, respectively, while wheat and apple had optimal segmentation scales of 65. In addition to phenological characteristics, the number of selected spatial features for corn, vegetables, buckwheat, wheat, and apple were 9, 7, 16, 12, and 10, respectively. The CNN model demonstrated high consistency with the RF model in the classification results, but the accuracy of RF model is higher than that of CNN model on the whole. The overall accuracy of classification using RF model in four test areas registered 91.93%, 94.92%, 89.37% and 90.68%, respectively. This paper introduced crop phenological factors, effectively improving the extraction precision of shattered agricultural planting structure in the Loess Plateau of eastern Gansu Province. Its findings have important application value in crop monitoring, management, food security and other related fields.

The presence of anti SARS-CoV2-RBD antibody (Anti-RBD) prevents severe COVID-19. We aimed to determine the accuracy of a point-of-care Anti-RBD test implemented in person living with HIV (PLWH), systemic lupus erythematosus (SLE), and chronic kidney disease (CKD). We enrolled 182 non-comorbid subjects and 335 persons with comorbid (PLWH, SLE, CKD) to test anti-RBD assay compared to surrogate viral neutralization (SVNT) as the reference test. We performed linear correlation analysis between anti-RBD vs SVNT and a ROC analyses to ascertain anti-RBD cut-off at 30%, 60%, and 90% inhibition of SVNT to calculate accuracy. Correlations of anti-RBD to SVNT among all groups were excellent with R= 0.7903, R=0.7843, R=0.8153 among non-comorbid, SLE and CKD groups, respectively, with significantly higher correlation among the PLWH group (R=0.8877; p-value=0.0072) compared to non-comorbid group. The accuracy of the anti-RBD test among PLWH and CKD group was similar with the non-comorbid but showed lower sensitivity in the SLE group (p=0.000014). The specificity of the test remained high in all groups. In conclusion, the Anti-RBD test had excellent correlation to SVNT. The persistently high specificity in all groups suggests that this test can be reliably utilized to detect presence of low neutralization capacity, prompting additional vaccination.

Introduction. Intra-abdominal cystic formations represent heterogeneous pathologies with varied localization and clinical manifestation. The first challenge of a giant intra-abdominal cystic lesion is identifying the organ of origin. The clinical presentation of intra-abdominal cystic lesions varies from acute manifestations to non-specific symptoms or accidental discovery. Case presentation: A 2-year-old girl presents to the emergency unit with a fever of 38.5 Celsius, loss of appetite, and apathy. The investigations showed a gigantic intra-abdominal mass whose organ belonging could not be specified. Postoperatively, a giant mesenteric lymphangioma was evident, which was completely excised. Discussions Giant cystic formations modify the anatomical reports and become space-replacing formations, and the starting point is even more challenging to assess preoperatively. Nevertheless, the careful evaluation of the characteristics of the formation, the effect on the adjacent organs, the age of the patient, and the clinical picture can provide elements of differential diagnosis.

A new Mg-Zn-Zr-Ca alloy in powder state was obtained via mechanical alloying method, from pure elemental powder. Further, the obtained powder-alloy was processed by selective laser melting (SLM) procedure to obtain 3D printed samples for small biodegradable implants. A series of microstructural, mechanical and corrosion analysis were performed. The SEM analysis of powder-alloy reveal a good dimensional homogeneity, with uniform colored, no agglutinated and almost rounded particles, suitable for selective laser melting procedure. Further, the SLM samples reveal a robust and unbreakable morphology, with a suitable porosity and without undesirable balling effect. The tested Young’s modulus of the SLM samples, of 42 GPa, is close to cortical bone one, of 30 GPa. The corrosion tests performed in PBS (Phosphate-buffered saline) solution show that the corrosion parameters have a satisfactory evolution.

This study outlines the development of an innovative method utilizing UHPLC-PDA for the simultaneous identification of polyphenols and bitter acids (alpha-acids, beta-acids, and iso-alpha-acids) in beer samples. The resulting chemical profiles were leveraged to distinguish the characteristics of four bergamot-flavored beers, each representing distinct styles (IPA, Lager, Blanche, and ALE), produced on a pilot-scale plant. In a streamlined 29-minute analysis, twenty-nine polyphenols and fourteen bitter acids were successfully identified under optimized separation conditions. Rigorous validation, encompassing parameters such as Limit of Detection (LOD), Limit of Quantification (LOQ), R-squared (R2), repeatability, and reproducibility, was conducted for polyphenol quantification using constructed calibration curves with seven levels. Exploring polyphenolic components as potential discriminators among different beer styles, a total of thirty-two polyphenolic compounds were identified and quantified, including characteristic bergamot peel polyphenols like neoeriocitrin, naringin, and neohesperidin. The determination of bitter units and total phenols further aided in style differentiation. Multivariate analysis provided additional insights into variations among specific beer styles, revealing discrepancies in the presence or relative concentrations of specific compounds linked to brewing ingredients and processes. This research enhances to trace the fingerprinting of the chemistry governing beer quality through a straightforward and cost-effective analytical approach, readily applicable in common laboratories.

The literature offers limited information on the effect of obesity on the rate of force development, a critical parameter for mobility in older adults. The objectives of this study were; to explore the influence of obesity on RFD in older adults and to examine the association between this neuromuscular parameter and walking speed. 42 older adults were classified into two groups: the control group (CG, n=22; age=81.13±4.02 years; Body mass index (BMI)=25.13±3.35 kg/m²), and the obese group (OG, n=20; age=77.71±2.95 years; BMI=34.46±3.25 kg/m²). Walking speed (m/s) was measured using the 10-meter walking test. Neuromuscular parameters of the plantar flexors were evaluated during a maximal voluntary contraction test using a dynamometer. The RFD was calculated from the linear slop of the force – time curve in two phases: from the onset of the contraction to 50 ms (RFD50-100) and from 100 to 200 ms (RFD100-200). The gait speed was lower in the OG compared to the CG (p

A reduction in population sodium (as salt) consumption is one of the most cost-effective strategies to reduce the burden of cardiovascular disease and it is a global health priority. High potassium intake is also recommended to reduce cardiovascular disease. To establish effective policies for setting targets and monitoring effectiveness within each country, the current level of consumption should be known. Greece lacks data on actual sodium and potassium intakes. The aim of the present study was therefore to assess dietary salt (using sodium as biomarker) and potassium intakes in a sample of healthy adults in northern Greece and to determine whether adherence to a Mediterranean diet is related to different sodium intakes or sodium-to-potassium ratio. A cross-sectional survey was carried out in Thessaloniki greater metropolitan area (northern Greece) (n=252, aged 18-75 years, 45.2% males). Participants’ dietary sodium and potassium intakes were determined by 24h urinary sodium and potassium excretions. In addition, we estimated their adherence to Mediterranean diet by the use of an 11-item MedDietScore (range 0-55). The mean sodium excretion was 175 (SD 72) mmol/day, equivalent to 4,220 (1,745) mg of sodium or 10.7 (4.4) g of salt per day and potassium excretion was 65 (25) mmol/day, equivalent to 3,303 (1,247) mg/day. Men had higher sodium and potassium excretions compared to women. Only 5.6% of the sample had salt intake <5g/d, which is the target intake recommended by the WHO. Mean sodium-to-potassium excretion ratio was 2.82 (1.07). There was no significant difference in salt or potassium intake or their ratio across MedDietScore quartiles. No significant relationships were found between salt intake and adherence to Mediterranean diet, suggesting that the perception of the health benefits of the Mediterranean diet does not hold when referring to salt consumption. These results suggest the need for a larger nation-wide survey on salt intake in Greece and underline the importance of continuation of salt reduction initiatives in Greece.

The stromal vascular cell fraction (SVF) of visceral and subcutaneous adipose tissue (VAT and SAT) has increasingly come into focus in stem cell research, since these compartments represent a rich source of multipotent adipose-derived stem cells (ASCs). ASCs exhibit a self- renewal potential and differentiation capacity. Our aim was to study the different expression of embryonic stem cell markers NANOG, SOX2 and OCT3/4 and to evaluate if there exists a hierarchal role in this network in ASCs derived from both SAT and VAT. ASCs were isolated from SAT and VAT biopsies of 72 consenting patients (23 men, 47 women; age 45 ± 10; BMI between 25 and 30 range) undergoing elective open-abdominal surgery. Sphere-forming capability was evaluated by plating cells in low adhesion plastic. Stem cell markers CD90 and CD105 were analyzed by flow cytometry and stem cell transcription factors NANOG, SOX2 and OCT3/4 were detected by immunoblotting and Real-Time PCR. NANOG, SOX2 and OCT3/4 interplay was explored by gene silencing. ASCs from VAT and SAT confirmed their mesenchymal stem cell (MSC) phenotype expressing the specific MSC markers CD90, CD105, NANOG, SOX2 and OCT3/4. NANOG silencing induced a significant OCT 3/4 (70% ± 0.05) and SOX2 (75% ± 0.03) down-regulation whereas SOX2 silencing did not affect NANOG gene expression. Adipose tissue is an important source of MSC, and siRNA experiments endorse a hierarchical role of NANOG in the complex transcription network that regulates pluripotency and plasticity.

Colorectal cancer (CRC) remains a major global health issue. Although chemotherapy is the first-line treatment, its effectiveness is limited due to drug resistance developed in CRC. To overcome resistance and improve the prognosis of CRC patients, investigation for new therapeutic approaches is necessary. Using human colorectal adenocarcinoma (HT29) and metastatic CRC (SW620) cell lines, the potential anticancer properties of a newly synthesized compound 1-(Isobutyl)-3-(4-methylbenzyl) benzimidazolium chloride (IMBZC) were evaluated by performing MTT cytotoxicity, cell migration, and colony formation assays, as well as by monitoring apoptosis-related protein and gene expression using Western blot and reverse transcription-quantitative polymerase chain reaction technologies. Tested at various concentrations, the half-maximal inhibitory concentrations (IC50) of IMBZC on HT29 and SW620 cell growth were determined to be 6.97 μg/mL and 4.89 μg/mL, respectively. IMBZC did not alter cell growth of normal cells HEK293. In addition, IMBZC inhibited cell migration and significantly decreased colony formation, suggesting its promising role in suppressing cancer metastasis. Mechanistic analyzes revealed that IMBZC treatment increased the expression of pro-apoptotic proteins p53 and Bax, while decreasing the expression of anti-apoptotic proteins Bcl-2 and Bcl-xL, thus indicating the induction of apoptosis in IMBZC-treated CRC cells, compared to untreated cells. Additionally, the addition of IMBZC to conventional chemotherapeutic drugs (i.e., 5-fluorouracil, irinotecan, and oxaliplatin) resulted in an increase in the cytotoxic potential of the drugs. In conclusion, the study suggests that IMBZC has substantial anticancer effects against CRC cells through its ability to induce apoptosis, inhibit cancer cell migration and colony formation, and enhance the cytotoxic effects of conventional chemotherapeutic drugs. These findings indicate that IMBZC could be a promising chemotherapeutic drug for the treatment of CRC. Further research should be conducted using in vivo models to confirm the anti-CRC activities of IMBZC.

The detection and recognition of tables in image-based documents is a challenging and essential task for automated data extraction and anal- ysis. This paper introduces a methodology that utilizes Convolutional Neural Networks (CNNs) to address this problem. By harnessing the ro- bust visual recognition abilities of CNNs, the proposed method effectively detects and extracts tables from image-based documents. Additionally, an Encoder-Dual Decoder (EDD) architecture is employed to extract the textual content from table cells, enabling the transformation of visual data into structured, machine-readable formats. This structured data is then further processed using a Vector Space Model (VSM)-based language modeling technique for query-based table retrieval. The methodology’s accuracy is assessed by analyzing the spatial relationships between the extracted cells and comparing them against a pre-defined table structure. The results provide an evidence to the effectiveness of the proposed ap- proach, with an impressive 85% accuracy rate and a corresponding error rate of 15%. This accurate extraction and recognition of tables from image-based documents can significantly enhance applications in data analysis, information retrieval, and knowledge extraction.

X-ray absorption fine structure (XAFS) spectroscopy, temperature-programmed reduction (TPR) and temperature-programmed hydride decomposition (TPHD) were employed to elucidate the structures of a series of PdRe/Al2O3 bimetallic catalysts for selective hydrogenation of furfural. TPR evidenced low-temperature Re reduction in the bimetallic catalysts consistent with migration of [ReO4]- (perrhenate) species to hydrogen-covered Pd nanoparticles on highly hydroxylated  Al2O3. TPHD revealed strong suppression of β-PdHx formation in the reduced catalysts prepared by (i) co-impregnation and (ii) [HReO4] impregnation of reduced Pd/Al2O3 indicating formation of Pd-rich alloy nanoparticles; however, reduced catalysts prepared by (iii) [Pd(NH3)4]2+ impregnation of calcined Re/Al2O3 and subsequent re-calcination did not. Re LIII X-ray absorption edge shifts were used to determine average Re oxidation states after reduction at 400°C. XAFS spectroscopy and high-angle annular dark field (HAADF)-scanning transmission electron microscopy (STEM) revealed that a reduced 5 wt.% Re/Al2O3 catalyst contained small Re clusters and nanoparticles comprising Re atoms in low positive oxidation states (~1.5+) and incompletely reduced Re species (primarily Re4+). XAFS spectroscopy of the bimetallic catalysts evidenced Pd-Re bonding consistent with Pd-rich alloy formation. Pd and Re total first-shell coordination numbers suggest that either Re is segregated to the surface (and Pd to the core) of alloy nanoparticles and/or segregated Pd nanoparticles are larger than Re nanoparticles (or clusters). The Cowley short-range order parameters are strongly positive indicating a high degree of heterogeneity (clustering or segregation of metal atoms) in these bimetallic catalysts. Catalysts prepared using the Pd(NH3)4[ReO4]2 double complex salt (DCS) exhibit greater Pd-Re intermixing but remain heterogeneous on the atomic scale.

The aim of the current study has been to assess externalizing problems from a gender perspective in the juvenile population. This objective has been evaluated though the Child and Adolescent Assessment System questionnaire (SENA), to measure the dimension of externalized problems. A total of 128 Spanish students took part in the survey, comprising 58 (45.3%) male and 67 (52.3%) female, aged between 12 and 16 years old (M= 13,7; Sd= 1,14). The sample was taken from three High- Schools (state and private-subsidized) in Madrid, Spain. The research for this study was conducted through a descriptive, inferential, quantitative, ex post facto design. The data analysis was performed using SPSS 27.0. The result revealed an increase in externalized problems: Attention (M= 2.65, Sd=.88), Anger Control (M= 2.27, Sd=.85) and Hyperactivity- Impulsivity (M= 2.26, Sd=.68). In addition, female students score highly in Attention Problems (F= 4.124; Sig.: .004), Hyperactivity-Impulsivity (F: 6.18; Sig.: <.001), and Anger Control (F: 2.3; Sig.: .062). This study highlights the impact and increase on students externalized mental health problems currently. It is essential to have a protective environment and promote the development of emotional intelligence, encouraging the mental health in young people. This article is part of the findings of the research project “Therapeutic Innovation Classroom for the accompaniment of teenager with Serious Mental Disorder” (Reference: 2021V/EU-UNED/02).

Recent technological advancements in conservation genetics and genomics have resulted in diverse tools for aiding conservation of species. The precision and resolution of high throughput sequencing technologies provide valuable insights to aid conservation decisions, but these technologies are often financially unfeasible or unavailable in resource constrained countries. Inter-Simple Sequence Repeat (ISSR) markers, when combined with sensitive automated detection systems, provide a simple, cheap means to investigate genetic diversity and discriminate closely related species. Here we apply this technology to assess genetic diversity and taxonomic delimitation in the Encephalartos eugene-maraisii species complex, a highly threatened, taxonomically dubious group of cycads in South Africa. Our analyses support taxonomic singularity of E. dyerianus, E. dolomiticus and E. eugene-maraisii. Relationships between E. nubimontanus and E. cupidus remain uncertain. E. middelburgensis samples showed no clustering but had poor amplification success. This study demonstrates the suitability of automated ISSR fingerprinting as a method for plant conservation studies, especially in resource-constrained countries, and we make recommendations as to how this methodology can be effectively implemented.

The importance of Muscovy ducks in industrial poultry production is growing; however, little is known about the physiology of their reproductive cycles. This study investigated the influence of male biostimulation on female ducks before the commencement of the laying phase. A total of 15 female Muscovites were kept in contact with a male duck until the point of laying, while 15 other females were kept without any contact with a male conspecific. Before reaching egg-laying maturity, the cloacae of 29 adult ducks were subjected to daily clinical assessments. The evaluations yielded four unique categories of outcomes, determined by assessing factors such as the degree of redness and protrusion of the mucous membrane, moisture level, and swelling of the cloacal sphincter muscle. In terms of biostimulation, the findings demonstrated that, on average, ducks in contact with males laid the first egg 16 days earlier than isolated ducks. Furthermore, there was no significant difference observed in the mean initial egg weight between both groups (p = 0.841). The changes in the cloacal morphology indicated significant morphological changes 25–26 days before laying. Efforts to improve Muscovy production and develop biotechnological techniques to modify the reproductive cycle will benefit from these advancements.

The spread of micro- (MPs) and nanoplastics (NPs) in the environment has become a significant environmental concern, necessitating effective removal strategies. In this comprehensive scientific review, we examine the use of magnetic nanoparticles (MNPs) as a promising technology for the removal of MPs and NPs from water. We first describe the issue of MPs and NPs and their impact on the environment and human health. Then the fundamental principles of using MNPs for the removal of these pollutants will be presented, emphasizing that MNPs enable selective binding and separation of MPs and NPs from water sources. Furthermore, we provide a short summary of various types of MNPs that have proven effective in the removal of MPs and NPs. These include ferromagnetic nanoparticles, MNPs coated with organic polymers, as well as nanocomposites and magnetic nanostructures. We also review their properties, such as magnetic saturation, size, shape, surface functionalization and stability, and their influence on removal efficiency. Next, we describe different methods of utilizing MNPs for the removal of MPs and NPs. We discuss their advantages, limitations, and potential for further development in detail. In the final part of the review, we provide an overview of existing studies and results demonstrating the effectiveness of using MNPs for the removal of MPs and NPs from water. We also address challenges that need to be overcome, such as nanoparticle optimization, process scalability, and the removal and recycling of nanoparticles after the completion of the process. This comprehensive scientific review offers an extensive insight into the use of MNPs for the removal of MPs and NPs from water. With improved understanding and the development of advanced materials and methods, this technology can play a crucial role in addressing the issue of MPs and NPs and preserving a clean and healthy environment.

Carpels are a reproductive feature restricted to angiosperms, therefore they are a focus of many botanical studies. However, there are controversies over the nature of carpels. A reason underly-ing these controversies is mixing implications given by conflicting interpretations on fossil carpels in early fossil angiosperms from the Cretaceous. These controversies hinder a clear understanding of angiosperm evolution and systematics. A key to these questions is older fossil fruits bearing concerned information. Here we report a new fossil fruit, Xenofructus dabuensis gen. et sp. nov, from the Middle Jurassic of Liaoning, China. Unlike previously reported fruits of early angio-sperms that were interpreted as bearing seeds either on adaxial or abaxial margin by various au-thors, our fossil demonstrates clearly that the seeds in Xenofructus are neither borne on the adaxial nor abaxial margin of the fruit, instead the seeds of Xenofructus are borne on an axis positioned between two margins. This new feature implies that a placenta in carpels is an ovule/seed-bearing axis, a carpel is a composite organ comprising an enclosing leaf (fruit wall) and an axis (placenta). The adaxial or abaxial position of ovules/seeds frequently seen in fossil and extant angiosperms is a consequence derived through long time evolution (coalescence of placenta with either margin of fruits). Carpels can be taken as foliar structures enclosing their associated ovulate branches.

In this paper, a seamless connection between sensor technology and machine learning (ML) has been presented which has wide applicability in rehabilitation and physical medicine. The intent is to identify an ML algorithm which has a better performance, easy to deploy, and has less training time and consumes less computational resources. In short, we propose an algorithm which maximizes the synergy between a sensor and ML by maximizing classification performance and easy to do implementation, which is robust in computational power and lower in resource consumption. The premise of the work is to show the important considerations for evaluating ML algorithms for Upper-limb activity recognition for Physical medicine and rehabilitation field.

The process of developing therapies to treat rare diseases is fraught with financial, regulatory, and logistical challenges that have limited our ability to build effective treatments. Recently, a novel type of therapy called antisense therapy has shown immense potential for the treatment of rare diseases, particularly through single-patient N-of-1 trials. Several N-of-1 antisense therapies have been developed recently for rare diseases, including the landmark study of milasen. In response to the success of N-of-1 antisense therapy, the Food and Drug Administration (FDA) has developed unique guidelines specifically for the development of antisense therapy to treat N-of-1 rare diseases. This policy change establishes a strong foundation for future therapy development, and addresses some of the major limitations that previously hindered the development of therapies for rare diseases.

Quantum-dot cellular automata (QCA) is an emerging transistor-less field-coupled nanocomputing (FCN) approach to ultra-scale ‘nanochip’ integration. In QCA, to represent digital circuitry, electrostatic repulsion between electrons and the mechanism of electron tunnelling in quantum dots are used. QCA technology can surpass conventional complementary metal-oxide semiconductor (CMOS) technology in terms of clock speed, reduced occupied chip area, and energy efficiency. To develop QCA circuits, irreversible majority gates are typically used as the primary components. Recently, some studies have introduced reversible design techniques, using reversible majority gates as the main building block, to develop ultra-energy efficient QCA circuits. However, this approach resulted in time delays, an increase in the number of QCA cells used, and an increase in the chip area occupied. This work introduces a novel hybrid design strategy employing QCA irreversible, reversible, and partially reversible gates to establish an optimal balance between power consumption, delay time, and occupied area. The hybrid technique allows the designer to have more control over the circuit characteristics to meet different system needs. A combination of reversible, irreversible, and innovative partially reversible majority gates is used in the proposed hybrid design method. We have evaluated the hybrid design method by examining the half-adder circuit as a case study. We have developed four hybrid QCA half-adder circuits, each of which simultaneously incorporates various types of majority gates. The QCADesigner-E 2.2 simulation tool was used to simulate the performance and energy efficiency of the half-adders. This tool provides numerical results for the circuit input/output response and heat dissipation at the physical level, within a microscopic quantum mechanical model.

In bacteria, enzymes usually comprise of enzymatic domains only. In eukaryotes/mammals, and here particularly in context of signal transduction, proteins with enzymatic functions contain additional modules promoting interactions with cooperating signaling proteins. Often such protein-protein interaction domains, such as SH2- and SH3-domains, help to localize the enzymatic function (e.g. kinase, phosphatase) to another protein, cellular compartment, or membrane nanodomain. In such cases, the interaction domain(s) serve(s) the enzymatic function. However, there are molecular situations in which an interaction domain fulfills its task completely independent of the protein´s enzymatic function and in this review, we call such function the adapter function of an enzyme. Though many stories can be told, we will concentrate on several proteins playing crucial roles in cells of the immune system, such as BTK, PI3K, and SHIP1, as well as in cancer cells, such as proteins of the RAS/ERK MAPK pathway. We will also discuss how these adaptor functions of enzymes determine or even undermine the efficacy of targeted therapy compounds, such as ATP-competitive kinase inhibitors, thereby highlighting the need to develop pharmacological approaches, such as PROTACs, that eliminate the entire protein. We also review how genetic kock-out and knock-in approaches can be leveraged to identify adaptor functions of signaling proteins.

The fractional advection-dispersion equation FADE plays an important role, especially in explaining the process of solute-transport in natural porous media with different degrees of heterogeneity. However, studies of the flow and transport of contaminants in the underground environment are based on the knowledge of many functional parameters of the subsoil. The delay factor caused by nonlinear absorption is one of these parameters inheriting significant ambiguities in its estimation in heterogeneous media. In the study, a fractional advection-dispersion FADE model was developed by the implicit Euler method, based on a Grunwald and Caputo-Liousville approximation to explicitly evaluate and simulate the transport mechanism of contaminants in media with unsaturated porous materials subjected to a nonlinear sorption model. Better solute mass retention was observed for fractional advection-dispersion FADE model. Moreover, the absorption parameter of the retardation coefficient has a better impact on the motion of the solute in a saturated porous medium. In other words, it has a significant effect on the dispersion of pollutants in aquifers. This study highlights the need to characterize the aquifer to predict solute transport in porous media.

Previous studies separately addressed the impact of urban expansion on vegetation cover and thermal conditions, as well as its effect on moisture and drought indicators, using geospatial techniques. Some studies, such as those by Malah et al. (2021) and Niu and Li (2020), focused on assessing urban environmental quality using an environmental quality index without considering urban expansion. Meanwhile, other studies, like those conducted by Indrawati et al. (2020), primarily focused on evaluating urban environ-ments using an integrated environmental index consisting of four indicators (greenness, moisture, drought, and cumulative clustering). The study by Zhu et al. (2019) applied the same integrated environmental index (IEI) and, by comparing it with temperature, re-vealed a negative correlation illustrating the effects of the environmental index on land surface temperature (LST). These two studies could be utilized to construct an index assessing the environmental condition in Riyadh. This is the case in the present study, where the addition of a temperature indicator due to the hot desert nature of the study area created the Urban Environmental Thermal Index to evaluate the urban en-vironment and provide results suitable to this region. It is expected that the present study will align with the findings of previous relevant studies, showing a negative im-pact of urban expansion on urban environmental components.

This paper proposed emotion recognition methods for consecutive facial images, and implements the inference of neural network model on a field-programmable gate array (FPGA). The proposed emotion recognition methods are based on a neural network model architecture that combines convolution neural networks (CNNs), long short-term memory (LSTM), and fully connected neural networks (FCNNs), called CLDNN or ConvLSTM-FCN. This type of neural network mod-el can analyze the local feature sequences obtained through convolution of data, making it suita-ble for processing time-series data such as consecutive facial images. In this paper, sequences of facial images are sampled from videos corresponding to various emotional state of subjects. The sampled images are then pre-processed with the processes includes facial detection, greyscale conversion, resize, and data augmentation if necessary. The 2-D CNN in ConvLSTM-FCN is used for feature extraction for these pre-processed facial images. These sequences of facial im-age features are time sequences with dependent properties between the elements within them. The LSTM is then used to model these time sequences followed by fully connected neural net-works (FCNNs) for classification. The proposed consecutive facial emotion recognition method achieves an average recognition rate of 99.51% on RAVDESS dataset, 87.80% on BAUM-1s dataset and 96.82% on eNTERFACE’05 data set, using 10-fold cross-validation on the PC. Some com-parisons of recognition accuracies between the proposed method and the other existing related works are conducted in this paper. According to the comparisons, the proposed emotion recog-nition methods outperform the existing related researches. The proposed emotion recognition methods are then implemented on an FPGA chip using the neural network model inference algo-rithms in this paper, and the accuracies of the experiments conducted on the FPGA chip are iden-tical to those obtained on the PC. This verifies that the proposed neural network model imple-mented on the FPGA chip performs well.

For the first time, the effect of a significant change in the resistance of the aquatic environment of a population of protozoan microorganisms under the influence of radiofrequency electromagnetic radiation from cell phones has been experimentally studied. The results of the experiment demonstrate the biological nature of the changes occurring in the “water population of protozoa” system, which indicates that the impact of radiation directly affects the cell. This conclusion is confirmed by the same order of magnitude time of information exchange between individual individuals of the population in the calculation and in the experiment. An extremely low concentration of protozoa in the experiment was established, equal to 1000 pcs./liter, at which the indicated effect is observed.An unambiguous dependence of the biological effect in the “water – amoeba population” system on the average power of electromagnetic radiation of cell phones, both in standby mode and in talk mode, has been established. It is concluded that the presented method of changing the physical properties of the aquatic environment of a population of protozoa under the influence of electromagnetic fields can be a model experiment in identifying the mechanisms of interaction of biological systems with electromagnetic radiation, determining the response time of biological systems to external electromagnetic influence, and establishing the degree of influence of radiation in the 4G, 5G ranges.

Polycystic Ovary Syndrome (PCOS) is the most common endocrine disorder that affects women of reproductive age representing the primary cause of anovulatory infertility. The nonapeptide oxytocin (OT) plays an important role in cognitive, emotional, and reproductive functions in human beings. Oxytocin receptors are expressed in several body parts including the ovaries. Despite this, the possible role played by oxytocin in symptoms of PCOS is not clear. The present systematic review aimed at understanding, the presence of possible oxytocin level alterations in PCOS, the connection between alterations of OT levels and the symptoms of PCOS, and the effect of oxytocin administration in PCOS. After a systematic search in the principal databases, seven studies, five human and two animal, were included. Most of the studies highlighted the role played by oxytocin in fertility issues related to PCOS. Studies that analyzed oxytocin basal levels in PCOS women agreed that PCOS is associated with a reduction in the serum level of oxytocin. Two studies found that in PCOS the serum levels of oxytocin were lower than healthy controls. One human and one animal study agreed about lower levels of PCOS, confirming a possible implication of a dysfunction of OT, in the pathogenesis of PCOS.

Today's city needs more than ever methodological devices that ensure a specific urbanism, in keeping with the complexity of relationships that occur in the urban space. Networks or systems of diverse nature must be activated to achieve a certain success of the city, even more so in its fragile central fabrics. The study is focused on the historic neighborhoods of the city of Jaén (Spain), which have a high vulnerability index. The aim is to establish a strategy to revitalize their urban and social capital and improve their articulation with the rest of the urban and territorial structure. A methodological proposal for the analysis of vulnerability factors and an urban and cartographic analysis of the public space is addressed through an interweaving of a triple network: environmental, social, and urban. For this purpose, the configuration of this overlapping network of analysis and formulation of criteria is presented, which considers the urban multiplicity and promotes new dynamics for the integrated urban regeneration of the area and for the activation of public and collective urban spaces.

Vaccines decrease morbidity and mortality. Nevertheless, their benefits depend on public response. During COVID-19, vaccine hesitancy and refusal were rampant, threatening public health. A thorough understand-ing of opponents' arguments is required to address the diffusion of unreliable information on social media and prevent vaccine hesitancy from developing into vaccine refusal. Accordingly, the article examines vac-cine opponents' justifications on social media. Textual content analysis of reader comments on three health-related Israeli Facebook pages was conducted. Data collection encompassed the Israeli COVID-19 vaccination period from October 2020 to May 2022. The comments were analyzed according to the health beliefs model (HBM). We found that vaccine opponents were characterized by low perceptions of the severity of the disease combined with high perceptions of the damages of the vaccine; low perceived benefits of vac-cine compliance; vaccine hesitancy and fear along with public distrust as barriers to change; and call for ac-tion to resist the vaccine and spread related anti-establishment views on the web. As vaccination hesitancy was found to develop into public distrust in the state systems and escalate into conspiracy beliefs and an-ti-vaccination activism, its early detection may prevent future vaccine resistance.

The main inhibitory neurotransmitter in the mammalian brain is 4-aminobutyric acid (GABA). Phthalimide acts as a sodium channel antagonist, one of the finest targets for treating epilepsy is the sodium channel and JNK kinase activity is inhibited to treat epilepsy. a novel compound with multiple targets of action for the treatment of epilepsy also anti-oxidant activity has been designed. The compounds are designed in two series aldehydes and aniline. Docking of all the designed compounds has been done with the suitable protein GABA-AT, sodium channel, JNK protein, and anti-oxidant from protein bank. QSAR was done for constructing many linear regression models. In combination with the developed Docking and QSAR outcomes, ADMET has been performed for the active compounds. The result shows that 11 of the compounds have excellent binding energy in docking with all the receptors and also have good QSAR results and follow the ADMET. The structural understanding of human GABA-AT inhibition was obtained from molecular dynamics simulation studies for compound no. 11 at 5 nanoseconds. Synthesis and pharmacological activity also suggest that the designed compound no.11 be considered the best Novel Compound.

Continuous technological progress places significant demands on the materials used in increasingly modern devices. An important parameter is often the long-term thermal resistance of the material. The use of heat-resistant polymer materials worked well in technologically advanced products. An economically justified direction in searching for new materials is the area of polymer nanocomposite materials. It is necessary to appropriately select both the polymer matrix and the nanofillers best able to demonstrate the synergistic effect. A promising area of exploration for such nanocomposites is the use of organosilicon polymers, which results from the unique properties of these polymers related to their structure. This review presents the results of the analysis of the most important literature reports regarding organosilicon polymer nanocomposites with increased thermal resistance. Particular attention was paid to modification methods of silicone nanocomposites focused on the increase of their thermal resistance related to the modification of siloxane molecular structure and by making nanocomposites using inorganic additives, carbon nanomaterials. Attention was also paid to such important issues as the influence of the dispersion of additives in the polymer matrix on the thermal resistance of silicone nanocomposites and the possibility of modifying the polymer matrix and permanently introducing nanofillers thanks to the presence of various reactive groups. The thermal stability mechanism of these nanocomposites was also analysed.

Bio-inspired gyroid triply periodic minimum surface (TPMS) lattice structures have been the focus of research in automotive engineering because they can absorb a lot of energy and have wider plateau ranges. The main challenge is determining the optimal energy absorption capacity and accurately capturing plastic plateau areas using finite element analysis (FEA). Using nTop's Boolean subtraction method, this study combined walled TPMS gyroid structures with normal TPMS gyroid lattice. This made a composite TPMS-gyroid lattice with relative densities ranging from 14% to 54%. Using the ideaMaker software and the fused deposition modeling (FDM) Raise3D Pro 2 3D printer to print polylactic acid (PLA) bioplastics in 1.75 mm filament made it possible to slice computer aided design (CAD) models and fabricate 36 lattices samples precisely layer by layer technique. Shimadzu 100kN testing equipment was utilized for the mechanical compression experiments. And the validation using finite element analysis (FEA). Further, CTG was examined using a field emission scanning electron microscope (FE-SEM) before and after compression testing. The composite TPMS gyroid lattice showed potential as shock absorbers for vehicles with relative densities of 33%, 38%, and 54%. The Gibson-Ashby model showed that the composite TPMS gyroid lattice deformed mainly by bending, and the size effect was seen when the relative densities were less than 15%. The lattice's relative density had a significant impact on its ability to absorb energy. The research also explored the use of these innovative foam-like composite TPMS-gyroid lattices in high-speed crash box scenarios, potentially enhancing vehicle safety and performance.

Silencing of the fragile X mental retardation 1 (FMR1) gene and consequently lack of synthesis of FMR protein (FMRP) are associated with fragile X syndrome, which is one of the most prevalent inherited intellectual disabilities. FMRP is a multifunctional protein involved in many cellular functions in nearly all subcellular compartments under normal conditions and under conditions of cellular stress in both neuronal and non-neuronal cell types. This is achieved through its trafficking signals, nuclear localization signal (NLS), nuclear export signal (NES), and nucleolar localization signal (NoLS), as well as its RNA and protein binding domains, and is modulated by various post-translational modifications such as phosphorylation, ubiquitination, sumoylation, and methylation. This review summarizes recent advances in understanding the interaction networks of FMRP with a special focus on FMRP stress-related functions, including stress granule formation, mitochondrion and endoplasmic reticulum plasticity, ribosome biogenesis, cell cycle control, and DNA damage response.

Over the years, the need for autonomous systems such as drones, also known as unmanned aerial vehicles (UAVs), has significantly increased in popularity across several industries, including the military. The Internet of Battlefield Things (IoBT) represents a modern technological advancement that significantly enhances the operational efficacy of defense systems. It establishes an integrated military force by connecting individuals to intelligent technology in drones, radios, equipment, antennas and ground stations. This is achieved through the utilization of cloud and edge computing, sensors, mobile devices, embedded systems, and IoT-based systems. However, IoBT security is significantly compromised by enemies that exploit the vulnerabilities and malicious intrusions that specifically target the external environment or to obtain sensitive data. In addition, a comprehensive understanding of cyberattacks and countermeasures is essential for assuring the security of IoBT. On the other hand, as cyber threats get more complicated, trust becomes increasingly important for the security of digital systems. Within this context, the zero trust architecture contends that the security of a complex network is inherently vulnerable to internal and external threats. In defense, UAV security system applications, for example, the primary purpose of the zero trust architecture is to limit the vulnerability of military UAV systems to cyberattacks, hence reducing the possibility of data breaches and illegal entry. This study conducts a systematic review aimed at identifying different aspects of cybersecurity strategies for protecting UAV systems within the IoBT domain. Furthermore, zero trust architecture is presented in the study as an effective prospective solution to the security issues that develop in defense UAV systems.

The wealth of data obtained during the past 20 years using Laser-Induced Breakdown Spectroscopy (LIBS) indicates that the technique is very promising to detect small chemical contents of alloying elements. The potential of LIBS was looked more seriously during the past two decades or so as more data were obtained on Aluminum and steel to study the phenomena in the condition of local thermodynamic equilibrium and time-delay between a Q-switch laser and an intensified CCD camera. Since the past decade, some data on compounds were also shown to be useful in determining small concentrations of harmful elements. This manuscript is intended to show that the technique of LIBS performance is very promising in fields such as micro-machining, in alloying element analysis, surface cleaning and environmental applications even with lightweight spectrometers having a relatively low resolution, which can potentially be air-borne.

As Artificial Intelligence (AI) technology, particularly Machine Learning algorithms, becomes increasingly ubiquitous, our abilities to understand and interpret AI and machine learning algorithms are becoming increasingly desirable. Visualization has been used as a common tool to view and understand complex machine learning processes. In this paper, we will focus on developing a general framework for the visualization of machine learning models as a scalar valued multi-dimensional function to help users understand how the models behave over different viewing spaces. We first give a formal definition of the visualization problem. Interpolation-based morphing and subspace sampling techniques are applied to generate various renderings through projections and cross-sections of the model space as 3D surfaces or heatmap images. This method will be applied to two real-world datasets and applications: the diagnosis of Alzheimer's Disease (AD) using a human brain networks dataset and a real-world benchmark dataset for predicting home credit default risks. The visualizations show that different machine learning algorithms can behave quite differently under different conditions.

The study investigated the usage of open data in public organizations, focusing on the motives, preferences, and governance ideals that determine their quality. The study shed light on how open data platforms are created and improved, as well as their influence on government operations. The primary goal was to understand the motivations behind the usage of open data, evaluate gov-ernance ideals, and examine institutions' efforts to standardize data formats. Hierarchical regres-sion analysis divides variables into core reasons and different preferences, demonstrating a need for "diversification" in order to use open data effectively. Efficiency, accountability, community impact, knowledge, and high-quality service delivery are all emphasized in governance value analysis. The institution's dedication to standardizing open data formats is evidenced by legislative measures and the integration of many technologies. The findings illustrate the institution's dual strategy of em-ploying traditional techniques and new technologies for effective data management. The report suggests increasing data openness and standardization, investing in ongoing training, upgrading alerting and awareness systems, and adopting specific regulations for open data use. Monitoring and feedback techniques are critical for adjusting and refining open data services to satisfy de-velopment needs. This study adds to the scientific knowledge of open data use by highlighting important motives, preferences, and governance ideals. The offered guidelines provide practical insights for public organizations looking to improve their open data platforms by promoting openness, efficiency, and community participation.

Subnational governments play a key role responding to climate change risks in terms of policy strategies and instruments. This article analyzes how Brazilian municipal and state governments have developed and implemented public policies to mitigate and to adapt to climate change risks. We surveyed all cities’ and states’ climate policies within the country. The methodological approach includes five main points of analysis: 1. mitigation targets and intentions; 2. adaptation actions; 3. stakeholders’ participation; 4. policy implementation; 5. participation in networks related to climate change. Our results suggest that even though subnational climate policies in Brazil are isolated initiatives within the national context, they play an important role responding to climate change risks in different scales and levels. The strongest Brazilian policies with both mitigation and adaptation actions counted on previous mobilization for the climate issue involving different stakeholders from several segments of the society. These governments have also participated in transnational cooperation networks related to climate change.

Lung cancer (LC) continues to be an important public health problem being the most common form of cancer and a major cause of cancer deaths worldwide. Despite the great bulk of research to identify genetic susceptibility genes by genome-wide association studies, only few loci associated to nicotine dependence have been consistently replicated. Our previously published study in few phenotypically discordant sib-pairs identified a combination of germline truncating mutations in known cancer susceptibility genes in never smoker early-onset LC patient does not present in their healthy sib. These results firstly demonstrated the presence of an oligogenic combination of disrupted cancer predisposing genes in non-smokers patients, giving experimental support to a model of a “private genetic epidemiology”. Here, we used a combination of whole-exome and RNA sequencing coupled with a discordant sib’s model in a novel cohort of pairs of never-smokers early-onset LC patients and in their healthy sibs used as controls. We selected rare germline variants predicted as deleterious by CADD and SVM bio-informatics tools and absent in the healthy sib. Overall, we identified an average of 200 variants per patient, about 10 of which in cancer predisposing genes. In most of them, RNA sequencing data reinforced the pathogenic role of the identified variants showing: i) downregulation in LC tissue (indicating “second hit” in tumor suppressor genes); ii) upregulation in cancer tissue (likely oncogene); iii) downregulation in both normal and cancer tissue (indicating transcript instability). The combination of the two techniques demonstrates that each patient has an average of six (with a range from four to eight) private mutations with functional effect in tumor predisposing genes. The presence of a unique combination of disrupting events in the affected subjects may explain the absence of familial clustering of non-small cell lung cancer. In conclusion, these findings indicate that each patient has his/her own “predisposing signature” to cancer development and suggest the use of personalized therapeutic strategies in lung cancer.

The objective of this study was to determine how application with dolomitic limestone and grazing type (continuous or deferred) affect sheep grazing location and feed preference when the pasture growth rate is maximum. A 4ha field was divided into 4 plots: P1 and P2- without application of dolomitic limestone, continuous (CG) and deferred grazing (DG), respectively; P3 and P4- with application of dolomitic limestone, DG (1AUE), and CG (2.4 AUE), respectively. In DG, animals were placed and removed from the plots depending on the height of the pasture. In each plot, 12 georeferenced sampling points were identified. Throughout the pasture's vegetative cycle (autumn, winter, spring, and early summer) several measurements of pasture height and cut were carried out. From the beginning of March to the beginning of June, animal behavior was observed, by trained observers, through binoculars on six dates. Animals' activity grazing and location was recorded. The results show that: (i) the application of dolomitic limestone combined with CG provided higher values of pasture height; (ii) there were no significant differences in pasture quality between treatments; (iii) Deferred grazing led to 50% more sheep grazing days than continuous grazing; (iv) there were no significant differences in soil compaction between CG and DG; (v) the type of grazing and the treatment with dolomitic limestone did not seem to change the grazing pattern between treatments. This work contributes to understanding the relationships between different types of grazing in dryland pastures, with and without application of dolomitic limestone, and preferred grazing locations for sheep. This work could help agricultural managers make more informed decisions with the aim of promoting the sustainable intensification of livestock production in the Montado ecosystem.

Herein, we examined the effects of weather parameters and individual clinicodemographic risk factors on hemorrhagic stroke (HS) incidence, severity on admission, and disability at discharge in a harsh desert climate. In a retrospective design we studied patients admitted to a stroke unit in Arab Emirates in 2016-2019. With a distributed lag nonlinear model we explored immediate and delayed effects of weather on stroke incidence. Supervised machine learning was used to build models predictive of scores in NIHSS and mRS scales. We assessed model performance by calculating ROC AUC, F1 scores, specificity, and sensitivity. HS risk increased after a significant change in any weather parameter. The risk was reduced below baseline after 1-week adjustment to environmental changes. Climate input from the previous 3 days yielded reliable classification models. Humidex was a better predictor of severity than air temperature, whereas body mass index, age, and time of day at stroke onset were the strongest clinical predictors. Weather parameters before admission were stronger predictors of disease severity than individual clinical factors. We addressed limitations of previous studies by analyzing a full set of climate parameters: ambient temperature, relative humidity, humidex, atmospheric pressure, and wind speed. Predictive models may help to optimize patient management and develop preventative strategies.

Staphylococcus aureus is a gram-negative bacterium that causes superficial and deep infections that can be mild or potentially fatal. Recently, the bacterium has gained significant attention due to the increased incidence of multidrug-resistant (MDR) strains that make treatment with antibiotics dif-ficult. Owing to the MDR strains, alternative therapies such as antimicrobial photodynamic therapy (PDT) have emerged as good options to treat non-systemic infections. PDT combines a photosensi-tiser (PS) with light and oxygen to generate free radicals that destroy bacterial structures such as the plasma membrane, matrix, and genetic material. This systematic review aimed to identify the ef-fectiveness of PDT delivered using different types of hydrogels for treating wounds, burns, and contamination by S. aureus. This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Bibliographic research was conducted using the PubMed, Web of Science, and Scopus databases. Only full articles published in English between 2013 and 2024 from any country of origin (without restrictions) were included. The research was carried out from 15 June 2023 to 15 June 2024 and did not use any automatic biblio-graphic search tool. The articles collected were identified using keywords and selected using in-clusion and exclusion criteria in accordance with the PRISMA protocol. Seven articles were in-cluded that presented a good set of evidence associated with the use of PDT against S. aureus in in vitro and in vivo studies. To conclude, PDT can effectively complement antimicrobial therapy against S. aureus, in the healing of wounds and burns. The effectiveness of this technique depends on the PS used, hydrogel type, and lesion location. Some studies have already demonstrated the ef-fectiveness of PDT but most were in vitro and a few in vivo. Further studies are required to demonstrate the safety and efficacy of PDT delivered via hydrogels in in vivo models of bacterial infection.

Background/Objectives: Infectious Endocarditis often requires surgical intervention, with postoperative acute kidney injury (AKI) posing a significant concern. This retrospective study aimed to investigate AKI incidence, its impact on short-term mortality, and identify modifiable factors in patients with endocarditis scheduled for valve surgery. Methods: This single center study enrolled 130 consecutive endocarditis patients from 2013 to 2021 undergoing valve surgery. Creatinine levels were monitored pre- and postoperatively, and AKI was defined by Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Patient demographics, comorbidities, procedural details, and complications were recorded. Primary outcomes included AKI incidence, the relevance of creatinine levels for AKI detection, and the association of AKI with 30-, 60- and 180-day mortality. Modifiable factors contributing to AKI were explored as secondary outcomes. Results: Postoperatively, 35.4% developed AKI. The highest creatinine elevation occurred on the 2nd postoperative day. Best predictive value for AKI was a creatinine level of 1.35 mg/dl on the 2nd day (AUC: 0.901; sensitivity: 0.89, specificity: 0.79). Elevated creatinine levels on the 2nd day were robust predictors for short-term mortality at 30, 60 and 180 days postoperatively (AUC ranging from 0.708 to 0.789). CK-MB levels at 24 hours postoperatively and minimum hemoglobin during surgery were identified as independent predictors for AKI in logistic regression. Conclusions: This study highlights the crucial role of creatinine levels in predicting short-term mortality in surgical endocarditis patients. A specific threshold (1.35 mg/dl) provides a practical marker for risk stratification, offering insights for refining perioperative strategies and optimizing outcomes in this challenging patient population.

Drosophila melanogaster serves as a important research model both for genetic investigations and for the study of metal toxicity, facilitating the elucidation of physiological mechanisms comparable to those of human organisms. In our research, we evaluated the toxicity effect resulting from exposure to various concentrations of lead and copper on the prolificity rates throughout the life cycle (egg-adult) of four genotypes of Drosophila melanogaster: wild-type (control), white, brown, and white-vestigial. During our study, the prolificity rates were examined across three repetitions under the impact of exposure to concentrations of 0.50, 1.00, 2.00, and 4.00 mM of copper (CuSO₄) and lead (Pb(C₂H₃O₂₎₂). Prolificity rates throughout the life cycle exhibited variations as a direct consequence of genetic factors, the concentration of exposure, and the specific type of metal, either copper or lead. The mutant white-vestigial genotype revealed an IC₅₀ concentration for prolificity inhibition at lower doses of 2.00 mM for copper and 4.00 mM for lead, in contrast to the control genotype (wild-type), which exhibited an inhibition concentration rate >IC₅₀ of 4.00 mM only in the case of copper. Our results concluded that the (i) dose influences the prolificity rate in a directly proportional manner, (ii) comparative analyses between copper and lead revealed that copper displayed toxicity across all genotypes within the concentration range of 0.50 mM to 2.00 mM. In contrast, lead exhibited toxicity within the concentration range of 1.00 mM to 4.00 mM, highlighting a (iii) more acute toxicity characteristic in the case of copper. Thus, the results of this research reflect the importance of using Drosophila melanogaster as a genetic model in the comparative study of the interaction between genetic factors and the toxicity of metals, offering significant insights into monitoring their impact and defining the maximum permissible doses on organisms.

The agronomic characteristics of Cenchrus purpureus were assessed through a randomized block experimental design with seven accessions (Taiwan grass, King grass, Elephant grass, Merkeron, CT-115, Purpule grass and Maralfalfa) as treatments and four replications research was carried out at the Instituto Tecnológico Superior de Tantoyuca, in 2019 and 2020, under rainfed conditions. Sowing density was established at 36 tillers in 25 m2. Green and dry matter yield, daily rates of dry matter accumulation in leaves, leaf/stem ratio, height, leaf area index and cutting frequency were assessed. Rainfall amount, temperature, relative humidity and global radiation levels were recorded to assess their effect on the evaluated variables. One-way ANOVA and multivariate analysis techniques, such as multiple linear regression (MLR), Clustering, and Principal component analysis (PCA) with the Statistica V7 software, were used. The leaf area index was greatest (p &lt; 0.05) on the dry season. Green and dry matter yield were greatest in Maralfalfa (p &lt; 0.05). Variation in the results is attributed to weather phenomena; nonetheless, Elephant grass and Maralfalfa showed the highest yields. Quality parameters must be evaluated to identify those grasses with the best attributes.

Zinc cobalt oxide-zinc hydroxide (ZnCo2O4-Zn(OH)2) microspheres were successfully fabricated on carbon cloth via a sample hydrothermal method. The surface morphology of these microspheres and their efficacy in degrading methyl violet were further modulated by varying the thermal annealing temperatures. The manipulation of thermal annealing temperatures was pivotal in adjusting the porosity of ZnCo2O4-Zn(OH)2 microspheres to amplify their photocatalytic performance. Various analytical techniques were utilized to evaluate the physical and chemical properties of the ZnCo2O4-Zn(OH)2 microspheres, including field-emission scanning electron microscopy, energy-dispersive spectroscopy, X-ray diffraction, field-emission transmission electron microscopy, X-ray photoelectron spectroscopy, and UV-vis spectroscopy. Compared to untreated ZnCo2O4-Zn(OH)2 microspheres, those subjected to thermal annealing exhibited increased specific surface area and light absorption capacity, rendering them highly effective photocatalysts under UVC light exposure. Subsequent studies have confirmed the superior performance of ZnCo2O4-Zn(OH)2 microspheres as a reusable photocatalyst for degrading methyl violet and tetracycline. Additionally, trapping experiments during the photodegradation process involving ZnCo2O4-Zn(OH)2 microspheres have identified hydroxyl radicals (·OH) and superoxide radicals (·O2–) as the primary reactive species.

Human development encompasses the integration of neuromotor, psychological, social-emotional, and cognitive processes across time. However, a better understanding of the interconnectedness of motor and cognitive development throughout the lifespan is needed. The integrative and dynamic nature of short-term motor skill acquisition and long-term developmental processes may foster executive functions. Unfortunately, assessments of motor competence have traditionally focused on skillfulness from a movement perspective, using restrictive task protocols that decontextualize performance and limit cognitive involvement. Additionally, traditional motor-cognitive dual-task assessments centered on cognitive involvement during specific movement protocols, have minimized impacts of task complexity and motor competence on cognitive performance. To gain a more ecologically valid understanding of the relation between motor and cognitive development, a novel assessment paradigm using an integrative approach to motor-cognitive dual-tasking is needed. The purpose of the present paper is to: 1) provide a conceptual bridge, based on multidisciplinary evidence, to effectively link the concurrent development of motor competence and executive functions via learning-related and exercise-related neurotrophic mechanisms, and 2) use this conceptual bridge to inform the development of novel motor-cognitive dual-task assessments that account for the role of task complexity, current levels of motor competence, and the continuous decision-making inherent in “real world” performance environments.

The effect of the heterogeneity in sex factor is considered in the Markovian manpower modeling model. The estimation of the transition probability matrix of the staff flow was done using the maximum likelihood method. The expected future durations of the individuals in the manpower system were obtained under the aggregated and disaggregated (male and female) staff flow as well as their variances. Test for the heterogeneity of the staff based on sex factor was performed and the result of the heterogeneity test shows that there is difference between the disaggregated staff flows. The computed entrant probabilities also indicate that the male group has higher probabilities of attaining higher grades than the female group.

Aiming at solving difficulties related to aero-engine classification and identification, the infrared spectra of aero-engine hot jets are measured by telemetry Fourier transform infrared spectrometer, and a six types aero-engine hot jet spectrum data set is generated. The spectrum data set were randomly sampled at a ratio of 8:1:1 to generate training set, validation set and prediction set. In this paper, a Peak Finding Siamese Convolutional Neural Network (PF-SCNN) is designed to match and classify spectrum data. In the first place, the matching pairs of training set and validation set are made independently with the labels of positive and negative samples creating. The spectrum feature extraction and distance similarity calculation are carried out by the Siamese convolutional neural network (SCNN). When entering the prediction phase, the prediction set and training set are integrated to predict in the trained model. The prediction set labels are ultimately determined by matching them with the training set labels having the highest similarities to ensure accurate predictions. To improve the operation efficiency of the SCNN, a peak finding method is introduced to extract the spectrum peaks. Peak positions of high frequency are counted, while the peak data are extracted. The peak data are used to take the place of the original data for training and prediction. The performance measures are defined as Accuracy, Precision, Recall, Confusion matrix and F1-score, and the prediction accuracy was up to 99%. The experimental results indicate that the proposed PF-SCNN is suitable for our spectral dataset and can complete the task of infrared spectrum classification of aero-engine hot jets.

The iron roughneck is an automated equipment utilized for the connection and removal of drilling tools. This paper presents the design of an integrated iron roughneck, providing a detailed introduction to its clamp body structure, along with an analysis of its structural characteristics and performance requirements. The study delves into the integration mode and working characteristics of the clamping mechanism and spin buckle mechanism for the integrated upper clamp body structure of the iron roughneck. Additionally, this paper conducts an in-depth theoretical study on the spin buckle mechanism. Firstly, it analyzes the actual working condition of the spin buckle roller from two perspectives: contact theory and rolling friction theory, determining the structural form of the spin buckle roller. Secondly, it investigates the relative displacement between the spin buckle mechanism and the drilling tool, proposing a design method for the floating device mounted on the spin buckle roller and establishing the kinematic equation of the spin buckle roller under the influence of the floating device. Furthermore, the kinematic equations of the spin buckle roller under the influence of the floating device are established. Finally, a dynamics simulation experiment is performed to simulate the working process of the spin buckle mechanism under actual working conditions, analyzing the dynamics and kinematics of the spin buckle mechanism and obtaining the relevant parameter curves of the spin buckle mechanism and drilling tools. Through data comparison and analysis, the correctness of the theoretical analysis results and the rationality of the performance and structure of the spin buckle mechanism are verified.

Indoor environmental comfort is fundamental to human health as people spend 90% of their time indoors. This aspect is even more crucial in hospitals, where the concept of health is closely linked to well-being, ethics, and environmental aspects. Emerging methodologies and technologies such as Digital Twin, Building Information Modeling, the Internet of Things, sensing technologies, and data analytics offer new opportunities to ensure healthier environments and more efficient building management. This paper provides an assessment of how digitalization can support decision-making processes related to maintaining high levels of indoor environmental comfort in hospital settings, particularly by analyzing how real-time data processing and the application of machine learning can promote proactive interventions in these facilities. The methodological approach was based on four phases: defining the objectives of the digital twin, identifying the input data to build and feed the digital model, defining the KPIs to evaluate the system's correct functioning, and identifying the enabling technologies to be integrated into the system to achieve the set goal. The result is a digital twin for managing the operating room and its related services, with the aim of guiding decisions based on accurate data and improving operational efficiency, levels of environmental comfort, and safety regarding the diffusion of medical gases.

A total of 27 microsatellites markers , scattered all over the genom of barley, were used for characterization,and diversity analysis in 33 barley (Hordeum vulgare L.) accessions and cultivars of Algeria.Over the 27 genetic loci studied, 110 alleles were identified with a mean of 4.1 alleles per locus and the average polymorphism information content (PIC) of 0.46,the marker Ebma0806 showed the greatest value of PIC with 0.83.Genetic diversity at 27 microsatellite loci varied from 0 to 0.84 (Mean=0.50) for 33 Algerian cultivars. The genetic distance among the cultivars ranged from 0.2 to 0.85. Cluster analysis and principal coordinate analysis (PCoA) based on the SSR data clearly differentiate the all genotypes studied.

The superfamily of Acid proteases has two catalytic aspartates for proteolysis of their peptide substrates. Here, we show a minimal structural scaffold, the Structural Catalytic Core (SCC), which packs all conserved substructure elements around the catalytic machinery, and which can be found in all enzymes of the Acid proteases superfamily. The SCC is a dimer of several structural blocks, such as the DD-link, the D-loop and the G-loop, around two catalytic aspartates in each protease subunit or within an individual chain. The dimer of two D-loop/DD-link substructures makes a DD-zone, and the dimer of two D-loop/G-loop substructures makes a psi-loop. These structural markers are useful for protein comparison, structure identification, protein family separation and protein engineering.

An undesirable sensory attribute (“floral taint”) has been recently detected in red wines in some winegrowing jurisdictions in North America (e.g. Ontario, British Columbia, Washington), caused by introduction of frost-killed leaves and petioles [materials-other-than-grapes (MOG)] during mechanical harvest and winemaking. It was hypothesized that terpenes, norisoprenoids, and higher alcohols would be the main responsible compounds. Objectives were to investigate causative volatile compounds for floral taint, and explore threshold concentrations for this problem. Commercial wines displaying varying intensities of floral taints were subjected to GC-MS and sensory analysis. Several odor-active compounds were higher in floral-tainted wines, including terpenes (geraniol, citronellol, cis- and trans-rose oxide), norisoprenoids (β-damascenone, β-ionone), five ethyl esters, and three alcohols. Thereafter, fermentations of Cabernet franc (CF) and Cabernet Sauvignon (CS) (2016, 2017) were conducted. MOG treatments were (wt/wt): 0, 0.5%, 1%, 2% and 5% petioles, and 0, 0.25%, 0.5%, 1%, and 2% leaf blades. Terpenes (linalool, geraniol, nerol, nerolidol, citronellol, citral, cis- and trans-rose oxides, eugenol, myrcene), norisoprenoids (α- and β-ionone), and others (e.g. hexanol, octanol, methyl and ethyl salicylate) increased linearly/quadratically with increasing MOG levels in both cultivars. Principal components analysis separated MOG treatments from the controls with 5% petioles and 2% leaves as extremes. Increasing MOG levels in CF wines increased floral aroma intensity, and were primarily associated with terpenes, higher alcohols, and salicylates. Increased leaf levels in CF were associated with higher vegetal and earthy attributes. Increased petioles in CS were not correlated with floral aromas, but increased leaves increased floral, vegetal and herbaceous attributes. Overall, petioles contributed more to floral taint than leaves through increased terpenes and salicylates (floral notes), while leaves contributed norisoprenoids and C6 alcohols (green notes).

In this work, zinc oxide (ZnO)/ granular activated carbon (GAC) composites at different ZnO concentration (0.25M-ZnO@GAC, 0.5M-ZnO@GAC, and 0.75M-ZnO@GAC) were prepared by an in-situ hydrothermal method and demonstrated synergistic photocatalytic degradation and ad-sorption of Rhodamine B (RhB). The thermal stability, morphological structure, elemental com-position, crystallographic structure, and textural properties of developed catalysts were charac-terized by thermal gravimetric analysis (TGA/DTG), scanning electron microscopy equipped with energy dispersive-x-ray (SEM-EDS), x-ray diffraction (XRD), and Brunauer–Emmett–Teller (BET) analysis. Successful loading of ZnO onto GAC was confirmed by SEM-EDS and XRD analysis. The BET surface areas of GAC, 0.25M-ZnO@GAC, 0.5M-ZnO@GAC, and 0.75M-ZnO@GAC were 474 m2/g, 450 m2/g, 453 m2/g, and 421 m2/g, respectively. The decrease in GAC could be attributed to the successful loading of ZnO on the GAC surface. Notably, 0.5M-ZnO@GAC exhibited the best photocatalytic degradation efficiency of 82% and 97% under UV-A and UV-C light over 120 min, attributed to improved crystallinity and visible light absorption. The photocatalytic degradation parameters revealed that lowering the RhB concentration, raising the catalyst dosage and pH be-yond the point of zero charge (PZC) would favor the RhB degradation. Photocatalytic reusability was demonstrated over 5 cycles. Scavenger tests revealed that the hydroxyl radicals (•OH), su-peroxide radicals (O2−•), and photoinduced hole (h+) radicals play a major role during the RhB degradation process. Based on the TOC results, the RhB mineralization efficiency of 79.1% was achieved by 0.5M-ZnO@GAC. Additionally, GAC exhibited a strong adsorptive performance towards RhB with adsorption capacity and RhB removal of 487.1 mg/g and 99.5% achieved within 90 min equilibrium time. The adsorption characteristics were best described by pseu-do-second-order kinetics, suggesting chemical adsorption. This research offers a new strategy for the development of effective photocatalyst materials with potential for wider wastewater treat-ment applications.

This study aims to quantify greenhouse gas (GHG) emissions from China's sludge treatment industry and explore the potential of novel technologies to mitigate these emissions, promoting sustainable sludge management practices. Using a life cycle assessment approach, the total GHG emissions from sludge treatment in 2017 were estimated at 18.54 Mt CO2-eq, with significant regional variations. Incineration contributed the highest emissions (1,011.53 kg CO2-eq/t dry sludge), followed by landfill (717.51 kg CO2-eq/t) and land application (276.41 kg CO2-eq/t). The uneven distribution of emissions across cities highlights the need for targeted mitigation strategies that consider local sustainability challenges. Principal component analysis revealed that economic factors and treatment scale significantly influence emissions, emphasizing the importance of integrating sustainability goals with economic development. To reduce the carbon footprint of sludge treatment and enhance sustainability, the mitigation potential and costs of various technologies were evaluated, including thermal conversion, anaerobic digestion, hydrothermal processes, and wet oxidation. These technologies offer GHG emission reductions ranging from 0.09 to 0.46 t CO2-eq/t dry solids compared to conventional methods, while also promoting resource recovery and circular economy principles. However, further optimization is necessary to enhance their environmental and economic performance, ensuring long-term sustainability. By implementing these technologies and adopting optimization strategies, China's sludge treatment industry can significantly contribute to achieving the country's carbon neutrality goal and fostering sustainable development.

The onset of neurodegenerative diseases involves a complex interplay of pathological mecha-nisms, including protein aggregation, oxidative stress, impaired autophagy. This review focuses on the intricate connection between oxidative stress and autophagy in neurodegenerative disor-ders, highlighting autophagy as pivotal in disease pathogenesis. Reactive oxygen species (ROS) play dual roles in cellular homeostasis and autophagy regulation, with disruptions of redox sig-naling contributing to neurodegeneration. The activation of the Nrf2 pathway represents a criti-cal antioxidant mechanism, while autophagy maintains cellular homeostasis by degrading al-tered cell components. The interaction between p62/SQSTM1, Nrf2 and Keap1 forms a regulatory pathway essential for cellular stress response, whose dysregulation leads to impaired autophagy and aggregate accumulation. Targeting the Nrf2-p62/SQSTM1 pathway holds promise for thera-peutic intervention, mitigating oxidative stress and preserving cellular functions. Additionally, the review explores the potential synergy between the endocannabinoid system and Nrf2 signal-ing for neuroprotection. Further research is needed to elucidate the involved molecular mecha-nisms and develop effective therapeutic strategies against neurodegeneration.

The evidential value of an mtDNA match between biological remains and its potential donor is determined by the random match probability of the haplotype. This probability is based on the haplotype’s population frequency estimate. Consequently, implementing a population study representative of the population relevant to the forensic case is vital to correctly evaluating the evidence. The emerging number of poaching cases and the limited availability of such data emphasizes the need for improved fallow deer mtDNA population databank for forensic purposes, including targeting the entire mitochondrial control region. By sequencing the whole mitochondrial control region in 138 animals from five populations in Hungary we found four different haplotypes, including one which has not yet been described. Our results, supplemented with data already available from previous research do not support the possibility of determining the population of origin, although some patterns of geographical separation can be distinguished. Estimates of molecular diversity indicate approximately similarly low mtDNA diversity (Hd=0.565 and π = 0.002), compared with data from other countries. The calculated random match probability of 0.547 shows a high probability of coincidence and, therefore, a limited capacity for exclusion. Consequently, it may be necessary to search for polymorphic sites on other mitochondrial gene sections or to sequence the entire mitogenome of fallow deer.

Ice formation on aircraft surfaces poses significant safety risks, and current detection systems often struggle to provide accurate, real-time predictions. This paper presents the development and comprehensive evaluation of a smart ice control system using a suite of machine learning models. The system utilizes various sensors to detect temperature anomalies and signal potential ice formation. We trained and tested supervised learning models (Logistic Regression, Support Vector Machine, Random Forest), unsupervised learning models (K-means clustering), and neural networks (Multi-Layer Perceptron) to predict and identify ice formation patterns. Experimental results demonstrate that our smart system, driven by machine learning, accurately predicts ice formation in real-time, optimizes de-icing processes, and enhances safety while reducing power consumption. This solution holds the potential for improving ice detection accuracy in aviation and other critical industries requiring robust predictive maintenance.

In patients with heart failure, the evaluation of left ventricular (LV) diastolic function is vital, offering crucial insights into hemodynamic impact and prognostic accuracy. Echocardiography stands as the primary imaging modality for diastolic function assessment, and using it effectively requires a profound understanding of the underlying pathology. This review covers four main topics: first, the fundamental driving forces behind each phase of normal diastolic dynamics, along with the physiological basis of two widely used echocardiographic assessment parameters, E/e' and mitral annulus early diastolic velocity (e'); second, the intricate functional relationship between the left atrium and LV in patients with varying degrees of LV diastolic dysfunction (LVDD); third, the role of stress echocardiography in diagnosing LVDD and the significance of parameter changes in this context; and fourth, the clinical utility of evaluating diastolic function from echocardiography images across diverse cardiovascular care areas.

Background/Objectives: High-intensity anaerobic physical training frequently results in muscle damage among boxers and kickboxers, which can impede performance and recovery. Vibrational therapy (VT) and passive rest (PR) have been employed as methods to enhance muscular recovery and performance. This study evaluates the effectiveness of these two recovery methods on upper limb muscle strength and lactate levels in plasma after high-intensity exertion. Methods: Eighteen elite boxers and kickboxers, aged 19-32 years, underwent tests employing VT and PR as recovery methods in a controlled, crossover study. Muscle performance was assessed via isokinetic dynamometry, and lactate levels were measured pre-exercise, post-exercise, and post-recovery. The study adhered to the Declaration of Helsinki guidelines and was approved by the relevant bioethics committee. Results: The results showed that VT led to a faster recruitment of muscle fibers and improved muscle endurance as indicated by decreased fatigue work indices compared to PR. However, no significant differences were observed in peak torque or lactate levels between the two recovery methods. The VT group exhibited quicker recovery times in torque generation and better performance in fatigue resistance. Conclusions: VT appears to provide superior muscular recovery compared to PR following intense anaerobic effort, particularly in terms of muscle strength endurance and activation speed. These findings support the potential of VT in sports recovery protocols, although similar lactate response suggests that metabolic recovery rates are not significantly affected.

Buruli ulcer is a chronic ulcerative disease of skin and subcutaneous tissues caused by infection with Mycobacterium ulcerans. Although Australian possums are known to be susceptible to Buruli ulcer, many aspects of the disease in possums, including welfare impacts, remain largely unreported. Severe clinical Buruli ulcer was identified in four common ringtail possums (Pseudocheirus peregrinus) from Melbourne, Victoria. All four possums were euthanised due to welfare concerns and poor prognosis, based on the presence of deep ulcerative lesions to paws, some of which exposed carpal or tarsal bones. These lesions were considered likely to cause partial or complete loss of limb function, which would severely affect the welfare and survival of these wild arboreal animals. Histologically, there was severe ulcerative necrotising pyogranulomatous dermatitis, panniculitis, and myositis, with intralesional acid-fast bacteria. M. ulcerans was detected by real-time PCR in all swabs and biological tissues collected from all four cases. Buruli ulcer may be an important and under-recognised cause of poor possum welfare in endemic areas. In addition to severe cutaneous lesions, infection extends to underlying bones and joints, and the systemic distribution of M. ulcerans throughout all major tissues and internal organs, as observed in these four cases, may further impact the health and fitness of infected possums. Further research is needed to investigate the epidemiology, pathogenesis and impacts of Buruli ulcer in possums, and to inform the design of interventions that may protect the health and welfare of possums and other affected animal species.

Parental labour migration, either one or both parents, has been associated with various challenges among left-behind children (LBC). However, there is a limited understanding of the LBC’s own views and experiences of social and mental wellbeing and how the new daily life circumstances they encounter following their parents’ migration impact them. This study aimed to understand the influence of parental migration and its aftermath on the social and mental wellbeing of children and adolescents (referred to as LBC) in two rural districts in Indonesia. Employing a qualitative design, data were collected through individual in-depth interviews with LBC (n=24) aged 14 to 18 years, recruited using the snowball sampling technique. Data were thematically analysed, guided by a qualitative data analysis framework. The findings showed that parental migration negatively impacted the social wellbeing of LBC. This impact was reflected in negative labelling from friends and changes in familial roles which influenced their social interactions and activities with peers. Parental migration also caused challenges to the mental wellbeing of LBC. These manifested in the LBC experiencing fractured emotional bonds, leading to negative emotions, including stress, anxiety, sadness, depression, frustration, loss of motivation, and self-imposed isolation, which were associated with their parents’ migration and abrupt disruptions in parent-child communication. The transition to new life situations with caregivers after parental migration and the dynamics within the caregivers’ households were additional factors that detrimentally affected their mental well-being. Unmet basic needs and educational needs due to financial hardships faced by mothers and caregivers, further exacerbated mental health challenges for the children. The findings indicate the importance and improvement of policies and interventions in Indonesia (e.g., counselling services, non-cash food assistance, family hope program, direct cash assistance) that cover and address the diverse needs of mothers or caregivers and the LBC.

The clinical features of increasing muscle weakening are shared by a diverse set of illnesses known as muscular dystrophies. In early childhood, males with Duchenne muscular dystrophy (DMD) exhibit proximal muscle weakening and calf enlargement, making it the most frequent X-linked disease of muscular dystrophy in children. Development of motor skills is typically delayed, and wheelchair confinement eventually leads to early death from heart or lung problems. In terms of function, ambulation, quality of life, and life expectancy, treatment approaches like corticosteroid therapy and intermittent positive pressure breathing have improved. This is a case report of a 6-year-old kid who had early ambulatory stage Duchenne Muscular Dystrophy and complained to the neuro-physiotherapy department about frequent falls, walking difficulties, and dyspnea when walking. Other grievances included being unable to get off the ground and having trouble ascending stairs. He had physiotherapy and dynamic neuromuscular stabilization for his complaints. The main goals of treatment were educating the family, respiratory training, preventing ankle plantar flexors, maintaining strength, balance and gait training.

Childhood obesity has become a global epidemic, with significant increases in prevalence over recent decades. While excessive calorie consumption and physical inactivity are known factors, emerging research highlights the role of Endocrine-Disrupting Chemicals (EDCs), particularly obesogens, in obesity's pathogenesis. This review explores the historical context of the environmental obesogens hypothesis, their sources, mechanism of action, impact on prenatal and postnatal development and epigenetics. Additionally, it discusses the long-term consequences of childhood obesity and proposes prevention strategies that will mitigate the negative health effects. Obesogens were found to disrupt hormonal balance and metabolic processes through various mechanisms such as altering gene expression, hormonal interference, and inflammation. Especially significant, was exposure during critical windows of development which correlates with increased risk of obesity in childhood or adolescence. Long-term effects of childhood obesity include chronic health conditions and psychosocial issues. A comprehensive approach is necessary to address childhood obesity, encompassing genetic, environmental, and lifestyle factors. Prevention strategies should focus on reducing obesogens exposure, promoting healthy lifestyles, and implementing regulatory policies. Future research should investigate obesogens-diet interactions, microbiome impacts, and combined obesogens effects. Long-term human studies are also crucial for validating findings from animal models and allow for inform decision-making to combat the obesity pandemic.

Organic fertilizer application in agricultural land is known to improve soil microbial processes, fertility, and yield. In particular, stable changes in soil chemical composition through multi-year fertilization of organic fertilizers are thought to cause changes in the microbial community. Here, the effects of oil cake amendments (OC) on soil bacterial diversity, community profile and enzyme activity were evaluated and compared to those amended with chemical fertilizer (NPK). The comparison of diversity indices between OC and NPK amended soils shows that application of oil cake has increased microbial diversity potentially with an increase in the number of different microbial groups. The ordination plot distinguished and clustered both treatments showing differential effects of soils chemical factors on the microbial communities of each treatment. Proteobacteria, Verrucomicrobia and Bacteriodetes were significantly abundant in OC amended soil than in the NPK received soil, indicating alterations in community structure, composition, and diversity con-current to the changes in pH, Ca and Mg contents of the soil. These shifts in bacterial community structure and composition could also be observed from the phylum to the genus level in both NPK and OC amended soils partially explained by differences in soil chemical factors. The OC soil compared to the NPK amended soil also contain significantly higher abundance of predicted genes corresponding to enzymes related to biogeochemical cycling, decomposition and plant growth promotion. Collectively, these results support the use of an unconventional organic fertilizer positively altering bacterial populations in jujube orchards. The application of oil cake-based organic fertilizer improved microbial diversity and enhanced potential ecosystem functions related to bio-geochemical cycles, mineralization and plant growth promotion.

Maize is an important staple food crop in sub-Saharan Africa (SSA). However, the average grain yield on farmers’ fields falls considerably short of the demand of the region’s population. In addition, the normal endosperm maize widely consumed in SSA is deficient in vitamin A. Drought, a consequence of climate change, is a major constraint to maize production, resulting in seasonal low grain yield in farmers’ fields. The objectives of this study were to assess the performance of newly developed extra-early maturing provitamin A hybrids under managed drought and well-watered conditions, compare the outcomes of multiple trait base-index and multi-trait genotype-ideotype distance index selection procedures, and identify drought-tolerant hybrids with stable performance across contrasting environments for commercialization in SSA. One hundred and ninety provitamin A hybrids and six checks were evaluated under managed drought and well-watered conditions at Ikenne for two seasons between 2021 and 2023. A 14*14-lattice design was used for the field evaluations under both research conditions. Drought stress was achieved by the complete withdrawal of irrigation water 25 days after planting. Results revealed significant differences among the hybrids under drought and well-watered conditions. Grain yield, ears per plant, and plant aspect under managed drought were correlated to the same traits under well-watered conditions suggesting that the expression of these traits is governed by common genetic factors. Twenty-nine hybrids were identified as top-performing drought-tolerant hybrids by the multiple trait base index and multiple-trait genotype–ideotype distance index. Of the selected outstanding 29 hybrids, 34% were derived from crosses involving the tester TZEEIOR 197, demonstrating the outstanding genetic potential of this inbred line. Further analysis of the 29 selected hybrids revealed TZEEIOR 509 × TZEEIOR 197 as the hybrid that combined the most drought-tolerant adaptive traits. However, the hybrids TZEEIOR 526 × TZEEIOR 97, TZEEIOR 384 × TZEEIOR 30, TZEEIOR 515 × TZEEIOR 249, TZEEIOR 510 × TZEEIOR 197, TZEEIOR 479 × TZEEIOR 197, and TZEEIOR 458 × TZEEIOR 197 were identified as the most stable hybrids across drought and well-watered conditions. These hybrids should be extensively tested in multi-location trials for deployment and commercialization in SSA.

According to previous studies the median raphe region (MRR) is known to contribute significantly to social behavior. Beside serotonin, there are reports of a small population of dopaminergic neu-rons in this region. Dopamine is linked to reward and locomotion, but very little has been known about its role in the MRR. To address that, we first confirmed the presence of dopaminergic cells in the MRR of mice (immunohistochemistry, RT-PCR) and humans (RT-PCR). Next, we used chemogenetic technology in mice containing Cre enzyme under the promoter of the dopamine transporter (DAT). With the help of an adeno-associated virus, artificial receptors were expressed in the dopaminergic cells of the MRR (DAT-MRR). Four weeks later, extensive behavioral charac-terization started 30 minutes after the injection of the artificial ligand (Clozapine-N-Oxide). Stimu-lation of DAT-MRR decreased social interest without influencing aggression and with an increase in social discrimination. Additionally, inhibition of the same cells increased the friendly social be-havior during social interaction test. No behavioral changes were detected in anxiety, memory and locomotion. All in all, dopaminergic cells were present both in the mice and human MRR, and manipulation of dopaminergic neurons of the MRR elicited a specific social response.

The Australian tropical montane cloud forest (TMCF) is home to approximately 18 percent of the nation’s total vascular plant species. Over the past century, human activity and industrial development have caused global climate changes, posing a severe and irreversible danger to the entire land-based ecosystem, and WTWHA is no exception. The current average annual temperature of WTWHA in FNQ is 24 °C. However, in the coming years (by 2030), the average annual temperature increase is estimated to be between 0.5 and 1.4 °C compared to the climate observed between 1986 and 2005. Looking further ahead to 2070, the anticipated temperature rise is projected to be between 1.0 and 3.2 °C, with the exact range depending on future emissions. We identified 84 plant species endemic to the WTWHA in FNQ, which are already experiencing climate change threats. Few of these plants are used in herbal medicines. This study comprehensively reviewed metabolomics studies conducted on these 84 plant species until now toward understanding their physiological and metabolomics responses to global climate change. This review also discusses: i) recent developments in plant metabolomics studies that can be applied to study and understand the interactions of wet tropical plants with climatic stress, ii) medicinal plants and isolated phytochemicals with structural diversity, and iii) reported biological activities of crude extracts and isolated compounds.

Large datasets play a crucial role in the progression of surgical robotics, facilitating advancements in the fields of surgical task recognition and automation. Moreover, public datasets enable the comparative analysis of various algorithms and methodologies, thereby assessing their effectiveness and performance. The ROSMA (Robotics Surgical Maneuvers) dataset provides 206 trials of common surgical training tasks performed with the da Vinci Research Kit (dVRK). In this work, we extend ROSMA dataset with two annotated subsets: ROSMAT24, which contains bounding box annotations for instrument detection, and ROSMAG40, which contains high and low level gesture annotations. We propose an annotation method that provides independent labels for the right-handed tool and the left-handed tool. For instrument identification, we validate our proposal with a YOLOv4 model in two experimental scenarios. We demonstrate the generalization capabilities of the network to detect instruments in unseen scenarios. For gesture segmentation, we propose two label categories: high-level annotations that describe gestures at a maneuvers level, and low-level annotations that describe gestures at a fine-grain level. To validate this proposal, we have designed a recurrent neural network based on a bidirectional long-short term memory layer. We present results for four cross-validation experimental setups, reaching up to a 77.35% mAP.

This paper focus on the modeling and time-domain analyzing method of piecewise-smooth fractional-order circuit systems. Firstly, an analytical framework is constructed based on a generalized piecewise-smooth two-port impedance network model, which takes the topological characteristics of Dickson type switched-capacitor converters (SCCs) as examples, and considers the fractional-order characteristics of class-2 X7R ceramic capacitors, which are widely used in SCCs. Secondly, the time-domain analyzing method for such a piecewise-smooth fractional-order circuit system is developed, numerical solutions are obtained, and the influence of the fractional-order capacitor on the power conversion efficiency of the system are revealed. Finally, in order to validate the analysis, both numerical simulation and experiments are provided in the work, the results of which confirm that, the proposed fractional-order analytical framework can capture the power loss mechanism of piecewise-smooth fractional-order circuit systems more effectively than the traditional integer-order based approach, thus benefiting the design of circuit systems.

Antimony (Sb) has gained significance as a critical raw material (CRM) within the European Union (EU) due to its strategic importance in various industrial sectors, particularly in the textile industry for flame retardants and as a component of Sb-based semiconductor materials. Moreover, Sb is emerging as a potential alternative for anodes used in lithium-ion batteries, a key element in the Energy transition. This study focused on exploring the feasibility of identifying and quantifying Sb mineralizations through the spectral signature of soils using reflectance spectroscopy, a non-invasive remote sensing technique, and by employing deep learning algorithms such as Convolutional Neural Networks (CNNs). Common signal preprocessing techniques were applied to the spectral data, and the soils were analyzed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Despite achieving high R-squared values, the study faces a significant challenge of generalization of the model to new data. Despite the limitations, this study provides valuable insights into potential strategies for future research in this field.

Immune checkpoint inhibitors (ICI’s) are in the forefront of advanced Non Small Cell Lung Cancer (NSCLC) treatment. Still, only 27- 46% of patients respond to initial therapy with ICI’s and of those, up to 65% develop resistance within four years. After disease progression (PD), treatment options are limited, with 10% Objective Response Rate (ORR) to second or third-line chemotherapy. In this context, ICI rechallenge is an appealing option for NSCLC. Most data on the efficacy of ICI rechallenge are based on retrospective real-world studies of small, heavily pretreated, and heterogeneous patient groups. Despite these limitations, these studies suggest that ICI monotherapy rechallenge in unselected NSCLC patient populations who discontinued initial ICI due to PD is generally ineffective, with a median Progression-Free Survival (PFS) of 1.6-3.1 months and a Disease Control Rate (DCR) of 21.4%-41.6%. However, there is a subpopulation that benefits from this strategy, and further characterization of this subgroup is essential. Furthermore, immunotherapy rechallenge in patients who discontinued initial immunotherapy following treatment protocol completion and progressed after an immunotherapy-free interval showed promising efficacy, with a DCR of 75-81%, according to post-hoc analyses of several clinical trials. Future research of ICI rechallenge for NSCLC should focus on better patient stratification, to reflect the underlying biology of immunotherapy resistance more accurately.

The theory and working principle of fabric phase sorptive extraction (FPSE) is presented that eloquently explains the mystery behind this new and powerful sample preparation technique. FPSE innovatively integrates the benefits of sol-gel coating technology and the rich surface chemistry of cellulose/polyester/fiberglass fabric, resulting in a microextraction device with very high sorbent loading in the form of an ultra-thin coating. This porous sorbent coating and the permeable substrate synergistically facilitate very fast extraction equilibrium. The flexibility of the FPSE device allows for direct insertion into original, unmodified samples of different origin. Strong chemical bonding between the sol-gel sorbent and the fabric substrate permits the exposure of FPSE devices to any organic solvent for analyte back-extraction/elution and to highly acidic or basic environments (pH 1-12) if required. A sol-gel derived sorbent, highly polar sol-gel poly(ethylene glycol) coating, was generated on cellulose substrates. Five cm2 segments of these coated fabrics were used as the FPSE devices for sample preparation using direct immersion. An important class of environmental pollutants, substituted phenols, was used as model compounds to evaluate the extraction performance of FPSE. The high primary contact surface area (PCSA) of the FPSE device and porous structure of the sol-gel coatings resulted in very high sample capacities and incredible extraction sensitivities for both the compound classes in a relatively short period of time. Different extraction parameters were evaluated and optimized. The new extraction devices demonstrated part per trillion level detection limits for substitute phenols, a wide range of detection linearity, and good performance reproducibility.

In this study, a new type of temperature sensor device was developed. The circular electrode of the thermal sensitive sensor was modified with TMT and O₂ plasma to enhance the conductivity by forming a thin SnOxCy layer on the electrode surface. The Nano-Au particles were subjected to O₂ plasma pretreatment to form peroxide groups on the surface. The thermally sensitive sensor was made by mixing the above-treated Nano-Au particles with N-isopropylacrylamide (NIPAAm) to form solution and then UV-induced grafting polymerization of the NIPAAm-containing solution onto the electrode substrate. The composite hydrogels on the electrode introduce thermo-sensitive polymeric surface films for temperature sensing. Using ambient environment resistance test to measure the resistance, the LCST (lower critical solution temperature) of Nano-Au (MUA) mixed with NIPAAm hydrogel was found to be 32 °C. At ambient temperatures higher than LCST, the electrode resistance decreases linearly.

This study analyses regional development in one of the poorest provinces in China, Guizhou Province, between 2000 and 2012 using a multiscale and multi-mechanism framework. In general, regional inequality has been declining since 2000. In addition, economic development in Guizhou Province presented spatial agglomeration and club convergence, which shows how the development pattern of one core area, two-wing areas and a contiguous area at the edge of the province have been developed between 2006 and 2012. Multilevel regression analysis revealed that industrialization and investment level were the primary driving forces of regional economic disparity in Guizhou Province. The influences of marketization and decentralization on regional economic disparity were relatively weak. Investment level reinforced regional economic disparity and the development of core-periphery structure in the province. However, investment level actually weakened the regional economic disparity in Guizhou Province when the variable of time was considered. In addition, both the topography and urban–rural differentiation were the two main reasons for forming a core-periphery structure in Guizhou Province.

We present a very computationally light and fast approximation algorithm and then verify it with genetic algorithm and simulated annealing. We show that our algorithm is on par with GA and SA in terms of output produced while having a tightly bounded time complexity. Our algorithm works best when there is a strong positive correlation between the reliability of a component and its cost. We present two algorithms with the same essence. One of them is system cost bounded and the other is target reliability bounded. Our proposed algorithm works on a subsystem level redundancy instead of component level redundancy.

Traditional urban design often overlooks the synchronisation of human and ecological connectivities, typically favouring corridors for ecological continuity. Our study challenges this convention by introducing a computational design approach, Meta-Connectivity, leveraging the deep generative models performing cross-domain translation to integrate human-wildlife landscape connectivity in urban morphology amidst the planetary urbanisation. Utilising chained Pix2Pix models, our research illustrates a novel meta-connectivity design reasoning framework, combining landscape connectivity modelling with conditional reasoning based on deep generative models. This framework enables the adjustment of both human and wildlife landscape connectivities based on their correlative patterns in one single design process, guiding the re-materialisation of urban landscapes without the need for explicit prior ecological or urban data. Our empirical study in East London demonstrated the framework's efficacy in suggesting wildlife connectivity adjustments based on human connectivity metrics. The results demonstrate the feasibility of creating an innovative urban form in which the land cover guided by the connectivity gradients replaces the corridors based on simple geometries. This research thus presents a methodology shift in urban design, proposing a symbiotic approach to integrating disparate yet interrelated landscape connectivities within urban contexts.

In order to obtain stable and reliable configuration transformation ability, reliability optimization design is regarded as an effective way to reduce the probability of kinematic function failure for the constrained metamorphic mechanism. Based on the structural composition principle of multi-configuration source metamorphic mechanism that can operate in an under-actuated state, the modularized calculation methods are established for the force analysis of augmented Assur groups including metamorphic kinematic joints. According to the equivalent resistance gradient model of metamorphic mechanisms, with considering the uncertainties in the link dimensions, masses, and compliance parameters et al, a probabilistic evaluation method for describing the configuration transformation ability of the constrained metamorphic mechanism is established. Based on reliability evaluation and reliability sensitivity analysis, a reliability optimization design method for improving the configuration transformation ability is proposed, and then the optimization design is carried out for tolerances of random variables focusing on those structural parameters with higher reliability sensitivity, so that the optimized results can satisfy the requirements of both reliability and economic simultaneously. Finally, the feasibility and effectiveness of the proposed method is verified by the illustration of a paper folding metamorphic mechanism. The research provides the foundation of reliability design of metamorphic mechanisms to obtain the high-probability repeated execution ability of configuration transformation, it also has theoretical and practical significance to promote the engineering application of metamorphic mechanisms.

In vitro glucose uptake in yeast cell facilitated by Abelmoschus esculentus L. (okra seed) for management of type 2 diabetes was studied. Plant material was collected, identified, processed, and stored for further use. 80% methanol was employed for extraction and sonicated to release antidiabetic-bioactive component in solution and was filtered, concentrated, freeze-dried, and fractionated using standard techniques. Glucose uptake at an initial concentration of 5mM/L and 10mM/L by the crude extract was consistent to that of the known standard drug while at 25mM/L glucose concentration was equivalent with the crude extract. Also, at 0.625 mg/mL the linear equations, and R2 demonstrations that the crude extract was higher in dose predictability than the standard drug as presented by the equation; y = 35.754x - 57.822, and R² = 0.9502 (95%). The extract-fractions were employed to evaluate the ability of yeast cell line culture to take up glucose from the system through DPPH, FRAP, lipid peroxidation and anti-diabetes effect of extract-fraction assays. Extract-fractions were found to poses antioxidant activity high enough to inhibit stress-related diseases. The extract fractions were active as drug candidates both at low and high concentrations and were better compared with the standard drug and standard antioxidant was comparable. The high bioactive extract fractions require encapsulation with a nanoparticle as a drug candidate for type 2 diabetes patients. And an animal trial of the drug candidate may be necessary to monitor the in vivo performances of the extract fractions and subsequent human volunteered trial.

The present study aims at deposition of zinc phosphate coatings with the incorporation of nano Titanium dioxide particles by chemical phosphating method. Zinc phosphate coatings were developed on low carbon steel by using nano TiO2 in the standard phosphating bath. The Coated low carbon steel samples were assessed for corrosion studies using electrochemical impedance spectroscopy and potentiodynamic polarisation techniques in 3.5% NaCl solution. Chemical composition of the coatings was analysed by energy dispersive X-ray spectroscopy (EDX). Significant variations in the coating weight, porosity and corrosion resistance were observed with the addition of nano TiO2 in the phosphating bath. Corrosion rate of nano TiO2 incorporated chemical phosphate coated samples was found to be 3.5 mpy which was 4 times less than the bare uncoated low carbon steel (~14 mpy). Electrochemical impedance spectroscopy studies revels in the reduction of porosity in nano TiO2 phosphate coated samples. It was found that nano TiO2 particles in the phosphating solution yielded phosphate coatings of higher coating weight, greater surface coverage and enhanced corrosion resistance than the normal zinc phosphate coatings (developed using normal phosphating bath).

Aedes albopictus is considered one of the major invasive species in the world and can transmit viruses such as dengue, Zika, or chikungunya. The Sterile Insect Technique (SIT) can be used to suppress the native populations of Ae. albopictus. To support the development of the release strategy during the SIT application, Mark-Release-Recapture (MRR) studies are crucial. Mean-while, weather conditions can affect the MRR trial’s results and it is critical to understand the influence of climatic factors on the results. In October 2022 in Faro, Southern Portugal, 84,000 ir-radiated sterile males were released for three consecutive weeks and mosquitoes were recapture by Human Landing Collections (HLC) one, two, four and six days after. Generalised linear models with a negative binomial family and log function were used to estimate the factors asso-ciated with the number of recaptured mosquitoes, prevalence ratios, and the 95% confidence in-tervals (CI). A total of 84,000 sterile male mosquitoes were released, with 528 recaptured (0.8%) by HLC. The prevalence of recaptured mosquitoes was 23% lower when the wind intensity was moderate. Sterile-marked males had an average median distance travelled of 88.7 m. Median probability of daily survival and the average life expectancy were 61.6% and 2.1, respectively. Wild male population estimates was 443.33 males/ ha. Despite no statistically significant asso-ciation was found with humidity, temperature and precipitation, it is crucial to consider weather conditions during MRR trials analyses to obtain the best determinants estimation and a more ef-ficient application of SIT in an integrated vector management program.

Introduction: Despite its high prevalence and impact on health, metabolic dysfunction-associated steatotic liver disease (MASLD) is inadequately addressed in European primary care (PC), with a large proportion of cases going undiagnosed or diagnosed too late. A multi-country European re-search consortium led a project to design and evaluate a patient-centered, integrated model for MASLD screening, diagnosis and linkage to specialty care for European PC settings. Aim: Based on the lessons from this project, the latest research evidence and existing guidelines for the management of MASLD, we sought to develop a set of practice recommendations for screening, referral and management of MASLD in PC. Methods: The Rand/UCLA modified Delphi panel method, with two rounds, was used to reach consensus on practice recommendations. The international panel consisted of experts from six countries, representing family medicine, gastroenterology, hepatology, cardiology and public health. Initially, fifteen statements were drafted based on a synthesis of evidence from the literature and earlier findings from our consortium. Prior to the consensus meeting, the statements were rated by the experts in a first round. Then, in a hybrid meeting, the experts discussed findings of round one, adjusted the statements and reassessed the updated recommendations in a second round. Results: In round one, there was already a high level of consensus on 10 out of 15 statements. After round 2, there were fourteen statements with a high agreement (>90%). One statement was not endorsed. The approved recommendations addressed the following practice areas: risk screening and diagnosis, management of MASLD – Lifestyle interventions, pharmacological treatment of MASLD/MASH, pharmacological treatment for co-morbidity, integrated care, surgical management and other referrals to specialists. Conclusion: The final set of 14 recommendations focuses on increasing comprehensive care for MASLD in PC. The recommendations provide practical evidence-based guidance tailored to PC practitioners. We expect that these recommendations will contribute to the ongoing discussion on systematic approaches to tackle MASLD and support European PC providers by integrating the latest evidence into practice.

Mammalian species possess sophisticated innate immune mechanisms that collectively combat a wide array of viral pathogens. Among these, the well-characterized interferon (IFN) response has been extensively researched; however, the role of antiviral RNA interference (RNAi) in mammals is emerging as an area of significant interest. Previous research has noted that Dicer, an enzyme crucial for processing double-stranded RNA (dsRNA), exhibits reduced activity in vitro, and that the IFN response may overshadow or inhibit the antiviral functions of RNAi in mammalian cells. Consequently, the functional relevance of RNAi in antiviral defense within mammalian somatic cells remains an open question. The evolution of antiviral systems in human populations reflects their substantial advantages, paralleling the evolutionary pressure on genomes encoding such defense mechanisms. While the well-studied protein-guided immune responses in mammals are essential for survival in viral environments, small RNA-mediated antiviral systems, which utilize complementary base pairing to silence non self-genetic material, also play a crucial role. In mammals, evidence suggests that microRNAs (miRNAs) regulate genes integral to antiviral responses, and emerging data indicate that small interfering RNAs (siRNAs), PIWI-interacting RNAs (piRNAs), and transfer RNAs (tRNAs) can directly target virus-derived nucleic acids. This review aims to highlight some of the recent progress in understanding mammalian antiviral RNAi mechanisms.

Proteomics is the study of cellular proteome by investigating how different proteins interact with each other and the roles they play in the organism. For mRNA expression levels do not always correlate well with protein expression levels, and the study of mRNA does not consider protein posttranslational modifications (PTMs), complex formation and localization; all of which are key to protein function. Quantitative proteomics uses mass spectrometry to identify and quantify proteins so as to find differentially expressed proteins under different condition. This allows us to gain biological insights under stress or other pathological conditions. posttranslational modifications, such as lysine acetylation, succinylation and lactylation, occur after protein biosynthesis and play vital roles in protein activity and cell physiology regulation. Here we present the mass spectrometry analysis in detail to unveil protein acylase and deacylase’ roles in metabolic regulation based on PTMomics lysine acetylome and suincylome.

Immunohistochemistry (IHC) helps identify different types of tissues and provides important information about the pattern, shape, and structure of cells in a tissue sample. It is a very useful tool and widely used to uncover histology and pathology diagnosis uses. The IHC is a very useful tool to conduct research in the developmental biology area. Some insects, like butterflies, bees, beetles, ants, wasps, and moths, undergo a unique life cycle called complete metamorphosis, which has four distinct stages: egg, larva, pupa, and adult. Larvae are often wingless and have different habits and forms than adults, which are better suited for growth and development. During the metamorphosis, how does the insect legs change is a really an interesting issue.To better understand insect development, agriculture pest control, and insect pathogen interaction, here we use an insect Bombyx mori (domestic silk moth) as a model to detail how to conduct the IHC assays, such as HE staining, TUNEL to see the cell apoptosis, pH3 and BrdU staining to check cell division. The reagents can be easily found, and this step-by-step protocol is easily reproduced.

The maritime industry contributes to over 80% of global trade and ranks as the sixth-largest emitter of greenhouse gases. The International Maritime Organization has taken strides to reduce these emissions, while the European Union spearheads efforts to establish sustainable maritime transport. However, meeting decarbonisation targets poses significant challenges, with the potential implications of adopting an EU Emission Trading System (ETS) on shipping allowances, particularly at specific borders. If not managed effectively, this could result in diversifying regular container shipping routes away from EU ports, potentially leading to increased shipping emissions and disrupting the logistics trade and security chain. These challenges are exacerbated by the International Maritime Organization's lack of a carbon fee on bunkering, which creates an imbalance. The ETS Directive has fostered unfair competition between EU and non-EU ports due to discrepancies in applying emission unit allowances. It is imperative to implement preventive measures to contain and prevent the shift of operations from EU ports to nearby ports, ensure equitable treatment of EU transhipment ports and their competitors, and thwart carbon leakage. Additionally, the recent Houthis attacks on the Red Sea have significantly impacted shipping costs on the Cape of Good Hope route to Europe, necessitating increased allowances to and from Europe.

The traditional way to define cosmic acceleration, denoted \( q \), relies on a comoving frame of reference within a 3D space-like coordinate system. This is the acceleration of the background metric in a particular frame rather than the actual acceleration between different observers on time-like geodesics. This traditional choice obscures the true physical processes, much like the Earth-centered model historically obscured the understanding of gravitational forces before the heliocentric shift. In this study, we introduce \( q_E \), a new metric defined by distances between causal events (i.e. acceleration between observes) in 4D null space. We compare \( q_E \) with \( q \) using observational data from supernovae (SN) and radial clustering of galaxies and quasars (BAO). Our results show that \( q_E \) offers a closer alignment with this data. Our analysis reveals that cosmic expansion, when viewed from the rest frame, is actually decelerating, confined by dynamics inside an Event Horizon, similar to conditions within a Black Hole interior. This indicates that \( \Lambda \) acts not as an agent of new dark energy or as a modification of gravity, but as a boundary term exerting an attractive force similar to a rubber band, which resists further expansion and prevents horizon crossing of events. We show how this interpretation of cosmic expansion as deceleration in the rest frame challenges conventional cosmological models and suggests that a reevaluation of these models is necessary.

Recurrent sunspot groups were studied by using the Debrecen Photoheliographic Data (DPD) which covers more than 40 years. For this task it is necessary to make unambiguous the identification of the returning solar active regions. It starts with an algorithmic listing of possible returns, then the candidates of the algorithmic identifications are checked by the unique HTML-feature of the DPD. The final check is the application of an asymmetric Gaussian function introduced in previous articles to describe the development of short-lived sunspot groups observed continuously from start to end on the visible solar disc. The data of correctly identified recurrent sunspot groups fit surprisingly well to this function throughout the rotations enabling the reconstruction of the development also on the far side of the sun. The primary goal was to find any relationship between the maximum area and the lifetime deduced from the data of the asymmetric curves. This relationship is more complex than earlier results in the literature for short-lived groups. The lifetimes exhibit weak dependencies on the heliographic latitude and solar cycle phase. An apparently returning active area is rather an active nest if its data do not fit to the asymmetric Gaussian.

Sustainable development advocates for an environmentally friendly and resource-saving approach, fostering a new quality of productivity that is green and sustainable, and achieving a sustainable development where the economy and the environment are in harmony. The paper is based on clarifying the effects of coordinated development between the economy and the environment, and by establishing an indicator system, applying a remote sensing ecological index, entropy weight method, gray relational degree model, and a coupling coordination model, the relationship of coordinated development of Ordos in 2016-2022 is analyzed from a spatial-temporal perspective. The results are as follows: ① The years of coordinated development between the ecological environment and the economy are in the majority, while the uncoordinated years are fewer. ② The level of coordinated development between the ecological environment and the economy in the various regions of Ordos has been increasing year by year, but it still remains at the barely coordinated and primary coordinated levels. ③ The types of coordinated development between the ecological environment and the economy in Ordos exhibit significant spatial differentiation in terms of spatial distribution and clustering.Therefore, it is necessary to formulate coordinated development policies and measures according to the constraining factors of different regions.

The stability properties of the Hill equation are discussed, and especially those of the Mathieu equation that characterize ion motion in electrodynamic traps. The solutions of the Mathieu equation for a trapped ion are characterized by using the Floquet theory and Hill's Method solution, which yields an infinite system of linear and homogeneous equations whose coefficients are recursively determined. Stability is discussed for parameters $a$ and $q$ that are real. Characteristic curves are introduced naturally by the Sturm-Liouville problem for the well known even and odd Mathieu equations $ce_m(z,q)$ and $se_m(z,q)$. We illustrate the stability diagram for a combined (Paul and Penning) trap and represent the frontiers of the stability domains for axial and radial motion. In case of a Paul trap the stable solution corresponds to a superposition of harmonic motions. The problem of evaluating the maximum amplitudes of stable oscillations for the ideal conditions (taken into consideration) is also approached. Anharmonic corrections are discussed within the frame of the perturbation theory, while the frontiers of the modified stability domains are determined as a function of the chosen perturbation parameter. The results apply to 2D and 3D ion traps used for different applications in quantum engineering, among which optical clocks, quantum logic and quantum metrology, but not restricted only to these.

Depression, anxiety, and pain are part of a common phenomenon that requires to be studied together when evaluating patients with chronic pain. The aim of the study was to examine the correlations between depression, anxiety and pain intensity in patients with chronic pain and how they change when a depressive episode was added. A sample of 120 patients with chronic pain (age: 51.90±11.94; 81.7% female; 18.3% male) was studied in two stages with a three-month period between them. Patients with a depressive episode (n=61) were treated with antidepressants and analgesics, while a patient without depression (n=59) was treated only with analgesics. The scales used to achieve the objectives were: HAM-D-17, Spielberger‘s STAI and VAS. Insignificant correlations were found between depression, state and trait anxiety, and pain intensity (p&lt;0,05) in the group without depression, except for a significant one between depression and state anxiety (p&lt;0,01) in the second stage. Significant correlations were identified between all indicators (p&lt;0,01) in the group with depression at the two stages. Those in the second stage were stronger. The interrelations between sensory and affective aspects of pain were stronger when a depressive episode occurs, the severity of which determines their dynamics.

Measurement of Globe temperature is essential for investigating thermal comfort in street canyon. Globe thermometer is the most common instrument used to measure globe temperature (GT), however its application in scale models is still uncertain and not thoroughly investigated as of today. Therefore, this study is explicitly conducted to investigate globe thermometer measurements and proposed an improvised customization of the globe thermometer size to enhance reliability in scale models. The experiments were carried out outdoors using a typical street canyon model (scale 1:100) with East-West street orientation. The experiment presented a comparison between a low solar reflective street canyon (albedo of 0.4) and a high solar reflective canyon (albedo of 0.6) in terms of surface temperatures, heat flux and globe temperature. Furthermore, this study also investigated the influence of solar orientation on the globe temperature using both experimental using scale models and microclimatic modelling using ENVI-met. It is observed that although the surface temperatures are lower with high solar reflective canyon compared to that with low solar reflective canyon, GT is higher in high reflective canyon during daytime, which could be due to combined effect of direct radiation and shortwave reflection. However, for hours after the sun set, GT becomes lower (up to 1°C) in the case of high reflective canyon compared to low reflective canyon.

Driven by mounting environmental apprehensions stemming from the over dependence on fossil fuels in energy and transportation sectors, extensive exploration into alternative energy sources, particularly biomass, has stimulated profound research on harnessing the potential of computational and mathematical techniques. This comprehensive survey delves into optimal models and strategies, unveiling their pivotal role in the design of biomass gasification processes.of hydrogen through biomass gasification. In this study, we aim to provide a comprehensive overview of the computational and mathematical techniques employed in optimizing biomass gasification processes, with a specific focus on enhancing hydrogen yield. Through an extensive literature review, various models and strategies will be examined, including thermodynamic analysis, kinetic modeling, reactor design, and process optimization. By uncovering the power of these techniques, we aim to contribute to the advancement of sustainable and efficient biomass utilization for the hydrogen-based future economy.This paper aims to provide an updated and comprehensive coverage of the investigations conducted on the potential of producing hydrogen from biomass through gasification. To achieve this, we incorporate the latest works that have utilized numerical modeling, simulation, optimization techniques, process heat integration, and co-generation in their studies. By encompassing these aspects, we aim to offer a broader and more in-depth re-appraisal of the subject matter. This will ensure that readers gain a holistic understanding of the advances made in the field and the potential for sustainable hydrogen production of biomass gasification.Through a meticulous re-appraisal and analysis of each subject, we can identify their respective strengths and areas that require further research effort. By thoroughly examining numerical modeling, simulation, optimization techniques, process heat integration, and co-generation, we can assess their effectiveness and applicability in the context of biomass gasification for hydrogen production. This analysis shed light on the areas where these techniques excel, as well as pinpoint limitations or gaps in current understanding. By identifying these areas, we can highlight the need for further research and development, enabling us to make significant advancements in biomass gasification processes and pave the way for a sustainable and efficient hydrogen-based future economy..

This review study explores and analyzes distributed database management systems (DDBMS), focusing on the important role of transparency methods in improving the functioning and interaction between users and systems. Transparency in DDBMS refers to several important factors, such as data, replication, performance, scaling, and network transparency. Each one of these components plays a role in concealing the intricate operations that underlie distributed systems from the end user. This not only speeds interactions but also enhances the reliability of the system. The article highlights the criticality of data independence as well as replication transparency in particular. Data independence enables adaptable modifications to the system's architecture and alterations to be made without causing any disruption to user activities. On the other hand, replication transparency ensures that the data remains consistently accurate across distributed nodes, even in the absence of user awareness. Moreover, the article investigates the progression of DDBMS through the incorporation of cutting-edge technologies such as quantum computation and artificial intelligence, which are anticipated to significantly augment the capabilities of data processing. The text proposes potential avenues for further investigation, emphasizing how these advancements may enhance the fundamental resilience of database management systems (DBMS) and expand their applicability in intricate, data-rich settings.

This paper investigates the impact of debt financing on dividend payments when they face the agency costs of free cash flow. Focusing on a sample of 120 firms listed on the Saudi Stock Exchange during the period 2011-2021. The study found a negative association between agency cost of free cash flow and dividend payment. More importantly, our research highlights the significant role of long-term debt in making more prudent use of free cash flow. The obligation to meet interest and principal payments acts as an incentive for them to steer clear of unprofitable expenses and risky investments. Concurrently, long-term debt imposes restrictive clauses in debt contracts, such as minimum dividend distribution requirements, which further encourage higher dividend payments. Since interest and debt repayments are fixed obligations, using free cash flow for dividend disbursement is considered a more profitable and beneficial approach for shareholders in the context of Saudi Arabia.