Zoonotic abortive diseases represent a significant health and economic risk for national public health. This cross-sectional survey was conducted from April to October 2021 among 200 selected small ruminant farmers in the three northern regions of Cameroon. Data collection was done through questionnaires administered by exchange with the herder and responses were coded and recorded on an Excel spreadsheet. The data were then analyzed with R software, version 2.13.0. An ANOVA test was used to assess significant differences in mean of Knowledge, Attitudes, Practices and Perception of zoonotic risks (KAPP) scores between regions. Pearson correlations were used to calculate the association between KAPP scores within regions. Small ruminant farmers surveyed had low mean scores for knowledge of abortive Toxoplasmosis and Chla-mydophilosis (0.1 ± 0.2), desirable attitude (0.32 ± 0.07), appropriate practice (0.36 ± 0.13) in managing abortion, and positive perception of zoonotic risks of Toxoplasmosis and Chlamydo-philosis in small ruminants (0.12 ± 0.33), respectively. KAPP was significantly (p<0.01) and posi-tively associated with knowledge (r=0.98) and risk perception (r=0.99). However, attitudes (r=0.06), practices (r=0.05) and risk perception of toxoplasmosis (r=0.07) and Chlamydophilosis (r=0.08) were not associated with farmers' knowledge. This study revealed significant knowledge gaps, low levels of desired attitudes, and high-risk behavioral practices. These results therefore call for capacity building of health professionals and farmers to better integrate the One Health concept in the management of neglected zoonotic diseases.

We have recently introduced the possibility of performing operando small-angle X-ray scattering measurements using a novel industrially relevant injection moulding system for plastics. We show that useful time-resolving measurements can be performed with a time-cycle of 1s and we highlight the possible steps to reduce this to 0.5s. We show how we can use the transmission measurements to provide a time-marker when plastic first enters the mould cavity in the region probed by the incident X-ray beam. We show the opportunities provided by this experimental stage mounted on the NCD-SWEET beamline at ALBA to probe the reproducibility of the injection moulding system on different scales. The design of the equipment allows the development of the structure and the morphology to be evaluated in different parts of mould cavity and we evaluate any differences in a rectangular mould cavity. We identify future prospects for this equipment in terms of novel mould heating and cooling systems and the opportunities for quantitatively evaluating radical approaches to injection moulding technology.

Alfalfa is an important forage crop around the world. LncRNAs are considered to be a class of functional biomacromolecules, while little is known about lncRNAs in alfalfa. In this study, RNAs from different tissues of alfalfa were sequenced and anlyzed with full-length transcriptome sequencing technology, yielding the full-length transcripts dataset of alfalfa. Based on sequencing and public RNA-seq data, lncRNAs of alfalfa were predicted genome-wide by CPC2 and PLEK. The results showed most lncRNAs shared low sequence conservation with those in other plant species, part of which seems originate from plastid genome. We also identified 88563 lncRNAs, approximately 99.8% of total lncRNAs, with possibility of coding small ORFs using two prediction tools. Our research generated the biggest sequence set of alfalfa lncRNAs, and revealed some plastid originated lncRNAs with high sequence conservation.

Blast charge initiation procedures have a significant impact on both mining safety and production rates. In this study, the inventory benefit of an electric initiation system was investigated to assess its influence on both fragmentation and blast-induced damages. The Wipfrag software's was used to examine the size distribution and productivity of 12 small-scale blasts initiated by both non-electric and electric detonators. All blast rounds was initiated with plain type of electric and NONEL detonators. The average burden, spacing, stemming length, and charge weight were, respectively, 0.85 m, 1.10 m, 0.66m, and 1.1kg. The results showed that the mesh through which 80% of the blast fragments will pass for the electric blast is smaller than the mesh through which the material products from the NONEL blast will pass. The results also demonstrate that the generated blast-induced ground vibration (PPV) from all blast rounds for electric blast varies from 0.4–1.2 mm/s and 80–105dB, while that for non-electric blast ranges from 0.05–0.2mm/s and 72–95dB. As a result, the electric blast initiation technique was found to produce good fragmentation, with a higher percentage of optimum fragment sizes on spec than non-electrically initiated blasts.

We develop the theory of Heyting locally small spaces, including Stone-like dualities such as a new version of Esakia duality and a system of concrete isomorphisms and equivalences. In such a way, we continue building tame topology, realising Grothendieck's ideas. We use up-spectral spaces and define the standard up-spectralification of a Kolmogorov locally small space. This research gives more understanding of locally definable spaces over structures with topologies.

F-type ATP synthases play a key role in oxidative and photophosphorylation processes producing adenosine triphosphate (ATP) for most biochemical reactions in living organisms. In contrast to the mitochondrial FOF1-ATP synthases those of chloroplasts are known to be mostly monomers with approx. 15% fraction of oligomers interacting presumably non-specifically in a thylakoid membrane. To shed light to the nature of this difference we studied interactions of the chloroplast ATP synthases using small-angle X-ray scattering (SAXS) method. Here, we report evidence of I-shaped dimerization of solubilized FOF1-ATP synthases from spinach chloroplasts at different salinity. The structural data were obtained by SAXS and showed dimerization in response to changes in ionic strength. The best model describing SAXS data was two ATP-synthases connected through F1/F1’ parts, presumably via their δ-subunits, forming dimers with the “I” shape. Such I-shaped dimers might possibly connect the neighboring lamellae in thylakoid stacks assuming that the FOF1 monomers comprising such dimers are embedded in different thylakoid membranes. If this type of dimerization exists in nature, it might be one of the pathways of inhibition of chloroplast FOF1-ATP synthase for preventing of ATP hydrolysis in dark, when salinity in plant chloroplasts is rising. Together with a redox switch inserted into a γ-subunit of chloroplast FOF1 and lateral oligomerization, an I-shaped dimerization might comprise a subtle regulatory process of ATP synthesis and stabilize the structure of thylakoid stacks in chloroplasts.

Traceability is the ability to determine the path of a product from purchase to consumption to determine when and where it originated. This paper aimed to determine the factors that influence fishers’ decision-making to participate in tuna traceability program, it also explores the determinants of fish catch for small-scale fishers and the feasibility of implementing tuna traceability in the Davao Gulf, Philippines. The result of the interview showed that the significant factors that highly affected the decision-making of fishers in implementating tuna traceability program: boat capacity, fishing hours and communication of fishers (P≤0.05). Household size, years in community, fishing hours, volume of fish sold, and the fishers' communication in the fishing ground (P≤0.05) were other factors that determined the daily catch of the fishers. The results of this study showed that fishers from the Davao Gulf were willing to be part of traceability program that would sustain and increase the value of their fish catch. Moreover, communication was shown to be critically needed in such programs adjusting it for the fish catch to remain fresh or of good quality. Our study will help in deterring and mitigating illegal, unregulated and unreported fishing (IUU) through fish catch traceability.

The glycosaminoglycan, heparan sulphate (HS), orchestrates many developmental processes. Yet its biological role has not yet fully been elucidated. Small molecule chemical inhibitors can be used to perturb HS function and these compounds pro-vide cheap alternatives to genetic manipulation methods. However, existing chemical inhibition methods for HS also interfere with chondroitin sulphate (CS), complicating data interpretation of HS function. Herein, a simple method for the selective inhibition of HS biosynthesis is described. Using endogenous metabolic sugar pathways, Ac4GalNAz produces UDP-GlcNAz, which can target HS synthesis. Cell treatment with Ac4GalNAz resulted in defective chain elongation of the polymer and decreased HS expression. Conversely, no adverse effect on CS production was observed. The inhibition was transient and dose-dependent, affording rescue of HS expression after removal of the unnatural azido sugar. The utility of inhibition is demonstrated in cell culture and in whole or-ganisms, demonstrating that this small molecule can be used as a tool for HS inhibition in biological systems.

Small boat fishers are often the lifeblood of remote coastal communities in Iceland, contributing to employment, jobs and economic prosperity. This study conducts exploratory but highly practical research into the efficiency of onboard catch handling practices by Icelandic small boat fishers using fish handling tools called automatic jigging machines. Using applied research methods, this study researches whether standardisation of operations could be applied to make catch handling practices on small boats more time and resource efficient, leading to reduced waste, a consistently higher quality product, and potential increases in economic efficiency and sustainability. Thematic analysis, value stream mapping, flow analysis and Kaizen ideology were adopted to identify gaps and continuous improvement opportunities to standardise processes, leading to exemplary performance. Eight core recommendations are identified, seven of which are classed as straight-forward, ‘do now’ measures according to a Kaizen Priority Matrix. These include human and technological interventions in the areas of safety, organisational arrangements, hygiene, fish handling and bleeding, and cooling. Questionnaire responses reveal four main themes of importance to the sub-sector: changes in recent decades; the importance of small boat fishers; education and improvement; and the particularities of the sub-industry. The latter include the perception of a ‘race against time’ to land the catch, an issue that sometimes contributes to sub-optimal catch handling practices. Although this study has decidedly practical connotations for small boat fishers, its outcomes are also likely to be of interest to academics, particularly those focused on the organisational management of natural resources and general applications of the project management methodology and applied research methods as a means of solving practical problems in everyday life.

Non-coding RNAs (ncRNAs) comprise a diverse class of non-protein coding transcripts that regulate critical cellular processes associated with cancer. Advances in RNA-sequencing (RNA-Seq) have led to the characterization of non-coding RNA expression across different types of human cancers. Through comprehensive RNA-Seq profiling, a growing number of studies demonstrate that ncRNAs, including long non-coding RNA (lncRNAs) and microRNAs (miRNA), play central roles in progenitor B-cell Acute Lymphoblastic Leukemia (B-ALL) pathogenesis. Furthermore, due to their central roles in cellular homeostasis and their potential as biomarkers, the study of ncRNAs continues to provide new insight into the molecular mechanisms of B-ALL. This article reviews the ncRNA signatures reported for all B-ALL subtypes, focusing on technological developments in transcriptome profiling and recently discovered examples of ncRNAs with biologic and therapeutic relevance in B-ALL.

In the past few decades, the tourism sector has emerged as a significant economic activity in island nations, particularly in tropical regions. However, most of the tropical islands face similar constraints. National and international tourists visit the SIDS including A & N Islands and contribute to the GDP to significant share. The Covid-19 outbreaks in SIDs including A & N islands shows that number of people infected were less as compared to metros or big cities. However, tourism activities completely stopped due to lockdown resulting in decreasing tourist’s arrival, declined GDP and per capita income of SIDs to greater extent. The information gathered from various sources, mass media and net analysed and interpreted in this chapter. Due to Covid-19 tourist’s arrival declined which has serious consequences on the livelihood of islander. Our analysis revealed A&N Islands deficit in energy available at from different sources by 18.26%. However, they are surplus in protein. The burden of high expenditure coupled with poor infrastructure makes them more vulnerable in the circumstance of pandemic outbreaks. This outbreak has created the question of survival due to loss of jobs, halted economic activates, psychological, health unrest and livelihood threats among the depending people of these Island nations. Therefore, government interventions and subsidized package is very much essential to revive the tourism industry.

Exportin-1, the ubiquitous nuclear protein transporter, is widely confirmed as an active chemotherapeutic target in non-small cell lung cancer condition while Juglans mandshurica is a well-studied anticancer plant in some lung cancer cell lines. We intend to find novel exportin-1 inhibitor from Juglans mandshurica with better potential tolerability and pharmaco-dynamo-kinetic properties than the current selective inhibitors of nuclear export in non-small cell lung cancer treatment. Osiris property explorer DataWarrior, Glide standard precision docking, quantum mechanics polarized ligand docking, MMGBSA binding free energy calculations, Jaguar density functional theory analysis, and the online web-based SwissADME were employed respectively in this study to filter the retrieved compounds based on tolerability, toxicity, and Lipinsky’s rule of five violation potential, determine their druggability, establish relative stability of the lead compound in water solvation model, and evaluates druglikeness, lead-likeness, as well as synthetic accessibility of the lead compound. This study reveals eriodictyol as having higher binding free energy (-40 kcal/mol) than that of standard (-39.56 kcal/mol) in exportin-1 active site, better synthetic accessibility score (3.15 versus 3.29), high GI absorption, non-blood brain barrier permeant, lacks Brenk and PAINS alert, obeying Lipinski’s, Ghose’s, Veber’s, Egan’s, and Muegge’s rule of druglikeness and lead-likeness as well as non-cytotoxic to HepG2 cells. We therefore found eriodictyol as a lead-like, non-toxic exportin-1 inhibitor with good predictive stability and pharmacokinetic potential and thus provided data for further validation of eriodictyol as a candidate exportin-1 inhibitor in both preclinical and clinical studies involving lung cancer therapy.

Land degradation is a critical issue globally putting our future generations at risk. The decrease in farm productivity over the years is evidence of land degradation severity in Nepal. Among the many strategies in place, agroforestry, which is an integrated tree-based farming, is widely recommended to address this productivity issue. This paper thoroughly examines what influences the choice of agroforestry adoption by farmers and what discourages the adoption. For this, a total of 288 households were surveyed using a structured questionnaire. Two agroforestry practices were compared with conventional agriculture with the help of the Multinomial Logistic Regression (MNL) model. The likelihood of adoption was found to be influenced by gender; the male-headed households were more likely to adopt the tree-based farming practice. Having a source of off-farm income was positively associated with the adoption decision of farmers. Area of farmland was found being the major constraint to agroforestry adoption for smallholder farmers. Some other variables that affected positively included livestock herd size, provision of extension service, home-to- forest distance, farmers’ group membership and awareness of farmers about environmental benefits of agroforestry. Irrigation was another adoption constraint that the study area farmers were faced with. The households with means of transport and with larger family (household) size were found to be reluctant towards agroforestry adoption. A collective farming practice could be a strategy to engage the smallholder farmers in agroforestry.

Mediterranean catchments are characterized by significant spatial and temporal hydrological variability caused by the interaction of natural as well human-induced abiotic and biotic factors. This study investigates the (non-)linearity rainfall-runoff relationship at multiple temporal scales in representative small Mediterranean catchments (i.e., < 10 km2) to achieve a better understanding of the hydrological response. Rainfall-runoff relationship was evaluated in 44 catchments at annual and event –203 events in 12 of these 44 catchments– scales. A linear rainfall-runoff relation was observed at annual scale with higher scatter in pervious than impervious catchments. Larger scattering was observed at event scale, although pervious lithology and agricultural land use promoted significant rainfall-runoff linear relations in winter and spring. These relationships were particularly analysed during five hydrological years in Es Fangar catchment (3.35 km2; Mallorca, Spain) as a temporal downscaling to assess intra-annual variability in which antecedent wetness conditions played a significant role in runoff generation.

Membranes based on sulfonated synditoactic polystyrene were thoroughly characterized by contrast variation SANS over a wide Q-range in dry and hydrated states. The film samples were prepared by solid-state sulfonation that allowed a uniform sulfonation of only the amorphous phase while preserving the crystallinity of the membrane. The samples were loaded with different guest molecules in either the amorphous (fullerenes) or the crystalline (toluene) regions, in order to vary the neutron contrast or to reproduce the conditions enabling an increased resistance of the membranes to chemical decomposition. The use of uni-axially deformed film samples and contrast variation with different H2O/D2O mixtures allowed for the identification and characterization of different structural levels with sizes between nm and μm, which form and evolve in the membrane morphology in dry and hydrated states and produce scattering features on different detection sectors and at different detection distances after the sample, depending on their size and orientation.

Background: Plasma metabolites are associated with cognitive and physical function in the elderly. Because cerebral small vessel disease (SVD) and neurodegeneration are common causes of cognitive and physical function decline, the primary objective of this study was to investigate the associations of six plasma metabolites (two plasma phosphatidylcholines [PCs]: PC aa C36:5 and PC aa 36:6 and four sphingomyelins [SMs]: SM C26:0, SM [OH] C22:1, SM [OH] C22:2, SM [OH] C24:1) with magnetic resonance imaging (MRI) features of cerebral SVD and neurodegeneration in older adults. Methods: This study included 238 older adults in the Atherosclerosis Risk in Communities study at the fifth exam. Multiple linear regression was used to assess the association of each metabolite (log-transformed) in separate models with MRI measures except lacunar infarcts, for which binary logistic regression was used. Results: Higher concentrations of plasma PC aa C36:5 had adverse associations with MRI features of cerebral SVD (odds ratio of 1.69 [95% confidence interval: 1.01, 2.83] with lacunar infarct, and beta of 0.16 log [cm³] [0.02, 0.30] with log [White Matter Hyperintensities (WMH) volume]) while higher concentrations of 3 plasma SM (OH)s were associated with higher total brain volume (beta of 12.0 cm³ [5.5, 18.6], 11.8 cm³ [5.0, 18.6], and 7.3 cm³ [1.2, 13.5] for SM [OH] C22:1, SM [OH] C22:2, and SM [OH] C24:1, respectively). Conclusions: This study identified associations between certain plasma metabolites and brain MRI measures of SVD and neurodegeneration in older adults, particularly higher SM (OH) concentrations with higher total brain volume.

The aim of this study is to provide the scientists with a straightforward correlation that can be applied for predicting the Fanning friction factor and consequently the pressure drop during blood flow in small caliber vessels. Due to the small diameter of the conduit, the Reynolds numbers are low and thus the flow is laminar. The study has been conducted using CFD simulations validated with relevant experimental data acquired using an appropriate experimental set-up. The experiments concern pressure drop measurement during the flow of a blood analogue that follows the Casson model, i.e. an aqueous glycerol solution that contains a small amount of xanthan gum and exhibits similar behavior to blood, in a smooth, stainless steel microtube (L=5.6cm and D=400 μm). The interpretation of the resulting numerical data led to the proposal of a simplified model that incorporates the effect of the flow rate, the hematocrit value (35-55%) and the vessel diameter (300-1800 μm) and predicts with better than ±10% the Fanning friction factor and consequently the pressure drop during laminar blood flow in small caliber vessels.

Background and Objectives: The burdened symptomatology accompanying advanced non-small cell lung cancer (NSCLC) is associated with poor prognosis and lower quality of life (QoL). Although both chemotherapy and immunotherapy increase survival, they are still associated with reduced functionality due to their toxicity. This study aimed to estimate the QoL and symptom burden of NSCLC patients receiving second-line chemotherapy compared to patients receiving second-line immunotherapy. Materials and Methods: This comparative, prospective study, conducted from January 2020 to December 2021, included 111 NSCLC patients who were divided into two groups: 61 patients receiving second-line chemotherapy and 50 patients receiving second-line immunotherapy. Patients QoL and symptom burden were estimated using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ C-30) (value range 0 - 100) from treatment cycle 1 to 6. Results: The QoL (mean score > 50) and functionality dimensions (mean score > 50) were moderate to good in both treatment groups, while the symptoms burden did not appear to be a serious problem (mean score < 50). From cycle 3 to cycle 5, the QoL was significantly better in the immunotherapy group. From cycle 3, role and social functioning scores were higher in the immunotherapy group, while emotional and cognitive functioning were higher from cycle 2 (p < 0.05). The chemotherapy group experienced higher levels of nausea/vomiting, constipation and financial difficulties in all cycles (p < 0.05). Fatigue and appetite loss were significantly greater from cycle 2 and insomnia was significantly greater from cycle 3. On the contrary, the immunotherapy group experienced higher levels of diarrhea in cycles 5 and 6 (p < 0.05). Conclusions: Although both therapy groups did not report significantly impaired QoL and severe symptoms, it seems that QoL improved in the immunotherapy group, which reported less symptom burden compared to the chemotherapy group.

Objectives: This study investigated the efficacy and safety of performing phacoemulsification using the eight-chop technique with iris hooks in patients with small pupils. Methods: The iris hooks and control groups each included 65 eyes. Cataract surgeries were performed using the eight-chop technique. The operative time, phaco time, aspiration time, cumulative dissipated energy, and volume of fluid used were measured. Best-corrected visual acuity, corneal endothelial cell density (CECD), and intraocular pressure (IOP) were measured preoperatively and postoperatively. Results: In total, 130 eyes of 107 patients (mean age, 75.9 ± 7.1 years; 58 men, 72 women) with cataracts were evaluated. The mean operative time, phaco time, aspiration time, cumulative dissipated energy, and volume of fluid used were 10.6 min, 20.7 s, 101.1 s, 7.8, and 38.0 mL, respectively, in the iris hooks group and 4.6 min, 16.2 s, 72.1 s, 7.0, and 28.9 mL, respectively, in the control group. The decrease in CECD at 19 weeks postoperatively was 2.1% and 1.2% for the iris hooks and control groups, respectively. In both groups, IOP decreased significantly (all p &lt; .01) at 7 and 19 weeks postoperatively. No intraoperative complications were observed in either group. Conclusions: The eight-chop technique using iris hooks resulted in a small postoperative reduction in CECD and excellent values for intraoperative outcome measures. In addition, those cataract surgeries were very short, efficient, and safe, without complications. The eight-chop technique using iris hooks could provide an ideal solution for patients with small pupils.

Artificial Intelligence (AI) is fundamentally reshaping various industries by enhancing decision-making processes, optimizing operations, and unlocking new opportunities for innovation. This paper explores the applications of AI across four key sectors: healthcare, finance, manufacturing, and retail. Each section delves into the specific challenges faced by these industries, the AI technologies employed to address them, and the measurable impact on business outcomes and societal welfare. We also discuss the implications of AI integration, including ethical considerations, the future trajectory of AI development, and its potential to drive economic growth while posing challenges that need to be managed responsibly.

In response to the problem of poor detection ability of object detection models for small-scale targets in intelligent transportation scenarios, a fusion method is proposed to enhance the features of small-scale targets, starting from feature utilization and fusion methods. The algorithm is based on the YOLOv4 tiny framework and enhances the utilization of shallow and mid level features on the basis of FPN, improving the detection accuracy of small and medium-sized targets; In view of the problem that the background of the intelligent traffic scene image is cluttered and there is more redundant information, the CBAM attention module is used to improve the attention of the model to the traffic target; To address the problem of data imbalance and prior bounding box adaptation in custom traffic datasets that expand traffic images in COCO and VOC, we propose a Copy Paste method with improved generation method and a K-means algorithm with improved distance measurement to enhance the model's detection ability for corresponding categories. Comparative experiments were conducted on a customized 260 thousand traffic dataset containing public traffic images, and the results showed that compared to YOLOv4 tiny, the proposed algorithm improved mAP by 4.9% while still ensuring the real-time performance of the model.

Despite polycarbonate (PC) being a widely used engineering plastic, its notch and crack sensitivity pose challenges in critical applications. To address this, PC was blended with elastomeric polymers to explore the improvement in toughness. This study systematically investigates the toughening mechanisms of PC blended with acrylonitrile-butadiene-styrene (ABS), copolyether ester elas-tomer (COPE), and ABS and styrene-ethylene-butylene-styrene (SEBS) copolymer grafted with maleic anhydride (MA). The morphology and mechanical behavior were evaluated under qua-si-static and high-speed tensile tests and Charpy impact tests using optical, electronic, and atomic force microscopy and Raman spectroscopy. The morphological analysis reveals cavitation and crazing phenomena for COPE and SEBS-g-MA systems, and mostly debonding for ABS, indicating an improvement in toughening. While the addition of ABS improves the PC plastic deformation, modifying ABS with maleic anhydride enhances the elastic modulus. Blending PC with SEBS-g-MA increases the strain at break, and the addition of COPE significantly improves the deformation behavior of PC (by around 115%). This comparative study provides valuable insights into the performance of different PC-elastomer blends under similar conditions, supporting the selection of appropriate materials for given applications.

The study is aimed at developing a resilient benchmarking system for small hotels in Ukraine, designed to ensure their survival and growth amid global disruptions and local crises. Given the severe challenges associated with the COVID-19 pandemic and military actions, the resilience of the regional tourism business becomes particularly relevant. The methods used in the study, including factor and cluster analysis, the method of taxonomy, and dendrograms, have enabled the development of development programs for two clusters of hotels: those located in areas with increased military risk and those in relatively safe territories. The taxonomic analysis revealed significant differences in managerial practices and operational efficiency, largely determined by the geographic location of the hotels. Hotels in active combat zones experience a 40% reduction in tourist flow and financial instability, while hotels in safe areas demonstrate a 30% higher level of customer satisfaction. The application of advanced security systems and modern marketing techniques has led to a 40% reduction in incidents.

(Background) Canine mammary tumors (CMT) have emerged as an important model for understanding pathophysiological aspects of human disease. Liquid biopsy (LB), which relies on blood-borne biomarkers and offers minimal invasiveness, holds promise for reflecting the disease status of patients. Small extracellular vesicles (SEVs) and their protein cargo have recently gained attention as potential tools for disease screening and monitoring. (Objectives) This study aimed to isolate SEVs from canine patients and analyze their proteomic profile to assess their diagnostic and prognostic potential. (Methods) Plasma samples were collected from female dogs grouped into CMT (malignant and benign), healthy controls, relapse, and remission groups. SEVs were isolated and characterized using ultracentrifugation (UC), nanoparticle tracking analysis (NTA) and transmission electron microscopy (TEM). Proteomic analysis of circulating SEVs was conducted using Liquid Chromatography–Mass Spectrometry (LC–MS). (Results) While no significant differences were observed in the concentration and size of exosomes among the studied groups, proteomic profiling revealed important variations. Mass spectrometry identified exclusive proteins that could serve as potential biomarkers for mammary cancer. These included Inter-alpha-trypsin inhibitor heavy chain (ITIH2 and ITI4), phosphopyruvate hydratase or alpha enolase (ENO1), eukaryotic translation elongation factor 2 (eEF2), actin (ACTB), transthyretin (TTR), beta-2-glycoprotein 1 (APOH) and gelsolin (GSN) found in female dogs with malignant tumors. Additionally, Vitamin D-binding protein (VDBP), also known as group-specific component (GC), was identified as a protein present during remission. (Conclusion) The results underscore the potential of proteins found in SEVs as valuable biomarkers in CMT. Despite the lack of differences in vesicle concentration and size between the groups, the analysis of protein content revealed promising markers with potential applications in CMT diagnosis and monitoring. These findings suggest a novel approach in the development of more precise and effective diagnostic tools for this challenging clinical condition.

A multimodal detection system with complementary capabilities for efficient detection was developed for impurity detection. The system consisted of a visible light camera, a multispectral camera, image correction and registration algorithms. It can obtain spectral feature and color feature at the same time, and has higher spatial resolution than a single spectral camera. This system was applied to detect impurities in Pu ’er tea to verify its high efficiency. The spectral and color features of each pixel in the images of Pu ’er tea were obtained by this system and used for pixel classification. The experimental results show that the accuracy of Support Vector Machine (SVM) model based on combined features is 93%, which is 7% higher than that based on only spectral features. By applying median filtering algorithm and contour detection algorithm to the label matrix extracted from pixel-classified images, 8 impurities except hair were detected successfully. Moreover, taking advantage of the high resolution of visible light camera, small impurities can be clearly imaged. By comparing the segmented color image with the pixel-classified image, small impurities such as hair could be detected successfully. Finally, it is proved that the system can obtain multiple images to allow a more detailed and comprehensive understanding of the detected items, and has excellent ability to detect small impurities.

In this paper, four probability functions are compared with the purpose of establishing a methodology to improve the accuracy of the estimated wind energy in a desert city in northwestern Mexico. For the statistical modeling, 3 time series of wind speed data were used, corresponding to the years 2017, 2018, and 2019, recorded with a sonic anemometer at a sampling frequency of 10 Hz. From these, the analysis is performed with different stationarity periods (5, 30, 60, and 600 seconds). The estimation of the parameters characterizing the probability density functions was performed using different methods; the statistical models were evaluated by the coefficient of determination and the Nash-Sutcliffe efficiency coefficient, while their accuracy by the measured quadratic error, the mean square error, the mean absolute error, and the mean absolute percentage error. It was found that Weibull with the energy pattern factor method and Gamma using the method of moments were the probability density functions that best describe the statistical behavior of the wind speed and, therefore, better estimate the energy generated, so it is concluded that the proposed methodology will allow having greater confidence, both in the estimation of the wind speed and in the small wind energy available for its use.

A systematic review and meta-analysis were conducted to estimate the prevalence of chlamydiosis in small ruminants. The study included 133 publications that reported the presence of Chlamydia abortus in 109 and 74 studies in sheep and goats from 45 countries. The prevalence of chlamydiosis was estimated at global, regional, and national levels using meta-analyses of proportions. Meta-regression and cumulative meta-analyses were also performed. Globally, the prevalence of chlamydiosis in sheep and goats was estimated at 20.1% (95% CI: 17.8-22.4) and 14.4% (11.6-17.4), respectively. For sheep, chlamydiosis prevalence was heterogeneous at regional and national levels. South Asia had the highest prevalence (30.6%) and East Asia and Pacific the lowest (14.0%). Nationally, chlamydiosis was more prevalent in Romania, Hungary, and Germany (range 53.3-87.0%) compared to Costa Rica, Australia, and Zimbabwe (4.7-5.2%). Among goats, chlamydiosis prevalence was similar across regions (10.4-19.7%), but varied significantly among countries, 0.0% in Romania and Australia and 91.7% in Bosnia and Herzegovina. In both species, sample size, number of diagnostic techniques, and latitude were significant covariates. Prevalence varied widely in the first decades of publications before stabilizing. Our study found a high prevalence of chlamydiosis in small ruminants, with the pathogen being distributed globally but heterogeneously across countries.

Renewable Energy Communities (RECs), strongly sustained by the European Community as a viable way to fasten low carbon transition, slowly develop in Italy for regulatory . This study delves into the framework of RECs and explores the perspective of the specifically small and medium industries in the Lombardy region of Italy through a survey. Our findings reveal that while SMEs exhibit interest in RECs, there is a notable gap in knowledge and engagement. We argue that the active involvement of Public Administration Bodies (PABs) is crucial in disseminating information about RECs and highlighting their benefits. The survey results, elaborated through a non-parametric test (Mann-Whitney U test) indicate that PABs play a pivotal role in influencing SMEs' perceptions and willingness to participate in RECs. The data suggest that more direct and effective communication strategies by PABs could significantly enhance SMEs' understanding and involvement in RECs. This research underscores the need for targeted and strategic efforts by PABs to foster a more informed and proactive approach among SMEs towards renewable energy initiatives. Such endeavors could be instrumental in accelerating the adoption of RECs, contributing to a more sustainable and resilient energy future.

We study electrohydrodynamic (EHD) linear (in)stability of microfluidic channel flows, i.e. the stability of interface between two-shearing viscous (perfect) dielectrics exposed to an electric field in large aspect ratio microchannels. We then apply our results to particular microfluidic systems known as electroosmotic (EO) pumps. Our results are detailed analytical expressions for the growth rate of two-dimensional EHD modes in Couette-Poiseuille flows in the limit of small Reynolds number ($R$); the expansions to both zeroth- and first-order-$R$ are considered. The growth rates are complicated functions of viscosity-, height-, density- and dielectric-constant ratio, as well as of wavenumbers and voltages, and to our knowledge have not been presented before in literature. To make the results more useful, e.g., for voltage-control EO pump operations, we also derive equations for the impending voltages of the neutral stability curves that divide stable from unstable regions in voltage-wavenumber stability diagrams. The voltage equations and the stability diagrams are given for all wavenumbers. We finally outline the flow regimes in which our first-order-$R$ voltage corrections could potentially be experimentally measured. Our work gives the insight into the coupling mechanism between electric field and shear flow in parallel-planes channel flows, correcting an erroneous attempt from literature. Our general analysis enables us also to refine the renowned instability mechanism due to viscosity stratification, i.e., the case of pure shear instability, when the first-order-$R$ voltage correction equals zero.

In recent times, a great interest has been motivated in plant-derived compounds known as phytochemicals. The pentacyclic oleanane-, ursane-, lupane-type triterpenes are phytochemicals that exert significant activities against diseases like cancer. Lung cancer is the leading cause of cancer-related death worldwide. Although chemotherapy is the treatment of choice for lung cancer, its effectiveness is hampered by the dose‐limiting toxic effects and chemoresistance. Herein, we investigated the structure-activity relationship of six pentacyclic triterpenes: oleanolic acid (OleA), ursolic acid (UrA), asiatic acid (AsA), betulinic acid (BeA), betulin (Betu), lupeol (Lupe), on NSCLC A549 cells. From our studies, we confirmed that all these triterpenes showed cytotoxicity in the mid µM range, where BeA showed the strongest effect. Then, we determined that most of these triterpenes induced S-phase and G2/M phase cycle arrest, reactive oxygen species, mitochondrial depolarization, and caspase 3 activation. For chemoresistance markers, we elucidated that most triterpenes downregulated STAT3 and PDL1 genes. In contrast, ursane-type UrA and AsA also induced DNA damage, reactive nitrogen species and autophagy. These results showed that even slight structural changes in these triterpenes can influence the cellular response and mechanistic pathways. This study opens promising perspectives for further research on the pharmaceutical role of phytochemical triterpenoids.

Abstract Background: Small Cajal body-specific RNAs (scaRNAs) are a specific subset of small nucleolar RNAs (snoRNAs) that have recently been emerged as pivotal contributors in diverse physiological and pathological processes. However, their defined roles in carcinogenesis remain largely elusive. This study aims to explore the potential function and mechanism of SCARNA12 in bladder cancer (BLCA) and to provide a theoretical basis for further investigations into the biological functionalities of scaRNAs. Materials and Methods: TCGA, GEO and GTEx data sets were used to analyze the expression of SCARNA12 and its clinicopathological significance in BLCA. Quantitative real-time PCR (qPCR) and in situ hybridization were applied to validate the expression of SCARNA12 in both BLCA cell lines and tissues. RNA sequencing (RNA-seq) combined with bioinformatics analyses were conducted to reveal the changes of gene expression patterns and functional pathways in BLCA patients with different expression of SCARNA12 and T24 cell lines upon SCARNA12 knockdown. Single-cell mass cytometry (CyTOF) was then used to evaluate the tumor-related cell cluster affected by SCARNA12. Moreover, SCARNA12 was stably knocked down in T24 and UMUC3 cell lines by lentivirus-mediated CRISPR/Cas9 approach. The biological effects of SCARNA12 on the proliferation, clonogenic, migration, invasion, cell apoptosis, cell cycle and tumor growth were assessed by in vitro MTT, colony formation, wound healing, transwell, flow cytometry assays and in vivo nude mice xenograft models, respectively. Finally, chromatin isolation by RNA purification (ChIRP) experiment were further conducted to delineate the potential mechanisms of SCARNA12 in BLCA. Results: The expression of SCARNA12 was significantly up-regulated in both BLCA tissues and cell lines. RNA-seq data elucidated that SCARAN12 may play a potential role in cell adhesion and extracellular matrix (ECM) related signaling pathways. CyTOF results further showed that an ECM-related cell cluster with vimentin+, CD13+, CD44+, CD47+ was enriched in BLCA patients with high SCARNA12 expression. Additionally, SCARNA12 knockdown significantly inhibited the proliferation, colony formation, migration, and invasion abilities in T24 and UMUC3 cell lines. SCARNA12 knockdown prompted cell arrest in the G0/G1 and G2/M phase, and promoted the apoptosis in T24 and UMUC3 cell lines. Furthermore, SCARNA12 knockdown could suppress the in vivo tumor growth in nude mice. ChIRP experiment further suggested that SCARNA12 may combine transcription factors H2AFZ to modulate transcription program and then affect BLCA progression. Conclusion: Our study is the first to propose aberrant alteration of SCARNA12 and elucidate its potential oncogenic roles in BLCA via the modulation of ECM signaling. The interaction of SCARNA12 with the transcriptional factor H2AFZ emerges as a key contributor to the carcinogenesis and progression of BLCA. These findings suggest SCARNA12 may serve as a diagnostic biomarker and potential therapeutic target for the treatment of BLCA.

Wool quality and yield are important economic traits of livestock. In this study, the skin tissues of the upper scapula of Super Merino sheep (SM) and Small-Tailed Han sheep (STH) during the growing period were studied. Differentially expressed (DE) long non-coding RNAs (lncRNAs) and messenger RNAs (mRNA) were identified via histopathological observation and high-throughput RNA sequencing. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze differentially expressed genes. Reverse transcription quantitative Polymerase Chain Reaction (RT-qPCR) was used to verify nine selected DE lncRNAs and five DE mRNAs. Significant differences were found in the expression levels of LOC114113396 (KRTAP15-1), CRABP1, KRT10, KRTAP1-3, KRTAP4.3, KRT2, FGF1, IGF-1, and KIT in SM and STH skin tissues. These results indicate that these mRNAs may play an important role in the growth and development of hair follicles and the regulation of hair fiber traits. Differentially expressed lncRNA target genes and mRNAs were mainly enriched in biological processes and pathways related to skin development and fiber traits, which is consistent with previous studies. LncRNA MSTRG.9225.1, MSTRG.124320.1, MSTRG.96951.1, MSTRG.91685.1, MSTRG.122229.1, MSTRG.89255.1, MSTRG.98769.1, and MSTRG.84658.1 may indirectly participate in the growth and development of sheep hair follicles and the regulation of hair fiber diameter by regulating the expression of their respective target genes. These candidate lncRNAs and mRNAs may provide a basis for the study of sheep hair follicle growth and development and hair fiber traits.

Detecting rotational objects in remote sensing imagery is a significant challenge. These images typically encompass a broad field of view, featuring diverse and intricate backgrounds, with ground objects of various sizes densely scattered. As a result, identifying objects of interest within these images is a daunting task. While the integration of Convolutional Neural Networks (CNN) and Transformer networks leads to some advancements in rotational object detection, there is still room for improvement, particularly in enhancing the extraction and utilization of information related to smaller objects. To address this, our paper presents a multi-scale feature fusion module and a global feature context aggregation module. Initially, we fuse original, shallow, and deep features to reduce the loss of shallow feature information, thereby improving the detection performance of small objects in complex backgrounds. Subsequently, we compute the correlation of contextual information within feature maps to extract valuable insights. We name the newly proposed model the "Multiscale Feature Context Aggregation Module" (MFCA). We evaluate our proposed methodology on three challenging remote sensing datasets: DIOR-R, HRSC, and MAR20. Comprehensive experimental results show that our approach surpasses baseline models by 2.07\% mAP, 1.02\% mAP, and 1.98\% mAP on the DIOR-R, HRSC2016, and MAR20 datasets, respectively.

Mercury emissions from small-scale coal-fired boilers are still a serious environmental problem in Poland and the Czech Republic. The publication presents the results of mercury emission tests conducted using five different small-scale coal-fired boilers and five different coal fuels. The research was carried out under laboratory conditions, but also using residential users' heating devices. They covered a wide range of operational parameters, both energy and emission. It was shown that more than 94% of the mercury contained in coal fuel undergoing combustion is emitted into the atmosphere with the volatile products of combustion (including dust), and the amount of emissions is strongly dependent on the original mercury content of the fuel. One solution to the problem of mercury emissions from small-scale coal-fired boilers may be to replace traditional coal with low-emission carbon fuels. The paper shows that mercury emissions from burning such fuels are many times lower than from burning coal. The widespread use of low-emission carbon fuels in individual heating systems in Poland and the Czech Republic would reduce mercury emissions to the atmosphere by up to 90% compared to the current level of emissions generated by individual heating systems in these countries.

The images captured by UAVs during inspection often contain numerous small targets related to transmission lines, which are critical and vulnerable elements for ensuring the safe operation of these lines. However, due to various factors such as the small size of the targets, low resolution, complex background, and potential line aggregation, achieving accurate and real-time detection becomes challenging. To address these issues, this paper proposes a detection algorithm called P2-ECA-EIOU-YOLOv5 (P2E-YOLOv5). Firstly, in order to address the challenges posed by the complex background and environmental interference that impact small targets, an ECA attention module is integrated into the network. This module effectively enhances the network's focus on small targets while concurrently mitigating the influence of environmental interference. Secondly, considering the characteristics of small target size and low resolution, a new high-resolution detection head is introduced, which is more sensitive to small targets. Lastly, the network utilizes the EIOU-Loss as the regression Loss function to improve the positioning accuracy of small targets, as they tend to aggregate. Experimental results demonstrate that the proposed P2E-YOLOv5 detection algorithm achieves an accuracy P of 96.0% and an average accuracy (mAP) of 97.0% for small target detection in transmission lines.

Infrared detection plays an important role in the military, aerospace, and other fields, which has the advantages of all-weather, high stealth, and strong anti-interference. However, infrared dim small target detection suffers from complex backgrounds, low signal-to-noise ratio, blurred targets with small area percentages, and other challenges. In this paper, we proposed a multiscale YOLOv5-AFAM algorithm to realize high-accuracy and real-time detection. Aiming at the problem of target intra-class feature difference and inter-class feature similarity, the Adaptive Fusion Attention Module - AFAM was proposed to generate feature maps that are calculated to weigh the features in the network and make the network focus on small targets. This paper proposed a multiscale fusion structure to solve the problem of small and variable detection scales in infrared vehicle targets. In addition, the downsampling layer is improved by combining Maxpool and convolutional downsampling to reduce the number of model parameters and retain the texture information. For multiple scenarios, we constructed an infrared dim and small vehicle target detection dataset, ISVD. The multiscale YOLOv5-AFAM was conducted on the ISVD dataset, compared to YOLOv7, mAP@0.5 achieves a small improvement while the parameters are only 17.98% of it. By contrast with the YOLOv5s model, mAP@0.5 was improved by 4.3% with a 6.6% reduction in the parameters. Experiments results demonstrate that the multiscale YOLOv5-AFAM has a higher detection accuracy and detection speed on infrared dim and small vehicles.

We describe the behavior of mixtures of stearic acid (SA) and its hydroxylated counterpart 12-hydroxystearic acid (12-HSA) in aqueous mixtures at room temperature, as function of the 12-HSA/(fatty acid) mole ratio R. The morphologies of the self-assembled aggregates are obtained by a multi-structural approach that combines confocal and cryo-TEM microscopies with Small-Angle Neutron Scattering (SANS) and Wide-Angle X-Rays Scattering (WAXS) measurements, coupled with rheology measurements. Fatty acids are solubilized by an excess of ethanolamine counterions, so that their heads are negatively charged. The behavior is driven by the competition between mixing entropy and enthalpic effects. A clear trend towards partitioning between the two types of fatty acids is observed, presumably driven by the favorable formation of a H-bond network between hydroxyl OH function on the 12th carbon. For all R, the self-assembled structures are locally lamellar, with bilayers composed of crystallized and strongly interdigitated fatty acids. At high R, multi-lamellar tubes are formed, similarly as for pure aqueous solutions of 12-HSA. The doping by a low amount of SA molecules only slightly modify the dimensions of the tubes (radius and length), and slightly decreases the bilayers rigidity. The solutions have a gel-like behavior originating from entanglements between tubes and show a yield stress. At intermediate R, a partial local partitioning occurs between the two types of fatty acids. The tubes coexist in solution with helical ribbons. The two structures possibly merge to form very long snaky objects with straight and curved parts. The rigidity of the bilayers and the rheological behavior of the solutions are very similar to those of the high R case. At low R, local partitioning also occurs, and the architecture of the self-assemblies associates the two morphologies of the pure fatty acids systems, respectively 2-D planar bilayers for SA and the tubes describe above for the 12-HSA molecules: they are facetted objects with planar domains enriched in SA molecules, capped with curved domains enriched in 12-HSA molecules. The rigidity of the bilayers is strongly increased, as well their storage modulus, compared to systems with larger R. The solutions remain however viscous fluids in this regime of low R.

Small hydro-power systems seem to be the best solution for energy generation through the use of pump as turbine (PAT) due to its low cost and lesser environmental hazards associated with it. Recently, PAT applications are gaining global attention in energy generation but its operation is not fully understood. The performance and flow behavior is affected by several operational conditions. This study seeks to investigate the effects of rotational speed on flow behavior and performance of a PAT. Rotational speed is an important physical parameter that affects the operation of a PAT. A selected centrifugal pump model of four blades and splitters was used for the study. Numerical simulations were carried out using k-ε turbulence model to solve the three-dimensional (3D) equations in both pump and PAT modes. The outcomes were then validated using experimental results in the pump mode to obtain overview flow physiognomies. The results predicted that the efficiency increases as the rotational speed increases in the pump mode whereas in turbine mode, higher rotational speed cannot convert hydraulic energy into mechanical energy. Thus, a rotational speed of 1500 rpm performed the highest efficiency of 69.8% at QBEP among the other rotational speeds selected. Moreover, the head performance in the turbine mode increases as the flow rate increases. This research provides useful information which will help improve PAT performance as well as selecting PAT for small hydro-power site.

Small rodents and insectivores are potential reservoirs of many pathogens transmissible to humans such as bacteria, parasites and viruses responsible for epidemics in sub-Saharan Africa, particularly in West Africa. Few studies on small mammal species in the Kolikoro and Sikasso regions are available, hence the interest in investigating the different species of small rodents and insectivores, and their role in the transmission of pathogens to humans. The study aims to identify commensal small mammal species circulating in Faladjè and Bougouni areas, and likely to represent major risks of epidemic disease emergence. Sessions of trapping were carried out in December 2016 in Faladjè and Bougouni with wire mesh traps type “Besançon tous services” (BTS) baited with peanut butter and/or onion. All animals captured were identified morphologically. Out of 123 small rodents and insectivores captured in 674 trap nights, 75 (60.97%) were from Faladjè and 48 (39.02%) from Bougouni, Of these, six species of small rodents belong to the family Muridae (Mastomys erythroleucus, Mastomys natalensis, Rattus rattus, Praomys daltoni, Gerbilliscus gambianus, Taterillus gracilis) and two species of insectivores associated with the genus Crocidura spp. belong to the family Soricidae and Erinaceidae (Crocidura cf olivieri and Atelerix cf albiventris) respectively. There is low specific diversity within these two stands, but the variation in relative abundance is significant (binomial test, p = 0.018 ˂ 0.05) between the Faladjè and Bougouni stands of small mammals. Mastomys erythroleucus was the most dominant species (57.33%, 43/75) in the Faladjè settlement and R. rattus dominated (37.5%,18/48) that of Bougouni. These two species of small mammals are potentially involved in the transmission of bacteria, parasites and pathogenic viruses to humans.

The ever-growing repertoire of genomic techniques continues to expand our understanding of true diversity and richness of prokaryotic genomes. Riboproteogenomics laid the foundation for dynamic studies of previously overlooked genomic elements. Most strikingly, bacterial genomes were revealed to harbour robust repertoires of small open reading frames (sORFs) encoding a diverse and broadly expressed range of small proteins, or sORF-encoded polypeptides (SEPs). In recent years, continuous efforts led to great improvements in annotation and characterization of such proteins, yet many challenges remain to fully understand the pervasive nature of small proteins and their impact on bacterial biology. In this work we review recent developments in the dynamic field of bacterial genome reannotation, catalogue important biological roles carried out by small proteins and identify challenges obstructing the way to full understanding of these elusive proteins.

Resolving small molecule mixtures by nuclear magnetic resonance (NMR) spectroscopy has been of great interest for a long time for its precision, reproducibility and efficiency. However, spectral analyses for such mixtures are often highly challenging due to overlapping resonance lines and limited chemical shift windows. The existing experimental and theoretical methods to produce shift NMR spectra in dealing with the problem have limited applicability owing to sensitivity issues, inconsistency and / or requirement of prior knowledge. Recently, we have resolved the problem by decoupling multiplet structures in NMR spectra by the wavelet packet transform (WPT) technique. In this work, we developed a scheme for deploying the method in generating highly resolved WPT NMR spectra and predicting the composition of the corresponding molecular mixtures from their 1H NMR spectra in an automated fashion. The four-step spectral analysis scheme consists of calculating WPT spectrum, peak matching with a WPT shift NMR library, followed by two optimization steps in producing the predicted molecular composition of a mixture. The robustness of the method was tested on an augmented dataset of 1000 molecular mixtures, each containing 3 to 7 molecules. The method successfully predicted the constituent molecules with a median true positive rate of 1.0 against the varying compositions, while a median false positive rate of 0.04 was obtained. The approach can be scaled easily for much larger datasets.

Mechanical recycling of solid plastic wastes on a small-scale level can be accomplished with the correct approaches. Thermoplastics are mostly considered for mechanical recycling because of their physical properties and ease of reprocessing. This paper reviews the mechanical reprocessing techniques of selected thermoplastics (polyethylene terephthalate and polyolefins) since they constitute a significant proportion of plastics used commercially. Furthermore, necessary considerations for effective operation of small-scale plants, including energy requirements of machinery and optimisation in order to improve efficiency and product quality, are discussed. A clearer understanding and addressing of the process-related challenges will lead to successful establishment and management of small-scale mechanical recycling facilities to benefit communities. Efficient small-scale mechanical reprocessing establishments have become essential in reducing the environmental impacts of solid plastic wastes and for energy conservation.

We describe the design and fabrication of an industrial injection moulding system which can be mounted and used on the NCD-SWEET Small-angle X-Ray Scattering Beamline at ALBA. We show how highly useful time-resolved data can be obtained using this system. We are able to evaluate the fraction of material in the mould cavity and identify the first material to solidify and how this varies with the injection tem-perature. The design follows current industrial practice and provides opportunities to collect time-resolved data at several points within the mould cavity so we can build up a 4D perspective of the morphology and its temporal development. The quantitative data obtained will prove invaluable for the optimisation of the next generation of in-jection moulding techniques. This preliminary work used results from the injection moulding of a general purpose isotactic polypropylene.

In northern Thailand, the problem of small particulate matter happens every year, with the pri-mary source being agricultural weed burning and wildfire. The tourism industry is strongly impacted and has been the spotlight for the past few years. Thus, the study aims to investigate the effect of small particulate matter on tourism and related SMEs in Chiang Mai, Thailand. The data was collected from 286 entrepreneurs in the tourism and related SMEs sectors. The data was analyzed using data mining and association rule techniques. The study revealed that small particulate matter has a considerable impact on customer factors, especially the number of customers has decreased. Operational factors and prod-uct/service factors are also affected by the dust in the form of adjustments to keep the business running and the protection of the health of employees and customers. Certainly, financial factors are affected by the small particulate matter situation, both lower revenues and higher costs.

MicroRNAs (miRNAs) are a class of small non-coding RNAs, which function as regulators of gene expression and contribute in numerous physiological processes. However, little is known referring to miRNAs function in insect chemosensation. In the current study, nine small RNA libraries were constructed and sequenced from the antennae of nymphs, adult males and females of Apolygus lucorum. In total, 399 miRNAs were identified including 275 known and 124 novel miRNAs. Known miRNAs were classified into 71 families, amongst which, 23 families were insect-specific. Expression profile analysis showed that miR-7-5p_1 was the most abundant miRNAs in the antennae of A. lucorum. Altogether, 69708 target genes related to biogenesis, membrane and binding activities were predicted for 399 miRNAs. Particularly, 15 miRNAs were found to target 16 olfactory genes. These miRNAs could be involved in regulation of olfactory-associated genes ex-pression. Comparing the antennae of nymphs, adult males and females, 94 miRNAs were found to be differentially expressed. The expression levels of some differentially expressed miRNAs measured by qPCR were consistent with sequencing results. This study provides a global miRNAs transcriptome in the antennae of A. lucorum and valuable information for further investigation on miRNA-mRNA interactions, especially the functions of miRNAs in regulating chemosensation.

HIV-1 Tat protein interacts with TAR RNA and recruits CDK9/cyclin T1 and other host factors to induce HIV-1 transcription. Thus Tat-TAR RNA interaction, which is unique for HIV-1, represents an attractive target for anti-HIV-1 therapeutics. To target Tat-TAR RNA interaction, we used a crystal structure of TAR RNA with acetylpromazine bound to the bulge of TAR RNA, to dock compounds from Enamine database containing 1.6 million individual compounds. Docking identified 173 compounds that were analyzed for the inhibition of HIV-1 infection. Top ten inhibitory compounds with IC50 ≤ 6 µM were selected and the three least toxic compounds, T6780107 (IC50=2.97 μM), T0516-4834 (IC50=0.2 μM) and T5628834 (IC50=3.46 μM), were further tested for HIV-1 transcription inhibition. Only T0516-4834 compound showed selective inhibition of Tat-induced HIV-1 transcription, whereas T6780107 compound inhibited equally basal and Tat-induced transcription and T5628834 compound only inhibited basal HIV-1 transcription. The T0516-4834 compound also showed strongest inhibition of HIV-1 gag RNA expression and p24 production in CEM T cells infected with HIV-1 IIIB. Of the three compounds, only the T0516-4834 compound disrupted Tat-TAR RNA interaction indicating that it might target TAR RNA. Also, of the three tested compounds, T5628834 but not T6780107 or T0516-4834 disrupted Tat-CDK9/cyclin T1 interaction. Taken together, our study identified novel compound T0516-4834 that disrupted Tat-TAR RNA interaction and inhibited Tat-induced transcription and HIV-1 infection suggesting that this compound might serve as a new lead for anti-HIV-1 therapeutics.

Higher-risk myelodysplastic syndrome (HR-MDS) has a poor prognosis in the absence of efficient therapy. The evaluation of new therapies in animal models of HR-MDS is hampered by the absence of accurate in vivo biomarkers of the disease. In this study we compared [18F]Fluoro-desoxyglucose Positron Emission Tomography (FDG-PET) and [18F]Fluoro-thymidine (FLT)-PET imaging for disease follow-up in a triple transgenic MMTVtTA/TetoBCL-2/MRP8NRASD12 mouse model of HR-MDS. Normal control FVB/N mice (G1,n=9) and HR-MDS mice (G2,n=12) underwent both FDG- and FLT-PET procedures at 2-day intervals, on a dedicated small animal device. Blood cell counting, BCL-2 and Mac-1hi/Gr-1lo expression measurements in blood were performed before each PET procedure. Visually, PET images of G2 mice demonstrated homogeneous FDG uptake in the whole skeleton similar to that observed in G1 mice, and abnormal FLT hot spots in bone marrow not observed in G1 mice. The intensity of FLT hot spots in bone marrow was higher in 3-months old G2 mice than in 2-months old G2 mice, concordant with a higher percentage of cells expressing Mac-1hi/Gr-1lo and lower platelets counts. We conclude that FLT-PET/CT imaging is a more valuable surrogate non-invasive quantitative marker of HR-MDS bone marrow involvement than FDG-PET/CT in our mouse model of HR-MDS.

In an insightful article published in Nature human behavior on November 2020, the effectiveness of 46 “non-pharmaceutical interventions” (NPI) regarding Covid-19 pandemic have been compared¹. One of these 46 categories, the one which is ranked as the most effective measure, is named “small gatherings cancelation”. In the discussion section of that article, the authors introduce a list of what they probably assume to be representative examples of this category, namely, “closures of shops”, “closure of restaurants,” “mandatory home–working”, “gathering of 50 people or less” and so on. The name that the authors have given to this category could give rise to confusions and misunderstandings. We used corpus analysis to show that “small gathering” is commonly used to denote a planned or spontaneous “event”, and consequently does not convey what the authors intend this term to cover as its most representative instances i.e., Simultaneous presence of people (crowd) in shops or offices. Furthermore, taking a top-down approach, we focused on the information which was provided in reference material like CDC and WHO documents. The analysis showed that “small gatherings” is encoded in those sources to denote “events” and “small gatherings cancelation” is used to denote cancelling preplanned events. In conclusion, neither unspecialized language nor official/institutional discourse uses “small gathering” the way that the authors of the aforementioned article use it i.e., to refer to simultaneous presence of people (crowd) in shops or offices. Therefore, when language users come across this phrase, if they do not read the entire article, the only semantic frame that is evoked in their mind would be that of a festive or social “event” rather than of crowded shops or offices; this misunderstanding is cognitively justified and consequently changing this terminology is recommended.

In the last years, more and more studies highlight the advantages of complementing traditional master classes with additional activities that improve students´ learning experience. This combination of teaching techniques is specially advised in the field of structural engineering, where intuition of the structural response it is of vital importance to understand the studied concepts. This paper deals with the introduction of a new (and more encouraging) educational tool to introduce intuitively students in the dynamic response of structures excited with an educational shaking table. Most of the educational structural health monitoring systems use sensors to determine the dynamic response of the structure. The proposed tool is based on a radically different approach, as it is based on low-cost image-recognition techniques. In fact, it only requires the use an amateur camera, a black background and a computer. In this study, the effects of both the camera location and the image quality are also evaluated. Finally, to validate the applicability of the proposed methodology, the dynamic response of small-scale buildings with different typologies is analyzed. In addition, a series of surveys were conducted in order to evaluate the activity based on student´s satisfaction and the actual acquisition and strengthening of knowledge.

Small Island States (SIDS) are among the nations most exposed to climate change (CC) and are characterised by a high degree of vulnerability. Their special nature means there is a need for more studies focused on the limits to CC adaptation on such fragile nations, particularly in respect of their problems and constraints. This paper addressed a perceived need for research into the limitations of adaptation on SIDS, focusing on the many restrictions which are unique to them. The main research question raised by this study was that how and to what extent the challenges by human activities (e.g., agriculture and tourism) posed to coastlines of SIDS could be addressed. This paper identified and described the adaptation limits they have, by using a review of the literature and an analysis of case studies from a sample of five SIDS in the Caribbean and Pacific regions (Barbados, Trinidad and Tobago, Cook Islands, Fiji, Solomon Islands, and Tonga). The findings of this research showed that an adaptable SIDS is characterised by awareness of various values, appreciation and understanding of a diversity of impacts and vulnerabilities, and acceptance of certain losses through change. The implications of this paper are two-fold. It explains why island nations continue to suffer from the impacts of CC, and suggest some of the means via which adequate policies may support SIDS in their efforts to cope with the threats associated with a changing climate. This study concluded that, despite the technological and ecological limits (hard limits) affecting natural systems, adaptation to CC is not only limited by such complex forces, but also by societal factors (soft limits) that could potentially be overcome by more adequate adaptation strategies.

Human cytomegalovirus (HCMV) is a leading cause of severe diseases in immunocompromised individuals, including AIDS and transplanted patients, and in congenitally infected newborns. The utility of available drugs is limited by poor bioavailability, toxicity, and emergence of resistant strains. Therefore, it is crucial to identify new targets of therapeutic intervention. Among the latter, viral protein-protein interactions are becoming increasingly attractive. Since dimerization of HCMV DNA polymerase processivity factor ppUL44 plays an essential role in the viral life cycle being required for oriLyt-dependent DNA replication, we performed an in silico screening and selected 18 small molecules (SMs) potentially interfering with ppUL44 homodimerization. Antiviral assays using recombinant HCMV TB40-UL83-YFP in the presence of the selected SMs led to the identification of four active compounds. The most active one, B3, also efficiently inhibited AD169 in plaque reduction assays and impaired replication of an AD169-GFP reporter virus and its ganciclovir-resistant counterpart to a similar extent. As assessed by Western blotting experiments, treatment of infected cells with B3 specifically reduced viral gene expression starting from 48 h post infection, consistent with activity on viral DNA synthesis. Therefore, inhibition of ppUL44 dimerization could represent a new class of HCMV inhibitors, complementary to those targeting the DNA polymerase catalytic subunit or the viral terminase complex.

Drug design is used for different applications of bioinformatics tools analyze DNA, genome, and sequence target region of a small organic molecule in order to understand the molecules of disease. Bioinformatics tools are identified a newly wide research field and minimize future risks through web servers and data mining. Clinical sample test performed with the bioinformatics tools as the biomedical detective. A particular structure and configuration of protein obliging in Drug design concluded Bioinformatics. This review bioinformatics tools and webserver will discuss functions of small organic molecules according to clinical pharmacology.

Importance: The COVID-19 pandemic is currently accelerating. Patients with locally advanced non-small cell lung cancer (LA-NSCLC) may require treatment in locations where resources are limited and the prevalence of infection is high. Patients with LA-NSCLC frequently present with comorbidities that increase the risk for severe morbidity and mortality from COVID-19. These risks may be further increased by treatments for LA-NSCLC. Observation: We present expert thoracic oncology multidisciplinary (radiation oncology, medical oncology, surgical oncology) consensus of alternative strategies for the treatment of LA-NSCLC during a pandemic. The overarching goals of these approaches are to reduce the number of visits to a healthcare facility, reduce the risk of SARS-CoV-2 exposure, and attenuate the immunocompromising effects of lung cancer therapies. Patients with resectable disease can be treated with definitive non-operative management if surgical resources are limited or the risks of perioperative care are high. Non-operative options include chemotherapy, chemoimmunotherapy, and radiation therapy with sequential schedules. The order of treatments may be based on patient factors and clinical resources. Whenever radiation therapy is delivered without concurrent chemotherapy, hypofractionated schedules are appropriate. For patients who are confirmed to have COVID-19, usually cancer therapies may be withheld until symptoms have resolved with negative viral test results. Conclusions and Relevance: The risk of severe treatment-related morbidity and mortality is significantly elevated for patients undergoing treatment for LA-NSCLC during the COVID-19 pandemic. Adapting alternative treatment strategies as quickly as possible may save lives and should be implemented through communication with the multidisciplinary cancer team.

After globalization, South Korea’s retail landscape has been saturated with large-scale, corporate type retails. However, recently new commercial districts composed of small retail units are returning and bringing about a change. This study sought to take note of this phenomenon and identify its features and meanings from the perspective of urban ecology. A density-distribution analysis was conducted to investigate how they were forms, and an analysis of traces on the Internet and an analysis on the types of businesses were done to identify sociocultural characteristics. Results showed that they had similar type of locations and growth patterns, that they harmoniously congregated in a form of smaller-individual stores, and that their use of similar names for their stores had an impact of branding their entire districts. It was also noted that a shared culture through social networking services served as a growth boost for their unfavorable location. The spontaneous formation of such commercial districts can be an outcome of an urban ecological process geared toward blank niches burgeoning in the current retail structure of Korea. The causes and conditions found in the cases reveal meaningful policy implications for cities facing the same urban crisis diversity.

Beta adrenoblockers is a large class of drugs mainly used to manage abnormal heart rhythms. Over the last couples of decades, the anticancer effects of these compounds has been extensively studied. There is much evidence about their activity in non-small cell lung, pancreatic, breast, colorectal, prostate and ovarian cancer. However, the mechanism of beta blockers anticancer activity is still not known, and more detailed studies are needed. The aim of our study was to evaluate the anticancer activity of beta adrenoblockers in non-small cell lung cancer cell lines A549 and H1299. In order to find the relationship with their selectivity to beta adrenoreceptors, in our study we used selective (atenolol, betaxolol, esmolol, metoprolol) and non-selective (pindolol, propranolol and timolol) beta blockers. The effect on cell viability was evaluated by MTT assay and the activity on cell ability to form colonies was tested by clonogenic assay. The type of cell death was evaluated by cell double staining with Hoechst 33342 and Propidium iodide. The most active adrenoblockers against both tested cancer cell lines were propranolol and betaxolol. They completely inhibited lung cancer cell colony formation at 90% of EC50 (half maximal effective concentration) value. Most tested compounds induced cell death through apoptosis and necrosis. In A549 cell lines apoptosis was mainly induced while in H1299 cell line compounds induced both apoptosis and necrosis. There was no correlation established between beta adrenoblocker anticancer activity and their selectivity to beta adrenoreceptors.

Since the 1970s, land subsidence has been developing rapidly in the Beijing Plain, the systematic study of its evolution mechanism is of great significance to the sustainable development of the regional economy. First, based on ENVISAT ASAT and RADARSAT2 data, the land subsidence data in Beijing Plain were obtained using permanent interferometer technology. Second, based on the GIS platform and using fishing net tools, vector data of ground settlement with different resolutions were obtained. Through a series of tests, a scale of 960 metres was selected as the research unit, and the subsidence rate of the grid was obtained from 2004 to 2015. Finally, based on the Mann-Kendall mutation test method, a trend analysis of land subsidence changes in various grids was carried out. The results showed that single-year mutation mainly distributed in the middle and lower parts of the Yongding River alluvial fan and the Chaobai River alluvial fan, mainly occurring in 2015, 2005 and 2013, respectively. The upper and middle alluvial fan of the Chaobai River, the vicinity of the emergency water source and the edge velocity of the groundwater funnel have undergone several sudden changes. Combined with hydrogeology, basic geological conditions and the impact of the South-to-North Water transfer project, we analysed the causes of the mutations in the grid. The research results can provide a basis for the study and prevention of land subsidence in this area and help to further explore the trend characteristics of land subsidence in this area.

Filamentous fungi such as Aspergillus spp. are opportunistic pathogens, which cause highly invasive infections, especially in immunocompromised individuals. Control of such fungal pathogens is increasingly problematic due to the small number of effective drugs available for treatment. Moreover, the increased incidence of fungal resistance to antifungal agents makes this problem a global human health issue. The cell wall integrity system of fungi is the target of antimycotic drugs echinocandins, such as caspofungin (CAS). However, echinocandins cannot completely inhibit the growth of filamentous fungal pathogens, which results in survival/escape of fungi during treatment. Chemosensitization was developed as an alternative intervention strategy, where co-application of CAS with the intervention catalyst octyl gallate (OG; chemosensitizer) greatly enhanced CAS efficacy, thus achieved ≥ 99.9% elimination of filamentous fungi in vitro. Based on hypersensitive responses of Aspergillus antioxidant mutants to OG, it is hypothesized that, besides destabilizing cell wall integrity, the redox-active characteristic of OG may further debilitate fungal antioxidant system.

In this paper, the spatial distribution of stony desertification characteristics and its influencing factors in Karst areas in different sampling scales are studied using a grid sampling method based on geographic information system (GIS) technology and geo-statistics, with the rock bareness rate obtained through sampling with 150m × 150m grids in the Houzhai River Basin being taken as the original data and five grid scales (300m × 300m, 450m × 450m, 600m × 600m, 750m × 750m, and 900m × 900m) as the subsample sets. The results show that the rock bareness rate does not vary much from one sampling scale to another while average values of the five sub-samples all fluctuate around the average value of the entire set. As the sampling scale is expanding, the maximum value and the average value of rock bareness rate are decreasing gradually, with a gradual increase in the coefficient of variability. In the scale of 150m × 150m, the areas of minor stony desertification, medium stony desertification, and major stony desertification in the Houzhai River Basin are 7.81 km2, 4.50 km2, and 1.87 km2, respectively. The spatial variability of stony desertification on small scales is influenced by many factors, and that on medium scales is jointly influenced by gradient, rock contents, and rock bareness rate. On large scales, the spatial variability of stony desertification is mainly influenced by soil thickness and rock bareness rate.

Small non-coding RNAs (sRNAs) are ubiquitously found in the three domains of life playing large-scale roles in gene regulation, transposable element silencing, and defense against foreign elements. While a substantial body of experimental work has been done to uncover function of sRNAs in Bacteria and Eukarya, the functional roles of sRNAs in Archaea are still poorly understood. Recently, high throughput studies using RNA-sequencing revealed that sRNAs are broadly expressed in the Archaea, comprising thousands of transcripts within the transcriptome during non-challenged and stressed conditions. Antisense sRNAs, which overlap a portion of a gene on the opposite strand (cis-acting), are the most abundantly expressed non-coding RNAs and they can be classified based on their binding patterns to mRNAs (3’ UTR, 5’ UTR, CDS-binding). These antisense sRNAs target many genes and pathways, suggesting extensive roles in gene regulation. Intergenic sRNAs are less abundantly expressed and their targets are difficult to find because of a lack of complete overlap between sRNAs and target mRNAs (trans-acting). While many sRNAs have been validated experimentally, a regulatory role has only been reported for very few of them. Further work is needed to elucidate sRNA-RNA binding mechanisms, the molecular determinants of sRNA-mediated regulation, whether protein components are involved, and how sRNAs integrate with complex regulatory networks.

In small-scale hydropower scheme, the most important component is electro-mechanical equipment. Since cost contribution of this component is high because hydrokinetic projects require negligible civil works. Turbine and alternator contribute major fraction of the hydrokinetic projects. Thus, there is a requirement to estimates the electromechanical equipment cost for the hydrokinetic hydropower scheme. The present paper investigates design parameters of the hydrokinetic turbines and intends to develop cost correlation which depends on most critical parameters of hydropower sites such as velocity and power capacity. In this present work, three zero head turbines are considered including straight blade Darrieus, two Stage Savonius, and Gorlov Helical. The size and cost of major components have been calculated based on material, manufacturing, research and design, and assembly costs. Based on cost and site parameters, cost correlation has been developed. The obtained cost has been validated with available zero head turbines in the market and installed projects. A techno-economic analysis has been carried out to select economical hydrokinetic turbine for river and canal application.

Artisanal and small-scale gold mining (ASGM) has been an important source of income for communities in the Madre de Dios River Basin in Peru for hundreds of years. However, in recent decades, the scale of ASGM activities in the region has increased dramatically, and exposures to a variety of occupational and environmental hazards related to ASGM, including mercury, are becoming more widespread. The aims of our study were to: (1) examine patterns in the total hair mercury level of human participants in several communities in the region and compare these results to the 2.2 µg/g total hair mercury level equivalent to the World Health Organization (WHO) Expert Committee of Food Additives (JECFA)’s Provisional Tolerable Weekly Intake (PTWI); and (2), to measure the mercury levels of paco (Piaractus brachypomus) fish raised in local aquaculture ponds, in order to compare these levels to the EPA Fish Tissue Residue Criterion of 0.3 µg Hg/g fish (wet weight). We collected hair samples from 80 participants in four communities (one control and three where ASGM activities occurred) in the region, and collected 111 samples from fish raised in 24 local aquaculture farms. We then analyzed the samples for total mercury. Total mercury levels in hair were statistically significantly higher in the mining communities than in the control community, and increased with increasing distance away from the Madre de Dios headwaters (as the crow flies), did not differ by sex, and frequently exceeded the reference level. Regression analyses indicated that higher hair mercury levels were associated with residence in ASGM communities. The analysis of paco fish samples found no samples that exceeded the EPA tissue residue criterion. Collectively, these results align with other recent studies showing that ASGM activities are associated with elevated human mercury exposure. The fish farmed through the relatively new process of aquaculture in ASGM areas appeared to have little potential to contribute to human mercury exposure. More research is needed on human health risks associated with ASGM to discern occupational, residential, and nutritional exposure, especially through tracking temporal changes in mercury levels as fish ponds age, and assessing levels in different farmed fish species. Additionally, research is needed to definitively determine that elevated mercury levels in humans and fish result from the elemental mercury from mining, rather than from a different source, such as the mercury released from soil erosion during deforestation events from mining or other activities.

One of the major concerns in structural health management (SHM) is the early detection of a growing crack. Using this, future damage due to crack propagation can be mitigated or eliminated by implementing proper repair and maintenance. Acoustic Emission (AE) is a non-destructive testing (NDT) method with potential applications for locating and monitoring fatigue cracks. The research presented in this paper focuses on SHM using AE. A novel AE signal analysis approach was proposed in order to detect crack initiation and assess small crack lengths. Experimental investigation indicated that initiation of a crack could be identified through the statistical analysis of the resulting features of the AE signals. A probabilistic AE-based model for small fatigue crack sizing was developed and the uncertainties of the model were estimated. In addition, a probabilistic model validation approach was implemented to confirm accurate estimation of the results. The outcome of this research can be used to evaluate the integrity of structures under fatigue loading. The proposed approach can also be applied as an approach to manage health and assess prognosis of structures.

Neuroendocrine neoplasms (NENs) comprise a heterogeneous group of rare malignancies mainly originated from hormones secreting cells, which are widespread in human tissues. The identification of mutations in ATRX/DAXX genes in sporadic NENs, as well as the high burden of mutations scattered throughout MEN-1 gene in both sporadic and inherited syndromes, provided new insights into the molecular biology of tumour development. Other molecular mechanisms, such as the NOTCH signaling pathway, have shown to play an important role in the pathogenesis of NENs. NOTCH receptors are expressed on neuroendocrine cells and generally, act as tumour suppressor proteins, but in some contexts can function as oncogenes. The biological heterogeneity of NENs suggests that to fully understand the roles and the potential therapeutic implications of gene mutations and NOTCH signaling in NENs, a comprehensive analysis of genetic alterations, NOTCH expression patterns and their potential roles across all NEN subtypes is required.

In aerial image object detection, small targets present significant challenges due to limited pixel information, complex backgrounds, and sensitivity to bounding box perturbations. To tackle these issues, we propose SO-RTDETR for small object detection. The model introduces a Cross-Scale Feature Fusion with S2 (S2-CCFF) module, a Parallelized Patch-Aware attention (PPA) module, and the Normalized Wasserstein Distance (NWD) loss function, leading to significant performance improvements. Specifically, the S2-CCFF module enhances small object information by incorporating an additional S2 layer, while SPDConv downsampling maintains key details and reduces computational cost. The CSPOK-Fusion mechanism integrates global, local, and large branch features, capturing multi-scale representations and effectively mitigating interference from complex backgrounds and occlusions, thereby enhancing the spatial representation of features across scales. The PPA module, embedded in the Backbone network, leverages multi-level feature fusion and attention mechanisms to retain and strengthen small object features, addressing the issue of information loss. The NWD loss function, by focusing on the relative positioning and shape differences of bounding boxes, increases robustness to minor perturbations, enhancing detection accuracy. Experimental results on the VisDrone and NWPU VHR-10 aerial datasets demonstrate that our approach outperforms state-of-the-art detectors.

Background Small intestinal neuroendocrine tumors (SI-NETs) are characterized by carcinoid syndrome and carcinoid heart disease (CHD). The aim of study was to identify early risk markers for carcinoid heart disease and survival in a prospective median-term follow-up setting. Methods We measured 5-HIAA, cumulative 5-HIAA exposure (Cum-5-HIAA) based on repeat measurements, proBNP, vascular function, hepatic tumor load and transthoracic echocardiography (TTE) were assessed at baseline and during median 5-year follow-up. Of 65 patients with SI-NETs; 54 patients underwent prospective follow-up. In addition, survival was evaluated during median follow-up of 6 years. Results At baseline three patients had CHD. During median follow-up of 5 years, two patients (4%) developed CHD. Cum-5-HIAA and proBNP correlated with CHD (Westberg Score, Spearman’s ρ = 0.32 and 0.31, respectively). Cum-5-HIAA had a superior diagnostic capability, predicting CHD in receiver operator characteristics analysis with AUC of 0.98 (95% CI: 0.94–1.00) and outperformed proBNP, chromogranin A (CgA), as well as individual serum 5-HIAA measurements (AUC = 0.75, 0.85, and 0.91, respectively). Minor changes in valve regurgitation were frequently detected but did not correlate with vascular function. In 29% of tricuspid and 30% of pulmonic valves regurgitation increased or decreased. CHD, hepatic tumor load, serum 5-HIAA, and elevated aortic pulse wave velocity (PWV) associated with increased mortality in SI-NET patients. Conclusions Cum-5-HIAA is a promising biomarker for CHD risk and outperformed other biomarkers. CHD and hepatic tumor load are strongest predictors of mortality. PWV is a novel predictor of survival. The incidence of CHD was small among the SI-NET patients, probably reflecting successful treatment regimens.

This study aims to enhance the detection and assessment of safety hazards in small-scale reservoir engineering using advanced image processing and deep learning techniques. Given the critical importance of small reservoirs in flood management, water supply, and ecological balance, the effective monitoring of their structural integrity is crucial. This paper developed a fully convolutional semantic segmentation method for hidden danger images of small reservoirs using an encoding-decoding structure, utilizing a deep learning framework of convolutional neural networks (CNNs) to process and analyze high-resolution images captured by UAVs. The method incorporated data augmentation and adaptive learning techniques to improve model accuracy under diverse environmental conditions. Finally, the quantification data of hidden dangers (length, width, area, etc.) was obtained by converting the image pixels to the actual size. Results demonstrate significant improvements in detecting structural deficiencies, such as cracks and seepage areas, with increased precision and recall rates compared to conventional methods, and the HHSN-25 network (Hidden Hazard Segmentation Network with 25 layers)proposed in this paper outperforms other methods. The main evaluation indicator mIoU of HHSN-25 is higher than other methods, reaching 87.00%, and Unet is 85.50%, Unet++is 85.55%. The proposed model achieves reliable real-time performance, allowing for early warning and effective management of potential risks. This study contributes to the development of more efficient monitoring systems for small-scale reservoirs, enhancing their safety and operational sustainability.

In recent years, Big Data (BD) has become a crucial tool for Small and Medium-sized Enterprises (SMEs), impacting their performance and growth in significant ways. This systematic literature review aims to analyze the effects of BD on SMEs by examining 93 research papers published from 2014 to 2024. Employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, the review focuses on key drivers and barriers to BD adoption, including business improvement, economic performance, and revenue growth. The methodology involved a comprehensive analysis of research methodologies used in the studies, addressing biases, gaps, and the need for diverse approaches. The findings reveal that while BD has led to notable enhancements in operational efficiency and revenue for many SMEs, challenges such as limited resources and technical expertise remain. A significant reporting bias was observed, with 47% of the literature comprising quantitative studies, followed by 28% case studies, while mixed-methods and qualitative studies were underrepresented (22% and 17%, respectively). This imbalance suggests a potential overemphasis on quantitative approaches, limiting the diversity of insights available. Addressing these biases is essential to fully harness the potential of BD for SMEs to drive innovation, enhance competitiveness, and achieve better performance in the increasingly data-driven business environment.

Building small populations mortality tables has great practical importance in actuarial applications. In recent years, several works in literature explored different methodologies to quantify and assess longevity and mortality risk, especially within the context of small populations: many models dealing with this problem usually use a two-population approach, modelling a mortality spread between a larger reference population and the population of interest, via likelihood-based techniques. To broaden the tools at actuaries’ disposal to build small population mortality tables, a general structure for a two-step two-populations model is proposed, its main element of novelty residing in a machine-learning based approach to mortality spread estimation. In order to obtain this, Contrast Trees and related Estimation Contrast Boosting techniques have been applied. A quite general machine learning-based model has then been adapted in order to generalize Italian actuarial practice in company tables estimation and implemented using data from Human Mortality Database. Finally, results from the ML-based model have been compared to those obtained from the traditional model.

The paper investigates the accuracy of the angular velocity estimation based on measurements of the components of the induction vector of the Earth's magnetic field. A comparative analysis of angular velocity estimates using the Boer formula, the derivative of the induction vector of the Earth's magnetic field and direct measurements of the components of the angular velocity vector using a gyroscopic sensor for the ISOI small spacecraft (SXC3-219) is carried out. The results obtained make it possible to investigate the accuracy of estimates of the angular velocity of a small spacecraft in various ways to improve the quality of its target tasks.

Traffic sign detection plays a pivotal role in autonomous driving systems. The intricacy of the detection model necessitates high-performance hardware. Real-world traffic environments exhibit considerable variability and diversity, posing challenges for effective feature extraction by the model. Therefore, it is imperative to develop a detection model that is not only highly accurate but also lightweight. In this paper, we proposed YOLO-ADual, a novel lightweight model. Our method leverages the C3Dual and Adown lightweight modules as replacements for CPS and CBL modules in YOLOv5. The Adown module effectively mitigates feature loss during downsampling while reducing computational costs. Meanwhile, C3Dual optimizes the processing power for kernel feature extraction, enhancing computation efficiency while preserving network depth and feature extraction capability. Furthermore, the inclusion of the CBAM module enables the network to focus on salient information within the image, thus augmenting its feature representation capability. Our proposed algorithm achieves a mAP@0.5 of 70.1% while significantly reducing the number of parameters and computational requirements to 51.83% and 64.73% of the original model, respectively. Compared to various lightweight models, our approach demonstrates competitive performance in terms of both computational efficiency and accuracy.

Public safety and intelligent surveillance systems critically depend on anomaly behavior detection for effective monitoring. In real-world pedestrian detection scenarios, prevalent challenges such as missed detections, complex background interference, and small target sizes hinder accurate anomaly identification. To address these issues, this study introduces YOLO-ABD, a lightweight method for anomaly behavior detection that integrates small target detection and channel shuffling. This method employs YOLOv8n as the baseline model, incorporating a small target detection mechanism in the Head part and utilizing GSConv convolution in the Backbone to enhance perceptual capability. Additionally, the SimAM attention mechanism is integrated to mitigate complex background interference, thereby improving target detection performance. Evaluation on the IITB-Corridor dataset demonstrated mAP50 and mAP50-95 scores of 89.3% and 60.6%, respectively. Generalization testing on the street-view-gdogo dataset further highlighted the superiority of YOLO-ABD over advanced detection algorithms, underscoring its effectiveness and generalizability. With a relatively small parameter count, YOLO-ABD presents an excellent lightweight solution for pedestrian anomaly behavior detection.

Commercial production of Choromytilus meridionalis (black mussel) and Mytilus galloprovincialis (Mediterranean mussel) contributes to half of the South African marine aquaculture production per year. However, limited ready-to-eat black mussel products are available. The aim of this preliminary study was to investigate the effects of storage (15 days at room temperature) on the total viable counts (TVC), coliforms, proximate composition, and fat oxidation (TBARS) of a small-scale kitchen-based ready-to-eat hot smoked black mussel product preserved with vegetable oil. Three batches of black mussel meat were smoked at 80ºC for 15 minutes. Half of each batch were packaged in sterile glass jars with heated (50ºC) vegetable oil and half without oil. Microbiological analyses were done at days 1, 3, 9 and 15. Proximate composition was determined at day 1 and TBARS at days 1 and 15. Coliforms for all samples throughout the storage period were undetected. TVC plates for mussels stored without oil had no growth at days 1 to 5, however, reached TVC > 5 log10.g-1 at day 15. TVC for mussels with oil increased from 0 at day 1 to > 5 log10.g-1 at day 3 and remained at counts > 5 log10.g-1. There was no significant difference (P > 0.05) in moisture, protein, and ash for mussels stored with oil and those without oil, while significant differences (P < 0.001) in total fat and carbohydrates (10.27 ± 2.10% and 6.80 ± 2.22% with oil, and 5.05 ± 1.49% and 10.59 ± 3.00% without oil) were detected. These differences were due to the presence of additional fats from the vegetable oil. TBARS at day 15 showed no significant difference (P > 0.05) between mussels stored with oil and those without oil. There were no significant differences in TBARS from day 1 to 15 for both oil and without oil. Small-scale kitchen-based smoked black mussels preserved without vegetable oil could be stored for up to 9 days at room temperature.

Connexins (Cxs) are transmembrane proteins that assemble into gap junction channels (GJCs) and hemichannels (HCs). Previous research supports the involvement of Rho GTPases and actin microfilaments in the trafficking of Cxs, formation of GJCs plaques, and regulation of channel activity. Nonetheless, it remains uncertain whether distinct types of Cxs HCs and GJCs respond differently to Rho GTPases or changes in actin polymerization/depolymerization dynamics. Our investigation revealed that inhibiting RhoA, a small GTPase that controls actin polymerization, or disrupting actin microfilaments with cytochalasin B (Cyto-B), resulted in reduced GJCs plaque size at appositional membranes and increased transport of HCs to non-appositional plasma membrane regions. Notably, these effects were consistent across different Cx types, since Cx26 and Cx43 exhibited similar responses despite having distinct trafficking routes to the plasma membrane. Functional assessments showed that RhoA inhibition and actin depolymerization decreased the activity of Cx43 GJCs while significantly increasing HCs activity. However, the functional status of GJCs and HCs composed of Cx26 remained unaffected. This study supports the hypothesis that RhoA, through its control of the actin cytoskeleton, facilitates the transport of HCs to appositional cell membranes for GJCs formation while simultaneously limiting the positioning of free HCs at non-appositional cell membranes, independently of Cx type. This dynamic regulation promotes intercellular communication and reduces non-selective plasma membrane permeability through a Cx-type dependent mechanism, whereby Cx43 HCs and GJCs are affected, but Cx26 channels are not.

Results from the phase III Keynote-024 clinical trial have established Pembrolizumab monotherapy as the first-line standard of care for patients with metastatic NSCLC who have PD-L1 expression ≥ 50%, EGFR and ALK wild-type. However, given the differences between patients treated in routine clinical practice and within a clinical trial, real-world data are needed to confirm the treatment benefit in standard practice. Given the lack of data on large cohorts of patients with long follow-up, we designed a retrospective observational study of patients with NSCLC who were treated with Pembrolizumab, starting from its reimbursement eligibility until December 2020. The primary endpoints were to assess PFS and OS using the Kaplan-Meier method, treatment response and safety. We followed 880 patients (median follow-up: 35.1 months) until February 2022. Median PFS and OS were 8.6 months (95% CI: 7.6-10.0) and 25.5 months (95% CI: 21.8-31.6), respectively. We also found that ECOG PS, PD-L1 expression and smoking habit were prognostic factors for PFS, while age, sex, ECOG PS, smoking habit and histology had an impact on OS. Multivariable analysis confirms prognostic role of PD-L1 for PFS and ECOG for both PFS and OS. 39.9% of patients reported an adverse event, but only 6.3% of patients discontinued therapy due to toxicity. Our results suggest a long-term benefit of Pembrolizumab in the first-line setting as well as a safety profile consistent with the results of Keynote-042. Many collected variables appear to influence clinical outcome, but results from these exploratory unadjusted analyses should be interpreted with caution.

Outcome of redo-mitral valve replacement in the small mitral annulus with the use of the chimney technology is not well documented. From 2019 to 2020, 77 consecutive patients underwent redo-mitral valve replacement with the use of the chimney technology because of a small mitral annulus. To evaluate heart structural integrity and clinical outcomes, postoperative clinical data and echocardiograms were examined. Mean age was 56.7 ± 15.98 years. All patients underwent mitral valve surgery of which 62 were mitral valve replacements, 7 mitral valve repairs, and 8 double valve replacements. Preoperative Mitral valve mean gradient was 18.07 ± 9.40 mmHg. Postoperative mitral prosthesis size 28.51 ± 1.22 mm. The median increment of mitral size enlargement was 4 (0, 6) valve sizes. Mean mitral gradient coming out of the operating room was 10.34 ± 2.12 mmHg and at follow-up echocardiogram performed at 3 years after the procedure was 10.36 ± 1.70 mmHg. One-year survival was 93.3%, while 4-year survival was 89.3% with no reoperation. Use of the chimney technology in small mitral valve re-mitral valve replacement results in larger valve sizes. Moreover, the mean gradients over the mitral valve are acceptable intraoperatively and over time.

Proposed study aims to investigate the digital transformation of Greek small and medium enterprises (SMEs), with a particular focus on their digital maturity and the strategic and organizational factors contributing to digital transformation. The research issue of digital transformation is attracting considerable interest among academics and business practicians since COVID-19 accelerated the procedure of implementing Industry’s 4.0 principles all over global economies. Quantitative research on 147 Greek SMEs revealed most important issues on how these businesses implement digital transformation, factors accelerating or decelerating the process, barriers and expected outcomes. Research enlights how SMEs face the transition to digital business and reveals the factors that can facilitate the whole process. Results can be valuable for stakeholders enabled to digital transformation process from both business and academic point of view, while there exist aspects that can contribute to policy makers / motivation developers in state’s level as well.

Pancreatic ductal adenocarcinoma (PDAC) is a ravaging disease whose poor prognosis requires a more detailed understanding of its biology to foster the development of effective therapies. The unsatisfactory results of treatments targeting cell proliferation and its related mechanisms suggested to rather focus on the inflammatory tumor microenvironment (TME). Here, we discuss the role of cancer secreted proteins in the complex TME tumor-stroma crosstalk, to sched lights on druggable molecular targets for the development of innovative, safer and more efficient therapeutic strategies.

Targeted radionuclide therapy is become increasingly prominent as a nuclear medicine subspe-cialty. For many decades, treatment with radionuclides has been mainly restricted to the use of iodine-131 in thyroid disorders. Currently, radiopharmaceuticals, consisting of a radionuclide coupled to a vector that binds to a desired biological target with high specificity, are being de-veloped. The objective is to be as selective as possible at the tumor level, while limiting the dose received at the healthy tissue level. In recent years, a better understanding of molecular mecha-nisms of cancer, as well as the appearance of innovative targeting agents (antibodies, peptides, small molecules) and the availability of new radioisotopes, have enabled considerable advances in the field of vectorized internal radiotherapy with a better therapeutic efficacy, radiation safety and personalized treatments. For instance, targeting the tumor microenvironment, instead of the cancer cells, now appears as particularly attractive. Several radiopharmaceuticals for therapeutic targeting have shown clinical value in severals types of tumors and have been or will soon be approved and authorized for clinical use.

Small modular reactors (SMR) (&lt;300 MW) offer a potentially attractive nuclear energy option for the middle-east region (MER). Currently, the MER uses a significant amount of fossil fuel to process heat applications such as water desalination and in petroleum refineries and chemical plants, besides generating electricity. SMR technologies represent an opportunity to meet future energy demand in the MER. This paper discusses issues related to the future development and use of SMR technology in nuclear-renewable hybrid energy systems for application in the middle east. SMRs have also been examined as part of a resilient hybrid energy system that combines nuclear energy with renewable energy and traditional fossil energy to produce chemicals, fuels, and electricity. This paper presents the results of a techno-economic analysis of a Nuclear-Renewable-Conventional Hybrid Energy System. The paper concludes that SMR technology will be an essential feature of future hybrid energy systems for the MER.

Low charge density nanometric ions were recently shown to bind strongly to neutral hydrated matter in aqueous solution. This phenomenon, called (super-)chaotropic effect, arises from the partial dehydration of both, the nano-ion and the solute, leading to a high gain in enthalpy. Here, we investigate the chaotropic effect of the polyoxometalate α-PW12O403- on the triblock copolymer P84: (EO)19(PO)43(EO)19 with (EO)19 the polyethoxylated and (PO)43 the polypropoxylated chains. The combination of phase diagrams, spectroscopic (nuclear magnetic resonance) and scattering (small angle neutron/X-ray scattering) techniques reveals that (i) below the micellization temperature of P84, PW12O403- exclusively binds to the propylene oxide moiety of P84 unimers and (ii) above the micellization temperature, PW12O403- mostly adsorbs on the ethylene oxide micellar corona. The preferential binding of the PW12O403- to the PPO chain over the PEO chains suggests that the binding is driven by the chaotropic effect and reinforced by the hydrophobic effect. At higher temperatures, the copolymer micellization leads to the displacement of PW12O403- from the PPO chain to the PEO chains. This study deepens the understanding of the subtle interplay between the chaotropic and hydrophobic effects in complex salt-organic matter solutions.

We performed Bayesian network meta-analysis (NMA) to suggest frontline treatments for patients with high PD-L1 expression (at least 50%). A total of 5,237 patients from 22 studies were included in this NMA. In terms of progression-free survival, immune checkpoint inhibitors (ICIs) plus bevacizumab plus chemotherapy had the highest surface under the cumulative ranking curve (SUCRA) value (98.1%), followed by ICI plus chemotherapy (82.9%). In terms of overall survival (OS), dual immunotherapy plus chemotherapy had the highest SUCRA value (79.1%), followed by ICI plus bevacizumab plus chemotherapy (73.4%). However, there was no significant difference of survival outcomes among treatment regimens combined with immunotherapy. Moreover, ICI plus chemotherapy failed to reveal a significant OS superiority to ICI monotherapy (hazard ratio = 0.978, 95% credible internal: 0.771-1.259). In conclusion, this NMA indicates that ICI plus chemotherapy with/without bevacizumab might to be the best options in terms of OS for NSCLC with high PD-L1 expression. Considering there was no significant difference of survival outcomes among treatment regimens incorporating immunotherapy and ICI plus chemotherapy failed to show significant survival benefits over ICI monotherapy, however, ICI monotherapy may be reasonable as first-line treatment for advanced NSCLC with high PD-L1 expression and no targetable aberrations.

Recently, there has been renewed interest in the performance, functionality, and sustainability of traditional small-scale storage interventions (check dams, farm bunds and tanks) used across India for the improvement of local water security. The Central Groundwater Board of India is en-couraging the construction of such interventions for the alleviation of water scarcity. It is of critical importance to understand the hydrological effect of these interventions at basin scales to maximise their effectiveness. The quantification of small-scale interventions in hydrological modelling is often neglected, especially in large-scale modelling exercises. A bespoke version of the GWAVA model was developed to assess the impact of interventions on the water balance of the Cauvery Basin and two smaller sub-catchments. Model results demonstrate that farm bunds appear to have a negligible effect on the estimated average annual simulated streamflow at the outlets of the two sub-catchments and the basin whereas tanks and check dams have a more significant effect. In-terventions generally were found to increase evaporation losses across the catchment. The model adaption used in this study provides a step-change in the conceptualisation and quantification of the consequences of small-scale storage interventions in large- or basin-scale hydrological models.

Water quality retrieval for small urban waterbodies by remote sensing get used to be difficult due to coarse spatial resolution of the remote sensing imagery. The recently launched Sentinel-2 produces imagery with a spatial resolution of 10 m. It provides an opportunity to solve the problem of retrieving water quality for small waterbodies. Additionally, many water management issues also require fine resolution of imagery, e.g. illegal discharge to an urban waterbody. Since illegal discharges are an important issue for urban water management, chemical oxygen demand (COD), total phosphorous (TP), and total nitrogen (TN) were chosen as the target parameters for water quality retrieval in this study. COD, TP and TN, however, are non-optically active parameters. There were limited studies in the past to retrieve these parameters in comparison with optically active parameters, e.g. Chlorophyll-A etc. This study compared three machine learning models, namely Random Forest (RF), Support Vector Regression (SVR), and Neural Networks (NN), to investigate the opportunity to retrieve the above non-optically active parameters. Results showed that R² of TP, TN, and COD by NN, RF and SVR were 0.94, 0.88, and 0.86, respectively. The performances of water quality retrieval for these non-optically active parameters were significantly improved by the optimized machine learning models. These models hence solved the problem to use remote sensing data to retrieve these non-optically active water quality parameters and provided a new monitoring strategy for small waterbodies. Water quality mapping obtained by Sentinel-2 imagery provided a full spatial coverage of the water quality characterization for the entire water surface. Compared with water samples collecting and testing, it greatly reduced labor cost, reagents cost, and waste treatment cost. It also may help identify illegal discharges to urban waterbodies. The method developed in this research provides a new practical and efficient water quality monitoring strategy in managing water with consideration of environmental sustainability.

This case study assessed marketing arrangements used by small scale farmers in the Lake Basin and Lower Eastern bean corridors of Kenya to determine which markets work for rural producers and what changes are needed to produce and supply sufficient quantities for trade. Using exploratory research, data was collected through focus group discussions with six farmer groups representing a total of 1255 bean farmers and key informant interviews with extension staff. The results indicated that 94% of the farmers produced beans before identifying buyers with only 6% participating in group marketing. Though spot-market transactions with brokers and traders provided ready cash for the farmers, formal buyers were perceived to be more reliable but difficult to find and, operated stringent requirements which were a barrier to entry. A theory of change to integrate smallholders into formal markets to sustainably produce and supply sufficient volumes for trade should entail a transformation agenda at four levels of the value chain: intensification of production through pure stand models with greater use of certified high yielding varieties; stable price guarantees; a market-driven research and extension service and; an enabling political, policy and business environment in the bean value chain. Further research is needed to pilot these changes in a case control study.

Groundwater is an important resource for many countries and its scarcity is a major concern in small territories, especially in the islands where the constant extraction is creating a high risk of public calamity. This issue has been increasing because of the anthropogenic activities and the climate change and it has called the attention of scientists and stakeholders in order to assess the sustainability of the water management system, and therefore, to establish strategies for a more sustainable water use. San Andres island was taking as case study and a description of the water balance was carried out in order to understand the management system. Then, a water system sustainability assessment was performed with indicators such as water security, water quality, drinking water, sanitation, infrastructure, climate robustness, biodiversity, attractiveness, and governance, according to the City Blueprint Methodology. The result for the 24 evaluated indicators was a score of 3.2, whose interpretation is “an unsustainable water management”. The qualitative assessment was the base to propose water security, water quality, and governance strategies to improve the water management in the island. The assessment and its discussions are relevant for the water management in small islands across the world whose economy is based on the tourism and whose water security is at a high risk.

Lambertianic acid (LA) is a biologically active compound from the leaves of Pinus koraiensis. In the present study, apoptotic mechanisms of LA plus TNF-related apoptosis-inducing ligand (TRAIL) were elucidated in non-small cell lung cancer cells (NSCLCs). Cytotoxicity assay, flow cytometry, immunoprecipitation and Western blotting were performed. Here, combined treatment of LA and TRAIL increased cytotoxicity, sub-G1 population and cleaved poly (ADP-ribose) polymerase (PARP) and caspase3/8/9 in A549 and H1299 cells compared to LA or TRAIL alone. Furthermore, combined treatment of LA and TRAIL significantly decreased anti-apoptotic proteins such as B-cell lymphoma 2 (Bcl-2), Fas-like inhibitor protein (FLIP) and X-linked inhibitor of apoptosis protein (XIAP) and enhanced the activation of pro-apoptotic proteins Bid compared to LA or TRAIL alone. In addition, combined treatment of LA and TRAIL upregulated the expression of Death receptor 4 (DR4) and downregulated phosphorylation of nuclear factor kappa-light-chain-enhancer of activated B cells (p-NF-B), inhibitory protein of kB family (p-IB) and FLIP in A549 and H1299 cells along with disrupted binding of XIAP with caspase3 or NF-B. Overall, these findings suggest that lambertianic acid enhances TRAIL-induced apoptosis via inhibition of XIAP/NF-B in TRAIL resistant NSCLCs.

Computers and artificial intelligence affect every field of life nowadays. In medical image interpretation automatic decision making using algorithms are used increasingly in every sub-field and computer aided diagnosis (CAD) is one of the main tools available to medical science today. CAD systems are used as an augmented option for both the medical practitioner and the patients, with image analysis and interpretation being of primary importance. In particular, spatial relations are used in knowledge representation, and these relations can be used for effective medical image interpretation. In this paper, we put forth an algorithm for defining non-small cells lungs cancer (NSCLC) stages in lungs images interpretation using topological spatial relations. We show an application case study in event motion predictions for lung cancer staging scoring - tumor, nodes and metastasis (TNM) - with combined topological and directional relations.

Omega-3 polyunsaturated fatty acids (ω3-PUFAs), including docosahexaenoic acid (DHA), have been shown to exert anticancer effects by inducing apoptotic cell death. However, the mechanism for DHA-induced cell death in lung cancer is not fully understood. Here, we show that DHA induces apoptosis in two human EGFR mutant non-small cell lung cancer (NSCLC) cell lines, and that DHA-induced cell death is accompanied by SIRT6 activation and attenuated Hedgehog (Hh) signaling. Knockdown of SIRT6 using siRNAs inhibited DHA-induced apoptosis, whereas SIRT6 overexpression increased apoptotic cell death. DHA-induced SIRT6 activation was associated with downregulation of Hh signaling, and knockdown of SIRT6 resulted in augmentation of Hh signaling. Pretreatment of NSCLC cells with a Smoothened agonist prevented DHA-induced decreases in the levels of Hh signaling proteins and increases in cleaved PARP levels. Moreover, endogenous production of ω3-PUFAs in PC9 cells via fat-1 expression resulted in elevated SIRT6 levels and reduced levels of Hh signaling molecules, including Gli, following DHA treatment. Overall, these results implicate that ω3-PUFAs induce apoptosis by downregulating Hh signaling via SIRT6 activation in human EGFR mutant NSCLC cells. These findings suggest that ω3-PUFAs potentially represent an effective therapy for the chemoprevention and treatment of NSCLC.

ABSTRACT This study focused for socio-economic benefit of Western shoreline of Lake Ziway ecosystem. The data collected from two woredas they are Adami Tulu Jidu Kombolch (ATJK) and Dugda woreda of fishermen and small scale irrigation users. Lake Ziway great importance food and water for both groups of respondents and additionally sources of raw material, energy, cultivation, organic fertilizers, genetic and medicinal plants. Lake Ziway also has a major economic benefit for both groups of respondents. The sampled fishermen cached mean amount of 2,524Kg per year with minimum and maximum amount of fish 504Kg and 16,800Kg per year respectively and with this fish catching they got average income of 51,398 Birr ($2,570) per year with range of 7,200 Birr ($360) and 288,000 Birr ($14,400) per year. As like of fishermen small scale irrigation also got economic benefit with their production of cereal crops, fruits and vegetables. They produce in average 13.47Quintal of cereal crop and 69.56Quintal of fruits and vegetables per year and they got average income of 7,727 Birr ($386) and with range of 13,714 Birr ($686) per year respectively. this incurred that wetland ecosystem has a lot of socio-economic benefit for the people live near by specially for developing countries like Ethiopia they are more dependent on natural ecosystem like of Lake Ziway. Because of its high importance, we have to protect and conserve and use sustainably of Lake Ziway and similar wetland ecosystems. Key Words: Wetland ecosystem service; Lake Ziway; Socioeconomic benefit; Fishermen; Small scale irrigation users

This study assessed the financial management practices and challenges of food cart businesses in Cabanatuan City, Nueva Ecija. The study used a descriptive research design and structured surveys and questionnaires to gather quantitative data from 20 food cart businesses. The data were analyzed using statistical tools such as weighted means, frequencies, and percentages to provide a comprehensive overview of these small enterprises' financial practices and challenges. Key findings highlight that while many businesses demonstrate basic financial literacy, significant gaps exist in financial record-keeping, budgeting, and revenue management. The study emphasizes the importance of improving these practices to ensure the sustainability and growth of food cart businesses. The research contributes to the broader discourse on small business management and economic development by identifying common challenges and offering targeted recommendations. The findings underscore the need for targeted interventions, such as financial training and policy support, to enhance the financial acumen of food cart owners. This study adds to the existing body of knowledge as it provides practical insights that can benefit business owners, policymakers, and community stakeholders in fostering a more resilient and economically vibrant local economy.

The terrestrial subsurface harbors unique microbial communities that play important biogeochemical roles and allows studying a yet unknown fraction of the Earth’s biodiversity. The Saint-Leonard cave in Montreal city (Canada) is of glaciotectonic origin. Its speleogenesis traces back to the withdrawal of the Laurentide Ice Sheet, 13 000 years ago, during which the moving glacier dislocated the sedimentary rock layers. Our study is the first to investigate the microbial communities of the cave. By using amplicon sequencing, we analyzed the taxonomic diversity and composition of bacterial, archaeal and eukaryotes communities living in the groundwater (0.1µm- and 0.2µm-filtered water), in the sediments and in surface soils. We identified a microbial biodiversity typical of cave ecosystems. Communities were mainly shaped by habitat type and harbored taxa associated with a wide variety of lifestyles and of metabolic capacities. Although we found evidence of a geochemical connection between the above soils and the cave’s galleries, our results suggest that the community assembly dynamics are driven by habitat selection rather than dispersal. Furthermore, we found that the cave’s groundwater, in addition to being generally richer in microbial taxa than sediments, contained a considerable diversity of ultra-small bacteria and archaea.

Named Entity Recognition (NER) is a fundamental and pivotal stage in the development of various knowledge-based support systems, including knowledge retrieval and question-answering systems. In the domain of pig diseases, Chinese NER models encounter several challenges such as the scarcity of annotated data, domain-specific vocabulary, diverse entity categories, and ambiguous entity boundaries. To address these challenges, we propose PDCNER, a Pig Disease Chinese Named Entity Recognition method leveraging lexicon-enhanced BERT and contrastive learning. Firstly, we construct a domain-specific lexicon and pre-train word embeddings in the pig disease domain. Secondly, we integrate lexicon information of pig diseases into the lower layers of BERT using a Lexicon Adapter layer, which employs char-word pair sequences. Thirdly, to enhance feature representation, we propose a lexicon-enhanced contrastive loss layer on top of BERT. Finally, a Conditional Random Field (CRF) layer is employed as the model's decoder. Experimental results show that our proposed model demonstrates superior performance over several mainstream models, achieving a precision of 87.76%, a recall of 86.97%, and an F1-score of 87.36%. The proposed model outperforms BERT-BiLSTM-CRF and LEBERT by 14.05% and 6.8%, respectively, with only 10% of the samples available, showcasing its robustness in data scarcity scenarios. Furthermore, the model exhibits generalizability across publicly available datasets. Our work provides reliable technical support for the information extraction of pig diseases in Chinese and can be easily extended to other domains, thereby facilitating seamless adaptation for named entity identification across diverse contexts. The codes have been open-sourced at https://github.com/tufeifei923/pdcner.

YOLOv8, as an efficient object detection method, can swiftly and precisely identify objects within images. However, traditional algorithms encounter difficulties when detecting small targets in remote sensing images, such as missing information, background noise, and interactions among multiple objects in complex scenes, which may affect performance. To tackle these challenges, we propose an enhanced algorithm optimized for detecting small objects in remote sensing images, named HP-YOLOv8. Firstly, we design the C2f-D-Mixer (C2f-DM) module as a replacement for the original C2f module. This module integrates both local and global information, significantly improving the ability to detect features of small objects. Secondly, we introduce a feature fusion technique based on attention mechanisms, named Bi-Level Routing Attention in Gated Feature Pyramid Network (BGFPN). This technique utilizes an efficient feature aggregation network and reparameterization technology to optimize information interaction between different scale feature maps, and through the Bi-level Routing Attention (BRA) mechanism, it effectively captures critical feature information of small target objects. Finally, we propose the Smooth Mean Perpendicular Distance Intersection over Union (SMPDIoU) loss function. The method comprehensively considers the shape and size of detection boxes, enhances the model's focus on the attributes of detection boxes and provides a more accurate bounding box regression loss calculation method. To demonstrate our approach's efficacy, we conduct comprehensive experiments across the RSOD, NWPU VHR-10, and VisDrone2019 datasets. The experimental results show that the HP-YOLOv8 achieves 95.11%, 93.05%, and 53.49% in the mAP@0.5 metric, and 72.03%, 65.37%, and 38.91% in the more stringent mAP@0.5:0.95 metric, respectively.

Infrared small target detection (ISTD) plays a crucial role in both civilian and military applications. The detection of small targets against dense cluttered backgrounds remains a challenging task, requiring the collaboration of false alarm source elimination and target detection. Existing approaches primarily focus on modeling targets while often neglecting false alarm sources. To address this limitation, we propose a Target and False Alarm Collaborative Detection Network to leverage the information provided by false alarm sources and the background. Firstly, we introduce a False Alarm Source Estimation Block (FEB) that estimates potential interferences present in the background by extracting features on multiple scales and employing stepwise upsampling for feature fusion. Subsequently, we propose a framework that employs multiple FEBs to eliminate false alarm sources across multiple scales. Finally, a Target Segmentation Block (TSB) is introduced to accurately segment the targets to produce the final detection result. Experiments on public datasets demonstrate that, compared to other methods, our model achieves high accuracy in segmenting targets while being able to extract false alarm sources which can be used for further studies.

Patient-derived tumor organoids (PDTOs) are a novel preclinical model of non-small cell lung cancer (NSCLC) for studying tumor biology and precision medicine, which recapitulates tumor morphology and gene expression profile. However, some issues such as low establishment rates, long-term production, and the loss of the immune microenvironment have hindered their widespread practical use. In this study, we investigated the efficacy of a recently introduced free-floating organoid production method to address these issues. The free-floating approach provided PDTO establishment success rate of over 90 % resulting in organoid formation within a short period of one week. These organoids retained the elements of the parental tumor morphology and contained stroma and immune cell populations, as confirmed by flow cytometry analysis. Importantly, we found that the cytokine and growth factor expression profiles of the free-floating organoids correlated with those of the original tumors in 58 % of cases, indicating the preservation of tumor-associated signaling pathways. Obtained organoids exhibited different responses to anticancer chemotherapeutics that might be a result of variable expression of drug resistance-associated genes. Considering the high establishment rate and short time of free-floating organoid production, this technique provides a valuable tool for a more accurate evaluation of therapeutic strategies and cancer biology studies.

Small island developing states (SIDS) traditionally face a set of challenges like the narrow economic structure, environmental issues, and dependence on a few ranges of economic activities forcing them to open the economy to the exterior. Therefore, their development model, like in Cape Verde depends on migration, remittances, dependence on aid, tourism, and state employment. The current research offers an insight about the nature of Cape Verde’s economy as a SIDS and the degree to which its economy depends on tourism and government services, both of which are supported through aid programs. Understanding Cape Verde’s development model is important to clarify the challenges the country faces, and its development needs to gather a long-term resilience and to understand if it is changing from a MIRAB (Migrations, Remittances, Aid and Bureaucracy) model into another one.

Serine/threonine kinase (AKT) signaling regulates diverse cellular processes and is one of the most important aberrant cell survival mechanisms associated with tumorigenesis, metastasis, and chemoresistance. Targeting AKT has become an effective therapeutic strategy for the treatment of many cancers. AKT3 (PKBγ), the least studied isoform of the AKT family, has emerged as a major contributor to malignancy. AKT3 is frequently overexpressed in human cancers, and many regulatory oncogenic or tumor suppressor small non-coding RNAs (ncRNAs), including microRNAs (miRNAs), have recently been identified to be involved in regulating AKT3 expression. Therefore, a better understanding of regulatory miRNA/AKT3 networks may reveal novel biomarkers for diagnosis of patients with cancer and provide invaluable information for developing more effective therapeutic strategies. The aim of this review is to summarize current research progress in the isoform-specific functions of AKT3 in human cancers and the roles of dysregulated miRNA/AKT3 in specific types of human cancers.

Mathematical models of non-small cell lung cancer are powerful tools that use clinical and experimental data to describe various aspects of tumorigenesis. The developed algorithms capture phenotypic changes in the tumor and predict changes in tumor behavior, drug resistance, and clinical outcomes of anti-cancer therapy. The aim of this study was to propose a mathematical model that predicts the changes in the cellular composition of patient-derived tumor organoids over time with a perspective of translation of these results to the parental tumor, and therefore to possible clinical course and outcomes for the patient. Using the data on specific biomarkers of cancer cells (PD-L1), tumor-associated macrophages (CD206), natural killer cells (CD8), and fibroblasts (αSMA) as input, we proposed a model that accurately predicts the cellular composition of patient-derived tumor organoids at a desired time point. Combining the obtained results with “omics” approaches will improve our understanding of the nature of NSCLC. Moreover, their implementation into clinical practice will facilitate a decision-making process on treatment strategy and develop a new personalized approach in anti-cancer therapy.

Ship detection in large-scene offshore synthetic aperture radar (SAR) images is crucial in civil and military fields, such as maritime management and wartime reconnaissance. However, the problems of low detection rates, high false alarm rates, and high missed detection rates of offshore ship targets in large-scene SAR images are due to the occlusion of objects or mutual occlusion among targets, especially for small ship targets. To solve this problem, this study proposes a target detection model (TAC_CSAC_Net) that incorporates a multi-attention mechanism for detecting marine vessels in large-scene SAR images. Experiments were conducted on two public datasets, the SAR-Ship-Dataset and high-resolution SAR image dataset (HRSID), with multi-scene and multi-size, and the results showed that the proposed TAC_CSAC_Net model achieves good performance for both small and occluded target detection. Experiments were conducted on a real large-scene dataset, LS-SSDD, to obtain the detection results of subgraphs of the same scene. Quantitative comparisons were made with classical and recently developed deep learning models, and the experiments demonstrated that the proposed model outperformed other models for large-scene SAR image target detection.

Postprandial hyperlipidemia showing postprandial increase in serum triglyceride (TG) is atherogenic and associated with the development of coronary artery disease (CAD). To diagnose postprandial hyperlipidemia, the oral fat loading test (OFLT) should be performed, however, this test is very time-consuming and is difficult to perform. Ele-vated serum TG levels reflect an increase in TG-rich lipoproteins (TRL) such chylomi-crons (CM), very low-density lipoproteins (VLDL) and their remnants (CM remnant [CMR] and VLDL remnant [VLDLR]). Understanding of elevation in CMR and/or VLDLR can lead us to understand the existence of postprandial hyperlipidemia. The measurements of apo B48 which is a constituent of CM and CMR, non-fasting TG which includes TG content in all lipoproteins including CM and CMR, non-high-density lipoprotein-cholesterol (non-HDL-C) which includes TRL and low-density lipoprotein, and remnant cholesterol, are useful to suspect the existence of postprandial hyperlipidemia. Postprandial hyperlipidemia is observed in patients with familial type III hyperlipoproteinemia, familial combined hyperlipidemia, chronic kidney disease, metabolic syndrome and type 2 diabetes. Postprandial hyperlipidemia is closely related to postprandial hyperglycemia, and insulin resistance may be an in-ducing and enhancing factor for both postprandial hyperlipidemia and postprandial hyperglycemia. Remnant lipoproteins and metabolic disorders associated with post-prandial hyperlipidemia have various atherogenic properties such as induction of in-flammation and endothelial dysfunction. A healthy diet, calorie restriction, weight loss and exercise, positively impact postprandial hyperlipidemia. Anti-hyperlipidemic drugs such pemafibrate, bezafibrate, ezetimibe and eicosapentaenoic acid have shown to improve postprandial hyperlipidemia. Anti-diabetic drugs including metformin, alpha-glucosidase inhibitors, pioglitazone, dipeptidyl-peptidase-4 inhibitors and glu-cagon like peptide 1 analogues, have shown to ameliorate postprandial hyperlipidemia. Although sodium glucose cotransporter-2 inhibitors have not been proven to reduce postprandial hyperlipidemia, they reduced fasting apo B48 and remnant lipoprotein cholesterol. In conclusion, it is important to appropriately understand the existence of postprandial hyperlipidemia and to connect it to optimal treatments.