Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the nutritional spectrum and culinary applications of basil seeds (Ocimum basilicum L.) in the food industry: A comprehensive review

Basil seeds ( Ocimum basilicum L.) have gained increasing attention in recent years due to their diverse nutritional profile and versatile applications in the food industry. This comprehensive review synthesizes the current body of knowledge surrounding basil seeds, focusing on their nutritional composition, health-promoting properties and culinary applications. The review begins by highlighting the nutritional content of basil seeds, including essential nutrients such as proteins, fibers, vitamins, and minerals. Special emphasis is placed on unique bioactive compounds present in basil seeds, elucidating their potential health benefits and therapeutic applications. Furthermore, the paper delves into the functional properties of basil seeds, exploring their role in food formulation and product development. The gel-forming ability of basil seeds, in particular, is discussed for its relevance in creating innovative food textures and structures. The review explores traditional and contemporary uses of basil seeds in diverse cuisines, ranging from beverages and desserts to savory dishes. Innovations in culinary techniques that harness the unique properties of basil seeds for enhancing food quality and sensory experiences are highlighted. Moreover, the paper discusses the potential challenges and future directions in the utilization of basil seeds in the food industry. Considerations related to sourcing, quality control, and consumer acceptance are addressed to provide a holistic perspective for industry stakeholders. In conclusion, this comprehensive review serves as a valuable resource for researchers, food scientists, and industry professionals interested in understanding the nutritional spectrum and culinary applications of basil seeds. The synthesis of existing knowledge provides a foundation for future research and development, paving the way for the widespread adoption of basil seeds as a functional ingredient in the food industry.
PEMANFAATAN MODAL SOSIAL BAGI KELUARGA NELAYAN MISKIN DI MASA PANDEMI COVID-19 (Nelayan Miskin Nagari Painan Selatan Kabupaten Pesisir Selatan Provinsi Sumatera Barat)

This study aims to find out how poor fisherman families survived during the pandemic in Painan, Pesisir Selatan Regency, West Sumatra province. This research uses a qualitative approach, with theory as its unit of analysis. Through the studies that have been carried out, it is known that various ways of survival for families who went to sea on the south coast during the pandemic, it is known that the pillars of the capital triangle, which include intermediary relations and social networks with various components, can all come together. build mutually exclusive fishing groups. During the Covid-19 pandemic, this trust Association is the foundation for the use of social capital in the practice of Group life in fishing communities, this is evidenced by the existence of informal institutions that affect people's lives
A New Algorithm for Change Detection

Change detection was one of pivotal technologies for the application of remote sensing image. On the basis of analysis for algorithms for change detection, A new algorithm was proposed in this paper, the algorithm consists of three steps: optimized acquiring for difference image based on blocking by using wavelet transform; exact detection of change area by using self-adaptive threshold; correcting change detection result through detecting objects' shadow. A number of simulation results show that new algorithm can detect effectively change areas, and outlines of change objects are incarnated perfectly simultaneously. The algorithm has better robustress against background.
Breast cancer diagnosis through knowledge distillation of Swin transformer-based teacher–student models

Breast cancer is a significant global health concern, emphasizing the crucial need for a timely and accurate diagnosis to enhance survival rates. Traditional diagnostic methods rely on pathologists analyzing whole-slide images (WSIs) to identify and diagnose malignancies. However, this task is complex, demanding specialized expertise and imposing a substantial workload on pathologists. Additionally, existing deep learning models, commonly employed for classifying histopathology images, often need enhancements to ensure their suitability for real-time deployment on WSI, especially when trained for small regions of interest (ROIs). This article introduces two Swin transformer-based architectures: the teacher model, characterized by its moderate size, and the lightweight student model. Both models are trained using a publicly available dataset of breast cancer histopathology images, focusing on ROIs with varying magnification factors. Transfer learning is applied to train the teacher model, and knowledge distillation (KD) transfers its capabilities to the student model. To enhance validation accuracy and minimize the total loss in KD, we employ the state–action–reward–state–action (SARSA) reinforcement learning algorithm. The algorithm dynamically computes temperature and a weighting factor throughout the KD process to achieve high accuracy within a considerably shorter training timeframe. Additionally, the student model is deployed to analyze malignancies in WSI. Despite the student model being only one-third the size and flops of the teacher model, it achieves an impressive accuracy of 98.71%, slightly below the teacher’s accuracy of 98.91%. Experimental results demonstrate that the student model can process WSIs at a throughput of 1.67 samples s−1 with an accuracy of 82%. The proposed student model, trained using KD and the SARSA algorithm, exhibits promising breast cancer classification and WSI analysis performance. These findings indicate its potential for assisting pathologists in diagnosing breast cancer accurately and effectively.
Physical, mechanical and mineralogical properties of ophiolitic rocks at the Yakakayi dam site, Eskisehir, Turkey

This paper presents the physical, mechanical and mineralogical properties of ophiolitic rocks from Yakakayi dam site located 25 km away from the northern part of Eskisehir province. The collected samples were subjected to petrographic analyses and physico-mechanical tests. The most important engineering characteristic of rock material for rock characterization and design is its intrinsic strength, which is directly determined by unconfined compression strength (UCS) test. The rock, which units at the dam site are ophiolitic rocks of Upper Cretaceous in age and terrace, talus and alluvium of Quaternary age. The aim of this study is to determine the engineering, slake durability (SD) properties and petrography of ophiolitic rocks at Yakakayi dam site. The laboratory test results indicate that the mean UCS value of ophiolitic rocks as basalts is 63.02 MPa, limestones is 15.69 MPa, radiolarians is 28.37 MPa and serpentines is 13.47 MPa. Also, slake durability index properties of ophiolitic rocks are in high class.
BoLA DRB3 gene's polymorphism of Ukrainian cattle breeds in relation to mastitis

The results of studying the polymorphism of the BoLA-DRB3.2 gene and identifying the associations of its alleles with mastitis for three Ukrainian breeds are presented: Black-and-White milk (UBW), Red-and-White milk (URW) and White-Headed (UWH). In 162 UBP cows, 28 alleles were detected, six of which were determined with a frequency of over 5% (55.3% in total). The *22 allele is detected more frequently (12%). Four alleles are reliably associated with mastitis: susceptibility - *24 (P<0.05) and *26 (P<0.01); resistance - *13 (P<0.05) and *22 (P<0.05). For 117 URP cows 22 alleles were detected. Of these, seven were detected with a frequency of more than 5% (64.5% in total). The most common allele was *07 (15.4%). Four alleles were found to be significantly sensitive to mastitis: *07 (P<0.01) and *08 (P<0.05) are associated with the disease, *22 (P<0.001) and *24 (P<0.05) - with mastitis resistance. In 77 UWH blood samples, 28 alleles were detected, seven of which had a frequency of more than 5% (for a total of 59.6%). The most common variant in this population was *24 (12.3%). Two mastitis-sensitive alleles have been conclusively established: *22 variant (P<0.05) is associated with resistance and *24 with susceptibility to the disease (P<0.001). Alleles for which a statistically significant association with predisposition to the disease has been established can be used as DNA markers to improve the selection of cattle in order to create herds resistant to diseases, including mastitis.
Western Boundary Current Structure and Variability East of Abaco, Bahamas at 26.5°N

Abstract During April 1987 to June 1988, a four-mooring, transport-resolving current meter array was deployed in a section extending 70 km eastward from Abaco, Bahamas, at 26.5°N. Mean currents in the upper layer (≤800 m) showed a clockwise rotation that appears to be associated with a small scale, quasi-permanent, anticyclonic gyre centered just northeast or the Bahamas. Deep mean currents were persistenly southward and indicated a strong, deep jet, the Deep Western Boundary Current (DWBC), reaching core speeds of 20 cm s−1at 2500 m depth about 25 km seaward of the western boundary. Vertically integrated meridional volume transport over the section showed a surprisingly large variability, ranging from approximately 20 Sv northward to 70 Sv southward (1 Sv = 106m3s−1). The mean meridional volume transport was 30 Sv to the south, with about 3 Sv flowing northward above 800 m, which could be produced by a weak Antilles Current and 33 Sv flowing, southward below 800 m. The deep southward transport of 33 Sv i.
Unraveling the Intricacies of Autophagy and Mitophagy: Implications in Cancer Biology

Autophagy is an essential lysosome-mediated degradation pathway that maintains cellular homeostasis and viability in response to various intra- and extracellular stresses. Mitophagy is a type of autophagy that is involved in the intricate removal of dysfunctional mitochondria during conditions of metabolic stress. In this review, we describe the multifaceted roles of autophagy and mitophagy in normal physiology and the field of cancer biology. Autophagy and mitophagy exhibit dual context-dependent roles in cancer development, acting as tumor suppressors and promoters. We also discuss the important role of autophagy and mitophagy within the cancer microenvironment and how autophagy and mitophagy influence tumor host–cell interactions to overcome metabolic deficiencies and sustain the activity of cancer-associated fibroblasts (CAFs) in a stromal environment. Finally, we explore the dynamic interplay between autophagy and the immune response in tumors, indicating their potential as immunomodulatory targets in cancer therapy. As the field of autophagy and mitophagy continues to evolve, this comprehensive review provides insights into their important roles in cancer and cancer microenvironment.
Lightning return stroke electric and magnetic fields

Our present understanding of the microsecond- and submicrosecond-scale electric and magnetic fields generated by lightning return strokes is reviewed. First, the experimental data for strokes lowering both negative and positive charge are discussed. Then theory relating the remotely measured fields to the channel currents is presented. The significant gaps in our understanding of the return stroke fields are identified.
Effect of Complementary Therapy with Hydro-Ethanolic Extract of Aerial Parts of Portulaca oleracea on Clinical and Paraclinical Findings in Patients with Non-alcoholic Fatty Liver Disease: A Randomized Clinical Trial Protocol

Background: Non-alcoholic fatty liver disease (NAFLD) is a serious public health issue. Even though various natural and synthetic therapies are in the advanced stages of development, there is no authorized therapy for NAFLD. The use of anti-oxidant and anti-inflammatory compounds is one of these natural treatments. Portulaca oleracea aerial parts' extracts have shown various pharmacological properties, including antioxidant, anti-inflammatory, and liver protection due to alkaloid compounds, flavonoids, terpenoids, sterols, omega-3 unsaturated fatty acids, and many vitamins and minerals. Objectives: We intend to examine the effectiveness of Portulaca oleracea extract in improving the symptoms caused by NAFLD. Methods: A randomized, double-blinded, controlled, parallel clinical trial is designed to study the effects of P. oleracea supplementation on the clinical and paraclinical findings in patients with NAFLD. An intervention group will get 700 mg of P. oleracea supplementation for eight weeks, while a control group will receive a placebo. Throughout the intervention, the clinical and nutritional status will be assessed three times. At the 0, 30, and 60th days of the intervention, anthropometric evaluation, blood pressure, and gastrointestinal problems will be monitored. Transient elastography will be done at the start and end of the research to assess the liver state. In addition, an International Physical Activity Questionnaire (IPAQ) and a 3-day food record will be collected, as well as biochemical variables, such as CBC-diff (complete blood count with differential count), lipid profiles, FBS, Fasting Blood Sugar; serum insulin, hepatic-related parameters, namely enzymes [ALP (alkaline phosphatase), AST (aspartate aminotransferase), ALT (alanine aminotransferase), GGT (gamma-glutamyl transferase)], total and direct bilirubin, and inflammatory [hs-CRP (C-reactive protein), ESR (erythrocyte sedimentation rate) and IL-6 (interleukin-6)] and oxidative stress markers [SOD (super oxide dismutase), GSH-Px (glutathione peroxidase) and MDA (malondialdehyde)]. Discussion: This is the first randomized clinical trial (RCT) protocol specifically created for patients with NAFLD to evaluate the impact of P. oleracea supplementation. We intend to demonstrate that the suggested procedure is a novel and effective approach to decreasing NAFLD's laboratory and clinical symptoms. We also expect that supplementation with 700 mg of P. oleracea for 60 days will improve liver steatosis and clinical and nutritional status and reduce NAFLD patients' inflammation and oxidative stress.
Deep learning models for preoperative T-stage assessment in rectal cancer using MRI: exploring the impact of rectal filling

Background The objective of this study was twofold: firstly, to develop a convolutional neural network (CNN) for automatic segmentation of rectal cancer (RC) lesions, and secondly, to construct classification models to differentiate between different T-stages of RC. Additionally, it was attempted to investigate the potential benefits of rectal filling in improving the performance of deep learning (DL) models. Methods A retrospective study was conducted, including 317 consecutive patients with RC who underwent MRI scans. The datasets were randomly divided into a training set (n = 265) and a test set (n = 52). Initially, an automatic segmentation model based on T2-weighted imaging (T2WI) was constructed using nn-UNet. The performance of the model was evaluated using the dice similarity coefficient (DSC), the 95th percentile Hausdorff distance (HD95), and the average surface distance (ASD). Subsequently, three types of DL-models were constructed: Model 1 trained on the total training dataset, Model 2 trained on the rectal-filling dataset, and Model 3 trained on the non-filling dataset. The diagnostic values were evaluated and compared using receiver operating characteristic (ROC) curve analysis, confusion matrix, net reclassification index (NRI), and decision curve analysis (DCA). Results The automatic segmentation showed excellent performance. The rectal-filling dataset exhibited superior results in terms of DSC and ASD (p = 0.006 and 0.017). The DL-models demonstrated significantly superior classification performance to the subjective evaluation in predicting T-stages for all test datasets (all p < 0.05). Among the models, Model 1 showcased the highest overall performance, with an area under the curve (AUC) of 0.958 and an accuracy of 0.962 in the filling test dataset. Conclusion This study highlighted the utility of DL-based automatic segmentation and classification models for preoperative T-stage assessment of RC on T2WI, particularly in the rectal-filling dataset. Compared with subjective evaluation, the models exhibited superior performance, suggesting their noticeable potential for enhancing clinical diagnosis and treatment practices.
Effects of nitrogen on benthic diatom assemblages in high-elevation central and eastern alpine lakes

ABSTRACT We explored patterns of benthic diatom composition across sixty-two high-elevation alpine lakes spanning a wide range of nitrogen (N) concentrations due to atmospheric deposition and background variation in lake and watershed characteristics. Our goals were to (1) assess the effect of lake water N concentration on benthic diatom composition during late summer or fall conditions and (2) identify policy-relevant response thresholds. The analyses were carried out on a large set of diatom and water chemistry data, integrated with new data. Multivariate and correlation analyses revealed associations between pH, N concentration, and benthic diatom composition, but the effects of pH and N were confounded. However, partial correlation analysis allowed us to identify “N-responsive diatoms”; that is, diatom taxa with nonspurious associations with N. Focusing on these taxa, we detected a decline in the abundance of taxa preferring low N concentrations and an increase in the abundance of taxa preferring high N concentrations starting at NO3 concentrations of approximately 5 µmol L−1. We interpreted this shift as an effect of watershed N saturation due to atmospheric deposition. Based on the results, we suggest a late-summer or fall concentration threshold of 5 µmol NO3 L−1 to prevent change in benthic diatoms in high-elevation alpine lakes.
Degradation mechanism of the grass in Qinghai Plateau and its prevention and control countermeasures

Based on explanation about present situation of grass deterioration in southern Qinghai plateau,the cause and mechanism of grass deterioration are analyzed with systematic view point. It is recognized that the vulnerability of geographic environment of plateau,natural hazard and unreasonable human's activities are predominant factors resulting in grass deterioration. The internal relations between the factors are analyzed. The macroscopic strategy to recover and rehabilitate grass is explored. Some suggestions and countermeasures against grass deterioration with control theory and systematic engineering method are presented.
Mitigation of Ulaanbaatar city's air pollution - from source aportionment to ultra-low emission lignite burning stoves

Mongolia has an extreme continental climate with long, cold winters lasting 7 to 8 months. Monthly average temperatures are typically -20°C in January and February, dropping to -40°C at night. The urgent need for space heating in traditional gers (yurts) results in very high ambient particulate matter (PM) concentrations, largely the result of burning high moisture, high volatiles lignite in a sheet-metal woodburning stove. A study conducted in 2008-2009 found the annual average ambient PM level of Ulaanbaatar city is 150 μg m for PM2.5 and 300 μg/m for PM10 in the city centre. In the coal burning poor districts it is 300-620 μg m for PM2.5 and 350-900 μg m for PM10. The main sources are wind-blown soil, coal and wood combustion and vehicles. Low temperature coal combustion produces 87% of finer particles in residential districts. Wind-blown fugitive dust contributes 91% PM10 in the same areas. The extraordinary air pollution in Ulaanbaatar (up to 4 200 μg m) was monitored using Nucleopore® filters and particle counters. Particle analysis confirmed low temperature coal combustion as the major air quality problem in poor districts. High time-resolution PM 2.5 data showed particles are emitted during the ignition of lignite fires. Over 50% of all PM comes from the ignition phase of stoves lighted in the morning and in the late afternoon after people arrive home from work. A laboratory (modelled on the SeTAR Centre Laboratory, University of Johannesburg) was established to quantify domestic stove emissions. Measured particulate matter was as much as 12 g m of flue gases. Data analysis uses the SeTAR Centre Heterogeneous Testing Protocols and analytical methods. A combustor testing programme led rapidly to the development of an extremely clean-burning cooking and space heating stove that has been developed and brought to market within a single year. An acceptable 9 kW low-emission (up to 99% reduction of PM 2.5) and high efficiency (50% fuel savings) crossdraft cooking and space heating stove was developed and is being piloted for large scale production in Ulaanbaatar at this time.
Stefin B Inhibits NLRP3 Inflammasome Activation via AMPK/mTOR Signalling

Stefin B (cystatin B) is an inhibitor of lysosomal and nuclear cysteine cathepsins. The gene for stefin B is located on human chromosome 21 and its expression is upregulated in the brains of individuals with Down syndrome. Biallelic loss-of-function mutations in the stefin B gene lead to Unverricht–Lundborg disease-progressive myoclonus epilepsy type 1 (EPM1) in humans. In our past study, we demonstrated that mice lacking stefin B were significantly more sensitive to sepsis induced by lipopolysaccharide (LPS) and secreted higher levels of interleukin 1-β (IL-1β) due to increased inflammasome activation in bone marrow-derived macrophages. Here, we report lower interleukin 1-β processing and caspase-11 expression in bone marrow-derived macrophages prepared from mice that have an additional copy of the stefin B gene. Increased expression of stefin B downregulated mitochondrial reactive oxygen species (ROS) generation and lowered the NLR family pyrin domain containing 3 (NLRP3) inflammasome activation in macrophages. We determined higher AMP-activated kinase phosphorylation and downregulation of mTOR activity in stefin B trisomic macrophages—macrophages with increased stefin B expression. Our study showed that increased stefin B expression downregulated mitochondrial ROS generation and increased autophagy. The present work contributes to a better understanding of the role of stefin B in regulation of autophagy and inflammasome activation in macrophages and could help to develop new treatments.
Loss Analysis Of Centrifugal Compressor Volutes Based On A Second-Law Analysis Method

Loss modeling of centrifugal compressor volutes is generally based on the use of physical approaches in combination with empirical data, providing an abstract description of the loss development of the highly complex, three-dimensional volute flow. Another evaluation technique for the losses is provided by the so-called second-law analysis (SLA), in which entropy productions are used to analyze the loss mechanisms as well as to quantify the local loss distribution within the volute. The present work is based on the application of that method, in which numerical simulations are used to obtain further knowledge in the field of volutes of centrifugal compressors. Steady-state flow simulations of different volute types have been carried out using the industry-standard SST turbulence model, whose numerical methodology has been validated against experimental data for the standard case of an outward-wound volute with a circular cross-section. Based on the numerical results, a physical relation between the entropy production and the total pressure losses inside the volute is presented, allowing the attribution of the loss characteristics to the local entropy productions in specific flow regions of the volute.