Miracle-dz/UniFAR-FTUs huggingface dataset:
Critical Reviews in Food Science and Nutrition

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Chemical and Electrical Approaches to Sedation of Cobia: Induction, Recovery, and Physiological Responses to Sedation

To support the growing interest in marine ﬁsheries research in areas such as biotelemetry, tagging, and tracking, we assessed the ability of various sedatives to facilitate this research in juvenile cobias Rachycentron canadum ( ∼ 300 g), namely, tricaine methanesulfonate (MS-222; 150 mg/L), carbon dioxide (CO 2 ; ∼ 750 mg/L), eugenol (60 mg/L), benzocaine (150 mg/L), and pulsed-DC electrosedation (100 V, 30 Hz, 25% duty cycle, 5-s exposure). Induction times (CO 2 [z] > benzocaine [y] > eugenol [y] > MS-222 [y] > electrosedation [x]), recovery of equilibrium (CO 2 [z] > eugenol [z] > MS-222 [y] > benzocaine [y] > electrosedation [x]), and responsiveness to tactile stimulus (eugenol [z] > MS-222 [y] > benzocaine [y] > CO 2 [xy] > electrosedation [x]) differed signiﬁcantly among the sedative treatments (treatments with the same letters are not signiﬁcantly different). Total handling time from initial sedative exposure to recovery differed among the sedatives as well (CO 2 [z] > eugenol [y] > benzocaine [x] > MS-222 [x] > electrosedation [w]), with cumulative means ± SEs of 5.9 ± 0.2 min for CO 2 , 4.1 ± 0.2 for eugenol, 2.7 ± 0.2 min for benzocaine and MS-222, and 1.0 ± 0.2 min for electrosedation. Physiological responses differed signiﬁcantly over time, with transient increases in plasma cortisol, glucose, osmolality, and lactate that were resolved within 6 h. The overall magnitude of the physiological responses differed among sedatives, depending on the response variable; however, in each case, CO 2 elicited the greatest response. Although variations in induction and recovery times were observed, it is likely that these differences can be reasonably accommodated within the context of typical research by adjusting the sedative treatments or allowing for longer induction and recovery times as needed.
The impact of zwf overexpression on plasmid biopharmaceutical production by Escherichia coli

Plasmid DNA vectors may find application as preventive or therapeutic DNA vaccines for viral, bacterial, or parasitic diseases or for other indications such as cancer, or gene therapy products. Therefore, the demand of pDNA is expected to rise significantly in the near future and the establishment of a high-yield and cost effective manufacturing process is one of the key challenges for the success of plasmid DNA market. With the goal of creating an E. coli strain specifically adapted to meet the upstream and downstream processing challenges associated with large scale production of plasmid vectors, some mutations have been made in its genome. One main area of focus is modification of central carbon metabolism genes to increase flux toward nucleotide and amino acid precursor synthesis and reduction of byproducts, such as acetate. The zwf and rpiA are two important genes of the Pentose Phosphate Pathway and its overexpression was already tested and appeared to increase plasmid amplification rate. Therefore, the overexpression of the zwf and rpiA genes in GALG20 (MG1655 ΔendAΔrecAΔpgi ) is intended in this project, by replacing its original promoters with stronger ones. The results obtained showed that zwf gene overexpression did not improve plasmid productivity in GALG20 strains, behaving similarly to GALG20rpiA.
Evaluating Instrument Validity using the Principle of Independent Mechanisms

The validity of instrumental variables to estimate causal effects is typically justified narratively and often remains controversial. Critical assumptions are difficult to evaluate since they involve unobserved variables. Building on Janzing and Schölkopf’s (2018) method to quantify a degree of confounding in multivariate linear models, we develop a test that evaluates instrument validity without relying on Balke and Pearl’s (1997) inequality constraints. Instead, our approach is based on the Principle of Independent Mechanisms, which states that causal models have a modular structure. Monte Carlo studies show a high accuracy of the procedure. We apply our method to two empirical studies: first, we can corroborate the narrative justification given by Card (1995) for the validity of college proximity as an instrument for educational attainment in his work on the financial returns to education. Second, we cannot reject the validity of past savings rates as an instrument for economic development to estimate its causal effect on democracy (Acemoglu et al., 2008).
“Complications of Repeated Caesarean Sections At A Tertiary Care Hospital”

: Background : In the light of increasing incidence of caesarean section and the complications associated with it, our study aims to evaluate the pregnancy outcomes (in terms of maternal and foetal complications) of repeated caesarean sections and to determine the influence of number of previous caesarean deliveries and type of current caesarean sections in such complications. Materials and Methods: 500 antenatal women attending Modern Government Maternity Hospital, Osmania Medical College, Hyderabad, India, during the period of Dec 2018 to May 2020 (18 mon), were included in the prospective observational study. Subjects were divided into single CS and multiple CS groups and also elective CS and emergency CS groups for evaluation. Results: In the present study, in comparison between one previous caesarean section (single CS) and two or more caesarean sections (multiple CS), we found that the maternal age and the need for upper segment incision increased with increasing number of caesarean deliveries. Bladder and lower uterine complications like drawn up bladder, thinned out uterine segment and scar dehiscence were significantly higher. Even though abnormal placentation was not significantly different between groups, the blood loss, the subsequent hospital stay were higher in the multiple CS group and the likelihood of caesarean hysterectomy also increased. Postoperatively, prolonged urinary catheterisation was significantly higher in multiple CS. In spite of no significant difference between the birth weights, foetal morbidity in the form of respiratory distress, neonatal jaundice as well as NICU admissions showed significant increase in multiple CS. In our comparison between elective and emergency caesarean sections, there was higher frequency of iatrogenic prematurity in emergency CS and an unbooked case or a referral case was more likely to undergo an emergency CS. There was no significant difference in the anaesthesia used, abnormal placentation, blood loss, blood component transfusion, incidence of caesarean hysterectomy, hospital stay and HDU/ICU care postoperatively. Drawn-up bladder was significantly more common in emergency CS. Lower uterine segment complications like thinned out lower uterine segment and scar dehiscence were more common in emergency CS, but the difference was not statistically significant. Postoperative complications were not significantly different. The birth weight of the neonates and subsequently, NICU admissions were significantly lower in emergency CS. Conclusion: There is a slight but definite increase in the frequencies of complications with an increasing number of caesarean sections. This calls for a conscious effort to curtail this healthcare epidemic on the part of every obstetrician, by reducing the rates of primary caesarean sections, increasing the rates of TOLAC in well-selected cases and also by limiting the family size in general.
Evolution geodynamique hercynienne des pyrenees centrales : contraintes structurales, metamorphiques, magmatiques et sedimentologiques

La chaine hercynienne des pyrenees correspond a un segment occidental de la chaine hercynienne d'europe. Son evolution tectono-metamorphique se caracterise par la succession de deux episodes: le developpement d'un metamorphisme de moyenne pression haute temperature au debut, la mise en place diapirique simultanee de migmatites et de magmas dans la croute superieure est responsable de domes structuraux et d'un metamorphisme de basse pression haute temperature. Cet episode tectono-metamorphique s'est produit au cours d'un raccourcissement pendant la sedimentation flysch carbonifere dans des bassins d'avant-chaine. Il fut suivi par l'emersion de la chaine au stephanien, accompagnee du developpement de bassins detritiques intamontagneux et d'un volcanisme calco-alcalin suggerant un contexte geodynamique en compression associe a un decrochement dextre parallele a la faille nord-pyreneenne. L'evolution geodynamique globale des pyrenees apparait semblable a celle d'une chaine en collision et s'integre bien dans le schema geodynamique de collision continentale propre a la chaine hercynienne dans son ensemble
Prevalence of Metabolic Syndrome among Sistanee Ethnic Women

Introduction: The frequency of the metabolic syndrome is increasing throughout the world. The etiology of the metabolic syndrome is dependent on different factors. This study aimed to evaluate the metabolic syndrome among Sistanee ethnic women in Gorgan, North East of Iran. Methods: The study conducted on the hundred and sixty Sistanee women (2040years) who were referred to the Health Centers in Gorgan. Metabolic syndrome was diagnosed using Adult Treatment Panel-III (ATP-III) guidelines. Results: The mean body mass index, waist circumference, systolic blood pressure, diastolic blood pressure, fasting blood glucose and levels were significantly higher in the subjects with metabolic syndrome. The prevalence of low High Density Lipoprotein-cholesterol level, high waist circumference, high triglyceride level, , high blood pressure and high fasting glucose were 23.12%, 22.50%, 16.25%, 12.50% and 0.62%, respectively. Low HDL-cholesterol level (23.12%) and high waist circumference (22.50%) are the most frequent characteristics in comparison to other metabolic components. Conclusion: The reasonable interpretation for our results is that Sistanee women in this area maybe had lower physical activity. Low HDL-cholesterol and high 364 Abdoljalal Marjani et al waist circumference were the most usual factors of metabolic abnormality among these women.
Multi-scale analysis of shear behaviour of crushable granular sand under general stress conditions

Grain crushing underpins key mechanical behaviours of granular materials. A variety of factors, including grading, particle shapes and loading conditions, have been recognised to affect the crushability of grains and the overall behaviour of a granular material. Among them, the role of intermediate principal stress in a general stress condition on the shear behaviour of crushable granular sand remains less understood, owing to the scarcity of experimental data and analytical tools available. In this paper, a multi-scale computational approach is employed to investigate the shear behaviour of crushable granular sand under general stress conditions with varying intermediate principal stresses and confining pressures. The computational approach features multi-scale coupling between non-smooth contact dynamics and peridynamics, and offers a rigorous way to consider the intertwined evolution of particle size and shape during the process of grain crushing. The numerical study helps to quantify comprehensively and analyse the grain crushing-induced changes of macro-and micro-scale material behaviours including strength, deformability, particle size and shape evolution, particle-scale forces and contact conditions, and the development of anisotropy. The competition between a void-filling mechanism due to grain size change and enhanced friction and interlocking due to grain shape change in dictating the deformation of crushable sand is further discussed. The findings offer insights into the complex behaviours of crushable granular materials under general stress conditions and facilitate future development of physics-based constitutive theories on crushable sand.
Machine Learning Approaches for Streamflow Modeling in the Godavari Basin with CMIP6 Dataset

Accurate streamflow modeling is crucial for effective water resource management. This study used five machine learning models (support vector regressor (SVR), random forest (RF), M5-pruned model (M5P), multilayer perceptron (MLP), and linear regression (LR)) to simulate one-day-ahead streamflow in the Pranhita subbasin (Godavari basin), India, from 1993 to 2014. Input parameters were selected using correlation and pairwise correlation attribution evaluation methods, incorporating a two-day lag of streamflow, maximum and minimum temperatures, and various precipitation datasets (including Indian Meteorological Department (IMD), EC-Earth3, EC-Earth3-Veg, MIROC6, MRI-ESM2-0, and GFDL-ESM4). Bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets were utilized in the modeling process. Model performance was evaluated using Pearson correlation (R), Nash–Sutcliffe efficiency (NSE), root mean square error (RMSE), and coefficient of determination (R2). IMD outperformed all CMIP6 datasets in streamflow modeling, while RF demonstrated the best performance among the developed models for both CMIP6 and IMD datasets. During the training phase, RF exhibited NSE, R, R2, and RMSE values of 0.95, 0.979, 0.937, and 30.805 m3/s, respectively, using IMD gridded precipitation as input. In the testing phase, the corresponding values were 0.681, 0.91, 0.828, and 41.237 m3/s. The results highlight the significance of advanced machine learning models in streamflow modeling applications, providing valuable insights for water resource management and decision making.
Community-Based Epidemiological Study on Diabetes in Pu-Li, Taiwan

Objective –To determine the prevalence and possible risk factors associated with diabetes in Pu-Li, Taiwan. Research Design and Methods –The project was a community-based cross-sectional study with stratified cluster sampling of residents ≥ 30 yr of age. Medical students conducted home-visit interviews with public health nurses, drew fasting blood samples from 1738 of 2573 registered residents ≥ 30 yr of age in Pu-Li, Taiwan. Results –The prevalence of diabetes, including those with a history of diabetes and newly diagnosed cases determined by modified World Health Organization criteria, was 12.4%. With the standard world population of Segi, the age-adjusted prevalences were 6.9% for previous diabetes and 4.4% for new diabetes. The age-specific prevalence of diabetes increased significantly with age for new diabetes cases but not for previously diagnosed cases. To study factors associated with diabetes, we first applied univariate analysis. Stratified analyses by age and sex were used for interaction assessment. A significant interaction effect on diabetes was found between age and sex. Logistic regression was used for multivariate analysis. The final model showed that, after controlling for all other covariates, the significant factors associated with diabetes were family history of diabetes (father and/or mother, yes vs. no, odds ratio [OR] 3.13, 95% confidence interval [CI] 1.17–8.33), obesity (yes vs. no, OR 2.69, 95% CI 1.09–6.63), and age (continuous, OR 1.04, 95% CI 1.00–1.08). Locality and physical activity were not significantly correlated with diabetes. Conclusions –The age-adjusted prevalence of diabetes in Pu-Li were 6.9% for previous diabetes and 4.4% for new diabetes. Possible risk factors associated with diabetes with logistic regression were family history of diabetes, obesity, and age. Locality and physical activity were not significantly correlated with diabetes.
Airborne surface profiling of glaciers: a case-study in Alaska

Abstract A relatively lightweight and simple airborne system for surface elevation profiling of glaciers in narrow mountain valleys has been developed and tested. The aircraft position is determined by kinematic global positioning system (GPS) methods. The distance to the glacier surface is determined with a laser ranger. The accuracy is about 0.3 m, sufficient to permit future changes to be observed over short time intervals. Long-term changes can be estimated by comparison of profiles with existing maps. Elevation profiles obtained in 1993–94 from three glaciers in central and south-central Alaska are compared with maps made about 1950. The resulting area-averaged, seasonally corrected thickness changes during the interval are: Gulkana Glacier (central Alaska Range)–11 m, Worthington Glacier (central Chugach Mountains) +7 m, and Bear Lake Glacier (Kenai Mountains) −12 m. All three glaciers retreated during the interval of comparison. The estimated uncertainty in the average thickness change is ±5 m. which is mainly due to errors in the existing maps. Constraints on the accuracy of the maps are obtained by profiling in proglacial areas.
Comparative Study the Effect of Induction of General Anesthesia with Propofol Versus Thiopentone in Pediatric Age Group on Cardiovascular System

We compared the hemodynamic responses of i.v. Propofol 2.5 mg/kg with thiopental 5.0 mg/kg in 41 healthy children during anesthesia induction in Imam Sadiq Teaching Hospital and Al Hilla General Teaching Hospital/ AL Hilla IRAQ from February 2014 to December 2016
Transports fluviaux de carbone organique par la Garonne à l'entrée de l'estuaire de la Gironde

Sur trois cycles hydrologiques annuels successifs, des mesures hebdomadaires des teneurs en carbone organique, en phases particulaires et dissoute, on ete faites dans les eaux de la Garonne, a la limite amont du systeme estuarien, afin de dresser un bilan fiable des flux de matiere organique entrant dans cet estuaire. Du fait d’un deficit hydrologique notable (pres de 40 %) sur la periode echantillonnee, les bilans etablis se sont reveles tres inferieurs a ceux proposes anterieurement sur des bases de donnees de moindre qualite. Neanmoins, cette etude a permis de preciser les relations liant debits-matieres en suspension et teneurs en carbone organique (ses composantes phytoplanctoniques et pedologiques) et de mettre en valeur certains effets de la secheresse (elevation des teneurs en carbone organique dissous, impact d’une crue faisant suite a un long etiage). Enfin, en se servant des methodes de calcul utilisees pour les cycles etudies et en les appliquant a une annee type (debit moyen annuel de 650 m³.s¯¹), un bilan des flux organiques entrant dans l’estuaire est propose. Il s’avere qu’en comparant ces flux a ceux qui sont expulses vers l’ocean au sorti de la Gironde, pres de 55 % de la charge organique particulaire entrante disparait dans l’estuaire apres mineralisation, phenomene confirme par les etudes en cours sur les fortes emissions de CO2 dans ces interfaces continent-ocean.
Place Recognition and Online Learning in Dynamic Scenes with Spatio-Temporal Landmarks

This paper presents a new framework for visual place recognition that incrementally learns models of each place and offers adaptability to dynamic elements in a scene. Traditional bag-of-features image-retrieval approaches to place recognition treat images in a holistic manner and are typically not capable of dealing with sub-scene dynamics, such as structural changes to a building facade or the rearrangement of furniture in a room. However, by treating local features as observations of real-world landmarks in a scene that are consistently observed, such dynamics can be accurately modelled at a local level, and the spatio-temporal properties of each landmark can be independently updated online. We propose a framework for place recognition that models each scene by sequentially learning landmarks from a set of images, and in the long term adapts the model to dynamic behaviour. Results on both indoor and outdoor datasets show an improvement in recognition performance and efficiency when compared to the traditional bag-offeatures image retrieval approach.
Water and Environmental Resources: A Multi-Criteria Assessment of Management Approaches

The present study applied a multi-criteria analysis to evaluate the best approach among six theoretical frameworks related to the integrated management of water–environmental resources, analyzing the frequency of multiple management criteria. The literature review covers the period from 1990 to 2015, with a notable presence of the theoretical frameworks of Integrated Water Resources Management (IWRM), Ecohealth, Ecosystem Approach (EA), Water Framework Directive (WFD), and, to a lesser extent, the Watershed Governance Prism (WGP) and the Sustainability Wheel (SW). The multi-criteria decision-making (MCDM) methods applied include AHP (Analytic Hierarchy Process), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations). Twenty-five criteria were analyzed, such as governance, participation, sustainability, decentralization, and health and well-being, among others. We started with five criteria for evaluating the hierarchy of the six theoretical frameworks using the AHP method. Subsequently, we again evaluated the five criteria using the TOPSIS and PROMETHEE methods to calibrate the results with the AHP. Then, using word counting, we evaluated the best approach, applying 10, 15, 20, and 25 more criteria. Our results indicate that the best integrated management alternative was the WFD, which fulfilled 47% of the management criteria. Second, with 45%, was the WGP, and third was IWRM, with 41%; less successful approaches to the criteria were demonstrated by the EA, SW, and Ecohealth methods. By applying this methodology, we demonstrated an excellent structured tool that can aid in the selection of the most important issue within a given sector.
Fast and Scalable Unsupervised Deep Subgraph Anomaly Detection

Mining anomalous subgraphs in networks is a crucial task in various application scenarios, such as disease outbreak detection, ﬁnancial fraud detection, and activity monitoring in social networks. However, identifying anomalous subgraphs is a challenging problem due to their complex topological structures, high-dimensional attributes, various notions of anomalies, and the exponentially large subgraph searching space in a given graph. Classical shallow models typically rely on handcrafted anomaly measure functions, which are not eﬀec-tive when prior knowledge is unavailable. To address this issue, deep learning-based methods have been proposed as an end-to-end way of learning anomaly measure functions. However, while these methods have been successful in detecting node-level, edge-level, and graph-level anomalies, detecting anomalous subgraphs has been largely underex-plored due to diﬃculties in subgraph representation learning, lackness of supervision, end-to-end anomaly quantiﬁcation, and their scalability. In this paper, we propose a novel deep framework called the A nomalous S ub g raph A uto e ncoder ( AS-GAE ) to extract anomalous subgraphs in an unsupervised and weakly-supervised manner. To enhance the scalability of our proposed model on large-scale graphs, we further design an edge sampling technique that reduces the time and memory complexity from a quadratic term of the number of nodes to a linear term of the number of edges. Our proposed method is demonstrated to be superior in terms of accuracy and eﬃciency through extensive experiments on two synthetic datasets and nine real-world datasets.