Miracle-dz/UniFAR-FTUs huggingface dataset:
The Development of New Toxicity Testing and Approval Processes for Oil Spill Treatment Products in the UK

Current experimental protocols for the toxicity assessment of oil spill treatment products in the UK have been established since the 1970s. To address health and safety, cost and scientific robustness issues the UK approach for dispersant testing and approval has been reviewed and updated for implementation during 2020. To provide more robust scientific advice for the risk assessments that enable effective decision making on the use of oil remediation products in the event of a spill there has been a focus on methods that already have internationally accepted protocols. Standardisation of dispersant testing will promote more effective cross-institute comparisons of toxicity data and will enable further harmonisation of approaches in the future. It is preferable that environmentally relevant test species are used but, as the scientific literature provides little conclusive evidence of a taxa-specific trend in sensitivity, species selection based on sensitivity alone was not justified. Eight dispersants, commonly stockpiled in the UK, were tested independently and in combination with a representative crude oil (Kuwait). Testing of dispersants in combination with oil has historically provided more variable results so this study has considered the benefits of this versus product only testing. Core test species included the harpacticoid copepod, Tisbe battagliai, and the algae, Skeletonema sp. , as both have cost-effective internationally standardised methods, whilst also being environmentally representative and using test species easily cultured under laboratory conditions with no seasonality. Other candidate test species, such as oyster embryos, had limitations in applicability due to seasonal issues. Fish testing was not considered as there was no ethical reasoning for vertebrate testing due to the absence of taxa-specific toxicity. Results showed that, if oil is excluded from the assessment, Skeletonema sp. and Tisbe battagliai, can produce reliable, reproduceable and interpretable results. When running the T. battagliai test, independently on multiple occasions, without oil, dispersant 1, 2 and 3 had EC50 results that were not statistically different. This suggests that product only testing is suitable for ranking products based on toxicological hazard. The redevelopment of the UK guideline to use standardised testing and the selection of appropriate, environmentally relevant test organisms will increase the quality and reliability of data used to underpin the UK oil spill treatment testing and approval scheme. The adoption of this approach will enable an approved list of products for use in UK waters to be maintained. However, the decision for dispersant use in any given scenario will need to be underpinned through expert advice applying a risk assessment approach taking account a range of incident-specific physical and environmental sensitivity information.
A Review on Systematic Investigation of Leucocytes Identification and Classification Techniques for Microscopic Blood Smear

Healthcare services are an important part of human beings and healthcare services are changing with new and innovative technologies. In recent day’s healthcare sector performing very crucial role in metamorphose of traditional health services to e-health technologies. This proposal provides an error-free and improved technology-based blood analysis service for the identification of leucocytes in blood samples of humans. Leucocytes play a vital and important character in human immune systems. This system helps to protect the body from suffering from leukemia. Leukemia, a blood cancer, nowadays is commonly found in all age persons. Leukemia is a type of disease and image processing techniques and algorithms can play a crucial role in disease diagnostic methodology. Identification of leukocytes in blood smear provides important information to pathologist as well as doctors to analyze and predicts different types of diseases, such as cancer. However, this analysis is critical and major complexities which results in errors and also takes a lot of time for analysis. Most of the time, the laboratory practitioners and doctors are interested only in leucocytes in blood smear. Medical image processing techniques strongly supports in their critical diagnosis and better results.
Gate-induced drain leakage current in MOS devices

The gate-induced drain leakage current (GIDL) in typical n-channel MOSFETs is calculated for direct and indirect tunneling from the valence band to the conduction band of silicon, as well as tunneling from the conduction band minimum of silicon to the interface traps, and compared to experimental data. The results show that in silicon MOSFETs the GIDL is dominated by tunneling from the conduction band to the interface traps, and the contribution from both direct and indirect band-to-band tunneling is negligible. >
Data-based wildfire risk model for Mediterranean ecosystems – case study of the Concepción metropolitan area in central Chile

Abstract. Wildfire risk is latent in Chilean metropolitan areas characterized by the strong presence of wildland–urban interfaces (WUIs). The Concepción metropolitan area (CMA) constitutes one of the most representative samples of that dynamic. The wildfire risk in the CMA was addressed by establishing a model of five categories (near zero, low, moderate, high, and very high) that represent discernible thresholds in fire occurrence, using geospatial data and satellite images describing anthropic–biophysical factors that trigger fires. Those were used to deliver a model of fire hazard using machine learning algorithms, including principal component analysis and Kohonen self-organizing maps in two experimental scenarios: only native forest and only forestry plantation. The model was validated using fire hotspots obtained from the forestry government organization. The results indicated that 12.3 % of the CMA's surface area has a high and very high risk of a forest fire, 29.4 % has a moderate risk, and 58.3 % has a low and very low risk. Lastly, the observed main drivers that have deepened this risk were discussed: first, the evident proximity between the increasing urban areas with exotic forestry plantations and, second, climate change that threatens triggering more severe and large wildfires because of human activities.
Increased risk of bladder cancer in young adult men with hyperlipidemia

Abstract A high-cholesterol diet increases the risk of bladder cancer. The purpose of this nationwide longitudinal population-based retrospective cohort study is to investigate whether hyperlipidemia is a risk factor for bladder cancer. Data from Taiwan National Health Insurance Database were analyzed. The primary study end point was the occurrence of newly diagnosed bladder cancer. The relative risk of bladder cancer in a hyperlipidemia cohort was compared with that in an age- and gender-matched non-hyperlipidemia cohort by using the Cox proportional hazards regression model. Cox regression analyses were further adjusted by the propensity score. Our data revealed that the hyperlipidemia cohort (n = 33,555) had a significantly higher subsequent risk of bladder cancer than did the non-hyperlipidemia cohort (n = 33,555) (adjusted hazard ratio [HR] = 1.37, P = .005) after propensity score adjustment. Subgroup analyses revealed that men in the hyperlipidemia cohort had a significantly higher subsequent risk of bladder cancer than did those in the non-hyperlipidemia cohort (adjusted HR = 1.36, P = .040). However, the risk of bladder cancer was not significantly different between women in the hyperlipidemia cohort and those in the non-hyperlipidemia cohort. Subgroup analyses further revealed that the risk of bladder cancer was significantly higher in men aged 20 to 39 years in the hyperlipidemia cohort than in those in the non-hyperlipidemia cohort (adjusted HR = 5.45, P = .029). In conclusion, hyperlipidemia is a risk factor for bladder cancer in young adult men.
Research Article Exogenous pyruvate mitigates the detrimental effects of water stress in contrasting peanut genotypes

Water stress triggers various cellular responses in plants, altering normal metabolic flow. Pyruvate, an important component of the glycolysis pathway, is directly involved in cell processes, triggering genes that influence drought tolerance. Research with Arabidopsis has shown that synthetic pyruvate relieves drought damage. We evaluated the effects of exogenous pyruvate at 100 and 50,000 μM on mitigation of drought stress in two peanut cultivars submitted to water restriction. The evaluations were based on growth, gas exchange, and photosynthesis rate analyses. In addition, superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX) enzymes, and free proline were also assayed. In general, exogenous application of pyruvate contributed to mitigate the effects of water stress in the cultivar IAC Caiapó (sensitive to drought), based on gas exchange and instantaneous efficiency of water use. Exogenous pyruvate contributed to restore the action of antioxidative enzymes in BR 1 (tolerant to drought), based on measures of SOD (45%), CAT (129%) and APX (60%) in stressed plants, and full recovery at 50,000 μM. When treated with proline, stress attenuation was found only at 100 μM in both cultivars; the excess seemed to have a negative effect on stressed plants, probably affecting the cell
Developing A Conceptual Framework for Science Teaching at Colleges of Education in Ghana

This paper looks at Science taught in Ghana generally. It defines Science and science education fundamentally, as the methodical observation, conception, analysis, and exhibition of patterns to understand what exist in the physical universe which is evidence-based and their interactions with each other. The understanding of these processes keeps changing as new relationships and explanations emerge. The motion and interactivity with materials employed by the pedagogies become key elements for creating exciting, dynamic and captivating experiences that motivate students to learn and pursue a science course with a greater sense of purpose. Science education is the teaching and learning of science to non-scientists, such as school children, college students, or adults within the general public. The field of science education includes work in science content, science process, some social science, and some teaching pedagogy. However, the employ of inappropriate teaching methodologies is one of the factors that contribute to the low participation and performance of students in science. Little effort is made to relate the concepts learnt and the examples/illustrations used to real life, especially within the context of the students' own lives and environment. This article attempts to proffer a concise definition to merge the ideas from some scholars for a better understanding of science; meaning of Science Education; relevance of the study of science (or science education); problems of science teaching in Ghana and the effects and propounds a challenging model for implementation for effective science teaching in Colleges of Education in Ghana.
Multi‐timepoint pattern analysis: Influence of personality and behavior on decoding context‐dependent brain connectivity dynamics

Behavioral traits are rarely considered in task‐evoked functional magnetic resonance imaging (MRI) studies, yet these traits can affect how an individual engages with the task, and thus lead to heterogeneity in task‐evoked brain responses. We aimed to investigate whether interindividual variation in behavior associates with the accuracy of predicting task‐evoked changes in the dynamics of functional brain connectivity measured with functional MRI. We developed a novel method called multi‐timepoint pattern analysis (MTPA), in which binary logistic regression classifiers were trained to distinguish rest from each of 7 tasks (i.e., social cognition, working memory, language, relational, motor, gambling, emotion) based on functional connectivity dynamics measured in 1,000 healthy adults. We found that connectivity dynamics for multiple pairs of large‐scale networks enabled individual classification between task and rest with accuracies exceeding 70%, with the most discriminatory connections relatively unique to each task. Crucially, interindividual variation in classification accuracy significantly associated with several behavioral, cognition and task performance measures. Classification between task and rest was generally more accurate for individuals with higher intelligence and task performance. Additionally, for some of the tasks, classification accuracy improved with lower perceived stress, lower aggression, higher alertness, and greater endurance. We conclude that heterogeneous dynamic adaptations of functional brain networks to changing cognitive demands can be reliably captured as linearly separable patterns by MTPA. Future studies should account for interindividual variation in behavior when investigating context‐dependent dynamic functional connectivity.
Measuring effectiveness of safety programmes in the Thai construction industry

Some safety programmes are more effective than others in improving safety performance at the project level. The effectiveness of safety programmes was evaluated by studying 70 construction projects in the Thai construction sector, examining the relationship between their actual status and associated site safety performance. The actual status was assessed by using an evaluation tool developed in compliance with Thai safety legislation and validated by safety experts. Safety performance was assessed by using reactive and proactive measures. Particularly, the accident rate was used as a reactive indicator, while the unsafe act index and the unsafe condition index were used as proactive indicators. The results demonstrated that safety performance was influenced by the nature of implemented safety programmes. First, safety programmes which positively affect accident rates include accident investigations, jobsite inspections, control of subcontractors and safety incentives. Secondly, five programmes, namely jobsite inspections, accident investigations, job hazard analysis, safety committees and safety record keeping, were found to have the most contributions to fewer unsafe acts. And thirdly, accident investigations, jobsite inspections, job hazard analysis, safety inductions and safety auditing were the most effective programmes in reducing unsafe conditions.
Antibody-drug conjugates in treating older patients suffering from cancer: what is the real value?

ABSTRACT Immunotherapeutic drugs and target therapies have represented an epochal change in treating cancer patients. They represent an attractive option in oncologists’ armamentarium, particularly if we consider the optimal balance between efficacy and toxicity. As a step forward, immuno- and target-therapies have merged intending to improve efficacy: antibody-drug conjugates ensure the perfect combination. They allow the delivery of large amounts of drugs to the target with a limited ‘off-target’ effect and a low rate of adverse events. These aspects could make immunoconjugates palatable as the first choice for fragile patients, but solid evidence does not exist on the use of these drugs in this population type, especially older people.
Assumptions and trade-offs in device simulation programs

The author examines the physical assumptions which underlie device simulation programs and considers their implications for advanced bipolar transistors. The limits of drift-diffusion equations are discussed, and advanced techniques such as hydrodynamic and Monte Carlo approaches are described. Some thoughts on the device simulation requirements for future generation bipolar transistors are also presented. <<ETX>>
Scheduling two-stage production lines with multiple machines

Abstract Most manufacturing process maintain separate fabrication and assembly centres. Based on this observation, the author coincides a manufacturing process that contains two stages of production with multiple machines. The manufacturer produces a variety of products to satisfy customer demands, operates under a 'push' mode and in a ‘ make-to-order’ environment. Each customer order consists of known quantities of different products which must be delivered as a whole shipment. Periodically, the manufacturer schedules all the accumulated unscheduled customer orders. The scheduling objective is to minimize the sum of weighted customer order lead times. Such manufacturing systems are formulated as a mathematical programming problem. It is then shown that this problem is unary NP-hard and remains unary NP-hard even when all the weights are equal. Some insights about the structure of the optimal schedule(s) are provided and some special cases solved in polynomial time. Several polynomial time heuristics are .
Evaluation and Field Load Testing of Timber Railroad Bridge

Several spans of a 60-year-old open-deck timber railroad bridge on the Southern Pacific Railroad Line (now the Union Pacific) in Southwest Texas were field tested. The tests were conducted with the sponsorship and cooperation of the Association of American Railroads to determine the vertical live load distribution characteristics of the superstructure. The bridge was originally constructed with Douglas-fir larch solid sawn stringers but was rehabilitated on several occasions to allow comparisons to be made with respect to different rehabilitation options, including the use of a helper stringer and the use of glued laminated timber (glulam) stringers. The test spans measured approximately 4.1 m (13.5 ft) center-to-center of supports and included two closely “packed” chords, each consisting of four timber stringers (one test span included an additional helper stringer added to one chord). One chord was made up of glulam timber and the other was made up of solid sawn timber. The bridge superstructure was generally in satisfactory condition, with some stringer horizontal splitting noted over the bents. The bents were in reasonably good condition, but chord bearing was uneven on bent caps. Static and dynamic deflection load test data were obtained using a special test train. The test results indicate that the glulam chord performed better than the older sawn stringer chord, even when a helper stringer was added. Individual stringers within a chord did not always share the load equally.
Novel strategies to oral delivery of insulin: Current progress of nanocarriers for diabetes management

Diabetes mellitus is one of the most serious public health problems in the world. Repeated daily injections of subcutaneous insulin is the standard treatment for patients with type 1 diabetes mellitus; however, subcutaneous insulin injections can potentially cause local discomfort, patient noncompliance, hypoglycemia, failure to regulate glucose homeostasis, infections, and fat deposits at the injection sites. In recent years, numerous attempts have been made to produce safe and efficient nanoparticles for oral insulin delivery. Oral administration is considered the most effective alternative route to insulin injection, but it is accompanied by several challenges related to enzymatic proteolysis, digestive breakdown, and absorption barriers. A number of natural and synthetic polymeric, lipid‐based, and inorganic nanoparticles have been investigated for use. Although improvements have recently been made in potential oral insulin delivery systems, these require further investigation before clinical trials are conducted. In this review, new approaches to oral insulin delivery for diabetes treatment are discussed, including polymeric, lipid‐based, and inorganic nanoparticles, as well as the clinical trials performed for this purpose.
Conceptualization and Psychometric Properties of the Sleep Behavior Self-regulation Dimensions: A Theory-Based Instrument

Background: Focus on sleep regulation is crucial due to the direct health consequences of insufficient sleep to adolescents’ health and education performance. This study aims to develop and validate an instrument to measure sleep behavior self-regulation (SBSR) and its influential factors in a student sample.Methods: A preliminary version of the measurement instrument was developed using a literature review and conceptual framework. Expert analysis of content validity, item analysis, factor analysis and reliability analysis was performed for the psychometric evaluation. This study has a total of 401 students. The data was analyzed using SPSS 22.0 and AMOS 22.0. Results: The exploratory factor analyses offered a structure with six factors. The model presents a good fit (χ2/df = 1.65, RMSEA = 0.053, CFI = 0.920, and GFI =0.826). General test reliability was good (α = 0.9). Conclusions: SBSRI is a multidimensional instrument and a valid and reliable way of obtaining information about sleep behavior self-regulation. The use of this instrument will make it possible to adjust behavior to subjective goals and real experiences to promote sleep-related behavior change.
Ultrafine MoS2 Nanosheets Vertically Patterned on Graphene for High-Efficient Li-Ion and Na-Ion Storage

Hierarchically two-dimensional (2D) heteroarchitecture with ultrafine MoS2 nanosheets vertically patterned on graphene is developed by using a facile solvothermal method. It is revealed that the strong interfacial interaction between acidic Mo precursors and graphene oxides allows for uniform and tight alignment of edge-oriented MoS2 nanosheets on planar graphene. The unique sheet-on-sheet architecture is of grand advantage in synergistically utilizing the highly conductive graphene and the electroactive MoS2, thus rendering boosted reaction kinetics and robust structural integrity for energy storage. Consequently, the heterostructured MoS2@graphene exhibits impressive Li/Na-ion storage properties, including high-capacity delivery and superior rate/cycling capability. The present study will provide a positive impetus on rational design of 2D metal sulfide/graphene composites as advanced electrode materials for high-efficient alkali–metal ion storage.
Using Artificial Intelligence in Source Code Summarization: A Review

Source code summarization is the methodology of generating the description from the source code. The summary of the source code gives the brief idea of the functionality performed by the source code. Summary of the code is always necessary for software maintenance. Summaries are not only beneficial for software maintenance but also for code categorization and retrieval. Generation of summary in an automated fashion instead of manual intervention can save the time and efforts. Artificial Intelligence is a very popular branch in the field of computer science that demonstrates machine intelligence and covers a wide range of applications. This paper focuses on the use of Artificial Intelligence for source code summarization. Natural Language Processing (NLP) and Machine Learning (ML) are considered to be the subsets of Artificial Intelligence. Thus, this paper presents a critical review of various NLP and ML techniques implemented so far for generating summaries from the source code and points out research challenges in this field.