Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Indian rock phosphates for predicting agronomic potential through chemical and biological methods

ABSTRACT The chemical reactivity of Indian rock phosphates (RPs) was measured by five chemical extraction methods (i.e. water, neutral ammonium citrate (NCA), 2% citric acid (CA), 2% formic acid (FA) and absolute citrate solubility (ACS)). These measurements were assessed by agronomic response data obtained by growing ryegrass and palmarosa in two highly weathered acidic soils under pot culture experiment. The phosphorus (P) solubility value of RP measured by different methods followed the order: ACS > 2% CA > 2% FA > NAC > water. Considering triple superphosphate (TSP) as a standard reference P fertilizer, the agronomic response of RPs followed the order Udaipur RP > Jhabua RP ≥ Purulia RP > Mussorie RP. Methods based on citrate solubility (i.e. NAC, 2% CA and ACS) were significantly and positively correlated with agronomic response irrespective of the plant species and soil types. The best correlation value obtained with NCA indicated that P solubility in NAC solution may offer better prediction of agronomic effectiveness of RP in terms of biomass yield, relative agronomic efficiency (RAE) and P recovery efficiency. So, the present investigation will help to predict the agronomic effectiveness of low-grade RP based on chemical methods.
The Beauty or the Beast? Unlocking Recombinant Determinants of Performance for Artistic and Functional Product Designs

Product innovation entails both technological and design innovation, yet our knowledge of determinants of innovation outcomes is limited to technological innovations. This is a significant limitation because design innovation represents an increasingly large share of total innovation activity by organizations and innovators. In this paper, we focus on two dimensions of design recombination: The number of parent designs, i.e., the number of designs that used in the creation of the focal design, and the transfer distance, i.e., the average categorical distance of parent designs to the focal design. We argue that using multiple parent designs is beneficial for functional designs and increases the likelihood that functional design is a “hit”. This outcome happens because using multiple parent designs enables designers to focus on improving a specific component or to focus on integrated functionality while using the best available components for the rest. For the artistic designs, however, transfer distance increases the likelihood that the design is a “hit”. When a designer uses design(s) from the same or similar categories, it may lead to a “design fixation” that reduces the novelty in the focal design, where novelty is a critical determinant of the success of artistic designs. Our findings, based on an online 3D printing community called Thingiverse, support our arguments. Our study has important implications for research on design innovation, recombinant innovation, and managing innovation communities.
Diversity of Escherichia coli from the enteric microbiota in patients with Escherichia coli bacteraemia

Objective The increase in Escherichia coli bloodstream infections mandates better characterisation of the relationship between commensal and invasive isolates. This study established a simple approach to characterize diversity of E. coli in the gut reservoir from patients with either E. coli bacteraemia, other Gram-negative bacteraemia, or patients without bacteraemia not receiving antibiotics. Stool or rectal swabs from patients in the three groups were cultured on selective chromogenic agar. Genetic diversity of E. coli in gut microbiota was estimated by RAPD-PCR. Results Enteric samples from E. coli bacteraemia patients yielded a median of one E. coli RAPD pattern (range 1-4) compared with two (range 1-5) from groups without E. coli bacteraemia. Of relevance to large-scale clinical studies, observed diversity of E. coli among E. coli bacteraemia patients was not significantly altered by sample type (rectal swab or stool), nor by increasing the colonies tested beyond ten. Overall, hospitalised patients demonstrated an apparently limited diversity of E. coli in the enteric microbiota and this was further reduced in those with E. coli bacteraemia. The reduced diversity of E. coli within the gut during E. coli bacteraemia raises the possibility that dominant strains may outcompete other lineages in patients with bloodstream infection.
Effect of Seasonal Variations (Breeding and Non-breeding Seasons) on Productive Performance and Reproductive Hormonal Profile in Nile Tilapia (Monosex and Mixed Sex)

Nile tilapia is one of the most widespread fish in Egypt and it is of great economic importance. This study aimed to know the effect of seasonal variations on the body, level of hormones and blood parameters. To conduct this study, Nile tilapia monosex and mixed sex were collected during breeding and nonbreeding seasons. Results revealed that seasonal variations on body parameters are more prominent in body weight, abdominal length, abdominal width, and abdominal circumference especially in female fishes. Reproductive hormones (FSH, LH, prolactin, testosterone, and Estradiol E2) are significantly increased during breeding season. The Erythrogram, total and differential leukocytic count increased significantly during breeding season, while thrombocytes are significantly declined during breeding season. The significant increase of Hepato-somatic index % and Gonado-somatic index % can be an indicator of breeding season in some fresh-water fish. Original Research Article Shawky et al.; JALSI, 19(4): 1-15, 2018; Article no.JALSI. 45850 2
Accounting for capacity: A real‐time optimization approach to managing observation unit utilization

Hospital observation units (OUs) are meant to host patients for relatively short periods of time, during which healthcare providers can observe a patient (usually following an emergency department encounter) and assess the need for an inpatient hospital admission. The initial placement of a patient in a unit (inpatient or observation) can have consequences for the care the patient receives and the patient's length of stay in the hospital, as well as financial implications for both the patient and the hospital. We propose a practical real‐time optimization algorithm that balances the need to place a patient in the OU with considerations for available capacity. Through computational experiments with inputs derived from real data, we study the benefit of using the algorithm for placing the right type of patients in the OU. We discuss the role of data‐driven decision support tools like the proposed algorithm for anchoring the decision‐making process in a hospital setting and for incorporating the viewpoints of multiple stakeholders by defining appropriate “rewards” for available alternatives.
Tibial Osteophytes as Indicator of Osteoarthritis: Morphometry and Clinical Importance

Background: An osteophyte is a bony outgrowth, covered with fibrocartilage,that is one of the hallmarks of osteoarthritis especially in the knee joint. Risk factors for development of osteophytes include age, physical activity, body mass index, and other genetic and environmental factors. Aim: To analyze the frequency and morphological features of osteophytes at the upper end of dry tibia bones and to define any relationship between the size of osteophytes and that of the intercondylar tibial spines. Methods: We evaluated 75 dry tibia bones for the degree of osteoarthritis at the upper end. Each plateau at the superior surface of the upper end was divided into four quadrants and the presence and size of bone outgrowths were recorded in each quadrant. The “medial/lateral tibial intercondylar spine index” for each specimen was calculated and relation with the osteophytes was observed. The measurements were meticulously recorded and the data were subjected to statistical analysis. Results: In the present study, osteophytes were found more frequently in the anterior quadrants of both the tibial plateaus than in the posterior quadrants. Grade 1 osteophytes were the most common type of osteophytes with predominance in anterior quadrants of both medial and lateral tibial plateaus. There was positive correlation between grades of osteophytes and spine index. Conclusion: This study would help clinicians to understand the morphological changes in the upper end of tibia in osteoarthritis which would help them in planning the management.
THE OVERVIEW OF GREEN TOBACCO SICKNESS AMONG TOBACCO FARMERS IN JEMBER DISTRICT, INDONESIA

Background: Green tobacco sickness (GTS) is a type of disease that is still not widely understood, but is often experienced by tobacco farmers. The duration and frequency of contact, the work procedures associated with wet tobacco, and individual vulnerability are risk factors for GTS. Purpose: This study aimed to measure the factors associated with incidences of GTS in tobacco farmers in Jember, Indonesia, to contribute to the prevention of GTS. Method: The research design used case-control. This research was conducted in Jember District, within a group of tobacco farmers. The case group included farmers who experienced GTS and the control group included farmers who did not experience GTS. The study measured age, sex, nutritional status, passive smoking status, alcohol consumption status, subjective complaints, individual hygiene, Occupational Health and Safety (OHS) attitudes, OHS actions, use of personal protective equipment, principal occupation, extra work, type of tobacco leaf, length of service, length of work-rest period, and workload. The study population were tobacco farmers. The sample size was determined using the Lemeshow sampling formula for case-control. The sampling technique was simple random sampling. Data analysis was conducted using chi-squared tests. Results: Variables related to GTS cases in tobacco farmers were sex (p = 0.01) and nutritional status (p = 0.03). There were no significant occupational factors. Conclusion: Factors that influence GTS are sex and nutritional status.
Segmentation-Enhanced CycleGAN

Algorithmic reconstruction of neurons from volume electron microscopy data traditionally requires training machine learning models on dataset-specific ground truth annotations that are expensive and tedious to acquire. We enhanced the training procedure of an unsupervised image-to-image translation method with additional components derived from an automated neuron segmentation approach. We show that this method, Segmentation-Enhanced CycleGAN (SECGAN), enables near perfect reconstruction accuracy on a benchmark connectomics segmentation dataset despite operating in a “zero-shot” setting in which the segmentation model was trained using only volumetric labels from a different dataset and imaging method. By reducing or eliminating the need for novel ground truth annotations, SECGANs alleviate one of the main practical burdens involved in pursuing automated reconstruction of volume electron microscopy data.
Block-Sparse Signal Recovery Based on Adaptive Matching Pursuit via Spike and Slab Prior

Spike and Slab prior is a well-suited sparsity promoting prior, which is widely used to recover sampled signal in Bayesian inference. However, some sparse signal further involve more prior information-block sparsity structure which the standard Spike and Slab prior cannot cover. Alternatively, the original optimization problem is a hard non-convex problem, which is usually solved through simplifying the assumptions, relaxations or even relying on strong data computing capability. Therefore, a novel block adaptive matching pursuit (BAMP) method based on a hierarchical Bayesian model is proposed, which both use block spike and slab prior to recover sampled signal with exploiting underlying block sparsity structure and settle the non-convex problem more efficiently. In addition, the intermediate steps of the method are calculated by alternating direction method of multipliers (ADMM) algorithm which makes the method much faster. Experimental results on both synthetic data and real dataset demonstrate the proposed BAMP algorithm perform better superior compared with other novel algorithms released in recent years.
Plastochron and yield of Physalis peruviana L. grown in different environments and transplanting dates

This study aimed to estimate plastochron, leaf area, and yield of Physalis peruviana seedlings grown in different environments and transplanted on different dates. The experiment was carried out in a completely randomized design, arranged in a 2 x 3 factorial scheme, namely: two cultivation environments (protected and field) and three transplanting dates (10/27/2013, 12/15/2013, and 02/11/2014). Four replicates of eight plants were used per plot, and the four central plants composed the useful area. Based on mathematical models and temperature data, plastochron was estimated for the entire crop cycle and vegetative and reproductive phases separately. Leaf area and node number were measured, and their relationship established at the end of the study. Other variables assessed were fruit number, mass, and yield per plant. Our results showed that the higher temperatures in the protected environment anticipated phenological timings. Plastochron values of 60.0 and 16.5 °C day-1 can be used during vegetative and reproductive stages, respectively. The protected environment increased vegetative growth and development, as well as yield of P. peruviana seedlings. In the Guarapuava-PR region, P. peruviana seedlings should be transplanted during the spring so that higher fruit yield and quality could be achieved.
Interactions among morphotype, nutrition, and temperature impact fitness of an invasive fly

Abstract Invasive animals depend on finding a balanced nutritional intake to colonize, survive, and reproduce in new environments. This can be especially challenging during situations of fluctuating cold temperatures and food scarcity, but phenotypic plasticity may offer an adaptive advantage during these periods. We examined how lifespan, fecundity, pre‐oviposition periods, and body nutrient contents were affected by dietary protein and carbohydrate (P:C) ratios at variable low temperatures in two morphs (winter morphs WM and summer morphs SM) of an invasive fly, Drosophila suzukii. The experimental conditions simulated early spring after overwintering and autumn, crucial periods for survival. At lower temperatures, post‐overwintering WM lived longer on carbohydrate‐only diets and had higher fecundity on low‐protein diets, but there was no difference in lifespan or fecundity among diets for SM. As temperatures increased, low‐protein diets resulted in higher fecundity without compromising lifespan, while high‐protein diets reduced lifespan and fecundity for both WM and SM. Both SM and WM receiving high‐protein diets had lower sugar, lipid, and glycogen (but similar protein) body contents compared to flies receiving low‐protein and carbohydrate‐only diets. This suggests that flies spend energy excreting excess dietary protein, thereby affecting lifespan and fecundity. Despite having to recover from nutrient depletion after an overwintering period, WM exhibited longer lifespan and higher fecundity than SM in favorable diets and temperatures. WM exposed to favorable low‐protein diet had higher body sugar, lipid, and protein body contents than SM, which is possibly linked to better performance. Although protein is essential for oogenesis, WM and SM flies receiving low‐protein diets did not have shorter pre‐oviposition periods compared to flies on carbohydrate‐only diets. Finding adequate carbohydrate sources to compensate protein intake is essential for the successful persistence of D. suzukii WM and SM populations during suboptimal temperatures.
Performance Evaluation of Two Machine Learning Techniques in Heating and Cooling Loads Forecasting of Residential Buildings

Nowadays, since energy management of buildings contributes to the operation cost, many efforts are made to optimize the energy consumption of buildings. In addition, the most consumed energy in the buildings is assigned to the indoor heating and cooling comforts. In this regard, this paper proposes a heating and cooling load forecasting methodology, which by taking this methodology into the account energy consumption of the buildings can be optimized. Multilayer perceptron (MLP) and support vector regression (SVR) for the heating and cooling load forecasting of residential buildings are employed. MLP and SVR are the applications of artificial neural networks and machine learning, respectively. These methods commonly are used for modeling and regression and produce a linear mapping between input and output variables. Proposed methods are taught using training data pertaining to the characteristics of each sample in the dataset. To apply the proposed methods, a simulated dataset will be used, in which the technical parameters of the building are used as input variables and heating and cooling loads are selected as output variables for each network. Finally, the simulation and numerical results illustrates the effectiveness of the proposed methodologies.
Influence of triclosan and triclocarban antimicrobial agents on the microbial activity in three physiochemically differing soils of South Australia.

Antimicrobial agents are being used in numerous consumer and health care products on account of which their annual global consumption has reached in millions of kilograms. They are flushed down the drain and become the part of wastewater and sewage sludge and end up in the ultimate sink of agricultural soils. Once they are in the soil, they may disturb the soil’s ecology as a result of which microbial activity useful for soil fertility and biodegradation of xenobiotics may severely be impacted. The present study was designed to assess the influence of two antimicrobial agents triclosan (TCS) and triclocarban (TCC), commonly used in consumer and health care products, on the microbial activity in the three agricultural soils from South Australia having different characteristics. The study was laid out following the two factors factorial design by applying 14 C-glucose at 5 µg g -1 with either TCS at 0, 30, 90 and 270 µg g -1 or TCC at 0, 50, 150 and 450 µg g -1 in three agricultural soils, Freeling (Typic Rhodoxeralf–sodic), Booleroo (Typic Rhodoxeralf) and Avon (Calcixerralic Xerochrepts). The 14 CO 2 , which was released as a result of microbial respiration, was trapped in 3 mL 1M NaOH and was quantified on Wallac WinSpectral α/β 1414 Liquid Scintillation Counter. The results revealed a significant difference in amounts of 14 C-glucose mineralized in the three soils. A significant concentration dependant suppressive effect of TCS on the biomineralization of 14 C-glucose appeared in all the tested soils as opposed to TCC where no such concentration dependent effect could be recorded. The reduction in 14 C-glucose biomineralization in the Freeling, Booleroo and Avon soils was recorded up to 53.6, 38.5 and 37.4 % by TCS at 270 µg g -1 and 13.0, 5.8 and 1.6 % by TCC at 450 µg g -1 respectively. However, a significant negative correlation of CEC and pH was recorded with TCS and TCC effects. These results may imply that presence of such antimicrobial agents in the soil environment may also be considered while designing the bioremediation strategy for any xenobiotic pollutants.
Response of Transplanted Paddy to Foliar Spray of Silicon in South Gujarat

Rice (Oriza sativa L.) is the most important food crop of India. In last few years rice yield has been found diminishing and nutritional imbalance has been reported as one of major concerned. In a more specific study of nutrients; the micronutrients now have been found equally important as macronutrients although they are required in a minute quantity. Balancing the micronutrients for rice cultivation enhanced the quality and yield Ma et al., (2007).
Wavelet Transform and Deep Learning approach to predict physico chemical parameters of water

Alton water reservoir located within the stunning countryside of Suffolk in UK has a history of cyanobacterial bloom, that are single-celled organisms that live in fresh, brackish, and marine water. The traditional approaches to monitoring water reservoirs are often limited by the need for data collection which often is time-consuming and expensive. In addition, Chlorophyll-a, algae and turbidity are important variable for the analysis of water quality, that are significant not only for human populations but also essential for plant and animal diversity. The main objective of this study is to predict these chemico physical parameters from 2014 to 2019 using time series analysis, satellite imagery, wavelet transform and deep learning. The satellites images were used to predict these parameters in Alton reservoir, manually selected samples were employed to validate estimated parameters using Wavelet Neural Networks. The results predicted by the neural network show good results, and good approximation to laboratory results, suggesting that the proposed model is suitable for environmental monitoring, contributing to monitor water quality parameters.
Is Vitamin C or HAT Therapy Effective in Treating Sepsis? A Mini Review

Background: One of the most common causes of mortality in critical patients admitted to the intensive care unit (ICU) is sepsis. In recent years, the administration of high doses of vitamin C and HAT (hydrocortisone, ascorbic acid and thiamine) therapy has attracted much attention in patients with sepsis. Objectives: The current article reviews the beneficial effects of HAT therapy in light of research conducted in this area. Methods: A general search for electronic databases was developed. The human studies of the influence of HAT therapy in critically ill patients were evaluated. Results: The results indicated that HAT therapy may improve clinical outcome in septic patients; however, widespread use of these therapeutic approaches in sepsis requires large clinical trials in order to more confidently recommend this therapeutic approach in septic patients admitted to intensive care units. Conclusions: HAT therapy may improve clinical outcome in septic critically ill patients.
Effects of the Twelve-Step Facilitation Treatment on Alcohol Consumption among Third Year Students at the University of Cape Coast, Ghana

Although alcohol consumption among students exists in the university and there are a number of studies to that effect, there is no intervention study that puts the Twelve-Step Treatment to test. The purpose of this study was to ascertain the effects of the Twelve-Step Facilitation Treatment on alcohol consumption among the participants who consume risky and abusive levels of alcohol. Out of 4,653 population, and using Krejcie and Morgan, 160 was selected using simple random technique and administered the questionnaire. Based on this, 51 met the inclusion criteria, however, 40 were selected at random for the intervention. Alcohol Use Disorder Identification Test developed by the WHO was used to collect quantitative data in this Quasi-experimental study. Data were analyzed using One-way ANCOVA where pretest scores were compared to post-test scores after eight weeks of the twelve-step facilitation treatment. The findings showed that the Twelve-Step Facilitation Treatment was effective in reducing alcohol consumption among the participants significantly. It is recommended that University Counsellors should make use of the Twelve-Step Facilitation Treatment in counselling undergraduate students with risky and abusive alcohol consumption behaviour.