Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Diversity in Local and Exotic Avena sativa L. (Oat) Germplasm Using Multivariate Analysis

Avena sativa L. , also known as Oat belongs to the Poaceae family, is one of the most significant crops that is grown for its seeds, fodder as well as for human consumption as oatmeal. In the current study, 236 genotypes of A. sativa were analysed for genetic diversity through agro-morphological and SDS-PAGE analysis. Cluster analysis based on agro-morphological characteristics grouped all the genotypes into nine clusters, whereas genotype numbers 537 and 728 were highly different from others. The seed yield production of cluster 9 genotypes was the highest per plant (38.2 ± 0.20 g), while cluster 2 genotypes produced maximum biomass per plant (122.5 ± 9.55 g) as compared to other clusters. In a principal component analysis where four variables were studied, and the observed total variations were 57.60%. Among the genotypes, a maximum grain yield of 38.2 g (each) was recorded for genotypes 22,350 and 728, followed by genotypes 737 and 22,390 (with 36.4 g and 35.6 g of seed productions, respectively). The SDS-PAGE analysis resulted in 13 bands and all the genotypes were grouped into seventeen clusters. At the extreme periphery of the dendrogram, genotype 537 and 22,332 were considered to be the most diverse genotypes. Our findings have implications for both understanding the diversity and relationships among these diverse genotypes of A. sativa and will provide a basis for obtaining the elite germplasm optimally adapted to local conditions. The selected genotypes based on agronomic performance may be potential breeding material to raise successful future cultivars.
The USDA‐Agricultural Research Service's long term agro‐ecosystems Walnut Gulch Experimental Watershed, Arizona, USA

The Walnut Gulch Experimental Watershed (WGEW) is one of the premier semiarid research watersheds in the world. This data note provides background and an overview of the watershed, data collected on the watershed, and citations and links to detailed descriptions of the instruments methods to make the observations. The long title of the dataset is: USDA‐ARS WGEW Database curated by the USDA‐Agricultural Research Service's (ARS) Southwest Watershed Research Center.
Understanding Emotions and their Role in the Design of Products: An Integrative Review

Background Today consumers expect more from a product than mere fulfillment of the intended function for which the product is designed. Modern-day consumers demand products that match and satisfy their preferences. Contemporary trends in design show consumer inclination towards objects which motivate them, improve their quality of life and spark emotions. Consequently, along with the functionality requirements, a product needs to serve consumers' emotional needs, and for that, the product must relate with them at their emotional level. The product's visual appearance is responsible for engendering first impressions and initiating a connection at the emotional level before product purchase. Previous research suggests that the emotional element of design could be more crucial in deciding the success of the product than the functional aspect as it affects consumer's decision-making in choosing a product. Therefore, design directed by emotional content is gaining more and more importance in current design practices, research, and education. Thus, designers must possess the necessary knowledge and skills to deal with this design paradigm of product emotions, analyzing the relationship between emotion, consumer behavior, and product design. This paper investigates associations between fundamental product design elements, product judgment attributes, consumer emotional response, and consumer behavior in the context of before product purchase scenario through an integrative review of literature in the domain of product design and emotions.
Lesson study as a way of improving school-day navigation for pupils with severe intellectual disability and autism

PurposeThis research explores lesson study as a way to enhance the quality of teaching for pupils with learning disabilities and autism spectrum disorder by observing changes to one pupil's (Wilma) active educational participation. The study also investigates if and in what ways the professional development impacted teaching practices.Design/methodology/approachFive teachers met with the author on four occasions. Between these meetings, the teachers delivered the lessons they had planned together. The author video recorded the meetings to discern how the teachers' expressions developed. The author shared their thoughts with another researcher to enable an interrater validity examination.FindingsThe implementation of the lesson study vehicle enabled the teachers to transform their thinking from mainly focusing on pupils' deficiencies to instead focusing on their strengths. A relationship was found between teachers' understanding of central coherence, their skills in adapting received instructions and pupils' abilities to process and contextualize information or discern the whole picture.Research limitations/implicationsResearch that involves teachers in the learning process emphasizes the relation between teachers’ thinking and their potential to enable the contextualized inclusion of pupils with learning disabilities.Originality/valueThis research offers important insights into how school-day navigation for pupils with severe intellectual disability and autism can be understood through the lens of variation theory; the teachers' repeated and adjusted use of the frame on the schedule strip enabled Wilma to discern what would happen next during the school day.
Hybrid Taguchi-PCA-utility approach for simultaneous optimisation of multiple responses in turning alloy steel

ABSTRACT This study focussed on the multi-response optimisation of turning process using an easier and accurate hybrid approach namely Taguchi-PCA-Utility approach. Turning of alloy steel under dry and LN2-assisted cryogenic cooling with two different geometry-shaped uncoated carbide inserts was carried out based on suitable design of experiments (Taguchi L16 orthogonal array). Five vital responses in turning such as temperature, roughness, feed force, cutting force and MRR were measured by varying the input factors (speed, feed, cutting condition and cutting inserts type). Principal component analysis (PCA) for relative weight calculation of responses and utility concept for deriving out the unified process index were followed. The optimum parameter settings for maximum utility value were found at 134 m/min speed with 0.12 mm/rev feed rate under cryogenic cooling using SNMG 120408-type cutting insert. Finally, in order to verifying the significance of proposed approach validation tests were conducted.
Attitudes, emotions, and acceptance of wolf management in Illinois

ABSTRACT To help the Illinois Department of Natural Resources develop a comprehensive wolf management strategy, a mail survey was conducted of non-hunters (n = 1,145) and hunters (n = 1,489). Results supported three bivariate hypotheses. Compared to urbanites, respondents who grew up in rural areas were more emotional toward wolves, held more negative attitudes toward wolves, and were less likely to accept wolf management. Hunters had stronger emotions and more negative attitudes toward wolves and were less accepting of wolf management than were non-hunters. People who lived in an area where a wolf had not been found were more emotional toward wolves, held more negative attitudes toward this species, and were less accepting of wolf management compared to those who lived in an area where a wolf had been seen. Results also supported the predicted three-way interaction effects for each of the three dependent variables, highlighting the complexities of managing wolves.
Intelligent control of a single-link flexible manipulator using sliding modes and artificial neural networks

This letter presents a new intelligent control scheme for the accurate trajectory tracking of flexible link manipulators. The proposed approach is mainly based on a sliding mode controller for underactuated systems with an embedded artificial neural network to deal with modeling inaccuracies. The adopted neural network only needs a single input and one hidden layer, which drastically reduces the computational complexity of the control law and allows its implementation in low-power microcontrollers. Online learning, rather than supervised offline training, is chosen to allow the weights of the neural network to be adjusted in real time during the tracking. Therefore, the resulting controller is able to cope with the underactuating issues and to adapt itself by learning from experience, which grants the capacity to deal with plant dynamics properly. The boundedness and convergence properties of the tracking error are proved by evoking Barbalat's lemma in a Lyapunov-like stability analysis. Experimental results obtained with a small single-link flexible manipulator show the efficacy of the proposed control scheme, even in the presence of a high level of uncertainty and noisy signals.
State of the Art in Comorbidities and Complications Associated with Sleep-Related Breathing Disorders

The term “sleep-related breathing disorders” (SRDB) comprehends a spectrum of pathologic conditions characterized by abnormal respiration during sleep, that can affect both adults and growing subjects. The expanding knowledge on this topic has revealed that impaired sleeping and breathing have profound effects on many systemic functions, therefore a modern approach requires the collaboration of different professionals like the otorhinolaryngologist, pneumologist, neurologist, cardiologist, psychologist, dentist, and many others. The real prevalence of such conditions is unknown, especially in children, even though a growing awareness can be found among Governments, researchers, and public opinion, especially for the social implications that SRDB can have. Moreover, recent studies have raised attention on comorbidities that can be associated with SRDB, influencing each other. Regarding the current international situation, it would be interesting to evaluate the progress of COVID-19 disease in SRDB patients. Defining the state-of-the-art knowledge on all the conditions orbiting around SRDB, from all points of view—aetiology, diagnosis, clinical management, interdisciplinarity, public health management—would be of great interest and impact to improve future research and the quality of life of SRDB patients.
Burden of central-line-associated bloodstream infections in 106 Ministry of Health hospitals of Saudi Arabia: a 2-year surveillance study

Background : Although the Saudi Ministry of Health (MOH) is managing the majority of inpatient bed capacity in Saudi Arabia, surveillance data for central-line-associated bloodstream infections (CLABSI) have never been reported at a national level. Objectives : To estimate unit-specific CLABSI rates along with central line utilization ratios in MOH hospitals. Additionally, to benchmark such rates and ratios with recognized regional and international benchmarks. Methods : A prospective surveillance study was conducted in 106 MOH hospitals between January 2018 and December 2019. The data from 14 different types of intensive care units (ICUs) were entered into the Health Electronic Surveillance Network (HESN) program. The surveillance methodology was similar to the methods of the US National Healthcare Safety Network (NHSN) and the Gulf Cooperation Council (GCC) Center for Infection Control. Results : During the 2 years of surveillance in ICU setting covering 1,475,177 patient-days and 475,913 central line-days, a total of 1,542 CLABSI events were identified. The overall CLABSI rate was 3.24 (95% confidence interval [CI], 3.08–3.40) per 1,000 central line-days, and the overall central line utilization ratio was 0.32 (95% CI, 0.322–0.323). CLABSI-standardized infection ratios in HESN hospitals were very similar (1.01) to GCC hospitals, but 3.2 times higher than NHSN hospitals and 36% lower than International Nosocomial Infection Control Consortium (INICC) hospitals. Central-line-standardized utilization ratio in MOH hospitals was 15–30% lower than the three benchmarks. Conclusions : The overall CLABSI rate was 3.24 per 1,000 central line-days, and the overall central line utilization ratio was 0.32. MOH CLABSI rates were very similar to GCC hospitals, but higher than NHSN hospitals and lower than INICC hospitals. MOH central line utilization is slightly lower than the three benchmarks.
AN APPRAISAL OF TWO TRACER METHODS FOR ESTIMATING TILLAGE EROSION RATES UNDER HOEING TILLAGE

An increasing recognition of tillage erosion processes has shown that soil redistribution by tillage directly contributes to soil loss in mechanically and nonmechanically agricultural areas worldwide. Soil translocation by tillage is normally measured by means of tracers, with which a volume of soil is labelled, and therefore yielding tillage erosion rates in a field. Two tracer methods for estimating tillage erosion rates were appraised to examine the application adaption to local conditions in the hilly areas, southwestern China, in terms of the accuracy, measurement sensitivity, manipulation facility, and time cost. The two tracer methods had a similar measurement accuracy of soil translocation. However, for the magnetic tracer method the result of tracer distribution after tillage was immediately obtained in the field, while there was a need to do a follow-up indoor determination for the stone chip method. The magnetic tracer method only required collecting a small volume of soil samples, while a large quantity of soil (i.e. all the soils into which tracers possibly redistributed) was collected to recover all the stone chips from tilled soils. As a result, the magnetic tracer method would be much time saving compared to the stone chip method. It is suggested that the magnetic tracer method would rather be used when there are large quantities of sampling plots to be measured on steep hillslopes of the hilly areas where hoeing tillage is practiced.
Comparison of Landsat 8, Sentinel-2 and spectral indices combinations for Google Earth Engine-based land use mapping in the Johor River Basin, Malaysia

Accurate land use information is the basis for scientific research related to carbon cycle analysis, hydro-climatic modelling, soil degradation assessment, etc. It is also an indispensable basic information for local land management departments in land use planning and management. With development in big data and internet network, Google Earth Engine (GEE), a cloud-based computing platform allows users to perform satellite images processing more efficiently. This study aims to improve the land use mapping in a tropical region based on the GEE platform. Seven satellite images and indices combinations include Landsat 8 (C1), Sentinel-2 (C2), Landsat 8+Sentinel-2 (C3), Landsat 8+Indices (C4), Sentinel-2+Indices (C5), Landsat 8+Sentinel-2+Indices (C6), Normalized Difference Vegetation Index (NDVI)+Normalized Difference Water Index (NDWI)+Enhanced Vegetation Index (EVI)+Elevation (C7) were developed to evaluate the best combination for land use mapping in the Johor River Basin (JRB), Malaysia. The Random Forest (RF) algorithm was used to classify the land use land cover (LULC) with 222 training samples and 78 verification samples obtained through the Google Earth Pro higher resolution satellite images and field samplings. The results show that the overall accuracies of all the seven combinations are mostly more than 75%, ranging from 72% (C1) to 86% (C6). The findings show that adding of additional indices information before the land use classification helps to increase the overall accuracy significantly. For instance, the overall accuracy of the C6 combination is 14% higher than that of the Landsat 8 image solely. This study can act as a reference to effectively improve the land use mapping in cloud-prone tropical regions. Keywords: Google Earth Engine, Image combination, Johor River Basin, Land Use, Malaysia, Random Forest
Millimeter-Wave Multi-Band Reconfigurable Differential Power Divider for 5G Communication

A differential four-way power divider for 24 to 30 GHz and a frequency reconfigurable differential four-way power divider for 24 to 30 GHz and 37 to 43.5 GHz are presented. The differential structure provides sound virtual grounds in a multiple-channel chip. Both circuits have a four-way Wilkinson power divider (WPD) configuration based on lumped elements that provide small chip sizes. The first one has a small core chip area of 0.09 mm2, a small insertion loss of 0.93 to 1.94 dB, and the port-to-port isolation of 19.1 to 25.6 dB from 24 to 30 GHz. It has a small amplitude and phase differences at four outputs. The second one allows frequency-reconfigurable operation by switching inductances and capacitances to cover widely separated frequency bands (5G NR n257-n261 bands). In addition, switched capacitors (SCs) are inserted to resonate out the parasitic series inductances in isolation resistors at both bands of 24–30 GHz and 37–43.5 GHz. It has a core chip area of 0.168 mm2, insertion losses of 1.65–1.89 dB at 24 to 30 GHz and 2.04–2.70 dB at 37 to 43.5 GHz, respectively. The port-to-port isolations are 23.4–37.6 dB at 24 to 30 GHz and 22.6–28.4 dB at 37 to 43.5 GHz.
NCScale: Toward Optimal Storage Scaling via Network Coding

To adapt to the increasing storage demands and varying storage redundancy requirements, practical distributed storage systems need to support storage scaling by relocating currently stored data to different storage nodes. However, the scaling process inevitably transfers substantial data traffic over the network. Thus, minimizing the bandwidth cost of the scaling process is critical in distributed settings. In this paper, we show that optimal storage scaling is achievable in erasure-coded distributed storage based on network coding, by allowing storage nodes to send encoded data during scaling. We formally prove the information-theoretically minimum scaling bandwidth for both scale-out and scale-in cases. Based on our theoretical findings, we also build a distributed storage system prototype NCScale based on Hadoop Distributed File System, so as to realize network-coding-based scaling while preserving the necessary properties for practical deployment. Experiments on Amazon EC2 show that the scaling time can be reduced by up to 50% over the state-of-the-art.
Speech Emotion Recognition

In human machine interface application, emotion recognition from the speech signal has been research topic since many years. To identify the emotions from the speech signal, many systems have been developed. In this paper speech emotion recognition based on the previous technologies which uses different classifiers for the emotion recognition is reviewed. The classifiers are used to differentiate emotions such as anger, happiness, sadness, surprise, neutral state, etc. The database for the speech emotion recognition system is the emotional speech samples and the features extracted from these speech samples are the pitch, energy, linear prediction cepstrum coefficient (LPCC), Mel frequency cepstrum coefficient (MFCC). The classification performance is based on extracted features. Inference about the performance and limitation of speech emotion recognition system based on the different classifiers are also discussed. Keywords—Feature Selection, Emotion recognition, Classifier,Feature extraction.
Natural convection of nanofluids in a wavy porous cavity

In this piece of work, a numerical investigation of natural convection is carried out on the buoyancy-driven flow of nanofluids and heat transfer through porous media packed inside a wavy cavity. The cavity is placed horizontal, and its right vertical wall is of wavy nature, the bottom and top walls of the cavity are adiabatic, and there is a temperature difference between the left and right vertical wall. The dimensionless governing equations for the flow of nanofluids through the Darcian porous media are solved iteratively by using finite difference method. The study is conducted for wide range of governing parameters, such as Rayleigh-Darcy number ( R a = 10 , 10 2 , 10 3 ) , nanoparticle volume fraction ( ϕ = 0 % , 5 % , 10 % , 15 % , 20 % ) for three types of nanofluids ( A l 2 O 3 - H 2 O , Cu- H 2 O , TiO2- H 2 O ) , the waviness of the vertical wall controlled by dimensionless length of amplitude of the wave ( a = 0.05 , 0.15 , 0.25 ) and number of undulations per unit length (N = 1, 3, 5). The simulated results reveals that the presence of nanoparticles enhances the convective heat transfer process at low Ra, and the wall affects the local convection rate and it also controls the overall heat transfer rate. For a cavity with N = 3, N u ¯ is increased by 33% at Ra = 10, and at R a = 10 3 , N u ¯ has a drop by 10% as the a is increased from 0.05 to 0.25 having 20% of nanoparticles.
Soils and Beyond: Optimizing Sustainability Opportunities for Biochar

Biochar is most commonly considered for its use as a soil amendment, where it has gained attention for its potential to improve agricultural production and soil health. Twenty years of near exponential growth in investigation has demonstrated that biochar does not consistently deliver these benefits, due to variables in biochar, soil, climate, and cropping systems. While biochar can provide agronomic improvements in marginal soils, it is less likely to do so in temperate climates and fertile soils. Here, biochar and its coproducts may be better utilized for contaminant remediation or the substitution of nonrenewable or mining-intensive materials. The carbon sequestration function of biochar, via conversion of biomass to stable forms of carbon, does not depend on its incorporation into soil. To aid in the sustainable production and use of biochar, we offer two conceptual decision trees, and ask: What do we currently know about biochar? What are the critical gaps in knowledge? How should the scientific community move forward? Thoughtful answers to these questions can push biochar research towards more critical, mechanistic investigations, and guide the public in the smart, efficient use of biochar which extracts maximized benefits for variable uses, and optimizes its potential to enhance agricultural and environmental sustainability.
Pharmaceutical Applications of Vitamin E TPGS

D-tocopheryl polyethylene glycol succinate (Vitamin E TPGS) has been approved as a safe pharmaceutical adjuvant by FDA, and several drug delivery systems (DDS) based on TPGS have been developed. TPGS properties as a P-gp inhibitor, solubilizer/absorption and permeation enhancer in drug delivery and TPGS-related formulations such as nanocrystals, nanosuspensions, tablets/solid dispersions, vaccine system adjuvant, nutritional supplement, film plasticizer, anticancer reagent, and so on, are discussed in this review. Consequenly, TPGS can inhibit ATP-dependent P-glycoprotein activity and act as a potent excipient that promotes the efficiency of delivery and the therapeutic effect of drugs. Inhibition of P-gp occurs through mitochondria-dependent inhibition of the P-gp pump. Many of the latest studies address the use of TPGS for many poorly water-soluble or permeable drugs in the manufacture of nanodrugs or other formulations. In addition, it has been reported that TPGS shows a robust improvement in chylomicron secretion at low concentrations and improves intestinal lymphatic transport, which would also boost the potential of drug absorption. It also indicates that there are still many problems facing clinical translation of TPGS-based nanomedicines, requiring a more deep evaluation of TPGS properties and a future-based delivery method.