Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Nitrogen Source and Rate on Soybean Yield and Quality

ABSTRACT The poultry industry in North Carolina (NC) has increased substantially over the past few decades, which has led to widespread availability of poultry litter. While many grain producers in NC utilize litter in their fertilization programs, it is typically applied to the corn or wheat crops that are in the rotation with soybean, instead of directly prior to soybeans. However, there is interest in application to soybean. Therefore, three field sites were established across NC in both 2019 and 2020, with four replicates of 11 treatments: four litter rates (22.4, 44.8, 89.7 and 134.5 Mg/hectare), six inorganic nitrogen (N) fertilizer rates (16.8, 33.6, 67.3, 134.5, 201.8, and 269.0 kg N/hectare), and a control. The impact of these treatments on biomass production, tissue N, plant population, yield, and grain quality were investigated. There was no significant effect on yield in 2019; however, there was a significant effect on yield in 2020, showing a negative correlation with inorganic N fertilizer in Plymouth and a 22% reduction in yield over the range of inorganic N treatments. It is possible there was an increased salt effect in these plots, as there was a negative response in plant population at five of six site years. While there was a positive correlation between grain protein and increasing inorganic N rate, growers are not paid based on grain quality. The results of this study suggest N application at planting is not beneficial for growers, but litter could be applied to meet soybean phosphorus or potassium demands.
Antecedents of Fan Purchase Intention for Team Color Products

Purpose: This study sought to identify the influence of satisfaction, loyalty, subjective norms, and team image on fans’ purchase intention for products in the team colors.Methods: A survey was conducted with 301 soccer fans, and the results were analyzed with PLS.Findings: The results suggest that the more satisfied a fan is with the team, the greater the influence of the opinion of third parties on them and the greater their loyalty to the team, and hence a greater intention to purchase products in the team’s colors. Regarding the relationship between team image and purchase intention, although the relationship was significant, the sign was negative, indicating an opposite trend in the relationship. In addition, the team's image did not influence the fan's loyalty.Managerial Contributions: Colored product companies do not necessarily need to license team products, but instead focus their sales efforts on products with the team's colors when they recognize the preferences of soccer fans.Originality: The novelty of this study is linked to its consideration of fan purchase intention for the team colors. Another justification is the possibility of clarifying the antecedents of fan purchase intention for products in the team’s colors from the constructs of team image, satisfaction, and behavioral loyalty.
The Formation of Galactic Bulges: Origin of Bulges

Insight into the origin of bulges is saught in this review only from the properties of their stellar populations. Evidence concerning the age of the Galactic bulge stellar population is reviewed first, then the case of the bulge of M31 is discussed. The similarity of bulges and ellipticals is then illustrated, inferring that the problems of the origin of bulges and of the origin of ellipticals may well be one and the same: i.e. the origin of galactic spheroids. In this mood, the current evidence concerning the age of the bulk stellar populations of early-type galaxies is then reviewed, both for low- as well as high-redshift galaxies, and both for cluster as well as field ellipticals. All reported evidence argues for the bulk of stars in galactic spheroids having formed at high redshift, with only minor late additions and small dependence on environment. In the final, more speculative Section an attempt is made to evaluate how current formation scenarios can account for this observational evidence. The role of spheroids in the cosmic star formation and metal enrichment history is also briefly discussed. Finally, some critical questions are asked, which answers may help our further understanding of the formation and evolution of galactic spheroids.
A critical assessment on the effect of nano-titanium dioxide on the properties of concrete

Recent advances in nanotechnology in various fields demonstrate tremendous promise for resolving a wide variety of problems. Nanotechnology has been shown to improve the efficiency of conventional building materials such as concrete. Numerous types of nanoparticles, such as nano-titanium dioxide, are being used to significantly improve the efficiency, longevity, and sustainability of concrete. This paper summarises prior research on the effect of nano-titanium dioxide on a variety of properties, including heat of hydration, workability, setting time, chemical shrinkage, mechanical strength, abrasion resistance, fire resistance, and freeze/thaw resistance. Water absorption, chloride penetration, and permeability are all low in conventional plain or blended cement systems. Additionally, the matrix containing nano-titanium dioxide is compared in this study to a matrix containing other nanoparticles. Civil engineers can use this paper as a quick reference.
Evaluation of Parameter Fine-Tuning with Transfer Learning for Osteoporosis Classification in Knee Radiograph

—Osteoporosis is a bone disease that raises the risk of fracture due to the density of the bone mineral being low and the decline of the structure of bone tissue. Among other techniques, such as Dual-Energy X-ray Absorptiometry (DXA), 2D x-ray pictures of the bone can be used to detect osteoporosis. This study aims to evaluate deep convolutional neural networks (CNNs), applied with transfer learning techniques, to categorize specific osteoporosis features in knee radiographs. For objective labeling, we obtained a selection of patient knee x-ray images. The study makes use of the Visual Geometry Group Deep (VGG-16), and VGG-16 with fine-tuning. In this work, the deployed CNNs were assessed using state-of-the-art metrics such as accuracy, sensitivity, and specificity. The evaluation shows that fine-tuning enhanced the VGG-16 CNN's effectiveness for detecting osteoporosis in radiographs of the knee. The accuracy of the VGG-16 with parameter fine-tuning was 88% overall, while the accuracy of the VGG-16 without parameter fine-tuning was 80%.
Correlates of programmer efficacy and their link to experience: a combined EEG and eye-tracking study

Background: Despite similar education and background, programmers can exhibit vast differences in efficacy. While research has identified some potential factors, such as programming experience and domain knowledge, the effect of these factors on programmers' efficacy is not well understood. Aims: We aim at unraveling the relationship between efficacy (speed and correctness) and measures of programming experience. We further investigate the correlates of programmer efficacy in terms of reading behavior and cognitive load. Method: For this purpose, we conducted a controlled experiment with 37 participants using electroencephalography (EEG) and eye tracking. We asked participants to comprehend up to 32 Java source-code snippets and observed their eye gaze and neural correlates of cognitive load. We analyzed the correlation of participants' efficacy with popular programming experience measures. Results: We found that programmers with high efficacy read source code more targeted and with lower cognitive load. Commonly used experience levels do not predict programmer efficacy well, but self-estimation and indicators of learning eagerness are fairly accurate. Implications: The identified correlates of programmer efficacy can be used for future research and practice (e.g., hiring). Future research should also consider efficacy as a group sampling method, rather than using simple experience measures.
Numerical Simulations of Galaxy Interaction

Cosmological theories that include a non-baryonic dynamic lly cold dark matter (CDM) have been stunningly successful at explaining observ ations of the universe on large scales. On the scale of individual galaxies, however, observations have been made which call into question the CDM paradigm. In particular, simulations of structure formation show CDM haloes with a density “cusp”, such that in the centre of the halo d ln ρ/d ln r ∼ 1 − 1.5. In contrast, observational studies suggest that CDM haloes have constant densit y cores. In this thesis I use gravitational N-body simulations to investigate the claim that the dark matter halo cusp can be removed by angular momentum tran sport from a rotating bar in a disc galaxy. I find that the simulations which were use d to support this claim were seriously flawed, and similar simulations designed to m i igate these flaws suggest that this is unlikely to be a mechanism for turning a cusp into a core. In the interests of further work on dark matter haloes, and on other problems in astrophysics, I design and implement a new method for constr ucting model galaxies with halo, bulge, and disc components. This method avoids th e use of an approximation to a Maxwellian velocity distribution. I show that this crea t s stable galaxy models, well suited to many applications. As an example of these applications, I conduct a thorough inv estigation of the structural and kinematic properties of the haloes of the remnants of 1:1 mass ratio mergers. I determine that the merger has virtually no effect on the hal o cusp strength, but a substantial effect on the halo velocity distribution. The remn ant haloes are significantly less spherical that those described in studies of mergers which c onsider gas cooling. Other properties of the remnants are noted and discussed.
Zinc nutrition improves fruit yield, quality, and reduces bacterial blight disease severity in pomegranate (Punica granatum L.)

Abstract The study was designed to identify the most effective way of fertilizing Zn for improved productivity and quality of pomegranate cv. Bhagwa on calcareous soil. Fertilization methods included foliar sprays of ZnSO4, Zn-EDTA, and amino acid chelated Zn; irrigation applied ZnSO4 and Zn chelate (Zn-EDTA); soil application of ZnSO4 (@ 12.5 and 25.0 g tree−1) and were evaluated on full grown pomegranate orchard for 2 years. All the Zn treatments of foliar and irrigation-applied methods were effective in raising the leaf Zn concentration above the recommended adequate level (>15.98 mg kg−1). Higher number of hermaphrodite flowers was observed with foliar sprays of ZnSO4, amino acid chelated Zn, irrigation applied Zn-chelate, and soil application of ZnSO4 @ 25 g Zn tree−1. Various Zn application methods except irrigation-applied ZnSO4 increased fruit yield by 4.33–23.63%. Some of the Zn treatments viz. foliar sprays of ZnSO4, amino acid chelated Zn and irrigation-applied Zn-chelate caused substantial improvement in fruit quality attributes such as fruit size, aril and juice percent, biochemical attributes like juice acidity (by 8.33–13.89%), anthocyanin, ascorbic acid concentration, and enrichment of Zn in the edible part of the fruit. Interestingly, sprays of ZnSO4 also enriched Fe, Mn, and Cu in the arils. While some of the Zn treatments viz. foliar spray of ZnSO4, irrigation-applied Zn-chelate and soil application of ZnSO4 could reduce bacterial blight disease incidence by 19.29–25.97% and severity by 22.18–47.36%. Hence, foliar sprays of ZnSO4 are recommended for enhancement of fruit yield as well as quality in pomegranate.
Towards real-time diffusion imaging : noise correction and inference of the human brain connectivity

Most magnetic resonance imaging (MRI) system manufacturers propose a huge set of software applications to post-process the reconstructed MRI data a posteriori, but few of them can run in real-time during the ongoing scan. To our knowledge, apart from solutions dedicated to functional MRI allowing relatively simple experiments or for interventional MRI to perform anatomical scans during surgery, no tool has been developed in the field of diffusion-weighted MRI (dMRI). However, because dMRI scans are extremely sensitive to lots of hardware or subject-based perturbations inducing corrupted data, it can be interesting to investigate the possibility of processing dMRI data directly during the ongoing scan and this thesis is dedicated to this challenging topic. The major contribution of this thesis aimed at providing solutions to denoise dMRI data in real-time. Indeed, the diffusion-weighted signal may be corrupted by a significant level of noise which is not Gaussian anymore, but Rician or noncentral chi. After making a detailed review of the literature, we extended the linear minimum mean square error (LMMSE) estimator and adapted it to our real-time framework with a Kalman filter. We compared its efficiency to the standard Gaussian filtering, difficult to implement, as it requires a modification of the reconstruction pipeline to insert the filter immediately after the demodulation of the acquired signal in the Fourier space. We also developed a parallel Kalman filter to deal with any noise distribution and we showed that its efficiency was quite comparable to the non parallel Kalman filter approach. Last, we addressed the feasibility of performing tractography in real-time in order to infer the structural connectivity online. We hope that this set of methodological developments will help improving and accelerating a diagnosis in case of emergency to check the integrity of white matter fiber bundles.
Development of a new method for manufacturing hollow fibre-reinforced plastic structures for aeronautical applications using structural CFRP cores

Currently applied manufacturing technologies for hollow composite structures impose design restrictions, such as limited integration potential, whereas differential designs are limited regarding lightweight design and load transfer due to the need of joints. This paper introduces the patented concept of structural carbon fibre-reinforced polymer (CFRP) cores, intending to overcome limitations allowing for integral, yet complex designs. The hollow cores are initially manufactured and partially cured via resin transfer moulding (RTM) with inflatable rubber core. These cores are then integrated in a dry textile-based preform which is impregnated in another RTM process. Here, the cores stabilize the preform during injection and afterwards remain in the component as load-carrying elements. Thereby the partial degree of cure of the cores before the second RTM process is optmised to balance dimensional stability and bonding strength. The process route using structural CFRP cores was successfully applied to a generic structure and proven by structural testing.
Wafer-Level Patterning of SnO Nanosheets for MEMS Gas Sensors

In the past few decades, gas sensitive nanomaterials are usually deposited on specific area of the wafer by drop-casting or inkjet printing for application in gas sensor fabrication. However, wafer-level patterning of sensing materials with satisfactory reproducibility still encounters challenge. In this letter, we propose a facile ‘top-down’ strategy to manufacture wafer-scale gas sensing chips with high-throughput by photolithography using a well-mixed photoresist-nanomaterial suspension, followed by calcination. The fabricated gas sensors based on the proposed approach yield excellent reproducibility and uniformity of sensing response to ethanol detection with a relative standard deviation (RSD) <4.5 %, suggesting promising application for high-volume production of MEMS compatible gas sensors.
TEACHERS’ PERCEPTIONS ON THE USE OF GOOGLE CLASSROOM IN ENGLISH LEARNING AMID THE COVID-19 PANDEMIC IN MANDAU SUB-DISTRICT

This research aimed to explore the teachers’ perceptions on the use of Google Classroom in English learning amid the COVID-19 pandemic in Mandau sub-district. There were 41 English 41 English teachers who have used Google Classroom from 8 public senior high schools chosen as samples. This study used a quantitative method that employed questionnaire to collect the data consisting of 20 statements. Using SPSS 25, the quantitative data were analyzed descriptively and inferentially. The results show that the use of Google Classroom is considered very helpful during the pandemic with mean value 4.28 (very high). In the learning process, the use of Google Classroom is considered very practical, showing the mean value 4.02 (high). In the teams of ease of learning, Google Classroom is considered easy to learn the features and uses with a mean value of 4.27 (very high). The teachers are satisfied with Google Classroom as indicated by the mean value of 4.29 (very high). Therefore, the teachers felt that using Google Classroom in online learning during the COVID-19 pandemic was effective because the application was a good way or alternative way to do the learning activity and made it easier to teach English during the COVID-19 pandemic.
Family Care-Work Interference and Mid/Late-Career Motivation and Intentions: Mediating Role of Occupational Future Time Perspective

The combination of work and family obligations can lead to two-way interference, resulting in Family Care Interference with Work (FCIW) and Work Interference with Family Care (WIFC). Both can impact late career motivation and intentions to continue working or retire and reduce their occupational time perspective (OFTP). Through two studies, this paper shows how OFTP mediates the relationship between FCIW/WIFC and mid and late career indicators such as early retirement intentions and motivation to continue working beyond the retirement age. Our findings contribute to increasing knowledge of how increasing family caregiving obligations may impact the career intentions of working carers in their mid and late career stages.
Early childhood stress responses to psychosocial stressors: The state of the science

Abstract The aim of this systematic review was to better understand whether and to what extent psychosocial stressors are associated with hypothalamic–pituitary–adrenal axis or autonomic nervous system stress responses in young children (1–6 years of age). Studies were classified by psychosocial stressors from the ecobiodevelopmental model: social and economic resources, maternal mental health, parent–child relationships, and the physical environment. Of the 2388 identified studies, 32 met full inclusion criteria, including over 9107 children. Child physiologic stress responses were measured as hair and urinary cortisol and cortisone, salivary diurnal and reactive cortisol, salivary reactive alpha‐amylase, and respiratory sinus arrhythmia. There were 107 identified relations between psychosocial stressors and physiologic stress responses. Nearly two thirds of these relations suggested that children have dysregulated stress responses as either significantly blunted (n = 27) or increased (n = 37); 43 relations were not significant. Children most consistently had significantly dysregulated stress responses if they experienced postnatal maternal depression or anxiety. Some reasons for the mixed findings may be related to characteristics of the child (i.e., moderators) or stressor, how the stress response or psychosocial stressor was measured, unmeasured variables (e.g., caregiving buffering), researcher degrees of freedom, or publication bias.
Fashion Image Retrieval based on Parallel Branched Attention Network

—With the increase in vision-associated applications in e-commerce, image retrieval has become an emerging application in computer vision. Matching the exact user clothes from the database images is challenging due to noisy background, wide variation in orientation and lighting conditions, shape deformations, and the variation in the quality of the images between query and reﬁned shop images. Most existing solutions tend to miss out on either incorporating low-level features or doing it effectively within their networks. Addressing the issue, we propose an attention-based multiscale deep Convolutional Neural Network (CNN) architecture called Parallel Attention ResNet (PAResNet50). It includes other supplementary branches with attention layers to extract low-level discriminative features and uses both high-level and low-level features for the notion of visual similarity. The attention layer focuses on the local discriminative regions and ignores the noisy background. Image retrieval output shows that our approach is robust to different lighting conditions. Experimental results on two public datasets show that our approach effectively locates the important region and signiﬁcantly improves retrieval accuracy over simple network architectures without attention.
Self-Attentive Models for Real-Time Malware Classification

Malware classification is a critical task in cybersecurity, as it offers insights into the threats that malware poses to the victim device and helps in the design of countermeasures. For real-time malware classification, due to the high network throughputs of modern networks, there is a challenge of achieving high classification accuracy while maintaining low inference latency. We first introduce two self-attention transformer-based classifiers, SeqConvAttn and ImgConvAttn, to replace the currently predominant Convolutional Neural Network (CNN) classifiers. We then devise a file-size-aware two-stage framework to combine the two proposed models, thereby controlling the tradeoff between accuracy and latency for real-time classification. To assess our proposed designs, we conduct experiments on three malware datasets: the Microsoft Malware Classification Challenge (BIG 2015) and two selected subsets from the BODMAS PE malware dataset, BODMAS-11 and BODMAS-49. We show that our transformer-based designs can achieve better classification accuracy than traditional CNN-based designs. Furthermore, we show that the proposed two-stage framework reduces the average model inference latency while maintaining superior accuracy, thereby fulfilling the requirements of real-time classification.
Die Spiegelkonfrontationstherapie zur Behandlung von Körperbildstörungen bei Essstörungen – Evidenz, Wirkmechanismen und Vorgehensweise

Zusammenfassung. Körperbildprobleme sind ein Kernmerkmal von Essstörungen. Daher gilt eine Verbesserung des Körperbildes bei der Behandlung von Essstörungen als zentrales Therapieziel. Verschiedene empirische Befunde weisen auf die Spiegelkonfrontation als wirksame Methode zur Reduktion von Körperbildstörungen hin. Ziel dieses Übersichtsartikels ist es, den aktuellen Stand der wissenschaftlichen Literatur zum Thema Spiegelkonfrontationstherapie bei Essstörungen darzulegen. Insbesondere sollen die Wirksamkeitsstudien getrennt für nicht-klinische, körperunzufriedene Gruppen mit und ohne Übergewicht sowie die verschiedenen Essstörungsgruppen systematisiert und unterschiedliche Vorgehensweisen beschrieben werden. Der Übersichtsartikel liefert Hinweise dafür, dass die Spiegelkonfrontationstherapie bei Hochrisikogruppen mit erhöhter Körperunzufriedenheit sowie bei Essstörungen zu positiven Veränderungen hinsichtlich der kognitiv-affektiven und behavioralen Komponente des Körperbildes führt. Jedoch mangelt es insgesamt an randomisiert-kontrollierten Studien, die die Wirksamkeit der Spiegelkonfrontationstherapie mit ausreichend großen Stichproben gezielt untersuchen – vor allem bei der Anorexia nervosa. Der Übersichtsartikel schließt mit einer Diskussion über mögliche Wirkmechanismen, (Kontra–)‌Indikationen und einem Ausblick für zukünftige Forschung ab.