Miracle-dz/UniFAR-FTUs huggingface dataset:
Traits of a bloom in urban greening: a nationwide survey of U.S. urban tree planting initiatives (TPIs)

Municipal leaders worldwide are showing substantial interest in urban greening. This encompasses incentives, policies, and programs to vegetate urban landscapes, and it often includes urban tree planting initiatives (TPIs). Over the past decade there has been a seven-fold increase in scholarly use of terms denoting TPIs, and roughly two-thirds of associated studies address TPIs in the United States (U.S.). This reflects a bloom of scholarly interest in TPIs. Yet, there has been limited research on contemporary TPIs as historically situated cultural phenomena, and there has to the best of our knowledge been no nationwide survey of TPIs across municipal scales. Addressing these gaps, this article presents findings from a survey of 41 TPIs in the United States. We report on typical traits of U.S. TPIs across six themes: background, dates and goals, public awareness, funding and governance, planting, and stewardship. Respondents identified over 115 traits that distinguish TPIs from typical urban tree planting activity, suggesting that TPIs are a discrete form J ur l P re -p ro of
Significance of Research in Realistic Optimism and Its Future Prospect in School Education

This study describes the concept of new realistic optimism, and also discusses how the concept of new realistic optimism will be applied into school education. Many studies have been conducted in optimism and several studies found the tendency of people to be unrealistically optimistic about future life events. The author defined realistic optimism as “a way of thinking and a way of life that can give good prospects for the future, even if people encounter various difficulties”. Then, The authors attempted to create the new realistic optimism scale, with considering the philosophical views, which were explained by Alain (1953), Keller (1904), Mandela (2012), and Ikeda (2016). The concept of realistic optimism seems to play a critical role to contribute to supporting children in terms of fostering their social, mental, and emotional developments. The study discusses how important it is to apply the new concept into educational activities, and also discuss its future prospect. 1 Overview of optimism studies Many studies have been conducted in measuring optimism and pessimism, and these showed the differences in its concept, factors and approaches to measure optimism and pessimism. Some researchers believed that optimism is diametrically opposite to pessimism, and also there are several different styles to measure optimism and pessimism. For example, Weinstein (1980) developed an “unrealistic optimism scale”, which investigated the tendency of people to be unrealistically optimistic about future life events. This scale was designed to investigate people’s optimistic views in terms of their biased and unbiased views (the perspective error of judgments). The scale was composed of 42 worded statements of both the positive and negative life events (18 positive and 24 negative statements) and participants were asked to compare themselves with others to fulfill these evaluation items. The positive life events include “Liking postgraduation job”, “Owning your own home”, “Starting salary over 235 創価大学教育学論集 第73号:加藤・ニシャート・鈎 pp. 235~246
MODELING OF TITANIUM ALLOYS PLASTIC FLOW IN LINEAR FRICTION WELDING

The article presents the results of the analysis of the plastic flow of titanium alloys in the process of the Linear Friction Welding (LFW). LFW is a high-tech process for joining critical structural elements of aerospace engineering from light and high-temperature alloys. Experimental studies of LFW modes of such alloys are expensive and technically difficult. Numerical simulation was carried out for understanding the physics of the LFW process and the formation laws of a strong welded joint of titanium alloys. Simulation by the SPH method was performed using the LS DYNA software package (ANSYS WB 15.2) and the developed module for the constitutive equation. The new coupled thermomechanical 3D model of LFW process for joining structural elements from alpha and alpha + beta titanium alloys was proposed. It was shown that the formation of a welded joint occurs in a complex and unsteady stress-strain state. In the near-surface layers of the bodies being welded, titanium alloys can be deformed in the mode of severe plastic deformation. A deviation of the symmetry plane of the plastic deformation zone from the initial position of the contact plane of the bodies being welded occurs during a process of LFW. Extrusion of material from the welded joint zone in the transverse direction with respect to the movement of bodies is caused by a pressure gradient and a decrease in the alloy flow stress due to heating. The hcp-bcc phase transition of titanium alloys upon heating in the LFW process necessitates an increase in the cyclic loading time to obtain a welded joint.
Cultural Similarity Effect on the Relationship Quality between Exporters and Intermediaries and Export Performance of SMEs

Quality is a crucial component for developing a relationship between SME exporters and exporter intermediaries. The key role that quality plays in enhancing the performance of SMEs in foreign markets has been highlighted. Additionally, in order to support the development of such a relationship, cultural similarity is a fundamental catalyst particularly for initial stages of the internationalization process due to the belief that companies perform better in foreign markets if they possess similar cultural backgrounds. However, there have been previous studies have reported inconsistencies in findings between cultural similarity and performance. Hence, the purpose of this study is to examine what are the mechanisms in which cultural similarity can lead to relationship quality as well as performance. This current study used the Internationalization Process (IP) Theory and the Relational Exchange Theory (RET) to examine the synergistic effect of several factors on export performance within the context of Malaysian exporting SMEs and exporter intermediaries. A quantitative method was employed in this study where the primary data derived from 203 SME manufacturing exporting firms in Malaysia. Structural Equation Modeling using SmartPLS was used for data analysis. The result indicates that all hypotheses are supported. Findings may contribute to enriching the existing literature on export performance of Malaysian SMEs which use foreign intermediaries.
Studies on the Electrodeposition of Aluminium

The result of the test of electrodeposition of chromium on aluminium is favorable with the following preparation and deposition conditions:Aluminium surface is first etched by hydrochloric acid, then dipped for 3-10 seconds in mixed acid solution of 3 parts of HNO3 (sp. gr. 1.42) and 1 part of HF (50%). On thus prepared surface, as an intermediate film, zinc or copper is electrodeposited from cyanide bath.Chromium deposition from the bath of 250g/l of CrO3 and 1.25g/l H2SO4, at the temperature of more than 40°C, by the current density of 30A/dm2, and for more than 30min is pretty thin but nice and tight.
Deep Learning for Defect Classiﬁcation of Photovoltaic Module Electroluminescence Images

In this work, we propose a deep learning segmentation model that segments and identiﬁes 2 different types of solar cell defects in electroluminescence images: cracks and contact defects. Our model uses a segmentation 2D fully convolutional network (FCN) with a ResNet-101 backbone. We achieve a weighted F1-score of . 91, a pixel level global accuracy of 91.6%, and a mean intersection over union (IoU) score of 63.36%. We have found that even though we use inverse distribution weights in a cross entropy loss function in attempt to counter major class imbalance, the class imbalance remains a large issue with this application and that a viable solution could result in much higher accuracies.
SPATIAL ANALYSIS WITH GIS MAPPING OF FUNGICIDE CONSUMPTION IN AGRICULTURAL AREAS

The development in agriculture has gradually increased the use of fungicides in Turkey. Fungicides negatively affect the life conditions of living organisms in water, air and soil right amounts of chemicals to be used in certain periods. The aim of this study is to spatially determine the amounts of fungicide consumption using Geographical Information System (GIS) mapping, and also to determine the level of during the 2010-2014 period. The data obtained from the Turkish Statist Directorate of Provincial Food Agriculture and Livestock has been evaluated by the help of Inverse Distance Weighting (IDW) method in the GIS. While the highest amount of fungicide consumption was observed to be 250.0 tons in 2010, the lowest amount of fungicide consumption was determined to be 179.78 tons in 2013. When examining the spatial distribution of fungicide consumption, the highest consumption intensity was observed in the consumption intensity is determined to be in the Southern (Central district) and South-western whole period. According to the spatial distribution, the highest concentration intensity has been
A rapid magnetic particle-based enzyme immunoassay for human cytomegalovirus glycoprotein B detection

Human cytomegalovirus (HCMV) is a herpes virus that can cause severe infections or even be fatal in immunosuppressed individuals, or those with immature immune system. The available methods for its diagnostic, usually through detection of antibodies in specimens, have the main disadvantage of requiring long time to be performed. In this work, a simple magnetic particle-based enzyme immunoassay (mpEIA) for the detection of glycoprotein B of Human cytomegalovirus (gB-HCMV) in urine samples is proposed. Glycoprotein B is the major antigen for the induction of neutralizing antibodies against HCMV, making it an interesting biomarker for immunoprophylaxis. Magnetic beads modified with protein-G (MBs-PrG) are used in immunoassays to promote the oriented immobilization of the capture antibody on a solid phase. The immunosensor scheme is based on the analyte protein gB-HCMV sandwiched between a primary monoclonal antibody, (MBs-PrG-mAb1), and a secondary anti-gB-HCMV antibody labelled with Horseradish peroxidase (Ab2-HRP) to allow spectrophotometric detection. The mpEIA analytical performance was tested in urine samples, showing a linear dependence between gB-HCMV concentration and the absorbance signal at 450 nm in a range of concentrations from 90 to 700 pg mL. The validation of the immunoassay was carried out according to the “Guideline on bioanalytical method validation”, from the European Medicines Agency (EMEA 2014). The calculated detection limits for gBHCMV were 90±2 pg mL and the RSD was about 6.7% in urine samples. The immunosensor showed good selectivity against other viruses from Herpesviridae family, namely varicella zoster and Epstein Barr viruses. The recoveries of spiked human urine samples at 0.30-0.50 ng mL concentration levels of gB-HCMV ranged between about 93 and 106%. The proposed mpEIA method allows rapid (it can be carried out in about 3 h.), successful and easy quantification of gB-HCMV in urine samples.
Effectiveness of E-Book in Improving Academic Performance and Attitudes toward Mathematic

: The aim of the study was to determine whether use of an e-book would lead to improvement in academic performance and more positive attitudes towards learning mathematics. Thus, an experiment was conducted with 56 Seventh Grade students from two middle schools in Abha, Saudi Arabia. The students were randomly assigned into either the traditional book condition (i.e., the control group) or the e-book condition (i.e., the experimental group). Improvement in academic performance from pretest to posttest differed significantly across the two conditions, with students in the e-book condition improving more than those in the traditional book condition. Further, students in the e-book condition expressed significantly more positive attitudes towards learning mathematics using an e-book after the study. Based on these results, it was recommended that technological advancement may promote learning via more positive attitudes toward mathematics.
Title: Deep learning to distinguish benign from malignant renal lesions based on routine MR imaging

: Purpose: With increasing incidence of renal mass, it is important to make a pre-treatment differentiation between benign renal mass and malignant tumor. We aimed to develop a deep learning model that distinguishes benign renal tumors from renal cell carcinoma (RCC) by applying a residual convolutional neural network (ResNet) on routine MR imaging. Experimental Design: Preoperative MR images (T2-weighted and T1-post contrast sequences) of 1162 renal lesions definitely diagnosed on pathology or imaging in a multicenter cohort were divided into training, validation, and test sets (70:20:10 split). An ensemble model based on ResNet was built combining clinical variables, T1C and T2WI MR images using a bagging classifier to predict renal tumor pathology. Final model performance was compared with expert interpretation and the most optimized radiomics model. Results: Among the 1162 renal lesions, 655 were malignant and 507 were benign. Compared to a baseline zero rule algorithm, the ensemble deep learning model had a statistically significant higher test accuracy (0.70 vs. 0.56, p=0.004). Compared to all experts averaged, the ensemble deep learning model had higher test accuracy (0.70 vs. 0.60, p=0.053), sensitivity (0.92 vs. 0.80, p=0.017) and specificity (0.41 vs. 0.35, p=0.450). Compared to the radiomics model, the ensemble deep learning model had higher test accuracy (0.70 vs. 0.62, p=0.081), sensitivity (0.92 vs. 0.79, p=0.012) and specificity (0.41 vs. 0.39, p=0.770). Conclusion: Deep learning can non-invasive distinguish benign renal tumors from RCC using conventional MR imaging in a multi-institutional dataset with good accuracy, sensitivity and specificity comparable to experts and radiomics.
Award Number: W81XWH-12-2-0082 TITLE: Evaluation of Novel Polyunsaturated Fatty Acid Derived Lipid Mediators of Inflammation to Ameliorate the Deleterious Effects of Blast Over Pressure on Eye and Brain Visual Processing Centers in Rats

for the 2014 National Capital Area TBI Research Symposium: Exposure to Primary Blast Waves Causes Traumatic Injury to the Visual System, in Rats. James C. DeMar, Ph.D., Stephen A. VanAlbert, Miya I. Hill, Robert B. Gharavi, Joseph R. Andrist, Andrea A. Edwards, Cory A. Riccio, and Joseph B. Long Blast-Induced Neurotrauma Branch, Center for Military Psychiatry and Neuroscience, Walter Reed Army Institute of Research, Silver Spring, MD 20910 Blast injury has emerged as arguably the greatest threat to warfighters in current theaters of operation, and is a leading cause of vision loss due to non-penetrating traumatic injuries to the eyes or brain, likely caused by blast shock waves. In light of the difficult lifelong disability that permanent loss of vision represents, we propose there is a dire need to determine the degree of injury occurring specifically to the retina (e.g., photoreceptors) and brain visual centers (e.g., optic tracts), as result of exposure to blast waves. Using an adult rat model of blast wave exposure, we have now quantified the cellular and functional damage to the retina and brain, by electroretinography (ERG), visual discrimination behavioral testing, and histopathology. Blast wave injury was carried out by placing rats in a compressed air driven shock tube and exposing them once to a 20 psi (260 Hz) blast over pressure wave. Animals were then assessed at 1, 7, and 14 days post-injury. By 2 weeks out, blasted rats versus shams showed significantly decreased ERG waveform amplitudes, impaired ability to visually discern a cue light of variable intensity to earn food rewards, and severe neuronal cell degeneration within the retina and most brain visual processing centers (H&E and silver stains). Our research is an important contribution to providing the pathophysiological knowledge needed for developing therapies for blast related injuries and to advancing military medicine. SUPPORT: This work is supported by a USAMRMC/ TATRC Vision Research Program grant award, #: W81XWH-12-2-0082.
Is voting patterns at the United Nations General Assembly (UNGA)a useful way to understand a country’s policy inclinations: Bangladesh’s voting records at the UNGA

This article explores Bangladesh’s voting coincidences at the United Nations General Assembly (UNGA) with China, India, Russia, and the United States for the period 2001–2017 to draw inferences about country’s political proximity and policy preferences on global issues. Although Bangladesh’s voting coincidence shifted from China toward India since 2013, country’s “opposite” votes with India remained 3 times higher compared with that of China, suggesting that the post-2013 change in voting coincidence is more about the types and content of the resolutions and not fundamental. Bangladesh maintained a principled position on disarmament, conventional arms control, nuclear nonproliferation, and prohibition of chemical weapons resolutions, which are greatly at odds with India and China. Such voting coherency suggests that the small developing countries can maintain a higher level of voting consistency on issues that are of great interest to them. However, Bangladesh’s voting inconstancy in the country-specific human rights resolutions reflects a selective adherence to the policy of non-interference, particularly with respect to neighbors. Bangladesh’s voting records on the human rights situation in Myanmar, reveals that it joined the majority member states condemning Myanmar only when the resolutions started mentioning Bangladesh as an affected country. Although the voting coincidence alone may not capture the whole dynamics of a state’s leanings, this article has revealed that systematic research of UNGA voting records has the capacity to add to the knowledge of political proximity and policy preferences of states in terms of the way they weigh their choices and chart their path through idealism and opportunism.
Efficient Placement of Pressure Sensors of a Sitting Cushion Stitched by Conductive Thread for Sitting Position

In this paper, efficient placement of pressure sensors is tested for correct posture under sitting cushion using conductive thread to connect the pressure sensors. Conductive thread Ada-641 from the Adafruit industries is used to connect sensors for the sitting cushion. In order to detect the correct sitting postures, an Arduino-based cushion seat with 16 pressure sensors is implemented. A conductive thread connects the sensors to accommodate the comfort of the sitting cushion. In order to test the efficient placement of the pressure sensors, several types of sensor locations are suggested to identify sitting postures. The least number of sensors included for a given type of pressure sensor location is four. Sitting posture detection with 8 and 12 sensors is also tested. The maximum number of sensors included in the experiment is 16. The efficient placement of the sensors is decided by comparing the detection probability of the correct sitting posture for a different number of sensors included in the sitting posture test. It is shown that the correct sitting posture can be detected 100% by using 8 sensors out of 16 sensors. The test results show a guideline for the minimum number of sensors required for reliable, correct posture detection. It is also shown that the performance of the sitting cushion with conductive thread type sensors is as good as the one with the copper wire connection.
Does Footwear Influence Countermovement Jump Parameters Used to Assess Performance in Collegiate Basketball Players?

Background: The countermovement jump (CMJ) is used to monitor short- and long-term changes in neuromuscular performance, where practically relevant alteration may be subtle, requiring detailed and consistent testing protocols to limit error and allow detection of meaningful change. Collegiate basketball players often wear different types of footwear depending upon the training activity, potentially influencing CMJ performance outcomes. Objective: This study evaluated the influence of footwear on key CMJ variables used for routine performance assessments in a cohort of 11 NCAA women’s collegiate basketball players. Method: In a cross-over repeated measures study design, players performed three CMJs in Basketball-, Training-(Trainers), and Olympic Weightlifting (WL) shoes, in a randomized order during one testing session. One-way repeated measures analyses of variance (p ≤ .05) and effect sizes (Cohen’s d) were used to discern differences in CMJ variables among shoe conditions. Results: WL demonstrated greater Eccentric Mean Force (p ≤ .014, d ≥ 0.03) and lower Flight Time:Contraction Time (p ≤ .029, d ≥ 0.31), Jump Height (p ≤ .040, d ≥ 0.32), and Reactive Strength Index-Modified (p ≤ .032, d ≥ 0.40) than both Basketball and Trainers. Additionally, WL exhibited lower Concentric Mean Force (p = .018, d = 0.19), Concentric Mean Power (p = .008, d = 0.29), Eccentric Peak Force (p = .050, d = 0.19), and Flight Time (p = .036, d = 0.31) compared to Trainer. No significant differences and only trivial effects appeared between Basketball and Trainers (p > 0.05, d < 0.1). Conclusion: These findings suggest footwear significantly influences CMJ performance. WL shoes appear to negatively impact CMJ performance; however, Basketball and Trainers appear to exert negligible effects that should allow clinicians and practitioners to feel confident about measurement and data quality when performing short- and long-term CMJ measurements in either Basketball or Trainers.
Combining User-Genre Preference Information with Neural Collaborative Filtering

In this paper, the user-genre preference information is introduced into collaborative filtering (CF) to deal with the sparsity which CF suffers from. This work classifies items by genre information, it applies neural collaborative filtering model in each category and combines all models together to get a final prediction. These experiments in the work are conducted on well-known dataset in which hit ratio and Normalized Discounted Cumulative Gain (NDCG) are introduced into the evaluation. It indicates that our model has fast performance growth and good results.
Running head: PERFECTIONISM AND COPING WITH INJURY

1 Previous research has found perfectionism dimensions to predict coping strategies in sport 2 when dealing with various stressors. We aimed to extend previous research by examining the 3 interactive effects of perfectionism dimensions on strategies employed by marathon runners 4 to cope with injury. This involved testing the hypotheses of the 2×2 model of perfectionism 5 in marathon runners. Marathon runners (n = 224, female n = 81, M age = 39.77 years, SD = 6 9.50 years) completed measures capturing four subtypes of perfectionism (pure self-oriented 7 perfectionism, pure socially prescribed perfectionism, mixed perfectionism, and non8 perfectionism) and strategies for coping with injury (problem-focused coping, emotion9 focused coping, and avoidance coping). Moderated regression analyses provided support for 10 all four hypotheses of the 2×2 model for problem-focused coping, one hypothesis for 11 emotion-focused coping, and none for avoidance-coping. Problem-focused coping was 12 highest for pure self-oriented perfectionism and lowest for pure socially prescribed 13 perfectionism. Emotion-focused coping was higher for pure self-oriented perfectionism 14 compared to non-perfectionism. Finally, avoidance coping was similar across all subtypes. 15 The results provide initial evidence that the 2×2 model of perfectionism explains differences 16 in the use of coping strategies in context of marathon running injury. 17