Miracle-dz/UniFAR-FTUs huggingface dataset:
Snowballing alongside Domino on Proliferation of Preferential Trade Agreements

With regard to the third-country effects on bilateral incentives to sign new preferential trade agreements (PTAs), we develop a theory-based empirical approach that enables the assessment of how a country’s pre-existing PTAs affect her formation of a new PTA. Assessment of this effect is not trivial because a country’s pre-existing PTAs are also the pre-existing PTAs of her potential PTA partner’s partner, generating two counter-acting effects on the bilateral incentives to sign a new PTA. Our empirical analysis shows that a country’s pre-existing PTAs generate a positive effect on her incentive to sign a new PTA (i.e., Own PTA effect) but they generate a negative effect on her new partner’s incentive to sign a PTA (i.e., Partner’s PTA effect), as our theory predicts. The analysis also reveals that members of a CU are less likely to sign a new PTA than non-CU member countries as the Partner’s PTA effect is magnified by the CU’s joint negotiation requirement for a new PTA. Based on our n-country model of PTA proliferation, we conduct some calibration exercises that yield a varying degree of predictive power. *Park: Professor, Department of Economics, Seoul National University (j-hpark@snu.ac.kr). Roh: Assistant Professor, Department of International Trade, Yeungnam University (acts8@yu.ac.kr). For their useful comments, we would like to thank Pol Antras, Chul Chung, and the conference participants at the IEFS-EAER Conference at Seoul National University. We also thank Daeeun Bae and Taegon Yang for their research assistance. Roh acknowledges the financial support from the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2019 1A 5A 8032141).
Only Buffer When You Need To: Reducing On-chip GPU Traffic with Reconfigurable Local Atomic Buffers

In recent years, due to their wide availability and ease of programming, GPUs have emerged as the accelerator of choice for a wide variety of applications including graph analytics and machine learning training. These applications use atomics to update shared global variables. However, since GPUs do not efficiently support atomics, this limits scalability. We propose to use hardware-software co-design to address this bottleneck and improve scalability. At the software level, we leverage recently proposed extensions to the GPU memory consistency model to identify atomic updates where the ordering can be relaxed. For example, in these algorithms the updates are commutative. At the hardware level, we propose a buffering mechanism that extends the reconfigurable local SRAM per SM. By buffering partial updates of these atomics locally, our design increases reuse, reduces atomic serialization cost, and minimizes overhead. Thus, our mechanism alleviates the impact of global atomic updates and improves performance by 28%, energy by 19%, and network traffic by 19% on average and outperforms hLRC and PHI.
Corporate Social Responsibility and Earnings Management: Evidence from Saudi Arabia after Mandatory IFRS Adoption

This study attempts to examine the relationship between corporate social responsibility (CSR) disclosure and earnings management practices in the context of Saudi Arabia after mandatory IFRS adoption. It is carried out on an unbalanced panel of 277 observations over the period 2017–2019. For this purpose, CSR disclosure is measured by Bloomberg ESG scores, while the residuals from the modified Jones model are considered for earnings management. As control variables, we have retained the firm performance, market-tobook ratio, firm size, financial leverage, board independence, ownership concentration, managerial ownership, and lagged discretionary accruals. Using the system GMM estimator in the dynamic panel, the results show a positive association between CSR disclosure and earnings management practices, thus supporting the perspective of agency theory. Managers engage in socially responsible activities beforehand to conceal their wrongdoing and convince stakeholders that the organization is transparent. They probably use ethical codes as a tool to achieve their own goals rather than the firm’s goals. Our contribution is the use of recent data (2017–2019) taking into account the mandatory adoption of IFRS in Saudi Arabia. Additionally, to our knowledge, this study is the first to address CSR disclosure and earnings management practices using GMM system estimates.
Charge-exchange X-Ray Signature in Laboratory Outflow Interaction with Neutrals

According to the principle of Euler similarity between laboratory and astrophysical plasmas, laboratory plasmas driven by high-power lasers have been used to simulate some aspects of astrophysical phenomena. And in doing so, they aid our understanding of shock heating, interaction structures, and the consequential evolution for astrophysical outflows within a short timescale (∼ns). In this work, we experimentally investigated the mechanism of X-ray emission originating from a hot outflow (plasma) with a velocity of around 330 km s−1, impinging on a cold medium. A hybrid model was set up to understand the high-resolution X-ray spectra taken at the interaction region and to deduce that charge exchange takes place in such a laboratory miniature of astrophysical outflow interacting with dense molecular clouds, as in the cases of HH 248 and Cap in M82, for example. Effects from targets with multiple electrons are also explored. A brief analysis has been performed for our laboratory analog and astrophysical objects by a dimensionless ratio of the length scale between X-ray-emitting and charge-exchange regions.
Automated identiﬁcation of lateral plant root emergence points (Computer vision)

Studies concerning plant characteristics often require analysis of large amounts of images, and often require manual annotation of features of interest. In many cases, this amounts to an object detection task. For our project, we collaborated with Dr. Johannes Scharwies, who is investigating the hydropatterning phenotypes of nearly 300 different strains of corn, each with a different genome (DNA). Hydropatterning refers to how plant root development changes in response to the presence or absence of water in the soil, and could play a role in determining a plant’s drought response. In particular, our collaborator is interested in identifying areas of corn DNA that influence the extent to which the plant initiates root development in dry vs wet conditions. This requires the tedious task of manually counting lateral (secondary) root emergence points across hundreds of root images, a task which we sought to automate. The input of our algorithm is a plant root image. We then use a YOLOv4-based single-class object detection model to predict bounding boxes for lateral root emergence points. For the purposes of our collaborator’s study, the ultimate result of interest is the number of emergence points predicted by the model for a given root image.
Effect Of Combined Training On Anaerobic Power And Motor Skills Of Korfball And Basketball Players

In this study, the effects of eight-week combined training program on the development of anaerobic power and some isometric forces of korfball and basketball players are examined. 29 male (10 basketball players, 9 korfball players and 10 control group) university students, whose age range is 19-24 years, participated in the study. While basketball and korfball players were included in the training program, the participants in the control group continued their routine daily activities. Mean power (watts), peak power (watts), relative power (kg / watts), vertical jump (cm), right hand and left hand paw force (kg) and leg force (kg) were measured before and after the training program. Eight-week training program (3 days a week) consisted of resistance exercises (60-1RM), plyometric exercises (30 cm, 40 cm and 50 cm safes), common and intensive intervals (60-80% HR max), coordination and technical-tactical exercises. Statistically significant increase are determined in the peak power, relative power, vertical jump and leg force values of the basketball group and vertical jump, right hand, left hand and leg force values of the korfball group (p<0.05). In the light of the data obtained, it is seen that the increase in the performance values of basketball players is higher than the korfball players. Anaerobic power and vertical jump in basketball are more dominant than the korfball branch and the game progress is faster than the korfball. These reflect the effects of the training. As a result, it was observed that the combined training program used in this study contributes to improving the performance of basketball players, while different training models should be used for korfball players.
EFFECTIVELY COMPACT SPACES

We give a systematic technical exposition of the foundations of the theory of e↵ectively compact metric spaces. We discover several new characterizations of e↵ective compactness and apply these characterizations to prove new results in computable analysis and e↵ective topology. We also apply the technique of e↵ective compactness to give new and less combinatorially involved proofs of known results from the literature. Some of these results do not have e↵ective compactness or compact spaces in their statements, and thus these applications are not necessarily direct or expected.
Cadmium and Lead Concentrations in Water, Sediment, Fish and Prawn as Indicators of Ecological and Human Health Risk in Santubong Estuary, Malaysia

Cadmium (Cd) and lead (Pb) are toxic heavy metals with a growing appeal for study due to their ability to bioaccumulate in fish which may pose threat to human health through fish consumption. This study reported the concentration of Cd and Pb in water, sediment, fish, and prawn in Santubong Estuary, Malaysia. Water, sediment, fish (Arius maculatus) and prawn (Fenneropenaeus merguiensis) samples were collected from three rivers namely Buntal, Penambir and Demak. These samples were digested and analyzed using Flame Atomic Absorption Spectrophotometer (FAAS) for the heavy metal contents. The potential ecological and human health risks were assessed by using the bioaccumulation factor (BAF), Geoaccumulation Index (Igeo), Enrichment Factor (EF), Provisional Tolerable Weekly Intake (PTWI), Health Risk Index (HRI) and Health Index (HI). Cd and Pb concentrations in water were within the permissible limits but were above the acceptable limits in sediment as recommended by WHO. The concentration of Cd in A. maculatus was (0.10 0.13 mg/kg) while the concentration of Cd in F. merguiensis was (0.11 0.15 mg/kg), and these values were below the safety limits set by FAO/WHO and MFA. The concentration of Pb in A. maculatus (0.19-1.46 mg/kg) was also below the safety limits; however, the concentration of Pb in F. merguiensis (1.35-2.97 mg/kg) surpassed these safety limits. The Igeo values were less than one, and EF values ranged between 5 and 20, suggesting that this area is polluted with heavy metals. The BAF values for Cd (0.001 0.002 mg/kg) and Pb (0.003 0.040 mg/kg) showed that there might be an appreciable chance of bioaccumulation of heavy metals in the fish and prawn. The PTWI of prawn was slightly above the acceptable PTWI of Pb recommended by FAO/WHO (2016). Comparison with the safety limits showed that the continuous consumption of these fish and prawn for a long period would impose bad impacts on health. HRI and HI in both organisms were greater than one, indicating that there were possible adverse effects. Therefore, close monitoring of this area is recommended to minimize the risks of aquatic organism consumption.
Influence of Fasting and Feed Constituents Size Variation on Broiler Performance and Intestinal Demonstrations

Investigation was performed to elucidate the effects of fasting and feed constituents’ size variation on broilers performance and GIT demonstrations. Experiment was performed on 90 newly hatched chicks by dividing them into 3 treatment groups including T1, T2 and T3. Chicks in group T1 were fasted for 48 hours, T2 were fed a coarsely ground diet and T3 were finely ground mash diet. Results showed significant difference for residual egg yolk weight (2.54 ± 0.29a) and final body weight (50.1 ± 0.3b) in group T1; however, concerning weight of proventriculus + gizzard significant difference occurred in the group T2 (8.20 ± 0.08a). Chicks in group T1 possessed significantly higher weight of pancreas (0.32 ± 0.00b), jejunum (2.28 ± 0.05b) and ileum (1.98 ± 0.14b), while length of duodenum appeared higher in group T2 (25.92 ± 0.51a) followed by T3 (20.32 ± 0.77b) and T1 (18.24 ± 0.29c). Length of jejunum (41.44 ± 0.82a) and ileum (40.22 ± 0.93a) was significantly different in group T2. Duodenum villi height, cell area and muscularis externa thickness were significantly different in the group T1; however, body weight gain, diet intake and feed conversion efficiency showed significant difference in the group T2. Study concludes that post hatch fasting negatively affects the growth performance, gross and histological structures of digestive organs in broilers.
Do We Blame it on the Machine? Task Outcome and Agency Attribution in Human-Technology Collaboration

With the growing functionality and capability of technology in human-technology interaction, humans are no longer the only autonomous entity. Automated machines increasingly play the role of agentic teammates, and through this process, human agency and machine agency are constructed and negotiated. Previous research on “Computers are Social Actors (CASA)” and self-serving bias suggest that humans might attribute more technology agency and less human agency when the interaction outcome is undesirable, and vice versa. We conducted an experiment to test this proposition by manipulating task outcome of a game co-played by a user and a smartphone app, and found partially contradictory results. Further, user characteristics, sociability in particular, moderated the effect of task outcome on agency attribution, and affected user experience and behavioral intention. Such findings suggest a complex mechanism of agency attribution in human-technology collaboration, which has important implications for emerging socio-ethical and socio-technical concerns surrounding intelligent technology.
Machine learning based prediction of esterases ’ promiscuity

Enzymes are of great interest for a vast variety of industries; however, the experimental characterization is very time consuming and expensive which has led to the development of plentiful of machine learning based platforms capable of predicting enzymes’ function, de novo . Nonetheless, industrial enzymes need to adapt to nonbiological conditions while maintaining high activity, promiscuity and stereo-selectivity, properties that are not well covered, currently, by prediction technologies which means that their characterization still relies solely on experimentation. This project has the intention of mitigating the problem by developing binary classifiers and multi-classifiers that can predict the promiscuity of esterases, one of the many industrially relevant enzymes. The results are quite promising with all the developed classifiers achieving high metric scores and presumably without overfitting, however, the performance of the predictors will need to be confirmed with experimental data. If it is verified, the next step would be to extend the same process to other enzymes in demand, such as the phosphatases.
Likawent Yeheyis and Wondimeneh Mekonnen

Though bitter white lupin is an ancient pulse crop to Ethiopia, sweet lupins are new to the country. Sanabor and Vitabor are recently introduced sweet blue lupin varieties to be used as multipurpose crop in the traditional lupin growing agro-ecologies of Ethiopia. These varieties were introduced from Germany and evaluated along with fourteen other varieties which have been tested in different locations of the country from 2009 to 2013. The varieties are registered at national level in 2014. The merits of the varieties are their low alkaloid content, high seed yield, resistance to anthracnose and fusarium, most importantly are palatable for livestock and can be used for human food. Thus, the varieties are recommended as multipurpose pulse crop for the traditional and new lupin growing areas.
Student Perceptions in Temporary and Cohort Groups

This research study described student perceptions towards learning and participation for temporary groups and cohort groups. The participants were 101 eighth grade social studies students. For five weeks, students were assigned to regularly work in groups of three to four students. Two classes worked in temporary groups, and two other classes worked in cohort groups. Students completed a pretestposttest survey and a group work survey after each learning activity to describe group participation and learning. Six students participated in a semi-structured interview to elaborate on their experiences after the study. Results showed that students in cohort groups had a more positive attitude towards group learning and greater development of trust and community. The study showed the importance of using strategically formed groups in cooperative learning. Document Type Thesis Degree Name Master of Education (MEd) Department Graduate Education First Advisor Patricia C. Kornelis
: IMPLICATIONS FROM A PANEL DATA ANALYSIS

An all-inclusive financial system is one of the channels through which information and communication technology (ICT) affects economic growth. Digital financial inclusion is an evolving phenomenon that enhances the ease of access to and availability of formal financial services. Further, economic freedom is one of the significant factors affecting financial development and growth. Hence, there is a strong rationale for examining the effect of economic freedom on financial inclusion. However, there is no empirical evidence on the linkages between these variables in the literature. Accordingly, we examined these relationships. The results of a panel data analysis that we performed on a dataset pertaining to emerging economies show that the nexus of ICT diffusion–economic freedom–financial development has a positive impact on financial inclusion in the long run, highlighting the importance of creating an economic environment that is conducive to sustained economic growth. The findings of this study have significant implications from an economic policy standpoint and call for a more holistic approach.
Machine learning models for Prediction of the need for future Covid-19 vaccine booster

—About 4 million Virginia citizens are fully vaccinated against COVID-19. According to medical data from nations like Israel and the United Kingdom, all those people may require another shot in the near future, at least when keeping transmissible diseases at bay. Health officials are looking at whether a booster shot is needed to ensure the vaccine’s effectiveness. To prepare it for predictions, we will develop a new simple logistic regression model. Make prediction models using classification and probability. With the vaccine immune response lifetime taken into account, we will run our model to forecast the completely vaccinated number timeline and observe when it achieves the herd immunity percentage of the overall Virginia population. The percentage of people that need to be vaccinated to attain COVID-19 herd immunity is still up for dispute. The goal of this study was to forecast when everyone would be fully immunized. COVID-19 vaccination loses nearly half of its defense antibodies every 108 days, according to Elie Dolgin. As a result, immunizations that initially provided 90% protection against mild episodes of the disease may only provide 70% protection after 6 or 7 months. The percentage of people that need to be vaccinated to attain COVID-19 herd immunity is still being disputed.
Human Activity Recognition for Healthcare Applications

Every year, more than 25% of the elderly population in the United States experience debilitating injuries, such as falls, which can lead to broken bones and major injuries. These injuries may go unreported, and the compounding health effects can significantly deteriorate quality of life [1]. Alternatives such as constant monitoring by trained personnel is impractical due to the cost, time, and restrictions this places on an individual’s living accommodation. These issues motivate the development of a remote health monitoring system that tackle problems ranging from logging patient vitals to identifying high-risk accidents. We train C3D, ResNet-18, ResNet-50, ResNet-101, ResNeXt-101 models on 9 healthcare-related actions from the NTU-RGB+D dataset. When the models are trained from scratch, the validation accuracy saturates at 53% for ResNet-50, ResNet-101 and ResNeXt-101. However, models pre-trained on Kinetics-600 have sufficient information to further train the deeper layers and can match existing state-of-the-art systems (84%). We further show that for real world deployment we can trade-off accuracy for resource efficiency, i.e., MobileNetV2 achieves 7% decrease in accuracy for 36x fewer paramters and 25x fewer floating point operations. Our work is publicly available and can be downloaded here: https://github.com/reetikaag/human-activity-recognition
The Effect of Peer Assessment on Improvement of Iranian Pre- Intermediate EFL Learners' Oral Production

Many researchers are currently interested in employing new assessment technique such as peer and self-assessment. The fundamental goals of such strategies are to increase student’s involvement in the classroom process and to share responsibility between teacher and students. The study's main aim was to discover the effect of applying peer assessment on the improvement of pre-intermediate Iranian EFL learner’s oral production. The participants were randomly assigned into four groups (control and experimental) based on their gender, with 20 students in each group. The experimental groups received treatment in the form of peer assessment questionnaire while the control groups ran traditional sessions. Also the Oxford placement test and Cambridge Oral test (COT) was used as pre-and post-test of the study. The study followed true-experimental design. One-way ANOVA was run to measure the significant difference between proficiency levels before the main phase of the study. After finishing the data collection process, two-way ANOVA was applied to post-scores to see whether any improvement had taken place as a result of treatment. The findings indicated that there was statistically significant difference between experimental and control groups (p = .000), but there was not statistically significant difference between male and female in terms of the oral production gains (p = .975).
Weathering an Unexpected Financial Shock: The Role of Federal Disaster Assistance on Household Finance and Business Survival

First, we document the impact of being hit by a devastating tornado on household finance and business survival. The tornado paths are random and cannot be predicted using risk information. Individuals in severely damaged census blocks have a small reduction in debt and no change in bill delinquency. The business establishment survival rate declines by 9%. Second, we provide insight on the role of federal disaster assistance, which includes direct cash assistance to disaster victims and grants to repair public infrastructure, in mitigating the shock. Individuals in severely damaged blocks have 30% less credit card debt post-disaster when disaster aid is available. Migration from damaged blocks increases. Credit-constrained victims have lower bill delinquency and increase consumption. Disaster assistance is a place-based policy and results in 9% more establishments and 14% more employees post-disaster in the average-damage neighborhood. These effects are concentrated among small nonmanufacturing establishments that rely on local demand.