Miracle-dz/UniFAR-FTUs huggingface dataset:
A Characterization Study of Merge Conflicts in Java Projects

In collaborative software development, programmers create software branches to add features and fix bugs tentatively, and then merge branches to integrate edits. When edits from different branches textually overlap (i.e., textual conflicts) or lead to compilation and runtime errors (i.e., build and test conflicts), it is challenging for developers to remove such conflicts. Prior work proposed tools to detect and solve conflicts. They investigate how conflicts relate to code smells and the software development process. However, many questions are still not fully investigated, such as what types of conflicts exist in real-world applications and how developers or tools handle them. For this article, we used automated textual merge, compilation, and testing to reveal three types of conflicts in 208 open-source repositories: textual conflicts, build conflicts (i.e., conflicts causing build errors), and test conflicts (i.e., conflicts triggering test failures). We manually inspected 538 conflicts and their resolutions to characterize merge conflicts from different angles. Our analysis revealed three interesting phenomena. First, higher-order conflicts (i.e., build and test conflicts) are harder to detect and resolve, while existing tools mainly focus on textual conflicts. Second, developers manually resolved most higher-order conflicts by applying similar edits to multiple program locations; their conflict resolutions share common editing patterns implying great opportunities for future tool design. Third, developers resolved 64% of true textual conflicts by keeping complete edits from either a left or right branch. Unlike prior studies, our research for the first time thoroughly characterizes three types of conflicts, with a special focus on higher-order conflicts and limitations of existing tool design. Our work will shed light on future research of software merge.
Finer Complexity Estimates for the Change of Ordering of Gröbner Bases for Generic Symmetric Determinantal Ideals

Polynomial matrices and ideals generated by their minors appear in various domains such as cryptography, polynomial optimization and effective algebraic geometry. When the given matrix is symmetric, this additional structure on top of the determinantal structure, affects computations on the derived ideals. Thus, understanding the complexity of these computations is important. Moreover, this study serves as a stepping stone towards further understanding the effects of structure in determinantal systems, such as those coming from moment matrices. In this paper, we focus on the Sparse-FGLM algorithm, the state-of-the-art for changing ordering of Gröbner bases of zero-dimensional ideals. Under a variant of Fröberg's conjecture, we study its complexity for symmetric determinantal ideals and identify the gain of exploiting sparsity in the Sparse-FGLM algorithm compared with the classical FGLM algorithm. For an n×n symmetric matrix with polynomial entries of degree d, we show that the complexity of Sparse-FGLM for zero-dimensional determinantal ideals obtained from this matrix over that of the FGLM algorithm is at least O(1/d). Moreover, for some specific sizes of minors, we prove finer results of at least O(1/nd) and O(1/m3d).
Science Teacher Education and a Sociopolitical Turn: The Implications for Democratic Citizenship, and Environmental and Social Justice

inherently socially negotiated character of meaning and the interested, concerned character of the thought and actions of persons-in-activity. This view also claims that learning, thinking and knowing are relations among people in activity in, with, and arising from the socially and culturally structured world. This world is socially constituted; objective forms and systems of activity, on the one hand, and agents’ subjective and intersubjective understandings of them on the other, mutually constitute both the world and its experienced forms. (p.
Detection of driver fatigue driving behaviour based on deep learning algorithm from the perspective of traffic psychology

In modern times, with mass transportation systems, driver fatigue has become one of the main causes of traffic accidents. The development of intelligent transportation systems holds great promise for safety. Increasingly, policies, laws, and regulations will consider artificial intelligence applications for minimising driver fatigue. This study presents the basic features of facial recognition systems applied to driver fatigue monitoring, as well as their comparative strengths and limitations. Traffic psychology has much to offer road safety from driver fatigue applying deep learning algorithms to reduce traffic accidents and ensure traffic safety.
Work stressors and vicarious trauma among South African Police Service members

This study explored vicarious stress experiences of South African Police Service members from a rural district serving victims of trauma. Informants were 19 police members (female = 26.3%; constables = 21%; age range = 27 to 55). The police members completed open-ended interviews about their experiences when engaging with victims of trauma. Following interpretative phenomenological analysis, findings indicated that the police members experienced vicarious types of stress due to their operational work, personal situations, and cultural prescriptions. Operational work vicarious stressors included perceptual stressors and police-victim interpersonal closeness. Personal situations vicarious stressors were due to cognitive overload resulting from vocation-life association and personal trauma history. Cultural-prescriptive stressors of societal cultural beliefs were also associated with vicarious trauma. These findings suggest a need for culturally appropriate mental health services and identifying personal and organisational strategies to manage vicarious traumatisation in the police services.
Linking theories and actions-in-practice: infusing N=1 action research projects into educational psychology courses

ABSTRACT This article discusses a study that examined how pre-service teachers could link academic theories and their teaching in graduate educational psychology courses. A mini-action research project to tutor individual students in the form of ‘N = 1 Action Research’ (NAR) was assigned in psychological foundation courses required in masters-level teacher education programs. The content analysis of 61 NAR papers found that some of them merely cited psychological theories without linking them to their teaching or were rigidly confined by their scope of the theories. Others flexibly made use of psychological theories to make sense of the varying needs of their students and engaged in critical inquiries into how academic theories could be further developed to encompass the complex needs of their students. This study suggests the need to look into pre-service teachers’ relationships to academic theories and help them engage in reflective inquiries into their personal theories and assumptions on teaching.
Interleaved high conversion ratio DC–DC converter with output self‐balancing and current auto‐sharing for DC nanogrid application

In the application of bipolar DC bus configuration in the DC nanogrid, the unbalanced voltage of two outputs in bipolar DC bus, due to the unbalanced conditions of loads and/or energy sources, will cause deterioration of the power quality of the bus and may damage the switch, affecting the stability and safety of the system. In order to solve the problem of unbalanced voltage of two outputs, interleaved series capacitor based dual‐output converter with a high conversion ratio is presented in this paper. By applying negative current mode (NCM) to the main inductor, the character of two‐output self‐balancing and zero voltage switching (ZVS) of all switches for such this topology configuration is achieved. In the NCM mode, the parallel diodes of main switches are not conducted during dead time and guarantee the flowing path to load side. Thus, based on this condition, volt‐second balance of main inductor is obtained to get the character of two‐output self‐balancing. Furthermore, by adopting series capacitor in the proposed topology and based on the charge‐balance of the intermediate block capacitor, inductor current existed in the two phase could be auto‐sharing. Comprehensive operational principle analysis, loss analysis, and efficiency of the proposed converter under different load conditions have been given, and the comparison analysis of three operation modes and selection of negative current mode is clarified. Small signal model of the proposed converter is described to convenient for the controller design. Finally, simulation results and a 20–220 V prototype are built to verify the character analysis of the proposed converter.
Activated Endolysosomal Cation Channel TRPML1 Facilitates Maturation of α-Synuclein-Containing Autophagosomes

Background: Protein aggregates are degraded via the autophagy-lysosome pathway and alterations in the lysosomal system leading to the accumulation of pathogenic proteins, including aggregates of α-synuclein in Parkinson’s disease (PD). The importance of the endolysosomal transient receptor potential cation channel, mucolipin subfamily 1 (TRPML1) for the lysosomal function is highlighted by the fact that TRPML1 mutations cause the lysosomal storage disease mucolipidosis type IV. In this study, we investigated the mechanism by which activation of TRPML1 affects the degradation of α-synuclein. Methods: As a model of α-synuclein pathology, we expressed the pathogenic A53Tα-synuclein mutant in HEK293T cells. These cells were treated with the synthetic TRPML1 agonist ML-SA1. The amount of α-synuclein protein was determined by immunoblots. The abundance of aggregates and autolysosomal vesicles was determined by fluorescence microscopy and immunocytochemistry. Findings were confirmed by life-cell imaging and by application of ML-SA1 and the TRPML1 antagonist ML-SI3 to human dopaminergic neurons and human stem cell-derived neurons. Results: ML-SA1 reduced the percentage of HEK293T cells with α-synuclein aggregates and the amount of α-synuclein protein. The effect of ML-SA1 was blocked by pharmacological and genetic inhibition of autophagy. Consistent with TRPML function, it required the membrane lipid PI(3,5)P2, and cytosolic calcium. ML-SA1 shifted the composition of autophagosomes towards a higher fraction of mature autolysosomes, also in presence of α-synuclein. In neurons, inhibition of TRPML1 by its antagonist ML-SI3 blocked autophagosomal clearance, whereas the agonist ML-SA1 shifted the composition of a-synuclein particles towards a higher fraction of acidified particles. ML-SA1 was able to override the effect of Bafilomycin A1, which blocks the fusion of the autophagosome and lysosome and its acidification. Conclusion: These findings suggest, that activating TRPML1 with ML-SA1 facilitates clearance of α-synuclein aggregates primarily by affecting the late steps of the autophagy, i.e., by promoting autophagosome maturation. In agreement with recent work by others, our findings indicate that TRPML1 might constitute a plausible therapeutic target for PD, that warrants further validation in rodent models of α-synuclein pathology.
Burnout Among Medical Staff 1 Year After the Beginning of the Major Public Health Emergency in Wuhan, China

Objectives Wuhan is the city where coronavirus disease (COVID-19) was first reported and developed into a pandemic. However, the impact of the prolonged COVID-19 pandemic on medical staff burnout remains limited. We aimed to identify the prevalence and major determinants of burnout among medical staff 1 year after the beginning of the COVID-19 pandemic in Wuhan, China. Materials and Methods A total of 1,602 medical staff from three hospitals in Wuhan, China, were included from November 1–28, 2021. Chi-square tests were conducted to compare the prevalence of burnout across groups based on sociodemographic and professional characteristics. A multivariate analysis was performed using a forward stepwise logistic regression model. Results Approximately 37.39% of the medical staff experienced burnout 1 year after COVID-19 pandemic. Emotional exhaustion (EE) was the most common symptom of burnout, with 1,422 (88.76%) participants reporting a severe EE. Burnout was associated with insufficient social support and “neutral” or “dissatisfied” patient-physician relationships. Respondents who participated in the care of COVID-19 patients had a higher risk of burnout symptoms than those who did not participate. In particular, mental resilience was negatively associated with burnout among the medical staff. Conclusion Nearly two-fifths of the participants had symptoms of burnout, with reduced personal accomplishment being the predominant symptom 1 year after COVID-19. Healthcare organizations should regularly measure and monitor burnout among the medical staff. In addition, creating positive work environments and improving the mental resilience of medical staff may be effective ways to reduce burnout.
Descriptive Analysis of Adaptive Behavior in Phelan–McDermid Syndrome and Autism Spectrum Disorder

Introduction The variety in symptomatology and clinical presentation of individuals diagnosed with Phelan-McDermid Syndrome (PMS) can delay medical diagnosis, so identifying specific neurobehavioral variables and facilitating differential diagnosis with patients with idiopathic Autism Spectrum Disorder (ASD) can guide early detection. Methods A descriptive analysis of the level of adaptive behavior in 50 patients diagnosed with PMS was performed (SHANK3deletion: N = 44; SHANKmutation: N = 6). Subsequently, a comparative analysis was performed with 28 children aged between 4 years and 6 years and 11 months (SHANK3deletion = 14; ASD = 14). Differences between the two groups were evaluated and Bonferroni correction was applied for multiple comparisons. Results Differences were identified in the variables of communication (z = −2.715, p = 0.007), Self-Direction (z = −2.199, p = 0.028) and social participation (z = −3.190, p = 0.001), with better adaptive behavior skills being observed in participants with a SHANK3mutation. Better adaptive skills in the sample of participants with ASD, were found and statistically significant differences were identified in the variables of academic skills (z = −3.084, p = 0.002), use of community resources (z = −1.889, p = 0.050) and health and safety (z = −2.90, p = 0.004). Conclusion Participants with SHANK3mutation show better communication and social participation skills than those with a diagnosis of SHANK3deletion. The observed differences between ASD and individuals with PMS reflect deficits in practical and conceptual adaptive skills that may limit and hinder daily adaptive functioning.
Innovation and Recycling—Drivers of Circular Economy in EU

In our days, a growing attention is paid to explain the influence of innovation on recycling. While many studies on this subject have been carried out, it's still needed for more investigations on measuring the effect of innovation on recycling. This paper is dedicated to measuring the intensity of the innovation influence on the recycling within EU member states. The methodology follows the next steps: visualization of data used, determining the stationarity of the time series analyzed, developing a panel model for 28 countries, applying specific statistical tests in case of the two indicators selected. After analyzing the models that resulted and applying Hausman test, the authors concluded that the regression panel with fixed effects is appropriate for our research. Thus, it is possible to show that the influence of the innovation on recycling is moderate and not instantaneous because there is manifested a lag of 2 years. In addition, the Fixed Effects model allows highlighting the heterogeneity that is present among member states. In addition, the authors concluded that the membership of the Euro Area has a positive influence on recycling and on circular economy as well. The article has several originality aspects: it took into account criteria that are not discussed very often as membership of Euro area; it has developed a model that brings quantitative aspects to describe the influence of innovation on recycling, it highlighted the heterogeneity existing among EU member states. Future research direction would be to consider including in the model some other variables as eco-investment.
Patient-Specific Assays Based on Whole-Genome Sequencing Data to Measure Residual Disease in Children With Acute Lymphoblastic Leukemia: A Proof of Concept Study

Risk-adapted treatment in acute lymphoblastic leukemia (ALL) relies on genetic information and measurable residual disease (MRD) monitoring. In this proof of concept study, DNA from diagnostic bone marrow (BM) of six children with ALL, without stratifying genetics or central nervous system (CNS) involvement, underwent whole-genome sequencing (WGS) to identify structural variants (SVs) in the leukemic blasts. Unique sequences generated by SVs were targeted with patient-specific droplet digital PCR (ddPCR) assays. Genomic DNA (gDNA) from BM and cell-free DNA (cfDNA) from plasma and cerebrospinal fluid (CSF) were analyzed longitudinally. WGS with 30× coverage enabled target identification in all cases. Limit of quantifiability (LoQ) and limit of detection (LoD) for the ddPCR assays (n = 15) were up to 10−5 and 10−6, respectively. All targets were readily detectable in a multiplexed ddPCR with minimal DNA input (1 ng of gDNA) at a 10−1 dilution, and targets for half of the patients were also detectable at a 10−2 dilution. The level of MRD in BM at end of induction and end of consolidation block 1 was in a comparable range between ddPCR and clinical routine methods for samples with detectable residual disease, although our approach consistently detected higher MRD values for patients with B-cell precursor ALL. Additionally, several samples with undetectable MRD by flow cytometry were MRD-positive by ddPCR. In plasma, the level of leukemic targets decreased in cfDNA over time following the MRD level detected in BM. cfDNA was successfully extracted from all diagnostic CSF samples (n = 6), and leukemic targets were detected in half of these. The results suggest that our approach to design molecular assays, together with ddPCR quantification, is a technically feasible option for accurate MRD quantification and that cfDNA may contribute valuable information regarding MRD and low-grade CNS involvement.
Insights Into the Template Effect on Nanostructured CuO Catalysts for Electrochemical CO2 Reduction to CO

Electrochemical CO2 reduction to CO using copper-based catalysts has been recognized a promising approach to realizing anthropologic carbon cycle. However, copper-based catalysts face the challenges of low reduction activity and poor selectivity in CO2 reduction reaction. Tuning particle size and oxygen vacancy represents an efficient strategy for boosting their activity and selectivity. Herein, we reported the preparation of nanostructured CuO catalysts for selective electrochemical CO2 reduction to CO. Several templates were employed in the template-assisted hydrothermal process to regulate the particle size and oxygen vacancy. Structure-property-activity relationships of the CuO nanostructures depend on the template effect. CuO-PVP and CuO-SDS synthesized using polyvinylpyrrolidone (PVP) and sodium dodecyl sulfate (SDS) as templates exhibited smaller particles sizes and higher concentrations of oxygen vacancy defects. Under the applied potential of −0.93 V vs. RHE, the desired CuO-PVP and CuO-SDS catalysts exhibited good CO2 reduction activity with high electrochemical surface area normalized partial current density of 2.21 and 1.37 mA/cm2 for CO production and outstanding CO selectivity with high faradaic efficiencies of 48.2 and 50.5%. Density functional theory (DFT) calculations indicated that oxygen vacancies in the CuO nanostructures not only promoted CO2 adsorption and activation but facilitated CO desorption from the catalyst surface, and therefore boosted the activity and CO selectivity in CO2 reduction. The results have deepened the understanding of the structure-property-activity relationships of CuO catalysts, and these will provide guidance for designing highly efficient and robust catalysts for electrochemical CO2 reduction to CO.
Antecedents and Consequences of Grit Among Working Adults: A Transpersonal Psychology Perspective

Positive psychology has paved the way for newer and more informed ideas of living a meaningful, integrated and well-rounded quality of living. The current era of the pandemic has also moulded the ways in which individuals perceive their quality of life and how they want to integrate a holistic approach towards their well-being. The workplace settings have seen tremendous changes in terms of how employers, employees and the organisations at large function and operate. The pre-pandemic concept of success has shifted its focus from hard work to developing grit among employees to increase the overall efficiency of the organisations. Grit has revolutionised the conventional standards of success, meaning in life and has impacted personal as well as occupational welfare. This integration of positive psychology and transpersonal psychology has catalysed the purpose for the current study. To help organisations and individuals thrive in their professional endeavours at the workplace and to provide them with relevant psychological tools to enhance their occupational growth, the present study has been conducted empirically to investigate the antecedents and consequences of grit among 209 working professionals in India. The results of this study indicate that the transpersonal capital of metacognition, flow, optimism and empathy have a significant role to play in developing grit among the participants. The findings have implications for enhancing job satisfaction and job performance of participants. The current research also provides a framework to organisations towards designing interventions for improving efficiency at the workplace.
Engagement Mediates the Relationship Between Emotion and Achievement of Chinese EFL Learners

Since the coming of Positive Psychology in the field of second language acquisition (SLA), the significance of emotion, especially positive emotion, has been well recognized by researchers. Educational research has indicated that both emotion and engagement play fundamental roles in learning process and psychological wellbeing, but research on their relationship is scant in SLA. The present study contributed to the development of Positive Psychology in SLA by investigating the relationships between achievement emotions, behavioral engagement, and self-reported English achievements. 633 students from four senior high schools in China participated in the study. Data collected through questionnaires revealed: (1) Participants reported a medium to high level of foreign language enjoyment (FLE), foreign language classroom anxiety (FLCA), and behavioral engagement; females had a higher level of FLE and behavioral engagement than males; the participants reported more anxiety and less enjoyment than western samples; (2) significant correlations were found between FLE, FLCA, behavioral engagement, and self-reported achievement; (3) significant mediating effects of behavioral engagement were found between both achievement emotions and self-reported achievement, and the mediating effect of engagement was stronger between FLCA and self-reported achievement. The findings extended the nomological network of achievement emotions, developed our insights into the complex relationships between emotions, learner engagement and language achievement, and revealed the mediating effects of behavioral engagement. Finally, directions for future study and implications for foreign language educators were provided.