Miracle-dz/UniFAR-FTUs huggingface dataset:
MR.CAP: Multi-Robot Joint Control and Planning for Object Transport

With the recent influx in demand for multi-robot systems throughout industry and academia, there is an increasing need for faster, robust, and generalizable path planning algorithms. Similarly, given the inherent connection between control algorithms and multi-robot path planners, there is in turn an increased demand for fast, efficient, and robust controllers. We propose a scalable joint path planning and control algorithm for multi-robot systems with constrained behaviours based on factor graph optimization. We demonstrate our algorithm on a series of hardware and simulated experiments. Our algorithm is consistently able to recover from disturbances and avoid obstacles while outperforming state-of-the-art methods in optimization time, path deviation, and inter-robot errors. See the code and supplementary video for experiments.
Analyzing Aspects of Gamification in the Manifestation of Gaming the System Behavior

In this article, we investigate the influence of variables related to gamification strategies promoted by an online learning environment on the “gaming the system” behavior presented by elementary school students in mathematics. To this end, we performed our research in four main stages: exploratory database analysis, database annotation, detector development, and analysis of the results. We developed a data-driven automatic detector involving the training of single and joint machine learning algorithms to classify “gaming the system” behavior and obtain models with the best accuracy, including exploring, evaluating, and comparing different algorithms. The detector's development involved training machine learning algorithms as a single category, including decision tree, K-NN, neural network, and Support Vector Machine and ensemble categories, such as Random Forest, Gradient Boosting Machine, Adaptive Boosting, and XGBoost. In addition, three human tutors annotated the database with log data of problem-solving from the math domain for elementary school students, who evaluated each student's problem-solving attempt in game and non-game classes. In total, 12,514071 rows of data were labeled in two rounds of labeling, with Cohen's Kappa of 0.82 for inter-rater reliability for differentiating between gaming and non-gaming behavior. Our findings suggest that gamification strategies used by online learning environments can provoke “gaming the system” behavior in elementary school students. At the same time, we provide evidence from the literature and exploratory data analysis that the incentive to seek performance over learning has motivated students to manifest non-learning behaviors. We hope these insights will contribute to improving the planning and development of a gamification strategy in an online learning environment.
Enhancing Safety and Dynamic Control in Hub Motor Electric Vehicles through ASC and PIR Current Control

Hub motor electric vehicles are a revolutionary technology that integrates electric motors into the wheel hubs, offering efficient power transmission and motion control. The increasing demand for hub motor electric vehicle performance has led to the development of fault tolerance and self-recovery technologies, particularly concerning safety. This paper addresses dynamic control issues and proposes a Proportional Integral-Resonance (PIR) closed-loop current controller for hub motors, specifically to suppress surge current after active short-circuit (ASC) engagement. The research demonstrates the effectiveness of the PIR control strategy in controlling surge current and improving vehicle stability during hub motor restarts. The simulation study showcases the benefits of PIR control over conventional PI control in terms of current tracking accuracy and dynamic response. The results indicate that PIR control significantly reduces signal amplitude errors, ensuring smoother operation and improved dynamic performance.
Characteristics and Driving Factors of Wastewater Emissions in Guangdong Province from 1990 to 2012——A Study based on STIRPAT Model and Decoupling Index

Based on wastewater emission and socio-economic statistical data in Guangdong province from1990 to 2012,the relationships among population,affluence,COD emissions intensity with wastewater emission were studied by ridge regression and STIRPAT model.The decoupling index was adopted to further analyze the relationship between GDP and wastewater emission.The results revealed that population was the major factor affecting wastewater emission in Guangdong.1% change in population,per capita GDP and COD emissions intensity would result in 0.648 1%,0.169 1%and 0.099 4%change in wastewater emission,respectively.The overall findings did not support the environment Kuznets curve hypothesis.The decoupling index was fluctuating,either in the state of relative decoupling or in re-coupling.In recent years,GDP and wastewater emission were at the stage of weak decoupling state overall.Industrial wastewater emissions were gradually under control,but owing to the rapid growth of domestic wastewater,the wastewater emissions would continue to rise in Guangdong province.
Acceptance and commitment therapy reduces psychological distress in patients with cancer: a systematic review and meta-analysis of randomized controlled trials

Objective This study aimed to systematically review and meta-analyze the clinical efficacy of acceptance and commitment therapy (ACT) in patients with cancer and psychological distress. Methods Randomized controlled trials (RCTs) from seven English electronic databases were systematically investigated from inception to 3 October 2023. A total of 16 RCTs from 6 countries with 711 participants were included in this study. Estimated pooled effect sizes (ESs) were calculated via inverse-variance random-effects or fixed-effects (I2 ≤ 50%) model and presented by standardized mean difference (SMD). Subgroup analyses were performed to reduce confounding factors and heterogeneity, and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system was used to evaluate the quality of the pooled ESs. Results The pooled ESs revealed that statistically significant improvements in anxiety [postintervention SMD = −0.41 (95% confidence interval (CI), −0.71, −0.11); p = 0.008; I2 = 65%; follow-up SMD = −0.37 (95% CI, −0.66, −0.08); p = 0.01; I2 = 29%], depression [postintervention SMD = −0.45 (95% CI, −0.63, −0.27); p < 0.001; I2 = 49%; follow-up SMD = −0.52 (95% CI, −0.77, −0.28); p < 0.001; I2 = 0%], and psychological flexibility [postintervention SMD = −0.81 (95% CI, −1.50, −0.11); p = 0.02; I2 = 84%; follow-up SMD = −0.71 (95% CI, −1.12, −0.31); p = 0.0006; I2 = 38%] in ACT-treated participants were observed compared to patients treated with control conditions. However, other outcomes, such as physical symptom alleviation, were not significantly associated. Conclusion The findings of this systematic review and meta-analysis suggest that ACT is associated with improvements in anxiety, depression, and psychological flexibility in patients with cancer. Systematic review registration https://www.crd. york.ac. uk/prospero/display_record. php? ID=CRD42022320515.
Clinical reasoning for the continuation or discontinuation of hip precautions after total hip arthroplasty in Switzerland: a qualitative study

BACKGROUND: Growing evidence raises doubts about the need for routine hip precautions after primary total hip replacements to reduce the risk of postoperative dislocation. However, hip precautions are still routinely and widely prescribed in postoperative care in Switzerland. We aimed to investigate experts’ clinical reasoning for hip precaution recommendations after total hip arthroplasty. METHODS: Using a convenience sampling strategy, 14 semi-structured expert interviews were conducted with surgeons, physiotherapists, and occupational therapists in the vicinity of an inpatient rehabilitation clinic in Switzerland. Data analysis followed Mayring’s principle of inductive and deductive structuring content analysis. RESULTS: Expert statements from the interviews were summarised into four main categories and 10 subcategories. Categories included statements on the incidences of dislocation and underlying risk factors; current preferences and use of hip precautions; their effect on physical function, anxiety, or costs; and patient’s adherence to the movement restrictions. Hip surgeons routinely prescribed hip precautions, although in different variations. Fear of dislocation and caution are barriers to changing current practice. Some surgeons are considering individualised prescribing based on patients’ risk of dislocation, which therapists would welcome. CONCLUSION: A lack of clear instructions from the surgeon leads to ambiguity among therapists outside the acute hospital. A shared understanding of the need for and nature of hip precautions, guidelines from societies, or at least specific instructions from surgeons to therapists are warranted.
Pure Epigallocatechin-3-gallate-Assisted Green Synthesis of Highly Stable Titanium Dioxide Nanoparticles

Nanoparticles (NPs) are conventionally produced by using physical and chemical methods that are no longer in alignment with current society’s demand for a low environmental impact. Accordingly, green synthesis approaches are considered a potential alternative due to the plant extracts that substitute some of the hazardous reagents. The general mechanism is based on the reducing power of natural products that allows the formation of NPs from a precursor solution. In this context, our study proposes a simple, innovative, and reproducible green approach for the synthesis of titanium dioxide (TiO2 NPs) that uses, for the first time, the major component of green tea (Camellia sinensis)—epigallocatechin-3-gallate (EGCG), a non-toxic, dietary, accessible, and bioactive molecule. The influence of EGCG on the formation of TiO2 NPs was analyzed by comparing the physicochemical characteristics of green synthesized NPs with the chemically obtained ones. The synthesis of bare TiO2 NPs was performed by hydrolysis of titanium isopropoxide in distilled water, and green TiO2 NPs were obtained in the same conditions, but in the presence of a 1 mM EGCG aqueous solution. The formation of TiO2 NPs was confirmed by UV-VIS and FTIR spectroscopy. SEM micrographs showed spherical particles with relatively low diameters. Our findings also revealed that green synthesized NPs were more stable in colloids than the chemically synthesized ones. However, the phytocompound negatively influenced the formation of a crystalline structure in the green synthesized TiO2 NPs. Furthermore, the synthesis of EGCG–TiO2 NPs could become a versatile choice for applications extending beyond photocatalysis, including promising prospects in the biomedical field.
Protein-lipid interactions and protein anchoring modulate the modes of association of the globular domain of the Prion protein and Doppel protein to model membrane patches

The Prion protein is the molecular hallmark of the incurable prion diseases affecting mammals, including humans. The protein-only hypothesis states that the misfolding, accumulation, and deposition of the Prion protein play a critical role in toxicity. The cellular Prion protein (PrPC) anchors to the extracellular leaflet of the plasma membrane and prefers cholesterol- and sphingomyelin-rich membrane domains. Conformational Prion protein conversion into the pathological isoform happens on the cell surface. In vitro and in vivo experiments indicate that Prion protein misfolding, aggregation, and toxicity are sensitive to the lipid composition of plasma membranes and vesicles. A picture of the underlying biophysical driving forces that explain the effect of Prion protein - lipid interactions in physiological conditions is needed to develop a structural model of Prion protein conformational conversion. To this end, we use molecular dynamics simulations that mimic the interactions between the globular domain of PrPC anchored to model membrane patches. In addition, we also simulate the Doppel protein anchored to such membrane patches. The Doppel protein is the closest in the phylogenetic tree to PrPC, localizes in an extracellular milieu similar to that of PrPC, and exhibits a similar topology to PrPC even if the amino acid sequence is only 25% identical. Our simulations show that specific protein-lipid interactions and conformational constraints imposed by GPI anchoring together favor specific binding sites in globular PrPC but not in Doppel. Interestingly, the binding sites we found in PrPC correspond to prion protein loops, which are critical in aggregation and prion disease transmission barrier (β2-α2 loop) and in initial spontaneous misfolding (α2-α3 loop). We also found that the membrane re-arranges locally to accommodate protein residues inserted in the membrane surface as a response to protein binding.
Formaldehyde-Free Wood Composite Fabricated Using Oil Palm Starch Modified with Glutardialdehyde as the Binder

Oil palm trunk is a kind of biomass rich in starch content. Oil palm trunk waste was available throughout the year in Malaysia and Indonesia due to continuous felling of nonproductive, over 25-year-old trees. Even though some manufacturers were using it in plywood and veneer production, they are hard to handle which later becomes less favorable raw materials due to a high moisture content where combination with a high starch content quickly attracts fungus and wood-decaying agents. The objective of this work was to evaluate properties of experimental wood composite panels, manufactured using oil palm-extracted starch modified with glutardialdehyde (OPSMG) as a binder. Different analyses were employed to characterize the properties of the samples besides evaluation of bending, internal bonding strength, and dimensional stability of the panels. Characterization on the functional group using the FT-IR analysis showed presence of aldehyde groups and ketone stretching vibrations at 1736.05 cm−1 and 1596.25 cm−1, which proves the presence of glutardialdehyde besides formation of bonding between the OPSMG and the woody materials. The XRD analysis showed the starch modification had lowered the crystallinity index which in turn increased the strength of the manufactured wood composites. The OPSMG wood composites were also found to have lower thermal stability, as evaluated using the TGA analysis. It was recorded that the maximum modulus of rupture for OPSMG wood composites was achieved at the 0.80 g/cm3 density level with an average value of 15.446 N/mm2 which showed 38.00% increment in strength between those two types of wood composites. Thickness swelling after immersion in water can still be improved by incorporating the moisture-repellent material later. After analyzing the results, it was concluded that modified oil palm starch has the potential to be used as an environment friendly binder for wood composite making.
Predicting Students' Software Engineering Class Performance with Machine Learning and Pre-Class GitHub Metrics

Research into predicting students' performance in computer science classes has been conducted globally for over five decades. Numerous metrics, including performance in prior courses, demographic information, and programming experience, have been used to predict success in computer science. Various analytical methods, such as linear regression, decision trees, ensemble methods, and even neural networks, have also been explored. In this study, we investigate whether pre-class GitHub contribution metrics, combined with machine learning techniques, can forecast student performance in a software engineering class. We address two research questions in this paper. Firstly, can pre-class GitHub contribution metrics predict students' performance? Secondly, which machine learning technique is most effective in predicting student performance? We collected data from 802 students over five years and 11 semesters, including pre-class GitHub contribution stats, students' exam grades, project grades, documentation grades, and review writing grades. Eight different machine learning methods were then tested to predict in-class performance using pre-class GitHub contributions. Our results indicate that exam performance can be relatively accurately predicted by machine learning methods. Ensemble methods such as Random Forest, AdaBoost, and XGBoost performed better than other methods. This suggests that pre-class GitHub contribution metrics can be a useful tool for predicting students' performance in software engineering classes, carrying significant implications for educators. This approach can help educators identify at-risk students at the earliest point in the class, enabling early intervention strategies to prevent failure. Our study uniquely utilizes pre-class GitHub contributions, providing a preliminary indication of a student's familiarity with the course material. While prior research has focused on using in-class data to predict student performance, our approach identifies struggling students from the very beginning. We believe this can provide the most beneficial support for students.
Linking Relationship Marketing to Customer Loyalty in The E-Banking Context: The Central Role of Customer Satisfaction

This research examines the interrelationships between relationship marketing, customer satisfaction and customer loyalty in e-banking’s context. The study was conducted in two phases: In-depth interviews and a quantitative survey with a sample of 690 Vietnamese individual and corporate e-banking customers. The research results show that customer satisfaction mediates the impact of relationship marketing on customer loyalty among individual customers. Meanwhile, instead of customer satisfaction, relationship marketing significantly and directly contributes to the loyalty of the corporate customer group. The significance and magnitude of the effects that the five dimensions of relationship marketing’s effectiveness have on customer satisfaction and loyalty, which include the banks’ commitment, customer experience, process-driven approach, service reliability and application of technology, are also different between the two customer segments. This study theoretically contributes to the research stream regarding the mechanism underlying the relationship between relationship marketing’s effectiveness and customer loyalty in the e-banking context, and proposes practical implications for commercial banks to effectively apply relationship marketing in the virtual business environment.
Persistence Priorities and Financial Servingness in an Emerging HSI

As the demographics in the United States' college going population continues to shift, the number of HSIs grows annually, yet research in higher education indicates a difference between enrolling Hispanic students in great numbers and serving the Hispanic/LatinX population [1], [2] Servingness is embodied in structures and practices that constitute HSIs, and is manifested in the acts of institutional agents who interpret policy, advocate for students, and access resources on behalf of students. This paper describes the findings from an initial case study of a public US east coast Emerging Hispanic Serving Institution recently funded by the National Science Foundation to provide scholarships for high-achieving students with great financial need. In an effort to understand financial barriers students face in attending college in a post-pandemic context, the first author interviewed key stakeholders at EAST STEM University. The research question driving the study was: How is EAST STEM changing its infrastructure to develop diverse support structures that serve students? Data for this pilot case study were collected from unstructured interviews with the lead faculty member of the grant in the computer science department, document analysis of institutional data (e.g., contextual data from the US Department of Education, publicly available information from Excellencia in Education, institutional profile data from the Institute of Educational Statistics), and from formal interviews with key stakeholders across the university. Interviews were transcribed and coded using emerging themes with Dedoose software. The staff interviewed in this study span five administrative offices and academic departments. Findings from this case suggest the institutional goals of promoting diversity and increasing persistence were values that aligned with the acts of servingness utilized at East STEM University to advocate holistically for student needs [3]. Interviews with institutional agents indicate two ways the institution supported student progression through the major-through human resource allocation and through financial prioritization for equity. Within this institutional context, institutional agents enacted servingness through their emphasis on equity and persistence priorities, with, in some cases, a critical lens supportive of student success[4]. Key to their efforts in promoting persistence for students were three actions-creating space for one-on-one engagement with students, advocating on students' behalf across multiple administrative offices, and adapting and reinterpreting policies to support continued student enrollment. This study illustrates how institutional agents aligned serving with a key institutional initiative, and shows how that alignment created space for innovation in meeting undergraduate students' financial needs.
Reducing Challenges in Design Thinking Adoption Using Intrapreneurship and a Learning Environment

Design thinking (DT) is increasingly used to develop solutions that identify users' real needs. However, resistance to adopting DT and a lack of knowledge about the tools and activities of this approach are significant challenges in its implementation. Thus, organizations need to create strategies that minimize these challenges. This paper explores an approach focused on intrapreneurship to motivate employees to develop new business ideas combined with a learning environment for exchanging knowledge as a mechanism to overcome resistance to the adoption of DT. In this sense, the research problem addressed here is the lack of strategies to minimize resistance and the lack of knowledge for adopting DT in software organizations. This work was conducted using action research in a Brazilian software development organization. Initially, a call for proposals for new software-based business ideas was launched at the organization. Then, the DT was applied to develop the proposed ideas. In parallel, a learning environment was created to train employees in DT and its tools. A feedback questionnaire and a retrospective meeting were held with the organization's employees to evaluate the action research. Our results suggest that an intrapreneurship approach and the learning environment proved to be effective within the context studied and managed to reduce resistance to the adoption of DT. Received: 13 September 2023 / Accepted: 22 December 2023 / Published: 5 January 2024