Miracle-dz/UniFAR-FTUs huggingface dataset:
A convolutional neural network approach for visual recognition in wheel production lines

China has been the world’s largest automotive manufacturing country since 2008. The automotive wheel industry in China has been growing steadily in pace with the automobile industry. Visual recognition system that automatically classifies wheel types is a key component in the wheel production line. Traditional recognition methods are mainly based on extracted feature matching. Their accuracy, robustness, and processing speed are often compromised considerably in actual production. To overcome this problem, we proposed a convolutional neural network approach to adaptively classify wheel types in actual production lines with a complex visual background. The essential steps to achieve wheel identification include image acquisition, image preprocessing, and classification. The image differencing algorithm and histogram technique are developed on acquired wheel images to remove track disturbances. The wheel images after image processing were organized into training and test sets. This approach improved the residual network model ResNet-18 and then evaluated this model based on the wheel test data. Experiments showed that this method can obtain an accuracy over 98% on nearly 70,000 wheel images and its single image processing time can reach millisecond level.
Narrative Substrates: Reifying and Managing Emergent Narratives in Persistent Game Worlds

Players in modern Massively Multiplayer Online Role-Playing Games progress through ambitiously designed narratives, but have no real influence on the game, since only their characters’ data, not the game environment, persists. Although earlier games supported player influence by persisting changes in the world, they relied on players’ capacity to form their own stories and lacked guidance for character progression. We explore how persistence and narrative emergence let us build upon players’ influence rather than restrict it. We ran four studies and found that players highly value first-time and unique events, and often externalize their experiences to the Web to collaborate and socialize, but unintentionally also disrupt some aspects of in-game play. We introduce Narrative Substrates, a theoretical framework for designing game architectures that represent, manage, and persist traces of player activity as unique, interactive content. To illustrate and test the theory, we developed the game We Ride and deployed it as a two-phase technology probe over one year. We identify key benefits and challenges of our approach, and argue that reification of emergent narratives offers new design opportunities for creating truly interactive games.
Incremental 3-D pose graph optimization for SLAM algorithm without marginalization

Pose graph optimization algorithm is a classic nonconvex problem which is widely used in simultaneous localization and mapping algorithm. First, we investigate previous contributions and evaluate their performances using KITTI, Technische Universität München (TUM), and New College data sets. In practical scenario, pose graph optimization starts optimizing when loop closure happens. An estimated robot pose meets more than one loop closures; Schur complement is the common method to obtain sequential pose graph results. We put forward a new algorithm without managing complex Bayes factor graph and obtain more accurate pose graph result than state-of-art algorithms. In the proposed method, we transform the problem of estimating absolute poses to the problem of estimating relative poses. We name this incremental pose graph optimization algorithm as G-pose graph optimization algorithm. Another advantage of G-pose graph optimization algorithm is robust to outliers. We add loop closure metric to deal with outlier data. Previous experiments of pose graph optimization algorithm use simulated data, which do not conform to real world, to evaluate performances. We use KITTI, TUM, and New College data sets, which are obtained by real sensor in this study. Experimental results demonstrate that our proposed incremental pose graph algorithm model is stable and accurate in real-world scenario.
BOLeRo: Behavior optimization and learning for robots

Reinforcement learning and behavior optimization are becoming more and more popular in the field of robotics because algorithms are mature enough to tackle real problems in this domain. Robust implementations of state-of-the-art algorithms are often not publicly available though, and experiments are hardly reproducible because open-source implementations are often not available or are still in a stage of research code. Consequently, often it is infeasible to deploy these algorithms on robotic systems. BOLeRo closes this gap for policy search and evolutionary algorithms by delivering open-source implementations of behavior learning algorithms for robots. It is easy to integrate in robotic middlewares and it can be used to compare methods and develop prototypes in simulation.
Synergistic Effect of Resveratrol with 5-Fluorouracil in Chemotherapy of Induced Oral Squamous Cell Carcinoma

Aim: To evaluate the anticancer effect of resveratrol alone or combined with 5-Fu on experimentally- induced tongue cancer in rats. Methodology: Forty male albino rats were divided into five groups: Group I: untreated (negative control), group II: positive-control, receiving 50 ppm 4-NQO in drinking water, group III: received i.p injection of (5-FU), group IV: oral-administration of resveratrol (RV), and group V: receiving both RV and 5-FU. Before euthanasia, blood samples were withdrawn to evaluate serum level of ALT, AST and creatinine. After euthanasia, the tongues were surgically excised, and processed for H&E, and mutant p53 IHC. The mean of positive cells/group were statistically analyzed. Results: Group I showed normal tongue mucosa with negative immune expression of mutant p53 cells. Group II revealed malignant ulcers in a form of well/moderately differentiated SCC, and the highest mean of mutant p53 immuno-expression. Group III showed mild dysplasia of the tongue epithelium with a significant regression of the mean number of mutant p53 positive-cells. Group IV expressed moderate dysplasia, with a significantly high mean of mutant p53. Group V showed mild dysplasia with comparable mean of mutated p53 positive cells. Regarding toxicity, group II showed the maximum elevation of ALT, AST, and serum creatinine. These levels were decreased significantly in the treated groups, but high compared to Group I. Conclusion: Resveratrol has a promising therapeutic effect against 4NQO- induced tongue cancer as 5-FU alone. Also, it diminished the cytotoxic effect of 5-FU and enhanced normal histologic-appearance of tongue mucosa when used in combination.
Lygus hesperus (Heteroptera: Miridae) Oviposition Behavior, Growth, and Survival in Relation to Cotton Trichome Density

One near-isogenic and two isogenic ‘Texas Marker-1’ (TM-1) cotton, Gossypium hirsutum L. , breeder lines differing in alleles for trichome density affected ovipositional behavior and nymphal growth weight of Lygus hesperus Knight. Femalesoviposited 28 and 31% fewer eggs on the normally hirsute and Smooth leaf lines, respectively, than the Pilose line. The leaf petiole was the most preferred oviposition site, with more than 49% of the eggs deposited there on the three lines. The Pilose isoline reduced nymphal weight by 37% compared with the Smooth leaf isoline. Differences in number of eggs laid, nymphal emergence, growth, and survival were not significantly different between the Smooth leaf and normally hirsute lines. Trichome density of 33 cotton genotypes was positively correlated with nymphal emergence. A regression equation was derived to predict nymphs per female based on trichome density
Determinants of Maintaining a Daily Yoga Practice: Health Locus of Control and Self-determination Theory Perspective

Background: Despite the growing evidence of the health benefits of a yoga practice, little is known about the factors that contribute to its sustained practice. Aims: The objectives of the present study were twofold: (1) to describe the personal characteristics (age, education level, and marital status) and yoga asana-related behavior of participants who practice Ashtanga and (2) to examine the health locus of control (HLOC) (an individual's beliefs about the extent of control that they have over things that happen to them) and self-determination theories. (People are able to become self-determined when their needs for competence, connection, and autonomy are fulfilled in relation to the motivated behavior.) Methods: Ashtanga yoga practitioners (n = 100, age range: 20–62 years) reported practicing yoga at least once a week completed self-report questionnaires: demographics, asana practice, the Perceived Choice and Awareness of Self Scale, HLOC, the General Health Questionnaire-12, the Perceived Stress Scale, and the State-Trait Anxiety Inventory. Results: It was observed that participants practiced yoga for an average 6.43 years, 5 days a week for 93 min representing a sustained, motivated health-related behavior. Years of practice and percentage of time spent in home practice explain 9% of the variance in the awareness of self, and 7% is explained by the number of practice days a week and state anxiety. Ashtanga yoga practitioners have a high internal HLOC; this is related to reduced trait anxiety and increased perceived choice. Conclusions: The Mysore system of yoga appears to facilitate sustained health-related behavior; it is suggested that health promotion should acknowledge the three aspects of self-determination theory: competence, autonomy, and relatedness, while focusing on the increasing intrinsic motivation and internalizing HLOC.
Improving Consumer Assessment of Health Care Providers and Systems Communication Scores in Hospice Care

Although patient satisfaction scores have been used in the inpatient setting for more than a decade, they are new to the hospice and home care setting. Hospice organizations began tracking Consumer Assessment of Healthcare Providers & Systems (CAHPS) scores in 2017, and beginning in 2019, the scores became accessible by the public. The purpose of this quality improvement project was to determine whether improved communication techniques had a positive effect on CAHPS scores at an outpatient nonprofit hospice organization. The intervention was divided into 2 parts, improving communication among staff and improving education provided to patients and their caregivers. This pilot project was implemented over a 4-month period, and the CAHPS scores were compared with those from the 4 months before preceding implementation.
Nutritional Assessment in the Critically Ill Patients

Background: Malnutrition is a prevalent complication among critically ill patients. It has very detrimental effects on the patients' clinical course. This study aimed to investigate the impact of nutrition in the intensive care unit (ICU) patients. Methods: In this epidemiologic-analytic study conducted in the surgical ICU of Imam Khomeini hospital, Ahvaz, Iran, 34 patients were selected and divided into two groups. The first group of patients received the appropriate nutrition. The second group received an inappropriate diet, and the nutritional risk was evaluated according to the modifiedNutrition Risk in Critically ill (m-NUTRIC) score. The energy was calculated by using 25 Kcal/kg, also the two groups were compared in terms of ICU mortality, ICU stays, Acute Physiologic Assessment and Chronic Health Evaluation (APACHE) II Scoring, and the Sequential Organ Failure Assessment (SOFA) Score. Results: Baseline data, such as APACHE II score and mean age, except sex, were not significantly different between the two groups. In this study, results were toward shorter ICU stay, less mortality, and better SOFA score in the group receiving appropriate nutrition compared to the other group. However, due to the low number of patients, no significant differences were observed in the two groups. Conclusion: Our data suggest that nutritional support should be considered as an essential part of the medication during critical illness.
Privacy Analysis of uery-Set-Size Control

The publication of user data for statistical analysis and research can be extremely beneicial for both academic and commercial uses, such as statistical research and recommendation systems. To maintain user privacy when such a publication occurs many databases employ anonymization techniques, either on the query results or the data itself. In this paper we examine and analyze the privacy ofered when using the query-set-size control method for aggregate queries over a data structures representing various topologies. We focus on the mathematical queries of minimum, maximum, median and average, and show some query types which may be used to extract hidden information. We prove some combinations of these queries will maintain a measurable level of privacy even when using multiple queries. We ofer a privacy probability measure, indicating the probability of an attacker to obtain information deined as sensitive by utilizing legitimate queries over such a system. Our results are mathematically proven and backed by simulations using vehicular network data based on the TAPASCologne project.
Systemic change, open data ecosystem performance improvements, and empirical insights from Estonia: A country-level action research study

The purpose of this paper is to provide an overview of how Estonia used action research and systems theory to improve the performance their Open Government Data (OGD) ecosystem. This paper understands performance of OGD ecosystems of as consisting of three parts: 1) OGD supply, 2) OGD usage, 3) communication, interaction, and linkages between OGD suppliers and users. It was believed that by taking a holistic approach, encouraging transparency and co-creation, and manipulating feedback loops it was possible to improve the performance of the ecosystem. The research uses and validates previous research on open government data ecosystems and by doing so also achieved increased levels of performance in Estonia’s OGD ecosystem. The paper’s main contributions are the creation of a framework based on systems theory, systems thinking, and action research for enacting strategic change in OGD ecosystems, conceptualizing feedback loops as a core part of OGD ecosystems, and the conceptualization of performance in OGD ecosystems. The paper concludes by offering nine core insights related to OGD ecosystems and their performance.
The promise and challenges of multimodal learning analytics

Learning outcomes are the result of interactions between intraindividual factors, such as prior knowledge, emotions, and motivation; as well as the contextual factors in which the learning takes place (Dumas, McNeish, & Greene, 2020). If any, perhaps only a few Learning Analytics (LA) researchers and practitioners would disagree with this shared understanding about learning among the modern learning scientists. After all, as stated in the definition of the field, LA aims to understand and optimise learning and the environments in which learning occurs through the measurement, collection, analysis and reporting of data about learners and their contexts. However, most LA research and practice today relies upon logged data from digital platforms, which oftentimes fall short to help us accurately and timely interpret and account for factors influencing learning. This is particularly the case for factors influencing the contexts in which learners perform and the intraindividual factors that are regularly categorised in the affective domain. Recently, Multimodal Learning Analytics (MMLA) provided promising results to make progress in this space to help us better understand, model, and support learning in situ. However, MMLA also poses significant methodological, practical, and ethical challenges. We are aware that MMLA research and practice can lead to significant concerns among educational stakeholders particularly with regards to the invasion of their privacy; bias, fairness, accountability and transparency of the MMLA models; as well as the risk of enabling a “surveillance” culture through constant monitoring of learner behaviours. In an attempt to raise awareness to some of these issues as well as providing some ways forward, we proposed this special issue on the promise and challenges of MMLA.
Omnivory dampens trophic cascades in estuarine communities

Predators often have large effects on prey populations and entire communities, but the nature of top-down control in speciose food webs is often difficult to assess due to consumer interactions such as complementarity, predator interference, and omnivory. To assess how top and intermediate predators affect community structure, we used predator exclusion experiments designed to isolate predator effects at different trophic levels in a species-rich community. Using oyster Crassostrea virginica reefs as a model system, predators were excluded using meshcovered cages with openings of 1.0 cm2 (small mesh) to exclude all potential oyster predators, 5.0 cm2 (large mesh) to allow intermediate consumers but not large predators to access oyster reefs, and controls with complete predator access. Natural oyster settlement and survival were greatest in the small mesh cage when oysters were completely protected from consumers. Meanwhile, abundances of adult Panopeus herbstii, the Atlantic mud crab, an intermediate consumer and known oyster predator, were an order of magnitude greater in the large-mesh cage than in the other treatments. Oyster survival did not differ between the large-mesh cage and controls, suggesting that top predators such as blue crabs Callinectes sapidus and sheepshead Archosargus probatocephalus are likely consuming mud crabs (or inducing mud crabs to avoid controls) and con suming juvenile oysters on these oyster reefs. Top-down processes are known to be important on oyster reefs, but in this system, omnivory can overwhelm density-mediated cascading effects of top predators. We also found mud crabs to induce oysters to grow heavier shells and less soft tissue. Efforts to model the direct and indirect effects of predators on ecological communities will benefit from a more thorough understanding of the relative strength of omnivory on cascading effects of top predators.
Application Effects of Moringa Leaf Powder in Fish Feed

[Objective] Moringa is an underutilized tree species.Developing of Moringa could make up for the shortage of traditional protein feed source for its high yield and abundant nutrition.The possibility of Moringa leaf powder as one of the main protein sources was discussed. [Method] We used Moringa leaf powder(15%) complete formula feed to intake the feed made from wheat middlings(8.7%) and rapeseed meal(6.3%). [Result] To compare test group with control group,the average weight,final weight,and average weight gain of test group were increased obviously while feed coefficient was decreased obviously.However,viability of test group was slightly lower than control group. [Conclusion] The study can provide basic data for aquatic animal nutrition research and high-efficient,cheap artificial fish feed.
Phyto-pharmacological screenings of two Rubiaceae family plants

In the present study, the ethanol extracts of two plant species namely Hymenodictyon excelsum Roxb. Wall and Mussaenda corymbosa Roxb. from the Rubiaceae family were screened for their phytochemical and pharmacological activities. Phytochemical investigations revealed the presence of important chemical moieties such as alkaloids, glycosides, tannins, falvonoids, saponins, reducing sugars etc. Extracts of M. corymbosa (EMC) showed potent 1,1-diphenyl-1-picrylhydrazyl (DPPH) inhibition at 100 μg/ml. In the antimicrobial activity test by disc diffusion method, the extract of H. excelsum (EHE) showed poor antibacterial activity but good antifungal activity and it strongly inhibited the species, Trichophyton sp. Whereas, EMC at dose of 500 μg/disc showed strong inhibition against Bacillus subtilis, Bacillus megaterium, Salmonella typhi but it was inactive against the test fungi. EHE and EMC showed potent anti-inflammatory, membranstabilizing, analgesic, antipyretic, and moderate amylase inhibition activities. H. excelsum showed stronger central nervous system (CNS) depressing activity on Swiss mice compared to EMC. In conclusion, the plant species may be considered as a medicinal plant and therefore its folk use and further exploitation.
Positive Psychological Factors and Impairment in Rheumatic and Musculoskeletal Disease: Do Psychopathology and Sleep Quality Explain the Linkage?

Little is known about potential mechanisms of action linking protective positive psychological variables and functional disability in patients with rheumatic and musculoskeletal disease. The present study was undertaken to examine symptoms of psychopathology, including stress, depression, anxiety, and sleep quality, as serial mediators of the association between gratitude, self‐compassion, self‐forgiveness, and functional impairment.
The dynamics of plant-herbivore interactions and their implications for spatial expansion

This dissertation investigates the population dynamics and spread of the gypsy moth population, which is a forest pest that was accidentally released near Boston in 1869, and now occupies more than 1,000,000 square kilometers of the northeastern United States. A model of plant-herbivore interactions based on the nutrient recycling of the forest and the biological properties of the herbivore is constructed using a host-parasite model with density dependence acting before the parasite attack. The dynamical behavior of the host and parasite populations as a function of the growth rate of the plant and the damage done by the parasite is studied. Bistability and a crisis of a strange attractor suggest two control strategies: Reducing the population of herbivores under some threshold (this suggests control procedures to reduce the herbivore population by actions such as spraying pesticides) or increasing the growth rate of the plant leaves (this could occur naturally under highly favorable growing conditions but could also be supported by fertilizing the plants). A second part of this dissertation investigates the impact of monotone plant growth models in general plant-herbivore models on the dynamics of the plant-herbivore interaction. It is shown that all monotone growth models generate a unique interior equilibrium. Monotone growth models with a single nonzero equilibrium of the plant population lead to noise sensitive bursting which is identified as a dynamical mechanism for almost periodic outbreaks of the herbivore infestation. Monotone and non-monotone plant growth models are contrasted with respect to bistability and crises of chaotic attractors. A dynamical model generating bistability is used to study the behavior of the plant and herbivore populations in two identical coupled patches where one patch is infected with the herbivore and the other one is not. The influence of the bistable dynamics on the spread of the