Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimum Velocity Profile of Multiple Bernstein-Bézier Curves Subject to Constraints for Mobile Robots

This article deals with trajectory planning that is suitable for nonholonomic differentially driven wheeled mobile robots. The path is approximated with a spline that consists of multiple Bernstein-Bézier curves that are merged together in a way that continuous curvature of the spline is achieved. The article presents the approach for optimization of velocity profile of Bernstein-Bézier spline subject to velocity and acceleration constraints. For the purpose of optimization, velocity and turning points are introduced. Based on these singularity points, local segments are defined where local velocity profiles are optimized independently of each other. From the locally optimum velocity profiles, the global optimum velocity profile is determined. Since each local velocity profile can be evaluated independently, the algorithm is suitable for concurrent implementation and modification of one part of the curve does not require recalculation of all local velocity profiles. These properties enable efficient implementation of the optimization algorithm. The optimization algorithm is also suitable for the splines that consist of Bernstein-Bézier curves that have substantially different lengths. The proposed optimization approach was experimentally evaluated and validated in simulation environment and on real mobile robots.
Revisiting Singing Voice Detection: A quantitative review and the future outlook

Since the vocal component plays a crucial role in popular music, singing voice detection has been an active research topic in music information retrieval. Although several proposed algorithms have shown high performances, we argue that there still is a room to improve to build a more robust singing voice detection system. In order to identify the area of improvement, we first perform an error analysis on three recent singing voice detection systems. Based on the analysis, we design novel methods to test the systems on multiple sets of internally curated and generated data to further examine the pitfalls, which are not clearly revealed with the current datasets. From the experiment results, we also propose several directions towards building a more robust singing voice detector.
An Exploratory Assessment of Community-Oriented Policing Implementation, Social Disorganization and Crime in America

Prior research has examined the impact of community-oriented policing (COP) on crime extensively. While the implementation of community policing has been considered mainly within the context of large police agencies, there is a paucity of research on how COP impacts crime reduction efforts in smaller locales. This study explores the effects of the degree of community policing implementation within smaller agencies and cities on crime. As part of the discussion on the impact of COP implementation, this paper also considers the impact of social disorganization on crime in the United States. The aim is to gain further insight into what variables may be influencing crime rates in contexts that garner less attention from researchers. The findings indicate that COP implementation does not significantly explain the variation of crime rates. Still, the statistically significant results on several social disorganization factors reflect the need to incorporate social disorganization theory with practice in order to maximize community-policing success. The implications of these results for police practice as well as directions for future research are discussed.
Voice Imitating Text-to-Speech Neural Networks

We propose a neural text-to-speech (TTS) model that can imitate a new speaker's voice using only a small amount of speech sample. We demonstrate voice imitation using only a 6-seconds long speech sample without any other information such as transcripts. Our model also enables voice imitation instantly without additional training of the model. We implemented the voice imitating TTS model by combining a speaker embedder network with a state-of-the-art TTS model, Tacotron. The speaker embedder network takes a new speaker's speech sample and returns a speaker embedding. The speaker embedding with a target sentence are fed to Tacotron, and speech is generated with the new speaker's voice. We show that the speaker embeddings extracted by the speaker embedder network can represent the latent structure in different voices. The generated speech samples from our model have comparable voice quality to the ones from existing multi-speaker TTS models.
Inferring Extended Probabilistic Finite-State Automaton Models from Software Executions

Behavioral models are useful tools in understanding how programs work. Although several inference approaches have been introduced to generate extended finite-state automatons from software execution traces, they suffer from accuracy, flexibility, and decidability issues. In this article, we apply a hybrid technique to use both reinforcement learning and stochastic modeling to generate an extended probabilistic finite state automaton from software traces. Our approach—ReHMM (Reinforcement learning-based Hidden Markov Modelling)—is able to address the problems of inflexibility and un-decidability reported in other state-of-the-art approaches. Experimental results indicate that ReHMM outperforms other inference algorithms.
Unpacking the Associations Among Maltreatment, Disengagement Coping, and Behavioral Functioning in High-Risk Youth

Given the association between child maltreatment and a host of negative behavioral consequences, there remains a need to continue to identify mechanisms underlying this association as a means of improving intervention efforts. The present study examined one potential mechanism, namely, disengagement coping. We asked 6- to 17-year-old maltreated (n = 249) and comparison (n = 133) youth questions about emotional experiences that induced sadness and anger, strategies they used to cope with those emotions, and behavioral functioning (i.e., behavioral problems and aggression). Maltreated adolescents reported higher levels of behavioral problems and aggression relative to comparison adolescents, and adolescents who disengaged from emotional situations reported more behavioral problems relative to those who did not disengage. Tests of mediation suggested that, for adolescent-age youth, part of the association between maltreatment status and behavioral problems was explained by disengagement. In children, maltreatment was not associated with disengagement or behavioral problems. Results have implications for understanding age-related differences in the emotional and behavioral consequences of maltreatment.
A new species of Melita from Japan (Crustacea, Amphipoda, Melitidae)

Abstract A new brackish-water species of melitid amphipod, Melita choshigawaensis, from the Choshigawa River, Mie Prefecture, Japan, is named and described. Melita choshigawaensis sp. n. is distinguished from the most similar M. shimizui (Uéno, 1940) by having an elongate and weakly arched male uropod 3, and a deep and strongly hooked anterior lobe of the coxa on the female’s pereopod 6. Nucleotide sequences of the mitochondrial cytochrome c oxidase subunit I (COI) of M. choshigawaensis and M. shimizui support divergence at the species level. A key to the Japanese species of Melita is provided.
HLA genetics in bipolar disorder

Bipolar Disorder (BD) is characterized by deregulated adaptive immune processes. Recent genome‐wide association studies (GWAS) implicate the major histocompatibility complex (MHC) region in BD. The present study investigates the potential influence of variations in human leukocyte antigen (HLA) on BD risk and/or clinical presentations. This may have relevance to the dysregulated inflammatory processes commonly found in BD.
Incorporation of rosuvastatin-loaded chitosan/chondroitin sulfate nanoparticles into a thermosensitive hydrogel for bone tissue engineering: preparation, characterization, and cellular behavior

Abstract Rosuvastatin (RSV) has been shown to have significant impact on the simulation of bone regeneration after local injection. The current study aimed to develop a localized controlled delivery system from RSV by incorporating RSV-loaded chitosan/chondroitin sulfate (CTS/CS) nanoparticles into thermosensitive Pluronic F127/hyaluronic acid (PF127/HA) hydrogel. RSV-loaded CTS/CS nanoparticles were prepared by ionic gelation, and the impact of various formulation variables was assessed using the Box–Behnken design. Consequently, optimized RSV-loaded nanoparticles were incorporated into the PF127/HA hydrogel. Rheological properties, degradation rates of hydrogels, and the release rate of RSV from hydrogel were examined. Mean particle size, zeta potential, entrapment efficiency, and mean release time of the optimized RSV-loaded nanoparticles were confirmed as 283.2 ± 16 nm, –31.2 ± 6.8 mV, 63.1 ± 4.2%, and 6.14 ± 0.3 h, respectively. The hydrogel containing 3% w/v CTS/CS nanoparticles existed as a solution with low viscosity at room temperature converted to a semisolid upon increasing the temperature to 35 °C. Hydrogel engrafted with CTS/CS showed controlled release of RSV during 48 h with superior in vitro gel stability. As revealed by cytotoxicity and mineralization assays, incorporation of RSV-loaded particles into PF127/HA hydrogel led to improvement in osteoblast viability and proliferation.
Predicting long‐term ischemic events using routine clinical parameters in patients with coronary artery disease: The OPT‐CAD risk score

BACKGROUND The prognosis of patients with coronary artery disease (CAD) at hospital discharge was constantly varying, and postdischarge risk of ischemic events remain a concern. However, risk prediction tools to identify risk of ischemia for these patients has not yet been reported. AIMS We sought to develop a scoring system for predicting long-term ischemic events in CAD patients receiving antiplatelet therapy that would be beneficial in appropriate personalized decision-making for these patients. METHODS In this prospective Optimal antiPlatelet Therapy for Chinese patients with Coronary Artery Disease (OPT-CAD, NCT01735305) registry, a total of 14 032 patients with CAD receiving at least one kind of antiplatelet agent were enrolled from 107 centers across China, from January 2012 to March 2014. The risk scoring system was developed in a derivation cohort (enrolled initially 10 000 patients in the database) using a logistic regression model and was subsequently tested in a validation cohort (the last 4032 patients). Points in risk score were assigned based on the multivariable odds ratio of each factor. Ischemic events were defined as the composite of cardiac death, myocardial infarction or stroke. RESULTS Ischemic events occurred in 342 (3.4%) patients in the derivation cohort and 160 (4.0%) patients in the validation cohort during 1-year follow-up. The OPT-CAD score, ranging from 0-257 points, consist of 10 independent risk factors, including age (0-71 points), heart rates (0-36 points), hypertension (0-20 points), prior myocardial infarction (16 points), prior stroke (16 points), renal insufficient (21 points), anemia (19 points), low ejection fraction (22 points), positive cardiac troponin (23 points) and ST-segment deviation (13 points). In predicting 1-year ischemic events, the area under receiver operating characteristics curve were 0.73 and 0.72 in derivation and validation cohort, respectively. The incidences of ischemic events in low- (0-90 points), medium- (91-150 points) and high-risk (≥151 points) patients were 1.6%, 5.5%, and 15.0%, respectively. Compared to GRACE score, OPT-CAD score had a better discrimination in predicting ischemic events and all-cause mortality (ischemic events: 0.72 vs 0.65, all-cause mortality: 0.79 vs 0.72, both P < .001). CONCLUSIONS Among CAD patients, a risk score based on 10 baseline clinical variables performed better than the GRACE risk score in predicting long-term ischemic events. However, further research is needed to assess the value of the OPT-CAD score in guiding the management of antiplatelet therapy for patients with CAD.
Position and velocity measurement method from a single image using modulated illumination

Visual feedback systems utilize position and velocity information estimated from frames captured by a camera. Since the velocity information is derrived through pseudo differential with two consecutive frames, the information must be delayed essentially, and the delay often limits the performance of visual feedback systems. To eliminate the delay, this paper proposed a novel technique to estimate position and velocity information from a single image. By detecting the start and end points of the motion blur of a target object in an image, the velocity information during the exposure time of the image can be estimated fundamentally. To tag such a temporal information on motion blurs, a modulated illumination was employed. This tagging method aimed to make motion blur detection robust against various background scenery. Some simulation results validated the feasibility of the proposed method.
Recent Advances and Opportunities in Scene Classification of Aerial Images with Deep Models

Scene classification is a fundamental task in interpretation of remote sensing images, and has become an active research topic in remote sensing community due to its important role in a wide range of applications. Over the past years, tremendous efforts have been made for developing powerful approaches for scene classification of remote sensing images, evolving from the traditional bag-of-visual-words model to the new generation deep convolutional neural networks (CNNs). The deep CNN based methods have exhibited remarkable breakthrough on performance, dramatically outperforming previous methods which strongly rely on hand-crafted features. However, performance with deep CNNs has gradually plateaued on existing public scene datasets, due to the notable drawbacks of these datasets, such as the small scale and low-diversity of training samples. Therefore, to promote the development of new methods and move the scene classification task a step further, we deeply discuss the existing problems in scene classification task, and accordingly present three open directions. We believe these potential directions will be instructive for the researchers in this field.
Ultrastructural localization of RNA in the chromatoid bodies of undifferentiated cells (neoblasts) in planarians by the RNase–gold complex technique

Undifferentiated cells of planarians (Platyhelminthes, Turbellaria), also called neoblasts, are totipotent stem cells, which give rise to all differentiated cell types, while maintaining their own density by cell proliferation. Neoblasts are the only somatic cells of planarians bearing chromatoid bodies in their cytoplasm; these organelles disappear as differentiation takes place. Studies on germinal cells of several groups of organisms have shown that chromatoid bodies contain substantial amounts of RNA. To test its presence in neoblasts, we have used an RNase–gold technique. We found chromatoid bodies labeled with RNase–gold particles. Heterogeneity in the density of the label, may be correlated with the functionality and complexity of these organelles. The gold marker was also present over the nucleus and rough endoplasmic reticulum, but mitochondria, secretory granules, and the extracellular space were devoid of label. This specific localization of RNA in planarian chromatoid bodies supports earlier findings on germ cells and embryonic cells in a variety of organisms, indicating that chromatoid bodies are information‐storage structures, essential during the process of cell differentiation. © 1993 Wiley‐Liss, Inc.
Draining the Data Swamp: A Similarity-based Approach

While hierarchical namespaces such as filesystems and repositories have long been used to organize data, the rapid increase in data production places increasing strain on users who wish to make use of the data. So called "data lakes" embrace the storage of data in its natural form, integrating and organizing in a Pay-as-you-go fashion. While this model defers the upfront cost of integration, the result is that data is unusable for discovery or analysis until it is processed. Thus, data scientists are forced to spend significant time and energy on mundane tasks such as data discovery, cleaning, integration, and management -- when this is neglected, "data lakes" become "data swamps. " Prior work suggests that pure computational methods for resolving issues with the data discovery and management components are insufficient. Here, we provide evidence to confirm this hypothesis, showing that methods such as automated file clustering are unable to extract the necessary features from repositories to provide useful information to end-user data scientists, or make effective data management decisions on their behalf. We argue that the combination of frameworks for specifying file similarity and human-in-the-loop interaction is needed to aid automated organization. We propose an initial step here, classifying several dimensions by which items may be considered similar: the data, its origin, and its current characteristics. We initially consider this model in the context of identifying data that can be integrated or managed collectively. We additionally explore how current methods can be used to automate decision making using real-world data repository and file systems, and suggest how an online user study could be developed to further validate this hypothesis.
Factors associated with poor satisfaction with treatment and trial discontinuation in chronic schizophrenia

Introduction Despite consistently high discontinuation rates due to withdrawal of consent (WOC) and insufficient therapeutic effect (ITE) in schizophrenia trials, insight into the underlying factors contributing to poor satisfaction with treatment and dropout is limited. A better understanding of these factors could help to improve trial design and completion rates. Methods Using data from 1,136 trial participants with schizophrenia or schizoaffective disorder, we explored associations between predictor variables with (1) dropout due to WOC and ITE and (2) satisfaction with treatment among patients and investigators by means of hierarchic multiple regression analyses. Results ITE was associated with poor clinical improvement, poor investigator satisfaction with treatment, and poor patient insight into their own disease, whereas WOC only showed a meaningful association with poor patient satisfaction with treatment. Investigator satisfaction with treatment appeared most strongly associated with Positive and Negative Syndrome Scale (PANSS) positive factor endpoint scores, whereas patient satisfaction with treatment was best predicted by the endpoint score on the PANSS emotional distress factor. The occurrence of severe side effects showed no meaningful association to satisfaction with treatment among investigators and patients, and neither did a patient’s experienced psychopathology, nor their self-rating of functional impairment. Conclusions Whereas trial discontinuation due to ITE is associated with poor treatment effectiveness, a patient’s decision to withdraw from an antipsychotic trial remains unpredictable and may occur even when the investigator observes a global clinical improvement and is satisfied with the treatment.
Antimicrobial Peptides: Interaction With Model and Biological Membranes and Synergism With Chemical Antibiotics

Antimicrobial peptides (AMPs) are promising novel antibiotics since they have shown antimicrobial activity against a wide range of bacterial species, including multiresistant bacteria; however, toxicity is the major barrier to convert antimicrobial peptides into active drugs. A profound and proper understanding of the complex interactions between these peptides and biological membranes using biophysical tools and model membranes seems to be a key factor in the race to develop a suitable antimicrobial peptide therapy for clinical use. In the search for such therapy, different combined approaches with conventional antibiotics have been evaluated in recent years and demonstrated to improve the therapeutic potential of AMPs. Some of these approaches have revealed promising additive or synergistic activity between AMPs and chemical antibiotics. This review will give an insight into the possibilities that physicochemical tools can give in the AMPs research and also address the state of the art on the current promising combined therapies between AMPs and conventional antibiotics, which appear to be a plausible future opportunity for AMPs treatment.
Wheat Gene TaATG8j Contributes to Stripe Rust Resistance

Autophagy-related 8 (ATG8) protein has been reported to be involved in plant’s innate immune response, but it is not clear whether such genes play a similar role in cereal crops against obligate biotrophic fungal pathogens. Here, we reported an ATG8 gene from wheat (Triticum aestivum), designated TaATG8j. This gene has three copies located in chromosomes 2AS, 2BS, and 2DS. The transcriptions of all three copies were upregulated in plants of the wheat cultivar Suwon 11, inoculated with an avirulent race (CYR23) of Puccinia striiformis f. sp. tritici (Pst), the causal fungal pathogen of stripe rust. The transient expression of TaATG8j in Nicotiana benthamiana showed that TaATG8j proteins were distributed throughout the cytoplasm, but mainly in the nucleus and plasma membrane. The overexpression of TaATG8j in N. benthamiana slightly delayed the cell death caused by the mouse apoptotic protein BAX (BCL2-associated X protein). However, the expression of TaATG8j in yeast (Schizosaccharomyces pombe) induced cell death. The virus-induced gene silencing of all TaATG8j copies rendered Suwon 11 susceptible to the avirulent Pst race CYR23, accompanied by an increased fungal biomass and a decreased necrotic area per infection site. These results indicate that TaATG8j contributes to wheat resistance against stripe rust fungus by regulating cell death, providing information for the understanding of the mechanisms of wheat resistance to the stripe rust pathogen.
Identity, community and care in online accounts of hereditary colorectal cancer syndrome

Sociological literature has explored how shifts in the point at which individuals may be designated as diseased impact upon experiences of ill health. Research has shown that experiences of being genetically “at risk” are shaped by and shape familial relations, coping strategies, and new forms of biosociality. Less is known about how living with genetic risk is negotiated in the everyday and over time, and the wider forms of identity, communities and care this involves. This article explores these arrangements drawing on online bloggers’ accounts of Familial Adenomatous Polyposis (FAP). We show how accounts of genetic risk co-exist with more palpable experiences of FAP in everyday life, notably the consequences of prophylactic surgeries. We consider how the act of blogging represents but also constitutes everyday experiences of hereditary cancer syndrome as simultaneously ordinary and exceptional, and reflect on the implications of our analysis for understanding experiences of genetic cancer risk.