Miracle-dz/UniFAR-FTUs huggingface dataset:
Fisho: A cost-effective intelligent autonomous robot fish

We developed a cost-effective fish-like Autonomous Underwater Vehicle (AUV) with a sophisticated intelligence. The robot fish, named Fisho, is able to avoid obstacles in a swimming pool, reflecting the usual behavior of a biological fish. As a general rule, a robot captures external stimulus by means of electrical sensors; Fisho has infrared sensors to find the distance to close objects and pressure sensors to estimate its vertical physical position (depth). Its brain is a small-sized 200-MHz Single Board Computer (SBC), that collects information from the sensors and sends decisions to electro-mechanical servos (in order to act on its tail and flippers, thus control its trajectory). Fisho's behavior is signed by its velocity and the vibration mode of its tail. Inspired in real fish, we designed its intelligence with a three-layer Markov chain by means of a full characterization of tasks, purposes and fish-moods. Its design and physical structure is both non-expensive and simple, trying to emulate a real fish, whereas addressing all typical challenges in an AUV. In this paper we discuss Fisho's physical implementation: sensing platforms, electro-mechanical structure and intelligence.
Part-based robot grasp planning from human demonstration

In this work we introduce a novel approach for robot grasp planning. The proposed method combines the benefits of programming by human demonstration for teaching appropriate grasps with those of automatic 3D shape segmentation for object recognition and semantic modeling. The work is motivated by important studies on human manipulation suggesting that when an object is perceived for grasping it is first parsed in its constituent parts. Following these findings we present a manipulation planning system capable of grasping objects by their parts which learns new tasks from human demonstration. The central advantage over previous approaches is the use of a topological method for shape segmentation enabling both object retrieval and part-based grasp planning according to the affordances of an object. Manipulation tasks are demonstrated in a virtual reality environment using a data glove. After the learning phase, each task is planned and executed in a robot environment that is able to generalize to similar, but previously unknown, objects
Video genre categorization using Support Vector Machines

In this paper, classifying and indexing video genres using Support Vector Machines (SVMs) are based on only audio features. In fact, those segmentation parameters are extracted at block levels, which have a major benefit by capturing local temporal information. The main contribution of our study is to present a powerful combination between the two employed audio descriptors Mel Frequency Cepstral Coefficients (MFCC) and signal energy in order to classify three common video genres: several sports analysis and matches, both studio and fields news scenes over and above various multi-speaker and multiinstruments music clips. Validation of this approach was carried out on over 6 hours of video span token from YouTube and yielding a classification accuracy of 99.83%. Finally we discuss SVM kernels performance on our proposed dataset.
Encouraging physical activity in teens Can technology help reduce barriers to physical activity in adolescent girls?

Physical activity levels of girls decline dramatically during adolescence and may be a contributor to the increasing number of obese teens in the United States. Research has shown that social support is positively correlated with physical activity levels in adolescents, particularly girls. We present the findings from a three week field study of a mobile phone application designed to create a support group for physical activity within an existing social network of adolescent girls. Our findings suggest design considerations for technologies that encourage physical activity for this user group.
Multi Domain Features Based Classification of Mammogram Images Using SVM and MLP

Breast cancer is the most common cancer diagnosed among U.S. women. In this paper we have done some experiments for tumor detection in digital mammogram images. First of all, we have described a method that segments the breast image automatically. As a preprocessing, we have used fuzzy based noise removal filter that removes noise. Then for segmentation, we have provided a background removal method. We have extracted eight different multi domains features. For accurate classification, we have used two different classification techniques: Support Vector Machine (SVM) and Multilayer Perceptrons (MLP). We have compared our results with a method that has used 8 features. We have shown results that four features are not sufficient for classification. Results show the superiority of the proposed algorithm in terms of sensitivity, specificity and accuracy. We have used MIAS [7] database of mammography.
Model based on Hybridized Game Theory to Optimize Logistics: Case of Blood Supply Chain

Several researches have been done to optimize different flows in blood supply chain. However, the use of game theory in this sense is rare. The following work focus on the case of Morocco, consisting of 16 Regional Blood Transfusion Centers (RBTC) centralized around a National Blood Transfusion and Hematology Center (NBTHC). An approach based on hybridized game theory is adopted to form core and strongly stable coalitions and optimize as much as possible the transport cost. Firstly, the optimal cost of each coalition of the 33 possible coalitions; that the Director of NBTHC validated; is computed by using a mixed integer linear Programming model (MILP). Then these costs are introduced as data of two other MILP to define which structure minimizes the total cost allocated to each RTBC while maintaining core stability, in the case of the first MILP, and strong equilibrium in the case of the second. The VRPPDTW is also introduced within each coalition in order to optimize the cost of transport more. General Terms Mixed integer linear programming, logistics, game theory.
Tackling Subutex abuse in Singapore.

Subutex® (or buprenorphine hydrochloride) was approved by the Ministry of Health (MOH) in 2000 as substitution treatment for opiate-dependent drug abusers within a framework of medical, social and psychological treatments. It was subsequently introduced into the Singapore market in 2002. When used appropriately, Subutex has been shown in other countries to reduce craving for heroin and facilitate improvement in social functioning such as employment and personal relationships(1).
Immunoprofiling of human uterine mast cells identifies three phenotypes and expression of ERβ and glucocorticoid receptor

Background: Human mast cells (MCs) are long-lived tissue-resident immune cells characterised by granules containing the proteases chymase and/or tryptase. Their phenotype is modulated by their tissue microenvironment. The human uterus has an outer muscular layer (the myometrium) surrounding the endometrium, both of which play an important role in supporting a pregnancy. The endometrium is a sex steroid target tissue consisting of epithelial cells (luminal, glandular) surrounded by a multicellular stroma, with the latter containing an extensive vascular compartment as well as fluctuating populations of immune cells that play an important role in regulating tissue function. The role of MCs in the human uterus is poorly understood with little known about their regulation or the impact of steroids on their differentiation status. The current study had two aims: 1) To investigate the spatial and temporal location of uterine MCs and determine their phenotype; 2) To determine whether MCs express receptors for steroids implicated in uterine function, including oestrogen (ERα, ERβ), progesterone (PR) and glucocorticoids (GR). Methods: Tissue samples from women (n=46) were used for RNA extraction (n=26) or fixed (n=20) for immunohistochemistry. Results: Messenger RNAs encoded by TPSAB1 (tryptase) and CMA1 (chymase) were detected in endometrial tissue homogenates. Immunohistochemistry revealed the relative abundance of tryptase MCs was myometrium>basal endometrium>functional endometrium. We show for the first time that uterine MCs are predominantly of the classical MC subtypes: (positive, +; negative, -) tryptase+/chymase- and tryptase+/chymase+, but a third subtype was also identified (tryptase-/chymase+). Tryptase+ MCs were of an ERβ+/ERα-/PR-/GR+ phenotype mirroring other uterine immune cell populations, including natural killer cells. Conclusions: Endometrial tissue resident immune MCs have three protease-specific phenotypes. Expression of both ERβ and GR in MCs mirrors that of other immune cells in the endometrium and suggests that MC function may be altered by the local steroid microenvironment.
Crystallographic Texture Development in CP Ti Subjected to ECAP

In this article we present the results of the experimental research and those of the processes developing the crystallographic texture of computer modeling in CP Ti in the process of 1-4 equal channel angular pressing (ECAP) passes along the route ВС. The goal of the research was to determine the active deformation mechanisms, depending on the strain degree, accumulated in the ECAP process. The research was carried out by the method of X-ray analysis and by computer modeling. Computer modeling was carried out on the example of visco-plastic self-consistent model. Thereby, the basal, the prismatic and the pyramidal (of the 1st and of the 2nd order) slip systems were considered as possible active slip systems. Besides, the possibility of activating the tensile and the compressive twinning systems were taken into consideration. As the result of the carried out experimental research, the objective laws of forming preferred orientations were determined. For the first time, with the help of computer modeling, made up to the 4th ECAP pass, it was shown that the crystallographic texture development processes in CP Ti in ECAP, realized at temperature of 723 K, can be explained by activation of the basal, prismatic and pyramidal (of the 1st order) slip systems and compressive twinning systems. Therefore, the increase of the ECAP passes can lead to amplification of contribution of the basal and prismatic slip systems, as well as the insignificant weakening of the contribution of pyramidal slip systems (of the 1st order). Moreover, the compressive twinning can become obvious only in the 1st ECAP pass.
The Benefits of Process Parameter Ramping During The Plasma Etching of High Aspect Ratio Silicon Structures

In the ongoing enhancement of MEMS applications, the STS Advanced Silicon Etch, (ASE TM ). process satisfies the demanding requirements of the industry. Typically, highly anisotropic. high aspect ratios profiles with fine CD (critical dimension) control are required. Selectivities to photoresist of 150:1 with Si etch rates of up to 10μm/min are demonstrated. Applications range from shallow etched optical devices to through wafer membrane etches. This paper details some of the fundamental trends of the ASE TM process and goes on to discuss how the process has been enhanced to meet product specifications. Parameter ramping is a powerful technique used to achieve the often-conflicting requirements of high etch rate with good profile/CD control. The results are presented in this paper.
A prime number labeling scheme for dynamic ordered XML trees

Efficient evaluation of XML queries requires the determination of whether a relationship exists between two elements. A number of labeling schemes have been designed to label the element nodes such that the relationships between nodes can be easily determined by comparing their labels. With the increased popularity of XML on the Web, finding a labeling scheme that is able to support order-sensitive queries in the presence of dynamic updates becomes urgent. We propose a new labeling scheme that take advantage of the unique property of prime numbers to meet this need. The global order of the nodes can be captured by generating simultaneous congruence values from the prime number node labels. Theoretical analysis of the label size requirements for the various labeling schemes is given. Experiment results indicate that the prime number labeling scheme is compact compared to existing dynamic labeling schemes, and provides efficient support to order-sensitive queries and updates.
Study on Diffusion of Invasion Species Along the Qinghai-Tibet Railway

In this paper, the study on the simulation of invasion species diffusion along the Qinghai-Tibet Railway is presented. On the basis of discrete diffusion model of invasion species, the diffusion model from multi-sources is studied combining with the geographical information in the studying region, and the diffusion rate from a single source is also studied. The simulation of the diffusion of invasive species along the Qinghai-Tibet Railway is discussed by using MATLAB and ArcGIS9.2 for given the diffusion coefficient, and some simulation results is obtained including from one-dimension to three-dimension. Those theoretical results can be easily used in the diffusion research on other invasion species to ensure its wide applications in the future.
MULTIMODAL PLAY BACK AND DEBUGGING IN CHARTER 2 . 1

A basic capability driving the development of systems is the ability to execute multiple versions of a system against the same set of data. That is essential for instance to verify that coding problems were corrected, to provide guarantees that changes to the code did not introduce errors (regression testing) and for comparison of performance among different algorithmic solutions. Multimodal systems process a combination of inputs and their results are susceptible to timing issues, which determine for instance whether a pair of inputs from different modalities combine or not. When a multimodal system is executed against corpus data, it becomes necessary to synchronize processing of the various input streams and to handle time-related information so as to emulate real-time execution. This is particularly complex when multiple components of the various input stream processors take longer than real-time. In this paper we describe a multimodal play back mechanism that addresses these problems. We report on two data collection and play back software and hardware environments — one used for system development and evaluation and the other used for supporting manual annotation of multimodal data.
Hooking up spectro-temporal filters with auditory-inspired representations for robust automatic speech recognition

Spectro-temporal filtering has been shown to result in features that can help to increase the robustness of automatic speech recognition (ASR) in the past. We replace the spectro-temporal representation used in previous work with spectrograms that incorporate knowledge about the signal processing of the human auditory system and which are derived from Power-Normalized Cepstral Coefficients (PNCCs). 2D-Gabor filters are applied to these spectrograms to extract features evaluated on a noisy digit recognition task. The filter bank is adapted to the new representation by optimizing the spectral modulation frequencies associated with each Gabor function. A comparison of optimized parameters and the spectral modulation of vowels shows a good match between optimized and expected range of frequencies. When processed with a non-linear neural net and combined with PNCCs, Gabor features decrease the error rate compared to the baseline and PNCCs by at least 19%.
Serum 25-Hydroxyvitamin D Concentrations and Depressive Symptoms among Young Adult Men and Women

There has been an increased interest in the role of vitamin D in depression; however, there have been few studies conducted in younger population groups. Our aim was to investigate the association between vitamin D status and depressive symptoms in a non-clinical young adult sample living in Dunedin, New Zealand. A cross-sectional sample of 615 young adults completed a questionnaire including demographics and the Centre for Epidemiological Studies Depression Scale (CES-D). Height, weight and a blood sample for 25-hydroxyvitamin D [25(OH)D] was obtained. Serum 25(OH)D was used to predict depression scores, adjusting for potential confounders including time spent outdoors for 13 consecutive days, BMI, age, sex and ethnicity. Prevalence of low vitamin D was high even in this age group, and serum 25(OH)D was negatively associated with depression symptoms before and after adjustment. When investigating the relationship between the presence versus absence of depressive symptoms and quartiles of 25(OH)D, participants in the lowest quartile were more likely to report depressive symptoms compared with those in the highest quartile. Although our findings suggest that vitamin D is a predictor of depression symptomatology, even when controlling for time spent outdoors, a randomised controlled trial in this young adult target group is needed to confirm the association.
Adaptive Dynamic On-chip Memory Management for FPGA-based reconfigurable architectures

In this paper, an adaptive architecture for dynamic management and allocation of on-chip FPGA Block Random Access Memory (BRAM) resources is presented. This facilitates the dynamic sharing of valuable and scarce on-chip memory among several processing elements (PEs), according to their dynamic run-time memory requirements. Different real-time applications are becoming increasingly dynamic which leads to unexpected and variable memory footprints, and static allocation of the worst-case memory requirements would result in costly overheads and inefficient memory utilization. The proposed scalable BRAM memory management architecture adaptively manages these dynamic memory requirements and balances the buffer memory over several PEs to reduce the total memory required, compared to the worst-case memory footprint for all PEs. The run-time adaptive system allocates BRAM to each PE sufficiently fast enough as required and utilized. In a case study, a significant improvement in BRAM utilization with limited overhead has been achieved due to the adaptive memory management architecture. The proposed system supports different BRAM types and configurations, and automated dynamic allocation and deallocation of BRAM resources, and is therefore well suited for the dynamic memory footprints of FPGA-based reconfigurable architectures.
Protection Motivation Theory in Predicting Intention to Engage in Protective Behaviors against Schistosomiasis among Middle School Students in Rural China

Background Among millions of people who suffer from schistosomiasis in China, adolescents are at increased risk to be infected. However, there is a lack of theory-guided behavioral prevention intervention programs to protect these adolescents. This study attempted to apply the Protection Motivation Theory (PMT) in predicting intentions to engage in protective behaviors against schistosomiasis infection. Methods The participants were selected using the stratified cluster sampling method. Survey data were collected using anonymous self-reported questionnaire. The advanced structural equation modeling (SEM) method was utilized to assess the complex relationship among schistosomiasis knowledge, previous risk exposure and protective measures in predicting intentions to engage in protective behavior through the PMT constructs. Principal Findings Approximately 70% of participants reported they were always aware of schistosomiasis before exposure to water with endemic schistosomiasis, 6% of the participants reported frequency of weekly or monthly prior exposure to snail-conditioned water. 74% of participants reported having always engaged in protective behaviors in the past three months. Approximately 7% were unlikely or very unlikely to avoid contact with snail-conditioned water, and to use protective behaviors before exposure. Results from SEM analysis indicated that both schistosomiasis knowledge and prior exposure to schistosomiasis were indirectly related to behavior intentions through intrinsic rewards and self-efficacy; prior protective behaviors were indirectly related to behavior intentions through severity, intrinsic rewards and self-efficacy, while awareness had an indirect relationship with behavior intentions through self-efficacy. Among the seven PMT constructs, severity, intrinsic rewards and self-efficacy were significantly associated with behavior intentions. Conclusions The PMT can be used to predict the intention to engage in protective behaviors against schistosomiasis. Schistosomiasis intervention programs should focus on the severity, intrinsic rewards and self-efficacy of protection motivation, and also increase the awareness of infection, and enrich the contents of schistosomiasis education.
Pose Estimation Under Anisotropic Scaling with Automatic Initialization

In this paper we investigate solutions to the problem of pose estimation for a class of rigid objects parameterized by anisotropic scaling (variable aspect ratios). We describe extensions of two known pose estimation algorithms to this scenario, that allow them to estimate aspect, in addition to rotation and translation. Our first contribution is a fully automatic example-based initialization scheme. We show that this scheme benefits iterative pose estimation methods across the board, dramatically improving convergence to accurate results. Our second contribution is a pose estimation algorithm called Scaled Exterior Orientation (SEO) that handles anisotropic scaling. In experiments on two object classes we show that combined with the proposed automatic initialization, SEO achieves best results in low noise conditions, and is on par with other algorithms under severe noise.
Structure and Dynamics of Signed Citation Networks

Citations are important to track and understand the evolution of human knowledge. At the same time, it is widely accepted that all the citations made in a paper are not equal. However, there is no thorough understanding of how citations are created that explicitly criticize or endorse others. In this paper, we do a detailed study of such citations made within the NLP community by differentiating citations into endorsement (positive), criticism (negative) and neutral categories. We analyse this signed network created between papers and between authors for the first time from a social networks perspective. We make many observations - we find that the citations follow a heavy-tailed distribution and they are created in a way that follows weak balance theory and status theories. Moreover, we find that authors do not change their opinion towards others over time and rarely reciprocate the opinion that they receive. Overall, the paper builds the understanding of the structure and dynamics of positive, negative and neutral citations.
Fabrication and thermal characteristics of multilayer metal-coated regenerated grating sensors for high-temperature sensing

Health monitoring of components operating at high temperatures requires the development of new sensors to measure temperature and deformation. A regenerated grating (RG) sensor with titanium (Ti)–silver (Ag)–nickel (Ni) multilayer coatings is fabricated by magnetron sputtering and electroplating processes. Optical and thermal tests are performed to evaluate the characteristics of the Ti–Ag–Ni-coated RG sensor. The shapes of the reflection spectra for the RG are slightly affected by the metallization process. The Ti–Ag–Ni-coated RG sensor exhibits a higher sensitivity than that of the bare RG for temperatures up to 600 ° C, with good repeatability and stability. It is verified that the titanium coating can achieve good adhesion to the optical fiber and that the silver coating is suitable as a conductive layer for electroplating. An analytical model for the axial strain and radial strain in a multilayer metal-coated optical fiber is proposed. Comparisons of the experimental results and the theoretical predictions show a good agreement below 250 ° C. These results indicate that multilayer metal-coated RG sensors can be successfully fabricated by combining magnetron sputtering with electroplating and provide great potential for high-temperature sensing.