Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy efficient green routing protocol for Internet of Multimedia Things

Internet of Things (IoT) envisions the notion of ubiquitous connectivity of `everything'. However, the current research and development activities have been restricted to scalar sensor data based IoT systems, thus leaving a gap to benefit from services and application enabled by `multimedia things' or Internet of Multimedia Things (IoMT). Moreover, a crucial issue for Information and Communication Technology (ICT) community is the steer increase in CO2 emissions, which mandates green communication to reduce energy consumption and carbon footprint emissions. Recently, IETF ROLL working group standardized an IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) for resource constrained devices. RPL builds a tree-like network topology based on some network metric optimization using RPL Objective Functions. Previous RPL implementations for scalar sensor data communication are not feasible for IoMT, since multimedia traffic pose distinct network requirements. The goal of this paper is to design an enhanced version of RPL for IoMT in which the sensed information is essentially provided by the multimedia devices. Our proposed RPL implementation minimizes carbon footprint emissions and energy consumption, along with the incorporation of application specific Quality of Service requirements. To evaluate the performance of the proposed scheme a simulation study is carried out in Cooja simulator for Contiki-OS, which suggests significant gains in terms of energy efficiency and delay.
On honest times in financial modeling

This paper demonstrates the usefulness and importance of the concept of honest times to financial modeling. It studies a financial market with asset prices that follow jump-diffusions with negative jumps. The central building block of the market model is its growth optimal portfolio (GOP), which maximizes the growth rate of strictly positive portfolios. Primary security account prices, when expressed in units of the GOP, turn out to be nonnegative local martingales. In the proposed framework an equivalent risk neutral probability measure need not exist. Derivative prices are obtained as conditional expectations of corresponding future payoffs, with the GOP as numeraire and the real world probability as pricing measure. The time when the global maximum of a portfolio with no positive jumps, when expressed in units of the GOP, is reached, is shown to be a generic representation of an honest time. We provide a general formula for the law of such honest times and compute the conditional distributions of the global maximum of a portfolio in this framework. Moreover, we provide a stochastic integral representation for uniformly integrable martingales whose terminal values are functions of the global maximum of a portfolio. These formulae are model independent and universal. We also specialize our results to some examples where we hedge a payoff that arrives at an honest time.
Using Topic Model for Intelligent Computer-Aided Diagnosis in Traditional Chinese Medicine

This research work presents the use of Latent Dirchlet Allocation (LDA), a generative topic modeling technique to extract latent patterns in Chinese Traditional Medical (CTM) diagnose and treatment data. It can help to capture the relationship between symptom and diseases. The purpose of the research is to acquire proficient medical knowledge by computer which can aid doctors to determine diagnosis. Our work proposed the framework which utilizes LDA to discoicvery latent patterns in the symptoms of medical cases and set up computer-aided diagnosis system in TCM.
A Synthetical Cipher Index Technology and its Cryptogram Query Strategy in Outsourced Databases

Cipher index is a well established technology for improving query efficiency. However, the existing index schemes have defect of lowness in query hit rate which leads to internet crowdedness. It is the key for this problem to reduce the redundant tuples in query results. A synthetical cipher index technology to eliminate redundant tuples is presented through considering numeric data and character data respectively. Firstly, according to the query requirement, users’ data is concluded into two classifications: the data of various fuzzy querying and that of numeric comparison. Next, cipher indices are established respectively. For the former, a newly cipher index scheme is presented, which determine k character indices for each character composed attribute domain through a mapping function. For the later, an order preserving encryption scheme is used as a cipher index scheme. Meanwhile, the effectiveness and security are analyzed. Finally, the cryptogram query strategy in outsourced databases is presented. Keywords-outsourced database; cipher index; accurate query; k-mapping cipher index scheme (k-MCIS); order preserving cipher index scheme (OPCIS)
Mineralocorticoid regulation of transcription of transfected mouse mammary tumor virus DNA in cultured kidney cells

Renal cells contain two corticosteroid-binding entities defined on the basis of hormone-binding selectivity as type I (mineralocorticoid) and type II (glucocorticoid). The mineralocorticoid, aldosterone can bind to both type I and type II receptors. This poses problems in defining the characteristics of a true mineralocorticoid regulated expression of specific genes. We have used chimaeric constructs bearing the mouse mammary tumor virus (MMTV) promoter to study aldosterone action in the feline renal cell line CRFK. We have shown that in these cells aldosterone induces MMTV transcription through its own receptor (type I). This induction of MMTV transcription by aldosterone is a primary response to the hormone. We have shown that the DNA sequences that mediate the aldosterone response overlap the hormone response element (HRE) required for the glucocorticoid, progestin, and androgen induction of transcription at the MMTV long terminal repeat region. Thus the aldosterone regulation of MMTV long terminal repeat transcription is identical to the mode of action of the other steroid hormones at this promoter.
Facial Features Tracking using Active Appearance Models

This thesis aims at building a system capable of automatically extracting and parameterizing the position of a face and its features in images acquired from a low-end monocular camera. Such a challenging task is justified by the importance and variety of its possible applications, ranging from face and expression recognition to animation of virtual characters using video depicting real actors. The implementation includes the construction of Active Appearance Models of the human face from training images. The existing face model Candide-3 is used as a starting point, making the translation of the tracking parameters to standard MPEG-4 Facial Animation Parameters easy.The Inverse Compositional Algorithm is employed to adapt the models to new images, working on a subspace where the appearance is "projected out" and thus focusing only on shape.The algorithm is tested on a generic model, aiming at tracking different people’s faces, and on a specific model, considering one person only. In the former case, the need for improvements in the robustness of the system is highlighted. By contrast, the latter case gives good results regarding both quality and speed, with real time performance being a feasible goal for future developments.
Reações dos pacientes adolescentes a situações potencialmente coercitivas no tratamento dos transtornos relacionados ao uso de substâncias

Background: Adolescence is considered a period that requires special attention regarding the use of psychoactive substances. The physical, psychological and social modifications in adolescence deepen the condition of vulnerability and increase the risk of precocious use of psychoactive substances (SPA). Knowing that, the Ministry of Health emphasizes the importance of actions that seek to attend this population, considering, especially, the particularities of the age group. The coercive aspects and social pressures may adversely affect the patient, the course of treatment and its outcomes. Objective: explore, by chart analysis, the reactions of adolescents users of psychoactive substances to potentially coercive situations, in order to identify what kind of reactions are triggered by them. Methods: The research is characterized by two distinct moments. First we conducted a cross-sectional study of all 229 medical records of adolescents users of psychoactive substances under treatment at a Psychosocial Care Centers (CAPS, acronym in Portuguese), from November 2002 to December 2012. This service is locally called CAPSIA. This period corresponds to the first 10 years of operation of the CAPSIA. Data were collected by reading the observation notes held by different members of the service staff in the medical records. Data were collected characterizing the moment of seeking treatment (gender, age, school status, source of referral), situations considered aggravating the condition of vulnerability (family violence, criminal involvement, truancy) and issues related to the treatment (used substances and hospital admission). The data obtained were evaluated quantitatively and descriptively, allowing the characterization of a biopsychosocial profile of these adolescents. In a second phase, a subsample of 23 from the 229 the medical records was selected through random sampling sequential process. The number of selected medical charts was set by the sample saturation criterion. In this sample we sought to identify observational notes about different moments of the treatment (first interview, doctor visits, hospital referral, home visits, etc .) in order to identify potentially coercive situations, these notes were selected for further analysis. After identifying the potentially coercive situations, social pressures were classified according to referral source into legal, formal, and informal. Subsequently, passages describing patients’ reactions to these coercive situations were identified in the medical records. The data
The Continuous Inverse Class-F Mode With Resistive Second-Harmonic Impedance

In this paper, an extended version of the continuous class-F-1 mode power amplifier (PA) design approach is presented. A new formulation describing the current waveform in terms of just two additional parameters, while maintaining a constant half-wave rectified sinusoidal voltage waveform, allows multiple solutions of fundamental and second-harmonic impedances that provide optimum performance to be computed. By varying only the imaginary parts of fundamental and second-harmonic impedances, it is shown that output performance in terms of power and efficiency is maintained constant and equal to that achievable from the standard class-F-1 . Indeed, when presenting resistive second-harmonic impedances, it will be demonstrated that the fundamental load can be adjusted to maintain satisfactory output performances greater than a certain predetermined target value. The measurements, conducted on a GaAs pHEMT device at 1 GHz, show a good agreement with the theoretical analysis, revealing drain efficiencies greater than 70% for a very large range of load solutions, which can translate to an ability to accommodate reactive impedance variations with frequency when designing broadband PAs.
Study on Financial Risk Pre-Warning of Combined Heat and Power Corporate

CHP (combined heat and power) corporates not only can economize energy source, but also can integrate the benefits of increasing the quality of heating supply. So CHP developed rapidly after reformation in China, especially after promulgating the Law of the People's Republic of China on conserving energy. However analysis and pre-warning about the financial risks of CHP is not found in present literature. This paper first established an financial risk index system after analyzing the characteristics of CHP corporates' financial risks. Then this paper gave an financial risk pre-warning model which was established based on set pair analysis (SPA) theory. At last, the paper gave an empirical study in order to verify the financial risk pre-warning model's feasibility in CHP corporates.
Network dynamics and idea-based performance advantages : Experimental results from an entrepreneurship bootcamp

Do networks plentiful in ideas provide startups with performance advantages? On the one hand, network positions that provide access to a multitude of ideas are thought to increase team performance. On the other hand, research on network formation argues that such positional advantages should be fleeting as entrepreneurs both strategically compete for the most valuable network positions and form relationships with others who have similar characteristics and abilities. I embed a field experiment in a three-week-long startup bootcamp and pre-accelerator to test if networks that are plentiful in ideas lead to performance advantages. Using detailed data from the bootcamp's custom-designed learning management platform, I find support for the first hypothesis. Teams with networks more plentiful in ideas receive better peer evaluations and more crowdfunding page views. I find little evidence that entrepreneurs actively build networks to others who could have provided a greater quantity of information and ideas. Instead, entrepreneurs seek feedback from those they have collaborated with in the past or who share similar ascriptive characteristics. These findings provide first-order evidence for the importance of knowledge spillovers within bootcamps, incubators, and accelerators. Furthermore, the findings provide a potential explanation for the durability of idea and information-based network advantages.
Ranking as Learning Structured Outputs

An admixture consisting essentially of two or more of the compounds selected from the group consisting of 5-hydroxymethylcytosine (5-HMC), a B6 vitamin and nicotinamide or nicotinic acid has been found to be effective as an alcohol detoxicant and useful to inhibit alcohol intoxication. There may be added to the aforesaid admixture a calcium ion donor, such as water-soluble calcium salt selected from the group consisting of calcium chloride, calcium nitrate, calcium acetate, calcium sulfate and calcium pantothenate. Also, there may be added to the aforesaid admixture a carbohydrate, such as mannose or fructose and the compound allantoin.
RhoanaNet Pipeline: Dense Automatic Neural Annotation

Reconstructing a synaptic wiring diagram, or connectome, from electron microscopy (EM) images of brain tissue currently requires many hours of manual annotation or proofreading (Kasthuri and Lichtman, 2010; Lichtman and Sanes, 2008; Seung, 2009). The desire to reconstruct ever larger and more complex networks has pushed the collection of ever larger EM datasets. A cubic millimeter of raw imaging data would take up 1 PB of storage and present an annotation project that would be impractical without relying heavily on automatic segmentation methods. The RhoanaNet image processing pipeline was developed to automatically segment large volumes of EM data and ease the burden of manual proofreading and annotation. Based on (Kaynig et al., 2015), we updated every stage of the software pipeline to provide better throughput performance and higher quality segmentation results. We used state of the art deep learning techniques to generate improved membrane probability maps, and Gala (Nunez-Iglesias et al., 2014) was used to agglomerate 2D segments into 3D objects. We applied the RhoanaNet pipeline to four densely annotated EM datasets, two from mouse cortex, one from cerebellum and one from mouse lateral geniculate nucleus (LGN). All training and test data is made available for benchmark comparisons. The best segmentation results obtained gave $V^\text{Info}_\text{F-score}$ scores of 0.9054 and 09182 for the cortex datasets, 0.9438 for LGN, and 0.9150 for Cerebellum. The RhoanaNet pipeline is open source software. All source code, training data, test data, and annotations for all four benchmark datasets are available at www.rhoana. org.
How Secure are Web Servers? An Empirical Study of Slow HTTP DoS Attacks and Detection

Slow HTTP Denial of Service (DoS) is an application layer DoS attack in which large number of incomplete HTTP requests are sent. If number of such open connections in the server exhaust a preset threshold, server does not accept any new connections thus creating DoS. In this paper we make twofold contributions. We do an empirical study on different HTTP servers for their vulnerability against slow HTTP DoS attacks. Subsequently we propose a method to detect Slow HTTP Dos attack. The proposed detection system is an anomaly detection system which measures the Hellinger distance between two probability distributions generated in training and testing phases. In the training phase it creates a normal profile as a probability distribution comprising of complete and incomplete HTTP requests. In case of Slow HTTP attack the proportion of incomplete messages is increased in the overall traffic and detection system leverages this for detection by generating another probability distribution and finding difference between two probability distributions. We experiment by collecting data from a real web server and report the detection performance of proposed detection system.
What We Talk About When We Talk About Diversity

Novelty and diversity are functions of three things: a system’s performance at ad-hoc retrieval, its ability to order documents diversely, and the collection over which the sys-tem is run. Ideally, our diversity evaluation framework (test collections and evaluation measures) would sort systems by their skill at ordering documents. Unfortunately, the current framework as exempliﬁed by TREC is actually dominated by ad-hoc performance and insensitive to document ordering. In this paper, we deﬁne a measure of diversity diﬃculty for a query and subtopics irrespective of any ranked list, and suggest cases for future failure analysis of diversity evaluation frameworks. We conclude with a suggested retrieval task that will sort systems by their ability at ordering documents given a query’s diversity diﬃculty while controlling for their ability to perform ad-hoc retrieval.
Influence of Repressive Coping Style on Cortical Activation during Encoding of Angry Faces

Background Coping plays an important role for emotion regulation in threatening situations. The model of coping modes designates repression and sensitization as two independent coping styles. Repression consists of strategies that shield the individual from arousal. Sensitization indicates increased analysis of the environment in order to reduce uncertainty. According to the discontinuity hypothesis, repressors are sensitive to threat in the early stages of information processing. While repressors do not exhibit memory disturbances early on, they manifest weak memory for these stimuli later. This study investigates the discontinuity hypothesis using functional magnetic resonance imaging (fMRI). Methods Healthy volunteers (20 repressors and 20 sensitizers) were selected from a sample of 150 students on the basis of the Mainz Coping Inventory. During the fMRI experiment, subjects evaluated and memorized emotional and neutral faces. Subjects performed two sessions of face recognition: immediately after the fMRI session and three days later. Results Repressors exhibited greater activation of frontal, parietal and temporal areas during encoding of angry faces compared to sensitizers. There were no differences in recognition of facial emotions between groups neither immediately after exposure nor after three days. Conclusions The fMRI findings suggest that repressors manifest an enhanced neural processing of directly threatening facial expression which confirms the assumption of hyper-responsivity to threatening information in repression in an early processing stage. A discrepancy was observed between high neural activation in encoding-relevant brain areas in response to angry faces in repressors and no advantage in subsequent memory for these faces compared to sensitizers.
EXPERIMENTAL AND NUMERICAL ANALYSIS OF THE DOE REFERENCE MODEL 1 HORIZONTAL AXIS HYDROKINETIC TURBINE

We present two studies, one experimental and another numerical, of a Horizontal Axis Hydrokinetic Turbine (HAHT) based on the DOE Reference Model 1. In the experiments, the performance and wake of a small array of three turbines was analyzed with measurements conducted on a 45:1 scale physical model of the DOE RM1 rotor. The influence of the Reynolds number dissimilarity between the laboratory model and the full scale is described. The numerical solution of the RANS equations solved around a computational model of the full scale geometry yield the details of the rotor flow field and wake evolution. The influence of turbulent closure models on the full scale Reynolds number flow is considered, as is the use of high resolution simulations in lower fidelity models for fast turn around, low computational cost, numerical design efforts.
Exploring Motivational Changes for Short In-class Extensive Reading

This study examined longitudinal changes in motivation for short inclass extensive reading (ER) and the relationship between these motivational changes and English proficiency, using selfdetermination theory (SDT; Deci & Ryan, 1985). Japanese university EFL learners (n = 133) took pre- and post-English proficiency tests and responded to a questionnaire designed to measure the five subtypes of SDT motivation (i.e., intrinsic motivation, identified regulation, introjected regulation, external regulation, and amotivation) thrice in one academic year. The results of one-way within-subjects repeated-measures MANOVA showed that while three subtypes of SDT motivation (i.e., intrinsic motivation, identified regulation, and external regulation) tended to decrease, amotivation increased, revealing that learners’ motivation for short in-class ER significantly decreased over time. The results of a recursive path analysis included that 1) initial English proficiency had significant direct effects on initial motivational status, but generally had only indirect effects on the subsequent motivational profiles via the initial motivational status; and 2) final motivational status was statistically irrelevant to final English proficiency. These findings revealed that although English proficiency initially influenced motivation, the relationship between motivation and English proficiency eventually became insignificant in short in-class ER. Low-level reading abilities do not ultimately demotivate learners to engage in ER.
Instantaneous magnitudes and frequencies of signals with positivity constraints

This paper proposes an optimization approach for representing instantaneous magnitudes and frequencies of signals. Signals are represented as the products of their magnitudes and the cosines of their phases. Also, both their instantaneous magnitudes and frequencies are positive. These two conditions are posed as linear functional inequality constraints. To have smooth signals, the sum of the total absolute values of the p th order derivatives of the magnitudes is minimized. To solve the optimization problem, the objective function is first converted to a linear objective function subject to linear functional inequality constraints. Finally, the functional inequality constraints are converted to the conventional linear equality constraints via the constraint transcription method. Experimental results show that the magnitudes obtained by our proposed method are much smoother than those obtained by existing methods.