Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation of 32-bit RISC processors without interlocked Pipelining on Artix-7 FPGA board

RISC processors have wide range of applications depending on speed and power consumption. Here a design of low power RISC processor is proposed using forwarding and stalling process. Using suitable clocking methodology speed can also be enhanced. A design of 5 stage pipelining architecture with hazard and forwarding unit for pipeline control is presented. Fetch, Decode, Execute, Memory and Write back are the 5 stages. A single edge trigger clock is used for intermediate stages. The RISC processor is designed based on MIPS instruction set. A non-interlocked pipelining technique is used. Power reduction of up to . 09W was achieved using above mentioned techniques. The design is implemented on Artix-7 FPGA using Xilinx Vivado.
An RSSI-based distributed real-time indoor positioning framework

In recent years, the application of indoor positioning and tracking have become more important, which may be applied to the navigation of large building, personnel tracking, etc. Due to the limitations of GPS, some researchers have utilized the received signal strength indicator (RSSI) in the wireless environment for indoor positioning. There are two major approaches are proposed: fingerprinting and trilateration techniques. In this research, we proposed an RSSI-based Distributed Real-time Indoor Positioning Framework which integrated these two techniques to construct a cost-effective solution in Bluetooth low energy environment.
Efficient Query Retrieval from Social Data in Neo4j using LIndex

The unstructured and semi-structured big data in social network poses new challenges in query retrieval. This requirement needs to be met by introducing quality retrieval time measures like indexing. Due to the huge volume of data storage, there originate the need for efficient index algorithms to promote query processing. However, conventional algorithms fail to index the huge amount of frequently obtained information in real time and fall short of providing scalable indexing service. In this paper, a new LIndex algorithm, which is a heuristic on Lucene is built on Neo4jHA architecture that holds the social network Big data. LIndex is a flexible and simplified adaptive indexing scheme that ascendancy decomposed shortest paths around term neighbors as basic indexing unit. This newfangled index proves to be effectual in query space pruning of graph database Neo4j, scalable in index construction and deployment. A graph query is processed and optimized beyond the traditional Lucene in a time-based manner to a more efficient path method in LIndex. This advanced algorithm significantly reduces query fetch without compromising the quality of results in time. The experiments are conducted to confirm the efficiency of the proposed query retrieval in Neo4j graph NoSQL database.
The regulatory effect of Genistein on granulosa cell in ovary of rat with PCOS through Bcl-2 and Bax signaling pathways

The effect of genistein on Bcl-2 and Bax protein expression in the ovarian tissue of rats with polycystic ovarian syndrome (PCOS) was evaluated. Sixty rats were divided into six groups. Rats in the Dose group received genistein at a concentration of either 5 (L-gen), 10 (M-Gen) or 20 (H-Gen) mg per kg of body weight per day. The expression of Bcl-2 mRNA and Bax mRNA was determined by in situ hybridization. Bcl-2 and Bax protein concentration was quantified by ELISA. The results showed that the expression of Bcl-2 mRNA and Bcl-2 protein was signiﬁcantly higher in the high genistein Dose group (H-Gen) when compared to the Model group (MG) (P<0.05). Genistein induced higher expression of the Bcl-2 gene at the transcriptional and translational level. Treatment with genistein resulted in an improvement of ovarian function with Bcl-2 expression being enhanced and Bax expression being suppressed. These alterations may be due to the structural and functional modifications that take place in these cells, and could be related to apoptotic changes that occur in rats with PCOS.
Analysis of CM EMI reduction with zero CM modulation scheme utilizing paralleled inverters

Common mode voltage is a key issue in variable speed AC motor drive, but conventional single three-phase voltage source inverter cannot effectively suppress the common mode voltage. The system of paralleled voltage source inverters is more flexible and can be utilized to implement novel modulation schemes to reduce the common mode component. This paper focuses on three modulation schemes which have different performance in common mode voltage suppression and fair comparison of electromagnetic interference is also implemented. Experimental results are provided to show the advantage of proposed method in common mode electromagnetic interference noise reduction and DC side electromagnetic interference filter design.
Access Control by Signature-Keys to Provide Privacy for Cloud and Big Data

Privacy of data in subjects of cloud computing or big data is one of the most principal issues. The privacy methods studied in previous research showed that privacy infringement for cloud computing or big data happened because multi risks on data by external or internal attackers. An important risk to take into consideration when speaking of the privacy of the stored transactions is represented by the transactions' information which is not in the owner's control. Such a case is represented by the cloud servers that are administered by cloud providers which cannot be wholly trusted by the users with sensitive, private data such as business plans or private information. A simple method for protecting data privacy is by applying certain privacy techniques onto transactions' data, followed by the upload of the modified data into the cloud. In this paper, we are proposing a case study that is built on levels containing three models: cloud's architecture, transaction's manager and clients. Moreover, we consider that our case study is based on the premise of zero trust among the three models, therefore all the transactions take place with third-parties and the data movements are realized going through various levels of security.
Population dynamic evolutionary algorithm for virtual routers running on multiprocessors system

This paper presents an evolutionary game model and proposes a dynamic evolutionary algorithm based on the model. We use the game model with numerous populations to analyze the dynamic selection course of the virtual routers running on multiprocessor systems, and the evolutionary equilibrium is regarded as the solution to this game. Our dynamic evolutionary algorithm is designed with the ability to make the whole system to converge at a stable state. The algorithm is equalizing on an equilibrium fixed point, in which each virtual router tries different processors, and changes the processor selection until a stable proportion distribution is formed. The experimental results show that the dynamic evolutionary approach has very fast convergence speed and is able to effectively balance loads among processors, guarantee fair usage of computing resources among virtual routers and maintain stable high-throughputs of the system.
Design of a UE-specific uplink scheduler for narrowband Internet-of-Things (NB-IoT) systems

Narrowband internet-of things (NB-IoT) is a 3GPP standard designed for Internet-of-Things (IoT) application. This paper presents the design consideration and possible options of a UE-specific uplink (UL) scheduler for NB-IoT system. We developed a unitary C emulation platform to verify the effectiveness of the proposed approaches, which is currently under integration within the OpenAirInterface NB-IoT project.
The Bergen 4-Day Treatment for Panic Disorder: A Pilot Study

The current article reports on the findings from a pilot treatment study on panic disorder (PD) with or without agoraphobia. Consecutively referred patients were included and treated with the Bergen 4-day treatment format. Twenty-nine patients were included, primarily from unsuccessful treatment courses in the Norwegian specialist mental health care system, either ongoing or previously. Prior to treatment, only 34% were able to work but at 3-month follow-up 93% were able to do so. The proportion achieving reliable change on the panic severity measure was 76% post-treatment and 90% at follow-up. The remission rate was 72% at both assessments. These effects are significantly higher than those reported for six standard CBT studies in the literature using the same primary outcome measure (Panic Disorder Severity Scale). It is concluded that the Bergen 4-day treatment is a promising treatment approach for PD, and a randomized controlled trial is warranted.
Perspectives on Social Robots: From the Historic Background to an Experts' View on Future Developments

Social robots are robots interacting with humans not only in collaborative settings, but also in personal settings like domestic services and healthcare. Some social robots simulate feelings (companions) while others just help lifting (assistants). However, they often incite both fascination and fear: what abilities should social robots have and what should remain exclusive to humans? We provide a historical background on the development of robots and related machines (1), discuss examples of social robots (2) and present an expert study on their desired future abilities and applications (3) conducted within the Forum of the European Active and Assisted Living Programme (AAL). The findings indicate that most technologies required for the social robots' emotion sensing are considered ready. For care robots, the experts approve health-related tasks like drawing blood while they prefer humans to do nursing tasks like washing. On a larger societal scale, the acceptance of social robots increases highly significantly with familiarity, making health robots and even military drones more acceptable than sex robots or child companion robots for childless couples. Accordingly, the acceptance of social robots seems to decrease with the level of face-to-face emotions involved.
Zero Linear Compressibility in Nondense Borates with a “Lu‐Ban Stool”‐Like Structure

Discovering materials that exhibit zero linear compressibility (ZLC) behavior under hydrostatic pressure is extremely difficult. To date, only a handful of ZLC materials have been found, and almost all of them are ultrahard materials with densified structures. Here, to explore ZLC in nondense materials, a structural model analogous to the structure of the “Lu‐Ban stool,” a product of traditional Chinese woodworking invented 2500 years ago, is proposed. The application of this model to borates leads to the discovery of ZLC in AEB2O4 (AE = Ca and Sr) with the unique “Lu‐Ban stool”‐like structure, which can obtain a subtle mechanical balance between pressure‐induced expansion and contraction effects. Coupled with the very wide ultraviolet transparent windows, the ZLC behavior of AEB2O4 may result in some unique but important applications. The applications of the “Lu‐Ban stool” model open a new route for pursuing ZLC materials in nondense structural systems.
Research on methods of improving customer profile in electric power marketing based on big data analysis of customer's electricity address

The paper is aimed at solving the problems of inconsistency, inaccuracy and non-real time of customer profile in the electric power marketing information system, and proposes the new methods of improving the customer profile in electric power marketing based on the big data analysis of customer's addresses. The core idea of the methods is that by the introduction of other industry data resources, the electricity address provided by electric power marketing information system and the customer address provided by other resources are analyzed with the big data technologies to achieve precise matching of these addresses. The address matching is followed by three steps: Chinese word segmentation with Hidden Markov Model algorithm, sentence similarity calculation based on the semantic and word order, and finally geographical coordinates matching for cross validation. Based on the matching results, the procedures of updating customer profile are processed respectively according to customer contact changes or changes in customer property rights, to achieve the consistency, accuracy and real-time data of customer profile. By implementing the automatic and intelligent operations of perfecting customer profile, the strong information support is provided for the marketing departments to enhance the “Internet+” electric power marketing services.
Effect of an Intervention Program Based on Active Video Games and Motor Games on Health Indicators in University Students: A Pilot Study

(1) Background: High levels of physical inactivity caused by sedentary digital screen leisure constitute one of the main causes of the high levels of obesity observed in today’s society; (2) Methods: The present study aims to analyse the effect of a 12-week intervention program based on the application of active video games and motor games on health status indicators, problematic use of video games, and resilience capacity in university students. Besides, the content blocks of the Physical Education (PE) field are worked on through these devices, revealing their potential as an Information and Communications Technology (ICT) resource. A longitudinal study with a pre-experimental design with pretest–posttest measurements in a single group (n = 47) was performed, using as main instruments a Tanita TBF300® bioimpedance scale, the 20mSRT test for maximum oxygen consumption (VO2max), the Adherence to a Mediterranean Diet Test (KIDMED), the Questionnaire for Experiences Related to Video games (QERV) and the Connor-Davidson Resilience Scale (CD-RISC); (3) Results: The main results were a discrete improvement in the percentage of fat mass and VO2max, representing a small effect size in both cases. The quality of the diet followed and the confidence and tolerance for adversity as a resilience factor were also improved, representing a medium size effect for this last variable; (4) Conclusions: Despite the limitations of this study as it does not have a control group, the main conclusions are that active video games and motor games can be a motivational resource to follow an active lifestyle, helping to improve health status indicators in young adults.
Characterization of GaN-HEMT in cascode topology and comparison with state of the art-power devices

The paper presents a fully static and dynamic characterization and also reliability investigations of a 650V, 28mΩ GaN-HEMT in Cascode-topology. To show the overall performance of GaN-HEMT the output current per chip area (A per mm2) versus switching frequency of a three phase inverter is presented for the 650V GaN-HEMT in comparison to 650V Si-IGBT3 (IFX) and Si-CooLMOS C7 (IFX, with fast Si-FWD and SiC-FWD).
AN EFFICIENT SYSTEM FOR THE ASYMMETRIC ACYLATION OF (R,S)-3-n-BUTYLPHTHALIDE CATALYZED BY NOVOZYME 435

Novozyme 435 could be a highly efficient catalyst in the asymmetric acylation of (R,S)-3-n-butylphthalide in tetrahydrofuran–hexane solvents. The effect of various reaction parameters such as agitation velocity, water content, mixed media, temperature, concentration of Novozyme 435, molar ratio of acetic anhydride to (R,S)-3-n-butylphthalide, reaction time, enantiomeric excess of substrate (eeS), enantiomeric excess of product (eeP), and enantioselective ratio (E) were studied. Tetrahydrofuran markedly improved (R,S)-3-n-butylphthalide conversion, enantiomeric excess of remaining 3-n-butylphthalide, and enantiomeric ratio. The optimum media were 50% (v/v) tetrahydrofuran and 50% (v/v) hexane. Other ideal reaction conditions were an agitation velocity of 150 rpm, 0.4% (v/v) water content, temperature of 30°C, 8 mg/mL dosage of Novozyme 435, 8:1 (0.4 mmol: 0.05 mmol) molar ratio of acetic anhydride to (R,S)-3-n-butylphthalide, and a reaction time of 48 hr. Under the optimum conditions, 96.4% eeS and 49.3% conversion of (R,S)-3-n-butylphthalide were achieved. In addition, enantiomeric excess of the product was above 98.0%.
A fast algorithm for mining temporal association rules based on a new definition

In literatures, there were several forms of definitions for temporal association rules which have different formulas for calculating support and confidence. In this paper, after reviewing the literatures, we first reform the definition of the association rule, and then give a general form of temporal association rule which was equipped with new formula for calculating its support and confidence. Based on the new definition, we propose a fast algorithm for mining temporal association rules. Experiments on a synthetic dataset and a real dataset exhibit the good performance of the new proposed algorithm.
Fast turbo codes using sub-block based interleaver

Information theory provides fundamental benchmarks based on which different communication systems can be compared. Given the channel model and transmission constraints, the information theory enables to compute rate at which reliable communication is possible. Once this rate or in other words the channel capacity is calculated, it is the task of system engineer to devise coding schemes that approach this capacity. Though the Shannon theory appears to be computationally feasible, still it was not practically implementable. The invention of turbo codes was established as an approach of reaching close to Shannon limit. The performance of turbo code depends largely on the design of interleaver. The bit error rate and delay incurred in encoding and decoding are highly influenced by the interleaver. In this paper, sub-blocking based interleaver architecture is proposed which can be extended to any existing interleaver structure. The advantage of sub-blocking the input frames is that the complexity of the interleaver reduces and consequently the execution time will be reduced drastically. In addition, a simultaneous processing of interleaving and de-interleaving can be achieved. In this paper, the said architecture is verified for block and 3GPP interleavers with different combinations. It is shown that a reasonable BER is achieved in very less time compared to all existing interleavers.
Protective effects of vitamin D on ischemia-reperfusion injury of the ovary in a rat model

Objective(s): The aim of the present study is to investigate probable acute effects of vitamin D on ischemia-reperfusion injury in the rat ovary. Materials and Methods: A group of 30 Wistar albino rats was divided into five groups of 6 each. Group 1: underwent laparotomy only and the ovaries were removed. Group 2: 3-hr ischemia followed by excision of the ovaries. Group 3: 3-hr ischemia and 3-hr reperfusion and the ovaries were removed. Group 4: vitamin D was administered 30 min prior to the 3-hr of ischemia and the ovaries were excised at the end of ischemia period. Group 5: vitamin D was administered 30 min prior to the 3-hr of ischemia and 3-hr reperfusion then the ovaries were removed at the end of reperfusion. The ovaries excised in each group also underwent biochemical and histopathologic analysis. MDA (malondialdehyde), SOD (superoxide dismutase), NO (nitric oxide), TAS (total antioxidant score), TOS (total oxidant score) were analyzed as biochemical parameters. Results: There were no significant differences between groups in TAS, TOS, or OSI (P>0.05). MDA levels were lower in the vitamin D treatment groups especially in group 5, significantly (P<0.05). In the histopathologic evaluation, we established that an improvement with vitamin D treatment. According to tissue injury scores, vascular congestion score was significantly different between group 3 and 5 (P<0.05). Conclusion: Vitamin D seems an effective molecule for protection of ischemia-reperfusion injury in rat ovary. There is some significant improvement in oxidative damages with vitamin D treatment.
Meglumine antimoniate intralesional infiltration for localised cutaneous leishmaniasis: a single arm, open label, phase II clinical trial

BACKGROUND Cutaneous leishmaniasis (CL) is a world-wide health problem which currently lacks effective, affordable and easy to use therapy. Recently, the meglumine antimoniate (MA) intralesional infiltration was included among the acceptable therapies for New World leishmaniasis. While this approach is attractive, there is currently little evidence to support its use in Americas. OBJECTIVES The aim of this study was to provide information about effectiveness and safety of a standardised MA intralesional infiltration technique for the treatment of CL. METHODS It is a single-arm phase II clinical trial conducted at a Brazilian referral centre. CL cases with parasitological confirmation presenting a maximum of three CL-compatible skin lesions were treated with weekly MA intralesional infiltration by using a validated technique, up to a maximum of eight infiltrations. RESULTS A total of 53 patients (62 lesions) were included. Overall, patients received a median of seven infiltrations (IQR25-75% 5-8) over a median treatment period of 43 days (IQR25-75% 28-52 days). The definitive cure rate at D180 was 87% (95% CI:77-96%). The majority of adverse events were local, with mild or moderate intensity. Bacterial secondary infection of the lesion site was observed in 13% of the treated patients, beside two intensity-three adverse events (hypersensitivity reactions).
Security Pattern Detection Using Ordered Matrix Matching

Security patterns implement security features in a software system. The missing or incomplete application of security patterns may produce vulnerabilities and invite attackers. Therefore, the detection of security patterns is the key to assuring security to software systems before release. In this paper, we propose a security pattern detection framework (SPDF) based on ordered matrix matching (OMM) technique. The framework provides a platform for data extraction, matching, and dictionary data checking. The experimental results show appropriate detection accuracy, reasonable time consumption, and zero false positives.
Context-Aware Pedestrian Motion Prediction In Urban Intersections

This paper presents a novel context-based approach for pedestrian motion prediction in crowded, urban intersections, with the additional flexibility of prediction in similar, but new, environments. Previously, Chen et. al. combined Markovian-based and clustering-based approaches to learn motion primitives in a grid-based world and subsequently predict pedestrian trajectories by modeling the transition between learned primitives as a Gaussian Process (GP). This work extends that prior approach by incorporating semantic features from the environment (relative distance to curbside and status of pedestrian traffic lights) in the GP formulation for more accurate predictions of pedestrian trajectories over the same timescale. We evaluate the new approach on real-world data collected using one of the vehicles in the MIT Mobility On Demand fleet. The results show 12.5% improvement in prediction accuracy and a 2.65 times reduction in Area Under the Curve (AUC), which is used as a metric to quantify the span of predicted set of trajectories, such that a lower AUC corresponds to a higher level of confidence in the future direction of pedestrian motion.
Email Sentiment Analysis Through k-Means Labeling and Support Vector Machine Classification

ABSTRACT Sentiment analysis for social media and online document has been a burgeoning area in text mining for the last decade. However, Email sentiment analysis has not been studied and examined thoroughly even though it is one of the most ubiquitous means of communication. In this research, a hybrid sentiment analysis framework for Email data using term frequency-inverse document frequency term weighting model for feature extraction, and k-means labeling combined with support vector machine classifier for sentiment classification is proposed. Empirical results indicate comparatively better classification results with the proposed framework than other combinations.