Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Research of under-Voltage Protection Circuit for Motor Driver Chip Based on Special Integrated Chip

Intelligent power integrated circuit chips play an increasingly important role in industrial automation, domestic medical appliances, automotive electronics, especially in modern military, aerospace and other fields. Based on the analysis of the current front-end verification problem of digital application specific integrated chip, the composition and working principle of motor drive chip, the design and composition technology of undervoltage protection function module and the perfect protection circuit not only ensure that the chip can work normally under some harsh conditions, but also play a vital role in the safety of the whole system sometimes. After the motor chip is verified by the flow sheet, packaging, testing and test result analysis are carried out to further predict and adjust the function and reliability of the motor chip. On the basis of analyzing the current front-end verification problem of digital application specific integrated chip, the circuit structure is simple, no additional bandgap reference circuit is needed, and the voltage comparator circuit is also omitted.
LUT-based high-speed point multiplier for Goldilocks-Curve448

Recent studies have shown that existing elliptic curve-based cryptographic standards provide backdoors for manipulation and hence compromise the security. In this regard, two new elliptic curves known as Curve448 and Curve25519 are recently recommended by IETF for transport layer security future generations. Hence, cryptosystems built over these elliptic curves are expected to play a vital role in the near future for secure communications. A high-speed elliptic curve cryptographic processor (ECCP) for the Curve448 is proposed in this study. The area of the ECCP is optimised by performing different modular operations required for the elliptic curve Diffie–Hellman protocol through a unified architecture. The critical path delay of the proposed ECCP is optimised by adopting the redundant-signed-digit technique for arithmetic operations. The segmentation approach is introduced to reduce the required number of clock cycles for the ECCP. The proposed ECCP is developed using look-up-tables (LUTs) only, and hence it can be ported to any field-programmable gate array family or standard ASIC libraries. The authors' ECCP design offers higher speed without any significant area overhead to recent designs reported in the literature.
Natural Language Questions for Semantic Web-Based News Aggregator

— The impressive growth of the Web in the last decade has made it becomes one of the most popular news sources. Web-users nowadays can access an unlimited amount of news items but only a subset of them meets their interest. The existing news systems on Web reveal more and more limitations in information search because news items are presented only for human consumption. This paper presents BKSport, a sports news aggregation system that provides users with the ability to find relevant news articles through queries that are formulated in natural language. Our contribution consists of a system development approach, which is totally based on Semantic Web technologies. First, semantic annotations about news item are created using an ontology and knowledgebase for sports domain. Additionally, we propose a method to transform natural language questions into SPARQL queries to carry out semantic search on these semantic annotations. Last, the system has been positively evaluated with respect to precision, based on a set of pre-defined questions belonging to various categories.
The Sleep Quality of Breast Cancer Patients

The quality of sleep is required by breast cancer patients to regenerate and repair the body cells. When patients’ sleep is disturbed, it may be affected to the physiological conditions, such as decreased appetite, weight loss, anxiety, irritability, and changes in natural and cellular immune functions. Breast cancer therapies can affect the quality of sleep. This study aimed to determine the sleep quality of breast cancer patients that had treatments in a public hospital in Bandung. This research used the quantitative descriptive approach. The sample was selected using the consecutive sampling technique (n = 31). Data were collected using the Pittsburgh Sleep Quality Index (PSQI) questionnaire. Sleep quality was categorized as good when the total score was ≤ 5, and sleep quality was poor when the total score was > 5. The results of this study indicated that all respondents (100%) had poor sleep quality. The components that contributed to the assessment were sleep latency, sleep duration, sleep efficiency, and daytime dysfunction. The worst sleep quality with the highest score (18) occurred in respondents who had radiotherapy and mastectomy (2 persons), and respondents in advanced stage (3 persons). This study concludes that the pharmacological therapies and the stages of cancer contributed to the sleep quality of breast cancer patients. It is expected that health professionals and hospitals notice the patient’s sleeping needs during treatment at the hospital.
A fast file system for UNIX

A reimplementation of the UNIX TM file system is described. The reimplementation provides substantially higher throughput rates by using more flexible allocation policies that allow better locality of reference and can be adapted to a wide range of peripheral and processor characteristics. The new file system clusters data that is sequentially accessed and provides two block sizes to allow fast access to large files while not wasting large amounts of space for small files. File access rates of up to ten times faster than the traditional UNIX file system are experienced. Long-needed enhancements to the programmers' interface are discussed. These include a mechanism to place advisory locks on files, extensions of the name space across file systems, the ability to use long file names, and provisions for administrative control of resource usage.
Doppio – A ROMS-based Circulation Model for the Mid-Atlantic Bight and Gulf of Maine: Configuration and comparison to integrated coastal observing network observations

We describe “Doppio”, a ROMS-based (Regional Ocean Modeling System) model of the Mid-Atlantic Bight and Gulf of Maine regions of the northwestern North Atlantic developed in anticipation of future applications to biogeochemical cycling, ecosystems, estuarine downscaling, and near-real-time forecasting. This free-running regional model is introduced with circulation simulations covering 2007– 2017. The ROMS configuration choices for the model are detailed, and the forcing and boundary data choices are described and explained. A comprehensive observational data set is compiled for skill assessment from satellites and in situ observations from regional associations of the U.S. Integrated Ocean Observing Systems, including moorings, autonomous gliders, profiling floats, surface-current-measuring coastal radar, and fishing fleet sensors. Doppio’s performance is evaluated with respect to these observations by representation of subregional temperature and salinity error statistics, as well as velocity and sea level coherence spectra. Model circulation for the Mid-Atlantic Bight and Gulf of Maine is visualized alongside the mean dynamic topography to convey the model’s capabilities.
CSMO-DSE

Determining the optimal microarchitecture configuration of a processor at the early stages of design is undeniably a challenge. Due to many parameters at the microarchitecture level, finding the proper combination of these parameters to arrive at a balanced design is difficult. Application-specific Design Space Exploration (DSE) is even more difficult, since the property of application needs to be considered during the DSE process. Improving the speed and accuracy of the DSE process remains a particular challenge in microprocessor design. In this article, we propose a novel processor DSE methodology based on criticality and sensitivity analysis, named Criticality and Sensitivity-based Multi-Objective DSE (CSMO-DSE). In our methodology, a dependence-graph is derived from the profile generated by running a program on an instrumented cycle-accurate microprocessor simulator. Then, the criticality of the processor’s performance events is obtained through critical path analysis. The sensitivity of microarchitecture parameters to various performance events is also analyzed. Then, this information is used to optimize performance, power/area, and energy efficiency of the design. Experiments with SPEC 2006 show that CSMO-DSE methodology is 4.73× faster than the baseline DSE methodology and that the quality of result (QoR) is better than the baseline methodology for all the benchmark programs.
A Physics Lesson Designed According to 7E Model with the Help of Instructional Technology (Lesson Plan).

Students enter the classrooms with a preexisting knowledge of science concepts. These science concepts sometimes show inconsistency with the accepted ones by the scientists and called as misconceptions. Studies applied science field have to get possession of abilities that not only detect these misconceptions also help to solve these problems. Hence, instructional methods that correct students‘ misconceptions become important. In this sense, a material related to the physics course is designed according to 7E model with the help of instructional technology.
A Survey: Prediction of Rating Based on Social Sentiment from Textual Reviews

In recent years, shopping online is becoming moreand more popular. When its needed to decide whether to purchase a product or not on-line, the opinions of others become important. Product or service retrieval from the huge data becomes very trouble, so users review and ratings are considered as a major point for recommendation and filtering. But, the user’s reviews are very high and this need a lot of time to take decision from the reviews. So, there is a need to summarize the reviews with finding sentiment analysis. This paper presents a survey on various Sentiment Analysis and mining techniques with different applications. From the comparative study, the new and optimal method can be detected and used for web app recommendation with Rating Prediction from huge set of text reviews.
Placental changes in hypertensive pregnancy: a comparison with normotensive pregnancy

Background: Hypertensive pregnancy may be responsible for vascular damage, enhanced systemic inflammation and insulin resistance in the placenta as oxygen and nutrient transfer is impaired and oxidative stress is generated affecting the placental growth and development. Placental growth pattern in hypertensive pregnancies shows a variable pattern owing to placental insufficiency. Present study was done to investigate the morphological and histological changes in placenta in hypertensive pregnancy. Methods: A total of 42 pregnant women with hypertensive disorder with gestational age 28-42 weeks and singleton pregnancy were enrolled as cases in the study. A total of 42 matched normotensive pregnant women were enrolled as controls. All the women were followed up till delivery. At delivery, placental specimen were collected and assessed for morphological, morphometric and histological changes. Findings were compared with normotensives. Data was compared using Independent sample’s ‘t’-test and Chi-square test. Results: Mean age of cases was 27.60±4.37 years, majority were gravida 1/2 (66.7%), 45.2% had moderate to severe edema, 50% had urinary albumin levels >100 mg/dl. A total of 8 (19.0%) had gestational hypertension, 16 (38.1%) had preeclampsia, 10 (23.8%) had severe preeclampsia and 8 (19.0%) had eclampsia. Mean placental weight and diameter of cases was significantly higher than that of control group. Mean placental thickness was also higher but difference was not significant statistically. Calcification, infarction and hematoma were seen in 45.2%, 16.7% and 11.9% of cases as compared to 28.6%, 4.97% and 0% of controls. Histologically, syncytial knots, cytotrophoblastic cellular proliferation, hyalinized area, proliferation of medium sized blood vessels, stromal fibrosis and fibrinoid necrosis in significantly higher proportion of cass as compared to controls (p<0.05). Mean fetoplacental ratio was 5.01±0.99 and 5.24±0.61 in controls (p=0.195). Conclusions: Hypertension during pregnancy affects the placental growth and development.
A Neural Network approach to Automated Essay Scoring: A Comparison with the Method of Integrating Deep Language Features using Coh-Metrix

Automated essay scoring (AES) has emerged as a secondary or as a sole marker for many high-stakes educational assessments due to remarkable advances in feature engineering using natural language processing, machine learning, and deep learning algorithms. The purpose of the study was to compare the effectiveness and the performance of two AES frameworks, each based on machine learning with deep language features and deep learning algorithms. More specifically, support vector machines (SVMs) in conjunction with Coh-Metrix features were used for a traditional AES model development and the convolutional neural networks (CNNs) approach was used for deep learning model development. Then, the strengths and weaknesses of the models under different circumstances (e.g., types of scoring rubric, length of essay, and essay type) were tested. The results were evaluated using the Quadratic Weighted Kappa (QWK) score and compared with the agreement between the human raters. The results indicated that the CNNs model performs better, producing more comparable results to the human raters than the Coh-Metrix + SVMs model. Moreover, our best models could achieve state-of-the-art performance in most of the essay sets with a high average QWK score.
Analysis of Molecular Resistance Mechanisms in Helicoverpa armigera (Hübner) (Noctuidae: Lepidoptera) Populations Under Pyrethroid Stress in Turkey

Helicoverpa armigera (Hubner) (Lepidoptera: Noctuidae) is a major pest of economically important crops such as cotton, tomato and soybean. In order to control this pest, pyrethroid insecticides have been extensively used in farming areas all over the world. However, applications of excessive amounts of these insecticides can result in resistance development in the field populations of H. armigera. Resistance to the pyrethroids, beta-cypermethrin and lambda cyhalothrin, was analysed using bioassays. It was found that a Canakkale field population of H. armigera field showed low (2.1-fold) and moderate (14.5-fold) resistance levels for beta-cypermethrin and lambda-cyhalothrin, respectively. Furthermore, expressions of selected CYP450, GST and esterase genes of H. armigera Canakkale field populations were compared to those of a susceptible strain using real-time PCR. Our results indicate that H. armigera reacts to pyrethroids mainly by increasing expression levels of CYP450s such as CYP9A12 and CYP9A14. However, GST and esterase genes expression levels were not significantly altered in a field population. GSTs and esterases were also analyzed using biochemical assays. While GSTs and esterase genes were not found to be up-regulated in the real-time PCR, except GST-DCNB activity, the biochemical assays also showed no significant increases in enzyme activities in the Canakkale field population as compared to the susceptible strain. Consequently, CYP9A12 and CYP9A14 together with certain GSTs, catalyzing DCNB substrate, are proposed to be involved in the metabolic responses against beta-cypermethrin and lambda-cyhalothrin insecticides in field population of H. armigera from Turkey.
Biomarkers of Metabolic Syndrome in Male Cigarette Smokers in Calabar

Background: There is an increasing but controversial evidence that smoking is associated with metabolic syndrome. Metabolic syndrome has recently attracted much attention due to increasing knowledge of its relationship with cardiovascular mortality and morbidity and other associated problems. Aim: This study assessed the biomarkers and frequency of metabolic syndrome as defined by the World Health Organization (WHO), International Diabetes Foundation (IDF) and the National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III) in adult male smokers. Methods: One hundred and forty one (141) apparently healthy male cigarette smokers and sixty (60) apparently healthy nonsmokers aged 18 to 45 years were recruited for the study. The smokers were subdivided into light (< 8 pack years), moderate (8-30 pack years) and heavy (> 30 pack years) smokers. Body mass index (BMI), waist circumference (WC), hip circumference, waist-hip ratio, systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured. Fasting blood sugar (FBS), total cholesterol (TC), triglycerides (TG) and high density lipoprotein-cholesterol (HDL-C) were estimated using colorimetric test methods while low density lipoprotein-cholesterol (LDL-C) and very low density lipoprotein (VLDL-C) were calculated using the Friedewald's equation. Serum insulin was estimated using enzyme linked immunosorbent assay. Insulin resistance was calculated using homeostasis model assessment of insulin resistance (HOMA-IR). Data were analyzed using Student's t-test and analysis of variance; P < 0.05 was considered statistically significant. Results: The smokers had significantly higher diastolic BP ( P = 0.0001), TC ( P = 0.008) and LDL-C ( P = 0.0001) and significantly lower HDL-C ( P = 0.0001) compared with the controls. There were no significant differences in the other parameters. Fasting blood sugar was significantly higher in the light smokers ( P = 0.001) than in the moderate and heavy smokers whereas, serum TC and LDL-C levels were significantly higher in heavy smokers ( P = 0.001) than in the light and moderate smokers. There were no significant variations in the other parameters among the groups. The percentage of smokers with metabolic syndrome was significantly higher than nonsmokers using the IDF ( P = 0.022) and NCEP-ATP III ( P = 0.032) criteria with dyslipidaemia being the most prevalent metabolic abnormality. Conclusion: The unfavorable changes in the lipid profile and blood pressure observed in this study may predispose smokers to a higher risk of cardiovascular disease and there is a higher frequency of metabolic syndrome among smokers in Calabar compared with the nonsmokers.
Significance of the norovirus GII.4 genotype as a cause of acute gastroenteritis in Finnish children, and the production of a candidate virus-like particle vaccine

11 Tiivistelmä . 13 Introduction . 15 1 Review of the literature . 17 1.1 Characterization of human noroviruses . 17 1.1.1 History of noroviruses . 17 1.1.2 Norovirus genome structure . 18 1.1.2.1 Nonstructural proteins . 19 1.1.2.2 Structural proteins . 20 1.1.3 Norovirus classification . 22 1.1. 4 Genetic variability . 22 1.1. 5 Laboratory diagnosis from past to present . 23 1.1. 5.1 Electron microscopy . 23 1.1. 5.2 Immunoassays . 24 1.1. 5.3 Reverse-transcriptase polymerase chain reaction . 24 1.1. 5.4 Genetic analyses. 24 1.2 Norovirus life cycle . 26 1.2.1 Host attachment factors and viral entry . 26 1.2.2 Protein translation and replication. 27 1.2. 3 Assembly and exit . 28 1.3 Burden of disease and norovirus epidemiology . 30 1.3. 1 Clinical and epidemiological features of norovirus infection . 31 1.3. 1.1 Symptoms . 31 1.3. 2 Transmission . 33
Adaptive tracking algorithm based on target moving speed

To solve the problem of tracking failure caused by fast object movement, we proposed an adaptive tracking algorithm based on object movement speed on the basis of ECO-HC (ECO for hand-crafted feature version). First, correlation filtering method was used to obtain the distance of the maximum response point of adjacent frames. Then the speed of the object was judged by the distance of the maximum response point of the adjacent frame. Then the number of scale filter factors and interval frames updated by the template were adjusted on the basis of the object’s speed. The comparative experiment on the VOT2016 benchmarks showed that our tracker improved the accuracy and robustness of object tracking.
Machine Learning Frameworks for Automated Software Testing Tools : A Study

Increased use of software and complexity of software functions, as well as shortened software quality evaluation periods, have increased the importance and necessity for automation of software testing. Automating software testing by using machine learning not only minimizes errors in manual testing, but also allows a speedier evaluation. Research on machine learning in automated software testing has so far focused on solving special problems with algorithms, leading to difficulties for the software developers and testers, in applying machine learning to software testing automation. This paper, proposes a new machine learning framework for software testing automation through related studies. To maximize the performance of software testing, we analyzed and categorized the machine learning algorithms applicable to each software test phase, including the diverse data that can be used in the algorithms. We believe that our framework allows software developers or testers to choose a machine learning algorithm suitable for their purpose.
A phase II study of a yeast-based therapeutic cancer vaccine, GI-6207, targeting CEA in patients with minimally symptomatic, metastatic medullary thyroid cancer.

TPS3127 Background: Saccharomyces cerevisiae has been genetically modified to express CEA protein and developed under a CRADA with GlobeImmune/NCI as a heat-killed immune-stimulating, therapeutic cancer vaccine (GI-6207). A phase I study with GI-6207 demonstrated safety, biomarker stabilization and enhanced immune response in some patients. CEA is over-expressed in multiple malignancies, including medullary thyroid cancer (MTC). Two therapies recently approved by the FDA for metastatic MTC (vandetanib, cabozantinib) come with toxicity and should be reserved for symptomatic/progressive disease. However, a large population of asymptomatic MTC patients has small tumor burden and/or disease that is more indolent. The standard management of these patients is observation. Preliminary data suggest that tumor growth measured by the rate of CEA and calcitonin increase can be quantified in a 3-6 months. Retrospective data from prostate cancer studies suggest vaccines can alter growth rates within 3-4 months. We hyp.
Coupling and monotonicity of queueing processes

The main purpose of this work is to give a survey of main monotonicity properties of queueing processes based on the coupling method. The literature on this topic is quite extensive, and we do not consider all aspects of this topic. Our more concrete goal is to select the most interesting basic monotonicity results and give simple and elegant proofs. Also we give a few new (or revised) proofs of a few important monotonicity properties for the queue-size and workload processes both in single-server and multi- server systems. The paper is organized as follows. In Section 1, the basic notions and results on coupling method are given. Section 2 contains known coupling results for renewal processes with focus on construction of synchronized renewal instants for a superposition of independent renewal processes. In Section 3, we present basic monotonicity results for the queue-size and workload processes. We consider both discrete-and continuous-time queueing systems with single and multi servers. Less known results on monotonicity of queueing processes with dependent service times and interarrival times are also presented. Section 4 is devoted to monotonicity of general Jackson-type queueing networks with Markovian routing. This section is based on the notable paper [17]. Finally, Section 5 contains elements of stability analysis of regenerative queues and networks, where coupling and monotonicity results play a crucial role to establish minimal suficient stability conditions. Besides, we present some new monotonicity results for tandem networks.