Miracle-dz/UniFAR-FTUs huggingface dataset:
Selective state retention design using symbolic simulation

Addressing both standby and active power is a major challenge in developing system-on-chip designs for battery-powered products. Powering off sections of logic or memories loses internal register and RAM states so designers have to weigh up the benefits and costs of implementing state retention on some or all of the power gated subsystems where state recovery has significant real-time or energy cost, compared to resetting the subsystem and re-acquiring state from scratch. Library IP and EDA tools can support state retention in hardware synthesized from standard RTL, but due to the silicon area costs there is strong interest in only retaining certain selective state for example the ldquoarchitectural staterdquo of a CPU to implement sleep modes. Currently there is no known rigourous technique for checking the integrity of selective state retention, and this is due to the complexity of checking that the correctness of the design is not compromised in any way. The complexity is exacerbated due to the interaction between the retained and the non-retained state, and exhaustive simulation rapidly becomes infeasible. This paper presents a case study based on symbolic simulation for assisting the designers to design and implement selective retention correctly. The main finding of our study is that the programmer visible state or the architectural state of the CPU needs to be implemented using retention registers whilst other micro-architectural enhancements such as pipeline registers, TLBs and caches can be implemented using normal registers without retention. This has a profound impact on power and area savings for chip design. By selectively retaining the state of the programmer's ldquoarchitecturalrdquo model and not the increasing proportion of extra state, one can incorporate energy-efficient sleep modes. To the best of our knowledge this is the first study in the area of rigourous design and implementation of selective state retention.
Towards on-line analytical mining in large databases

Great efforts have been paid in the Intelligent Database Systems Research Lab for the research and development of efficient data mining methods and construction of on-line analytical data mining systems.Our work has been focused on the integration of data mining and OLAP technologies and the development of scalable, integrated, and multiple data mining functions. A data mining system, DBMiner, has been developed for interactive mining of multiple-level knowledge in large relational databases and data warehouses. The system implements a wide spectrum of data mining functions, including characterization, comparison, association, classification, prediction, and clustering. It also builds up a user-friendly, interactive data mining environment and a set of knowledge visualization tools. In-depth research has been performed on the efficiency and scalability of data mining methods. Moreover, the research has been extended to spatial data mining, multimedia data mining, text mining, and Web mining with several new data mining system prototypes constructed or under construction, including GeoMiner, MultiMediaMiner, and WebLogMiner.This article summarizes our research and development activities in the last several years and shares our experiences and lessons with the readers.
The Case for the Web of Needs

E-marketplaces on the World Wide Web are information and transaction silos, which in the general case don't allow transactions across their boundaries. The consequence is that the Web, often termed the global marketplace, is fragmented along the dimensions of geography, content domain, supply or demand, user base, and many more. This fragmentation makes it inefficient to buy and sell commodities on the Web. We propose a framework that serves as a foundation for a distributed, de-centralized e-marketplace on top of the Web, making boundaries between existing systems disappear from the user's perspective. The framework standardizes the creation and description of objects that represent supply and demand. In addition to this, it allows for independent matching services to connect objects suitable for a transaction and it defines protocols for the message exchange between such objects.
Using systematic review in occupational safety and health

Evaluation of scientific evidence is critical in developing recommendations to reduce risk. Healthcare was the first scientific field to employ a systematic review approach for synthesizing research findings to support evidence-based decision-making and it is still the largest producer and consumer of systematic reviews. Systematic reviews in the field of occupational safety and health are being conducted, but more widespread use and adoption would strengthen assessments. In 2016, NIOSH asked RAND to develop a framework for applying the traditional systematic review elements to the field of occupational safety and health. This paper describes how essential systematic review elements can be adapted for use in occupational systematic reviews to enhance their scientific quality, objectivity, transparency, reliability, utility, and acceptability.
Getting patients to the right healthcare sources: from real-world questions to strategy hubs

To address the growing problem of novices accessing incomplete and unreliable information on the Web, this paper begins by probing the nature of strategic knowledge known by expert healthcare searchers. The analysis reveals the existence of a strategy that is focused to a specific type of healthcare question. To investigate whether there exist other similar strategies, we conduct two pilot studies. The first leads to the development of a taxonomy for skin cancer questions based on real-world questions. This taxonomy has high inter-rater agreement when tested with new real-world questions. The second pilot helps to identify 6 strategies that are specific to question types in the taxonomy. We demonstrate how these strategies can be made available to a wide range of users through a prototypical system referred to as a Strategy Portal. In conclusion, we briefly describe our current and future research to test if such a system can make patients more effective and efficient in the retrieval of reliable and relevant healthcare information on the Web.
A Deep Breath Bronchoconstricts Obese Asthmatics

Background: Asthma is characterized by the loss of a deep breath (DB)-induced bronchodilation and bronchoprotection. Obesity causes lung restriction and increases airway resistance, which may further worsen the capacity of a DB to induce bronchodilation; however, whether increasing BMI impairs the bronchodilatory response to a DB in asthmatics is unknown. Methods: The population consisted of 99 subjects, 87 with moderate to severe persistent asthma and 12 obese control subjects. Using transfer impedance we derived airway resistance (Raw). Participants breathed for 1 minute and took a slow DB followed by passive exhalation to functional residual capacity (FRC) and tidal breathing for another minute. Results: After a DB, obese asthmatics had the largest percent increase in Raw (median 9.8% interquartile range [IQR] 3.1–15.1), compared with overweight (6.5% IQR −1.3, 12.1) and lean (0.7% IQR −3, 7.9) asthmatics and obese controls (2.5% IQR –.6, 11) (p for trend = 0.008). The association between the percent increase in Raw after a DB and BMI as a continuous variable was significant (p = 0.02). Conclusions: In obese, moderate to severe and poorly controlled asthmatics, a DB results in increased Raw. This phenomenon was not observed in leaner asthmatics of similar severity or in obese control subjects.
Male Seminal Fluid Substances Affect Sperm Competition Success and Female Reproductive Behavior in a Seed Beetle

Male seminal fluid proteins are known to affect female reproductive behavior and physiology by reducing mating receptivity and by increasing egg production rates. Such substances are also though to increase the competitive fertilization success of males, but the empirical foundation for this tenet is restricted. Here, we examined the effects of injections of size-fractioned protein extracts from male reproductive organs on both male competitive fertilization success (i.e., P2 in double mating experiments) and female reproduction in the seed beetle Callosobruchus maculatus. We found that extracts of male seminal vesicles and ejaculatory ducts increased competitive fertilization success when males mated with females 1 day after the females’ initial mating, while extracts from accessory glands and testes increased competitive fertilization success when males mated with females 2 days after the females’ initial mating. Moreover, different size fractions of seminal fluid proteins had distinct and partly antagonistic effects on male competitive fertilization success. Collectively, our experiments show that several different seminal fluid proteins, deriving from different parts in the male reproductive tract and of different molecular weight, affect male competitive fertilization success in C. maculatus. Our results highlight the diverse effects of seminal fluid proteins and show that the function of such proteins can be contingent upon female mating status. We also document effects of different size fractions on female mating receptivity and egg laying rates, which can serve as a basis for future efforts to identify the molecular identity of seminal fluid proteins and their function in this model species.
Systematic Review Building a Preceptor Support System

This systematic review identifies the significance of the preceptor role in affecting new graduate nurse retention. Findings from 20 research studies provide support that nurse preceptors receiving continuing education and perceiving reward and recognition from the preceptor position positively affect new graduate nurse retention. Hospital administration, nurse managers, nurse educators, preceptors, and new graduate nurses each play a role in the successful implementation of a preceptor support system.
Clustering Uncertain Data with Possible Worlds

The topic of managing uncertain data has been explored in many ways. Different methodologies for data storage and query processing have been proposed. As the availability of management systems grows, the research on analytics of uncertain data is gaining in importance. Similar to the challenges faced in the field of data management, algorithms for uncertain data mining also have a high performance degradation compared to their certain algorithms. To overcome the problem of performance degradation, the MCDB approach was developed for uncertain data management based on the possible world scenario. As this methodology shows significant performance and scalability enhancement, we adopt this method for the field of mining on uncertain data. In this paper, we introduce a clustering methodology for uncertain data and illustrate current issues with this approach within the field of clustering uncertain data.
Antiproliferation effect of imatinib mesylate on MCF7, T-47D tumorigenic and MCF 10A nontumorigenic breast cell lines via PDGFR-β, PDGF-BB, c-Kit and SCF genes

Recent cancer molecular therapies are targeting main functional molecules to control applicable process of cancer cells. Attractive targets are established by receptor tyrosine kinases, such as platelet-derived growth factor receptors (PDGFRs) and c-Kit as mostly irregular signaling, which is due to either over expression or mutation that is associated with tumorigenesis and cell proliferation. Imatinib mesylate is a selective inhibitor of receptor tyrosine kinase, including PDGFR-β and c-Kit. In this research, we studied how imatinib mesylate would exert effect on MCF7 and T-47D breast cancer and MCF 10A epithelial cell lines, the gene and protein expression of PDGFR-β, c-Kit and their relevant ligands platelet-derived growth factor (PDGF)-BB and stem cell factor (SCF). The MTS assay was conducted in therapeutic relevant concentration of 2–10 µM for 96, 120 and 144 h treatment. In addition, apoptosis induction and cytostatic activity of imatinib mesylate were investigated with the terminal deoxynucleotidyl transferase dUTP nick end labeling TUNEL and cell cycle assays, respectively, in a time-dependent manner. Comparative real-time PCR and Western blot analysis were conducted to evaluate the expression and regulation of imatinib target genes and proteins. Our finding revealed that imatinib mesylate antiproliferation effect, apoptosis induction and cytostatic activity were significantly higher in breast cancer cell lines compared to MCF 10A. This effect might be due to the expression of PDGFR-β, PDGF-BB, c-Kit and SCF, which was expressed by all examined cell lines, except the T-47D cell line which was not expressed c-Kit. However, examined gene and proteins expressed more in cancer cell lines. Therefore, imatinib mesylate was more effective on them. It is concluded that imatinib has at least two potential targets in both examined breast cancer cell lines and can be a promising drug for targeted therapy to treat breast cancer.
Document-level re-ranking with soft lexical and semantic features for statistical machine translation

We introduce two document-level features to polish baseline sentence-level translations generated by a state-of-the-art statistical machine translation (SMT) system. One feature uses the word-embedding technique to model the relation between a sentence and its context on the target side; the other feature is a crisp document-level token-type ratio of target-side translations for source-side words to model the lexical consistency in translation. The weights of introduced features are tuned to optimize the sentence- and document-level metrics simultaneously on the basis of Pareto optimality. Experimental results on two different schemes with different corpora illustrate that the proposed approach can efficiently and stably integrate document-level information into a sentence-level SMT system. The best improvements were approximately 0.5 BLEU on test sets with statistical significance.
Robust electroencephalogram phase estimation with applications in brain-computer interface systems

Objective: In this study, a robust method is developed for frequency-specific electroencephalogram (EEG) phase extraction using the analytic representation of the EEG. Based on recent theoretical findings in this area, it is shown that some of the phase variations—previously associated to the brain response—are systematic side-effects of the methods used for EEG phase calculation, especially during low analytical amplitude segments of the EEG. Approach: With this insight, the proposed method generates randomized ensembles of the EEG phase using minor perturbations in the zero-pole loci of narrow-band filters, followed by phase estimation using the signal’s analytical form and ensemble averaging over the randomized ensembles to obtain a robust EEG phase and frequency. This Monte Carlo estimation method is shown to be very robust to noise and minor changes of the filter parameters and reduces the effect of fake EEG phase jumps, which do not have a cerebral origin. Main results: As proof of concept, the proposed method is used for extracting EEG phase features for a brain computer interface (BCI) application. The results show significant improvement in classification rates using rather simple phase-related features and a standard K-nearest neighbors and random forest classifiers, over a standard BCI dataset. Significance: The average performance was improved between 4–7% (in absence of additive noise) and 8–12% (in presence of additive noise). The significance of these improvements was statistically confirmed by a paired sample t-test, with 0.01 and 0.03 p-values, respectively. The proposed method for EEG phase calculation is very generic and may be applied to other EEG phase-based studies.
Size-Estimation Framework with Applications to Transitive Closure and Reachability

Computing the transitive closure in directed graphs is a fundamental graph problem. We consider the more restricted problem of computing the number of nodes reachable from every node and the size of the transitive closure. The fastest known transitive closure algorithms run inO(min{mn,n2.38}) time, wherenis the number of nodes andmthe number of edges in the graph. We present anO(m) time randomized (Monte Carlo) algorithm that estimates, with small relative error, the sizes of all reachability sets and the transitive closure. Another ramification of our estimation scheme is a O(m) time algorithm for estimating sizes of neighborhoods in directed graphs with nonnegative edge lengths. Our size-estimation algorithms are much faster than performing the respective explicit computations.
A Robust Content in DCT Domain for Image Authentication

Discrete cosine transform (DCT) coefficients of a natural image can be statistically modeled as the generalized Gaussian distribution (GGD) whose shape parameters can be estimated by the maximum likelihood (ML) estimation method. This paper presents a novel image authentication scheme based on the robust content in DCT domain, where a new concept robust feature is extracted using the modified ML principle. Our simulation results show that the proposed method can resist most content-preserving operations such as JPEG compression, brightness enhancement, histogram equalization, filtering, scaling, and rotation with small angles.
The phytoestrogen genistein induces thymic and immune changes: A human health concern?

Use of soy-based infant formulas and soy/isoflavone supplements has aroused concern because of potential estrogenic effects of the soy isoflavones genistein and daidzein. Here we show that s.c. genistein injections in ovariectomized adult mice produced dose-responsive decreases in thymic weight of up to 80%. Genistein's thymic effects occurred through both estrogen receptor (ER) and non-ER-mediated mechanisms, as the genistein effects on thymus were only partially blocked by the ER antagonist ICI 182,780. Genistein decreased thymocyte numbers up to 86% and doubled apoptosis, indicating that the mechanism of the genistein effect on loss of thymocytes is caused in part by increased apoptosis. Genistein injection caused decreases in relative percentages of thymic CD4+CD8− and double-positive CD4+CD8+ thymocytes, providing evidence that genistein may affect early thymocyte maturation and the maturation of the CD4+CD8− helper T cell lineage. Decreases in the relative percentages of CD4+CD8− thymocytes were accompanied by decreases in relative percentages of splenic CD4+CD8− cells and a systemic lymphocytopenia. In addition, genistein produced suppression of humoral immunity. Genistein injected at 8 mg/kg per day produced serum genistein levels comparable to those reported in soy-fed human infants, and this dose caused significant thymic and immune changes in mice. Critically, dietary genistein at concentrations that produced serum genistein levels substantially less than those in soy-fed infants produced marked thymic atrophy. These results raise the possibility that serum genistein concentrations found in soy-fed infants may be capable of producing thymic and immune abnormalities, as suggested by previous reports of immune impairments in soy-fed human infants.
Quality of Life, Health and Happiness

The basic work for this book was carried out during the spring of 1989 in Edinburgh, where I had been granted a research position at The Institute for Advanced Studies in the Humanities. I should like to express here my indebtedness to the Institute for the opportunity thus afforded me. I should also like to say how very grateful I am for the stimulating conversations I had there with Professor Timothy Sprigge and Dr. Elizabeth Telfer. Dr. Telfers’s own treatise Happiness (1980) has been a major influence on my view of the questions involved.The basic view of health and illness presented in this book is more fully set out in my On the Nature of Health (1987). As in the case of my previous larger projects, I have received a great amount of support and may wise comments from Professor Ingmar Porn, Helsinki. Three Danish experts – Anton Aggernaes, Erik Ostenfeld and Peter Sandoe – have made valuable comments. Professor Heng ten Have, Nijmegen, has improved my reading of the philosophy of Jeremy Bentham. I should also like to thank my colleagues at the Department of Health and Society, University of Linkoping, for helping me to avoid a number of the pitfalls that can so easily stumble into when it comes to a treatise like this. Especially I should like to mentioned Per-Erik Liss, Ingemar Nordin and Bo Petersson, all three of whom have read and commented on the entire manuscript.A Swedish version of this book, Livskvalitet och halsa, came out in 1991. I have been made quite a number of corrections and additions, one type of addition being replies to critical points made in reviews of the Swedish version.I should like to thank Malcolm Forbes for valuable help putting my English into publishable condition.Linkoping, May 1993Lennart Noredenfelt
Preliminary study of intensity weighted region-of-interesting image reconstruction using iterative algorithm

Sparse-view CT inspired by a compressive sensing (CS) theory, which acquires sparsely sampled data in projection angles to reconstruct volumetric images of the scanned object, is under active research for low-dose imaging. Also, region of interest (ROI) imaging method is one of the reasonable approaches to reducing the integral dose to the patient and the risk of overdose. In this study, we combined the two approaches together to achieve an ultra-low-dose imaging: a sparse-view imaging and the intensity-weighted region-of-interest (IWROI) imaging. IWROI imaging technique is particularly interesting because it can reduce the imaging radiation dose substantially to the structures away from the imaging target, while allowing a stable solution of the reconstruction problem in comparison with the interior problem. We used a total-variation (TV) minimization algorithm that exploits the sparseness of the image derivative magnitude and can reconstruct images from sparse-view data. In this study, we implemented an imaging mode that combines a sparse-view imaging and an ROI imaging. We obtained promising results and believe that the proposed scanning approach can help reduce radiation dose to the patients while preserving good quality images for applications such as image-guided radiation therapy. We are in progress of applying the method to the real data.