Miracle-dz/UniFAR-FTUs huggingface dataset:
Control-Flow Speculation through Value Prediction

In this paper, we introduce a new branch predictor that predicts the outcome of branches by predicting the value of their inputs and performing an early computation of their results according to the predicted values. The design of a hybrid predictor comprising the above branch predictor and a correlating branch predictor is presented. We also propose a new selector that chooses the most reliable prediction for each branch. This selector is based on the path followed to reach the branch. Results for immediate updates show significant misprediction rate reductions with respect to a conventional hybrid predictor for different size configurations. In addition, the proposed hybrid predictor with a size of 8 KB achieves the same accuracy as a conventional one of 64 KB. Performance evaluation for a dynamically scheduled superscalar processor, with realistic updates, shows a speed up of 8 percent despite its higher latency (up to four cycles).
A Formal Semantics for Data Analytics Pipelines

In this report, we present a new programming model based on Pipelines and Operators, which are the building blocks of programs written in PiCo, a DSL for Data Analytics Pipelines. In the model we propose, we use the term Pipeline to denote a workflow that processes data collections -- rather than a computational process -- as is common in the data processing community. The novelty with respect to other frameworks is that all PiCo operators are polymorphic with respect to data types. This makes it possible to 1) re-use the same algorithms and pipelines on different data models (e.g., streams, lists, sets, etc); 2) reuse the same operators in different contexts, and 3) update operators without affecting the calling context, i.e., the previous and following stages in the pipeline. Notice that in other mainstream frameworks, such as Spark, the update of a pipeline by changing a transformation with another is not necessarily trivial, since it may require the development of an input and output proxy to adapt the new transformation for the calling context. In the same line, we provide a formal framework (i.e., typing and semantics) that characterizes programs from the perspective of how they transform the data structures they process -- rather than the computational processes they represent. This approach allows to reason about programs at an abstract level, without taking into account any aspect from the underlying execution model or implementation.
Graphical representation of the significant 6R KUKA robots spaces

Trajectory planning for serial 6 degree of freedom (DOF) machinery systems is demanding due to complex kinematic structure which affects the machinery tool fame, position, orientation and singularity. These three characteristics represent the key elements for production planning and layout design of the manufacturing systems. Both, simple and complex machine trajectory is defined as series of connected points in 3D space. Each point is defined with its position and orientation related to the machine's base frames. To visualize the machine's reachable space, the work envelope is calculated and graphically presented as very well known machine's property. A methodology to predetermine regions of feasible tool orientation (work window) is analytically and graphically presented. The work envelope boundary is generated using the filtering points algorithm, while work window is generated using either empirical or analytical methods. The singularity regions are calculated by finding the determinant of the reconfigurable Jacobian matrix. These three tool path characteristics represent three different spaces which are identified both analytically and graphically and plotted in Cartesian space using MATLAB tools. The singularity regions will be represented within the workspace and work window for a single machinery kinematic structure. The KUKA KR robot family is used as a case study.
Predicting Hospital-Acquired Acute Kidney Injury—A Case-Controlled Study

Acute kidney injury is a major complication of hospitalization, occurring in 5–7 percent of hospitalized patients. The patient characteristics and prognostic variables that help predict acute kidney injury have not been studied in the general hospitalized population. The objectives of this study are to derive and validate a predictive score for hospital-acquired acute kidney injury (HAKI). We conducted a case-controlled study of HAKI involving 180 cases and 360 controls. A multivariate logistic regression model was developed in two-thirds of the subjects and validated in the other third. Upon admission, cases in the developmental sample were older (67 vs. 63 yrs, p = .008) and more likely to have diabetes (51% vs. 35%; p = .003), hypertension (77% vs. 60%, p = .001), heart failure (34% vs. 20%, p = .004), blood urea nitrogen ≥25 mg/dL (38% vs. 20%, p = <.001), creatinine ≥1.1 mg/dL (65% vs. 39%; p <.001), albumin ≤4 g/dL (85% vs. 71%; p = .033), and bicarbonate <24 mEq/L or >30 mEq/L (42% vs. 29%; p = .05) compared to controls. The final risk score included pulse, bicarbonate, creatinine, and specific medications (NSAIDs, ACE inhibitors, ARBs, and/or diuretics). The c-statistic for the risk score in the developmental sample was 0.69. In the validation sample, an increasing number of risk factors was associated with increased risk of HAKI (16% and 62% in the low and high-risk groups, respectively). In conclusion, a simple model based on readily available data stratifies patients according to their risk of developing HAKI and may guide clinical decision making and provide a basis for further research into HAKI.
Weight gain during olanzapine treatment for psychotic depression: effects of dose and age

Weight gain has often been associated with olanzapine treatment, yet little is known about the influence of patient age or cumulative dose on olanzapine-associated weight gain. The first 118 participants in the National Institutes of Mental Health Study of the Pharmacotherapy of Psychotic Depression randomized clinical trial (Clinical Trials.gov Registration NCT00056472) completing at least 4 weeks of treatment with olanzapine were analyzed to determine the relationship between weight gain, age, and cumulative olanzapine dose. Younger (age 18–59 years) and older (age 60+ years) participants received open-label olanzapine and either sertraline or placebo for up to 12 weeks. Linear mixed effect regression modeling was used to determine the effects of age and cumulative olanzapine dose on weight gain, controlling for potential confounders. Age was observed to have a significant negative association with weight gain (P=0.01), even after controlling for differences in cumulative dose and baseline body mass index. Each 10-year increase in age was associated with a decrease in mean weight gain over 12 weeks of approximately 0.6 kg (95% confidence interval: 0.14–1.05 kg). Cumulative olanzapine dose was also significantly associated with weight gain (P<0.0001). Approximately 60% of completers of the 12-week trial experienced clinically significant weight gain (≥7% of baseline weight).
Construct the Destination Image Formation Model of Macao: The Case Taiwan Tourists to Macao

The investigation based on the vigorous tourism industry and open up the gaming industry in the future to promote and construct the nation competition strength in Taiwan. Tourism destination image is an important factor which tourist chooses and plans their tourism schedule. But the concept of image includes inner psychology motivation, external environment factor or these two factors interaction to develop and integrate model. Therefore, this investigation aimed to construct the destination image formation model of Macao and take the Taiwan visitors to Macao for example. According to the findings, Taiwan tourists who actually visited Macao generally report positive tourist image in overall. Furthermore, the overall image of tourists visiting Macao can be enhanced if consumers’ return on investment and service superiority are conducted through experiential value perspective in terms of value/environment variables of Taiwan tourists’ perception or cognition perspective. Finally, a tourism image of Macao perceived by Taiwan tourists is built upon an experience in integrated industry surrounded by luxury atmosphere. To feel about the casino culture of mirage among Asian cities, and a national image of sense and sensibility after combining Eastern and Western culture are primary tourism motives of the study.
Identifying Risk for Attrition during Treatment for Depression

Background: Understanding patients’ ambivalence about treatment persistence may be useful in tailoring retention interventions for individual patients with major depressive disorder. Methods: Participants (n = 265) with major depressive disorder were enrolled into an 8-week trial with a selective serotonin reuptake inhibitor. At baseline and week 2, the participants were asked about their intent to return for the next visit, complete the study and continue in the study should they experience side effects or no improvement. Dropouts were defined as participants who discontinued attending clinic visits before completing the trial. Results: Participants who at baseline reported an uncertain/negative intent to continue if they experienced side effects or no improvement dropped out at a significantly higher rate by weeks 6 and 8. Uncertain/negative intent at week 2 predicted attrition at all following visits. Dropouts without side effects were more likely to have reported an uncertain/negative intent to attend at both baseline and week 2, while dropouts who experienced side effects were more likely to have reported an uncertain/negative intent to attend only at baseline. Positive intent to continue was associated with greater symptom improvement in both dropouts and completers despite the possibility of lack of efficacy. Conclusions: Participants’ pretreatment concerns about continuing antidepressant treatment in the presence of side effects signals challenges to the completion of a full 8-week acute phase treatment, even if the participant does not develop side effects. Individualized review of concerns and tailoring appropriate interventions may be necessary to reduce attrition.
Correlation of lipoprotein(a) with the extent of coronary artery disease in patients with established coronary atherosclerosis: gender differences

Objective To assess the gender differences in correlation lipoprotein(a) concentration with the extent of coronary artery disease in patients with established coronary artery disease. Patients and methods Blood lipids and lipoprotein(a) concentrations were measured in 351 consecutive patients (256 men and 95 women) who underwent coronary angiography between January and May 2010, and who had established coronary atherosclerosis (angiography score >1). A modified angiographic Gensini Score was used. Results Mean angiographic score was 19.6 in men and 15.0 in women. Men had lower mean high-density lipoprotein cholesterol level than women (1.05 vs. 1.18 mmol/l) and lower mean apolipoprotein A level (1.41 vs. 1.53 g/l). Mean lipoprotein(a) level was higher in men than women (307.1 vs. 282.7 mg/l). Significant inverse correlation between high-density lipoprotein cholesterol and apoA with angiographic score was identified in women (r = −0.23, p = 0.028 and r = −0.26, p = 0.025), but not in men. Lipoprotein(a) level correlated significantly with angiographic score only in men (r = 0.168, p = 0.0185). Conclusions Gender differences were identified in patients with established coronary atherosclerosis in the relation of blood lipids and lipoprotein(a) levels with the extent of coronary artery disease.
Fish-inspired robots: design, sensing, actuation, and autonomy—a review of research

Underwater robot designs inspired by the behavior, physiology, and anatomy of fishes can provide enhanced maneuverability, stealth, and energy efficiency. Over the last two decades, robotics researchers have developed and reported a large variety of fish-inspired robot designs. The purpose of this review is to report different types of fish-inspired robot designs based upon their intended locomotion patterns. We present a detailed comparison of various design features like sensing, actuation, autonomy, waterproofing, and morphological structure of fish-inspired robots reported in the past decade. We believe that by studying the existing robots, future designers will be able to create new designs by adopting features from the successful robots. The review also summarizes the open research issues that need to be taken up for the further advancement of the field and also for the deployment of fish-inspired robots in practice.
High Prevalence of Cardio-Metabolic Risk Factors in a Young Urban Sri-Lankan Population

Background South-Asian's are predisposed to early onset type 2 diabetes (T2DM). The prevalence of cardio-metabolic risk-factors in young Sri-Lankans is unknown. Methodology/Principal Findings To determine by questionnaire and anthropometry the prevalence of first degree family history (FH) of T2DM, physical inactivity, raised waist circumference (WC) and raised body mass index (BMI) in a representative healthy urban population selected by cluster sampling. Those with ≥2 risk-factors were evaluated for metabolic syndrome (MS) and recruited for an intervention trial. Of 23,296 participants screened, 22,507 (53% Female) were eligible [8,497 aged 10–14 yrs, 4,763 aged 15–19 yrs and 9,247 aged 20–40 yrs]. 51% had none of the 4 risk-factors, 26% 1 risk-factor and 23% (5,163) ≥2 risk-factors of whom 4,532 were assessed for MS. Raised BMI was noted in 19.7% aged 10–14 yrs, 15.3% between 15–19 yrs, and between 20–40 yrs, 27.4% of males vs. 21.8% of females p<0.001. Prevalence of raised WC was greater in females for each age group: 42.7% vs. 32.1%; 28.1% vs. 16.1%; 34.5% vs. 25.7% (p<0.05 for all) as was physical inactivity: 39.9% vs. 14.5%; 51.7% vs. 20.0%; 62.7% vs. 41.3% which rose in both sexes with age (p<0.05 for all). FH of T2DM was present in 26.2%. In 4532 (50%<16 yrs) with ≥2 risk-factors, impaired fasting glycaemia/impaired glucose tolerance (pre-diabetes) prevalence was 16%. MS was more prevalent in males [10–16 yrs (13.0% vs. 8.8%), 16–40 yrs (29.5% vs. 20.0%) p<0.001 for both]. Conclusions/Significance There is a high prevalence of modifiable cardio-metabolic risk-factors in young urban Sri-Lankans with significant gender differences. A primary prevention intervention trial is ongoing in this cohort. Clinical Trial Registration Number SLCTR/2008/World Health Organization (WHO) international clinical trial registry platform.
Biomarkers of (osteo)arthritis

Abstract Arthritic diseases are a major cause of disability and morbidity, and cause an enormous burden for health and social care systems globally. Osteoarthritis (OA) is the most common form of arthritis. The key risk factors for the development of OA are age, obesity, joint trauma or instability. Metabolic and endocrine diseases can also contribute to the pathogenesis of OA. There is accumulating evidence to suggest that OA is a whole-organ disease that is influenced by systemic mediators, inflammaging, innate immunity and the low-grade inflammation induced by metabolic syndrome. Although all joint tissues are implicated in disease progression in OA, articular cartilage has received the most attention in the context of aging, injury and disease. There is increasing emphasis on the early detection of OA as it has the capacity to target and treat the disease more effectively. Indeed it has been suggested that this is the era of “personalized prevention” for OA. However, the development of strategies for the prevention of OA require new and sensitive biomarker tools that can detect the disease in its molecular and pre-radiographic stage, before structural and functional alterations in cartilage integrity have occurred. There is also evidence to support a role for biomarkers in OA drug discovery, specifically the development of disease modifying osteoarthritis drugs. This Special Issue of Biomarkers is dedicated to recent progress in the field of OA biomarkers. The papers in this Special Issue review the current state-of-the-art and discuss the utility of OA biomarkers as diagnostic and prognostic tools.
Resource Selection & Integration of Data on Deep Web

Most web structures are huge, intricate and users often miss the purpose of their inquest, or get uncertain results when they try to navigate through them. Internet is enormous compilation of multivariate data. Several problems prevent effective and efficient knowledge discovery for required better knowledge management techniques it is important to retrieve accurate and complete data. The hidden web, also known as the invisible web or deep web, has given rise to a novel issue of web mining research. a huge amount documents in the hidden web, as well as pages hidden behind search forms, specialized databases, and dynamically generated web pages, are not accessible by universal web mining application. in this research we proposed a approach is designed that has a robust ability to access these hidden web techniques for better invisible web resources selection and integration system. In this research we using SC technique for invisible web resources selection and integration and its construction for real-world domains based on database schemas clustering, web searching interfaces and improve traditional methods for information retrieve. Applications of our proposed system include invisible web query interface mapping and intelligent user query intension recognition based on our domain knowledge-base.
Nursing Students’ Perspectives on Assisting Cancer Patients

Objective: The objective of this study was to examine the experiences of student nurses who have provided care to cancer patients. Methods: A mixed method approach consisting of semistructured focus groups (n = 61) and a survey questionnaire (n = 129) was used in the study. Student nurses were first interviewed, and then, a questionnaire was developed for them to answer. Following the content analysis, three themes and 19 subthemes were identified. Frequency and percent were used for qualitative data. Results: Among the student nurses, 80.6% reported that working with cancer patients was “difficult. ” Difficulties experienced by the student nurses included patients rejecting their care, a large number of problems cases encountered when providing care to cancer patients, communication problems (38.0%), working with patients and attendants who fear death, and problems arising from family attendants who obstruct care. The majority of students experienced patients fearing death (28.7%) and felt feelings such as pity (71.1%), sadness (50.0%), and fear of cancer (41.9%) during their internships in oncology clinics. Conclusions: Students should be supported by instructors and oncology nurses, and nursing curricula should contain topics on how to best approach cancer patients.
Cardiac surgery risk-stratification models

Abstract Risk models are widely used to predict outcomes after cardiac surgery. Not only is risk modelling applied in the assessment of the relative impact of specific risk factors on surgical outcomes, but also in patient counselling, the selection of treatment options, comparison of postoperative results, and quality-improvement programmes. At least 19 risk-stratification models exist for open-heart surgery. The focus of risk models was originally on pre-operative prediction of mortality. However, major morbidity is in general more common than mortality and the ability to predict only operative mortality is not an adequate method of determining surgical outcome. Multiple intra- and postoperative variables have been excluded in the majority of models and the possible effect of their future inclusion remains to be seen. The unique patient population of sub-Saharan Africa requires a unique risk model that reflects the patient population and levels of care.
Planar Ultrametric Rounding for Image Segmentation

We study the problem of hierarchical clustering on planar graphs. We formulate this in terms of an LP relaxation of ultrametric rounding. To solve this LP efficiently we introduce a dual cutting plane scheme that uses minimum cost perfect matching as a subroutine in order to efficiently explore the space of planar partitions. We apply our algorithm to the problem of hierarchical image segmentation.
DNA Structural Elements Required for ERCC1-XPF Endonuclease Activity*

The heterodimeric complex ERCC1-XPF is a structure-specific endonuclease responsible for the 5′ incision during mammalian nucleotide excision repair (NER). Additionally, ERCC1-XPF is thought to function in the repair of interstrand DNA cross-links and, by analogy to the homologous Rad1-Rad10 complex in Saccharomyces cerevisiae, in recombination between direct repeated DNA sequences. To gain insight into the role of ERCC1-XPF in such recombinational processes and in the NER reaction, we studied in detail the DNA structural elements required for ERCC1-XPF endonucleolytic activity. Recombinant ERCC1-XPF, purified from insect cells, was found to cleave stem-loop substrates at the DNA junction in the absence of other proteins like replication protein A, showing that the structure-specific endonuclease activity is intrinsic to the complex. Cleavage depended on the presence of divalent cations and was optimal in low Mn2+ concentrations (0.2 mm). A minimum of 4–8 unpaired nucleotides was required for incisions by ERCC1-XPF. Splayed arm and flap substrates were also cut by ERCC1-XPF, resulting in the removal of 3′ protruding single-stranded arms. All incisions occurred in one strand of duplex DNA at the 5′ side of a junction with single-stranded DNA. The exact cleavage position varied from 2 to 8 nucleotides away from the junction. One single-stranded arm, protruding either in the 3′ or 5′ direction, was necessary and sufficient for correct positioning of incisions by ERCC1-XPF. Our data specify the engagement of ERCC1-XPF in NER and allow a more direct search for its specific role in recombination.
Metabolic Activation of Pyrrolizidine Alkaloids Leading to Phototoxicity and Photogenotoxicity in Human HaCaT Keratinocytes

Pyrrolizidine alkaloids, produced by a large number of poisonous plants with wide global distribution, are associated with genotoxicity, tumorigenicity, and hepatotoxicity in animals and humans. Mammalian metabolism converts pyrrolizidine alkaloids to reactive pyrrolic metabolites (dehydropyrrolizidine alkaloids) that form covalent protein and DNA adducts. Although a mechanistic understanding is currently unclear, pyrrolizidine alkaloids can cause secondary (hepatogenous) photosensitization and induce skin cancer. In this study, the phototoxicity of monocrotaline, riddelliine, dehydromonocrotaline, dehydroriddelliine, and dehydroretronecine (DHR) in human HaCaT keratinocytes under ultraviolet A (UVA) irradiation was determined. UVA irradiation of HaCaT cells treated with dehydromonocrotaline, dehydroriddelline, and DHR resulted in increased release of lactate dehydrogenase and enhanced photocytotoxicity proportional to the UVA doses. UVA-induced photochemical DNA damage also increased proportionally with dehydromonocrotaline and dehydroriddelline. UVA treatment potentiated the formation of 8-hydroxy-2′-deoxyguanosine DNA adducts induced by dehydromonocrotaline in HaCaT skin keratinocytes. Using electron spin resistance trapping, we found that UVA irradiation of dehydromonocrotaline and dehydroriddelliine generates reactive oxygen species (ROS), including hydroxyl radical, singlet oxygen, and superoxide, and electron transfer reactions, indicating that cytotoxicity and genotoxicity of these compounds could be mediated by ROS. Our results suggest that dehydropyrrolizidine alkaloids formed or delivered to the skin cause pyrrolizidine alkaloid-induced secondary photosensitization and possible skin cancer.