Miracle-dz/UniFAR-FTUs huggingface dataset:
First Reported Case of Methicillin-Resistant Staphylococcus aureus Vertebral Osteomyelitis with Multiple Spinal and Paraspinal Abscesses Associated with Acupuncture

Acupuncture is one of the oldest medical procedures in the world and originated in China about 2,000 years ago. Acupuncture is a form of complementary medicine and has gained popularity worldwide in the last few decades. It is mainly used for the treatment of chronic pain. Acupuncture is usually considered a safe procedure but has been reported to cause serious complications including death. It has been associated with transmission of many viruses and bacteria. Two cases of Methicillin-Resistant Staphylococcus aureus have been reported recently following acupuncture therapy. We are reporting a case of a 57-year-old Korean female who developed vertebral osteomyelitis and intraspinal and paraspinal abscesses as a complication of acupuncture. Blood cultures, skin lesion culture, and body fluid culture yielded Methicillin-Resistant Staphylococcus aureus (MRSA). Good anatomical and medical knowledge, good hygiene standards, and proper acupuncture techniques should be followed to prevent the complications. Acupuncturists should consistently review the infection control guidelines to acupuncture. This case should raise awareness of such condition and hazards of presumably benign procedures such as acupuncture.
Current-mode control to enhance closed-loop performance of asymmetrical half-bridge dc-to-dc converters

Asymmetrical half-bridge dc-to-dc converters exhibit the fourth-order power stage dynamics. When the conventional voltage-mode control is employed, the fourth-order dynamics impose certain constraints on the feedback compensation design and the result could be poor closed-loop performance. This paper demonstrates that the current-mode control could alleviate the detrimental effects of the power stage dynamics and offer an improvement in the closed-loop performance. The principles, performance, and experimental results of current-mode control are presented in comparison with those of voltage-mode control.
Adapting pivoted document-length normalization for query size: Experiments in Chinese and English

The vector space model (VSM) is one of the most widely used information retrieval (IR) models in both academia and industry. It was less effective at the Chinese ad hoc retrieval tasks than other retrieval models in the NTCIR-3 evaluation workshop, but comparable to those in the NTCIR-4 and NTCIR-5 workshops. We do not know whether the lower level performance was due to the VSM's inherent deficiencies or to a less effective normalization of document length. Hence we evaluated the VSM with various pivoted normalizations of document length using the NTCIR-3 collection for confirmation. We found that VSM's retrieval effectiveness with pivoted normalization was comparable to other competitive retrieval models (for example, 2-Poisson), and that VSM's retrieval speed with pivoted normalization was similar to competitive retrieval models (2-Poisson). We proposed a novel adaptive scheme that automatically estimates the (near) best parameters for pivoted document-length normalization based on query size; the new normalization is called adaptive pivoted document-length normalization. This scheme achieved good retrieval effectiveness, sometimes for short (title) queries and sometimes for long queries, without manually adjusting parameter values. We found that unique, adaptive pivoted normalization can enhance fixed pivoted normalizations for different test collections (TREC-5 and TREC-6). We also evaluated the VSM with the adaptive pivoted normalization using the pseudo-relevance feedback (PRF) and found that this type of VSM performs similarly to the competitive retrieval models (2-Poisson) with PRF. Hence, we conclude that the VSM with unique (adaptive) pivoted document-length normalization is effective for Chinese IR and that its retrieval effectiveness is comparable to that of other competitive retrieval models with or without PRF for the reference test collections used in this evaluation.
G-Quadruplex Stabilizer 3,6-Bis(1-Methyl-4-Vinylpyridinium)Carbazole Diiodide Induces Accelerated Senescence and Inhibits Tumorigenic Properties in Cancer Cells

Carbazole derivatives that stabilized G-quadruplex DNA structure formed by human telomeric sequence have been designed and synthesized. Among them, 3,6-bis(1-methyl-4-vinylpyridinium)carbazole diiodide (BMVC) showed an increase in G-quadruplex melting temperature by 13°C and has a potent inhibitory effect on telomerase activity. Treatment of H1299 cancer cells with 0.5 μmol/L BMVC did not cause acute toxicity and affect DNA replication; however, the BMVC-treated cells ceased to divide after a lag period. Hallmarks of senescence, including morphologic changes, detection of senescence-associated β-galactosidase activity, and decreased bromodeoxyuridine incorporation, were detected in BMVC-treated cancer cells. The BMVC-induced senescence phenotype is accompanied by progressive telomere shortening and detection of the DNA damage foci, indicating that BMVC caused telomere uncapping after long-term treatments. Unlike other telomerase inhibitors, the BMVC-treated cancer cells showed a fast telomere shortening rate and a lag period of growth before entering senescence. Interestingly, BMVC also suppressed the tumor-related properties of cancer cells, including cell migration, colony-forming ability, and anchorage-independent growth, indicating that the cellular effects of BMVC were not limited to telomeres. Consistent with the observations from cellular experiments, the tumorigenic potential of cancer cells was also reduced in mouse xenografts after BMVC treatments. Thus, BMVC repressed tumor progression through both telomere-dependent and telomere-independent pathways. (Mol Cancer Res 2008;6(6):955–64)
A context-aware smart seat

This paper reports the characterization and test of an embedded implementation of the k-Nearest Neighbor (kNN) classifier in a resource constrained device applied to a seat to capture user postures and combine them with contextual information about the user. The embedded platform is a wearable multi-sensor device based on the 32 bit ARM Cortex M3 architecture, capable of data processing (sampling, windowing, filtering, Fast Fourier Transform) from 9 different sensors. The system, applied to the seat, identifies 6 different user postures - adopted while she/he is working on the desk - and fuses the result with the information available from other sensors worn by the user, collecting information about her/his activities and physiological state. The kNN classifier is evaluated in terms of required computational power and latency. 7 users have been monitored along 3 days. The posture recognition accuracy reaches 93.7%, it requires 9KB of memory and introduces a latency of 950usec, satisfying strict real-time requirements.
Simulation of forward-reverse stochastic representations for conditional diffusions

In this paper we derive stochastic representations for the finite dimensional distributions of a multidimensional diffusion on a fixed time interval, conditioned on the terminal state. The conditioning can be with respect to a fixed point or more generally with respect to some subset. The representations rely on a reverse process connected with the given (forward) diffusion as introduced in Milstein, Schoenmakers and Spokoiny [Bernoulli 10 (2004) 281-312] in the context of a forward-reverse transition density estimator. The corresponding Monte Carlo estimators have essentially root-$N$ accuracy, and hence they do not suffer from the curse of dimensionality. We provide a detailed convergence analysis and give a numerical example involving the realized variance in a stochastic volatility asset model conditioned on a fixed terminal value of the asset.
Robust Face Localisation Using Motion, Colour and Fusion

Face detection is fundamental for several important applications , such as, face recognition and human-computer interaction. This paper details a novel hierarchical face detector which combines motion, colour and late fusion. Motion segmentation is employed to eliminate background clutter and to reduce the initial search space. Subsequently, skin segmentation is used to determine a candidate face. Five simple eye-detection algorithms are fused to robustly localise the eyes within the candidate. Fusion is beneficial because the large amount of variation within the face makes it difficult for any individual technique to perform well under all conditions. The resulting system is capable of localising faces from still images in real-time with an accuracy of 93.75%.
Practical implementation of dual paraboloid shadow maps

In this paper, we present refinements to dual paraboloid shadow mapping algorithm from Brabec, et. al. This work makes the algorithm practical for broader use in video games. We give solutions for the tessellation constraints on shadow casters and receivers present in the original work. We also discuss heuristics for splitting plane placement and pitfalls in filtering.
Media portrayals of Muslims: a comparative sentiment analysis of American newspapers, 1996–2015

ABSTRACT Are Muslims portrayed more negatively than other religious groups? If so, what factors are associated with this negativity? We apply computer-assisted, lexicon-based coding to over 850,000 articles that mention Muslims, Hindus, Jews, or Catholics in 17 national and regional US newspapers over the 20-year period of 1996–2015 and compare them to a representative baseline of articles. We show that the average tone of articles about Muslims is considerably more negative than both this baseline and compared to articles about the other groups. The negative tone is most strongly associated with stories about extremism and events in foreign settings. However, even controlling for a wide range of factors does not eliminate the negativity in stories mentioning Muslims. We discuss the implications of these findings for media objectivity and for public attitudes and policy preferences with respect to Muslims and other social groups.
Clues From the Digital World: A Survey of Clinicians’ Reliance on Social Media as Collateral Data in Forensic Evaluations

Access to and use of social media has increased throughout the United States. In parallel, information gleaned from social media is often available as part of discovery packets provided to clinicians conducting forensic evaluations. As social media continues to be a primary mode of communication, forensic evaluators are likely to grapple with decisions to use information from these sites to inform psycholegal opinions. However, professional commentary on obtaining, interpreting, and integrating data from social networking sites (SNSs) in forensic practice began only recently. There have been few empirical efforts thus far to better understand whether and how forensic mental health evaluators use SNSs to inform their opinions about various psycholegal issues. Thus, the current study sought to address this gap in the professional literature by surveying practicing forensic evaluators (N = 102) regarding their use of SNS data in civil and criminal legal contexts. Quantitative and qualitative findings from our survey are presented and discussed to provide an overview of current practices and concerns among forensic clinicians. Overall, SNSs are used with some frequency in forensic mental health assessments and are generally perceived as a useful source. Findings are integrated with previous professional commentary about Internet-based data to facilitate greater understanding of how SNS data may be best incorporated into assessments and to identify emergent legal and ethical issues when such data are included.
Causality Rules: Performance Feedback on Hierarchically Related Goals and Capital Investment Variability

We extend March and Simon&#8217;s (1958) analysis of strategic decisions by distinguishing between two rules for allocating attention &#8211; priority versus causality. We develop theory concerning causality rules which have been largely overlooked in prior literature. Specifically, we examine how performance feedback on the intermediate productivity goal and the higher&#8208;order profitability goal independently and jointly influence the variability of firm capital investments. Panel analysis of 2,477 Spanish manufacturing firms reveals that these goals jointly affect the variability of capital investments through both priority and causality attention rules. Our study provides new insights on how firms handle multiple goals, deconstruct performance feedback, and cope with the attentional constraints of bounded rationality.
Classification of Heart Rate data using BFO-KFCM clustering and improved extreme learning machine classifier

The Electrocardiogram is a tool used to access the electrical recording and muscular function of the heart and in last few decades it is extensively used in the investigation and diagnosis of heart related diseases. It must be noted that the heart rate fluctuates not only because of cardiac demand, however is also influenced as a result of the occurrence of cardiac disease and diabetes. In addition, it has been shown that Heart Rate Variability (HRV) may well be utilized as an early indicator of cardiac disease susceptibility and the existence of diabetes. As a result, the HRV can be exercised for early clinical test of these diseases. Most existing systems make use of Support Vector Machine (SVM), owing to the generalization performance, it is not sufficient for the accurate classification of heart rate data. In order to overcome this complication, Improved Extreme Learning Machine (IELM) classifier is used, to obtain the best parameter value and best feature subset through the use of Bacterial Foraging Optimization (BFO) that feed the classifier. Here in this work, features of linear and nonlinear are extracted from the HRV signals. Following the preprocessing, feature extraction is done effectively together with feature selection with the assistance of BFO for the purpose of data reduction. Subsequently, proposed a scheme to integrate Kernel Fuzzy C-Means (KFCM) clustering and classifier to adequately enhance the accuracy result for ECG beat classification. The accuracy result for classification of heart rate data is shown in the proposed scheme.
Reactive DVFS Control for Multicore Processors

Several solutions are considered to reduce energy consumption of computers. Among them, Dynamic Voltage and Frequency Scaling (DVFS) emerged as an effective way to enhance energy efficiency by adapting processor frequency to workloads. We propose Forest, a new DVFS controller designed to efficiently exploit the recent technologies introduced in processors. Forest is a runtime DVFS controller able to estimate the energy savings it can achieve from power gains, evaluated offline using power probes embedded in modern CPUs, and speedups measured at runtime for the current workload. It does not use any performance model but rather directly measures the effect of frequency transitions on energy. Using such methodology, Forest can achieve energy savings on the whole system under user-defined slowdown constraints. In our experiments, Forest is able to achieve more than 39% CPU energy savings compared to the default Linux DVFS controller, with a slowdown below 5%, as requested by the user.
Acid‐evoked quantal catecholamine secretion from rat phaeochromocytoma cells and its interaction with hypoxia‐evoked secretion

1 Amperometric recordings using polarized carbon fibre microelectrodes were used to detect exocytosis of catecholamines from rat phaeochromocytoma (PC12) cells in response to a reduction in pHo. 2 Exocytosis was detected at pHo levels of between 7.2 and 6.8. This was probably due to intracellular acidification, since acid‐evoked secretion was enhanced by the Na+‐H+ exchange blocker ethylisopropylamiloride (30 μm), and was mimicked by sodium propionate (10 mM), which causes selective intracellular acidosis. 3 Acid‐evoked exocytosis was abolished by removal of Ca2+o or application of 200 μm Cd2+. It was unaffected by nifedipine, but significantly reduced by either ω‐conotoxin GVIA (1 μm) or ω‐agatoxin GIVA (200 nM). The two toxins applied together almost completely abolished (> 97 %) acid‐evoked secretion. 4 Hypoxia‐evoked catecholamine release was potentiated under acidic conditions and suppressed under alkaline conditions in a manner which indicated a greater than additive interaction of these two stimuli. 5 Our results indicate that, like carotid body arterial chemoreceptors, PC12 cells represent model chemoreceptor cells for both hypoxia and acidity and that the release of catecholamines in response to these physiological stimuli is dependent on Ca2+ influx through voltage‐gated N‐ and P/Q‐type Ca2+ channels.
The Sources of Increased Accuracy for Two Proposed Boosting Algorithms

We introduce two boosting algorithms that aim to increase the generalization accuracy of a given classiier by incorporating it as a level-0 component in a stacked generalizer. Both algorithms construct a complementary level-0 classiier that can only generate coarse hypotheses for the training data. We show that the two algorithms boost generalization accuracy on a representative collection of data sets. The two algorithms are distinguished in that one of them modiies the class targets of selected training instances in order to train the complementary classiier. We show that the two algorithms achieve approximately equal generalization accuracy, but that they create complementary classiiers that display diierent degrees of accuracy and diversity. Our study provides evidence that it may be useful to investigate families of boosting algorithms that incorporate varying levels of accuracy and diversity, so as to achieve an appropriate mix for a given task and domain.
Do pollen feeding, pupal-mating and larval gregariousness have a single origin in Heliconius butterflies? Inferences from multilocus DNA sequence data

Phylogenetic information is useful in understanding the evolutionary history of adaptive traits. Here, we present a well-resolved phylogenetic hypothesis for Heliconius butterflies and related genera. We use this tree to investigate the evolution of three traits, pollen feeding, pupal-mating behaviour and larval gregariousness. Phylogenetic relationships among 60 Heliconiina species (86% of the subtribe) were inferred from partial DNA sequences of the mitochondrial genes cytochrome oxidase I, cytochrome oxidase II and 16S rRNA, and fragments of the nuclear genes elongation factor-1α, apterous, decapentaplegic and wingless (3834 bp in total). The results corroborate previous hypotheses based on sequence data in showing that Heliconius is paraphyletic, with Laparus doris and Neruda falling within the genus, demonstrating a single origin for pollen feeding but with a loss of the trait in Neruda. However, different genes are not congruent in their placement of Neruda; therefore, monophyly of the pollen feeding species cannot be ruled out. There is also a highly supported monophyletic ‘pupal-mating clade’ suggesting that pupal mating behaviour evolved only once in the Heliconiina. Additionally, we observed at least three independent origins for larval gregariousness from a solitary ancestor, showing that gregarious larval behaviour arose after warning coloration. © 2007 The Linnean Society of London, Biological Journal of the Linnean Society, 2007, 92, 221–239.
A Context Dependent Pair Hidden Markov Model for Statistical Alignment

This article proposes a novel approach to statistical alignment of nucleotide sequences by introducing a context dependent structure on the substitution process in the underlying evolutionary model. We propose to estimate alignments and context dependent mutation rates relying on the observation of two homologous sequences. The procedure is based on a generalized pair-hidden Markov structure, where conditional on the alignment path, the nucleotide sequences follow a Markov distribution. We use a stochastic approximation expectation maximization (saem) algorithm to give accurate estimators of parameters and alignments. We provide results both on simulated data and vertebrate genomes, which are known to have a high mutation rate from CG dinucleotide. In particular, we establish that the method improves the accuracy of the alignment of a human pseudogene and its functional gene.
How do the clouds feed back to influence climate change ? This problem

Randall, D.A. , 1989. Cloud Parameterization for climate modeling: status and prospects. Atmos. Res., 23: 245-361. The current status of cloud parameterization research is reviewed. It is emphasized that the upper tropospheric stratiform clouds associated with deep convection are both physically important and poorly parameterized in current models. Emerging parameterizations are described in general terms, with emphasis on prognostic cloud water and fractional cloudiness, and how these relate to the problem just mentioned.
Mining public administration Big Data for a financial benefit Word

Our research study is related to data Mining software and analyzing big Data especially in public administration. The purpose of this study is to compare softwares and algorithms used for statistical analysis. Following the comparative study of supply chain management (SCM) softwares, we chose the best to make a comparative study of descriptive and predictive algorithms using dataset collected from the new IT solution developed in our PHD research study.
Increased collagen IV excretion in diabetes. A marker of compromised filtration function.

OBJECTIVE Increased albumin excretion in diabetes is believed to be derived from hemodynamic and/or permeability abnormalities, whereas mesangial matrix expansion gives rise to the reduction in glomerular filtration surface and decline in renal function in diabetic nephropathy. We postulated that the overproduction of extracellular matrix proteins underlying glomerulosclerosis in diabetes might be associated with the excretion of increased amounts of type IV collagen in the urine. RESEARCH DESIGN AND METHODS To explore this hypothesis, we measured the urinary excretion of (human) collagen IV by immunoassay in 65 patients with type 1 or type 2 diabetes and various degrees of albuminuria and examined its relationship to filtration function assessed by the reciprocal of the serum creatinine (RSC). RESULTS Collagen IV excretion showed a significant (P < 0.001) inverse correlation (r = -0.62) with the RSC, and this correlation pertained regardless of whether albumin cxcretion was in the low (< or =< or = 100 microg/mg creatinine r = -0.73) or high (>100 microg/mg; r = -0.53) range. In contrast, albumin excretion showed insignificant correlation with either collagen IV excretion (r = 0.12) or with the RSC (r = -0.20). Urinary collagen IV was significantly higher (P < 0.05) in patients with an RSC value < or = 100 (28.3 +/- 2.4 ng/mg creatinine) than in patients with an RSC value > 100 (16.0 +/- 0.8 ng/mg creatinine). CONCLUSIONS Because not all patients with microalbuminuria progress to declining renal function and some patients who develop nephropathy do not manifest albuminuria, the findings in this cross-sectional analysis suggest that measurement of urine collagen IV may be a useful noninvasive indicator to detect diabetic renal disease entering a phase of compromised renal function.