Miracle-dz/UniFAR-FTUs huggingface dataset:
The Donovan Site (5LO204): An Upper Republican Animal Processing Camp on the High Plains

Abstract The Donovan site (5LO204) is a Late Prehistoric animal processing campsite located in northeastern Colorado. The site has been extensively excavated by the University of Wyoming High Plains Archaeology Project since 1992. Containing at least 11 stratified occupation surfaces dating between about A.D. 1000 and 1300, Donovan represents a frequently visited western expansion of the Upper Republican phase of the Central Plains tradition. Material culture includes thousands of fragmented bison bones, lithic debitage, diagnostic ceramics, side-notched projectile points, and bifacial knives. Long thought to represent the activities of either indigenous High Plains occupants or central Plains hunting parties, this site and others on the western High Plains provide evidence for the complex interactions between foraging and farming communities on the Plains.
Age invariant face recognition based on texture embedded discriminative graph model

In an automatic face recognition system, it still remains a challenge to improve the robustness to aging. In this paper, we present a novel approach to address age invariant face recognition, by formulating it as a graph matching problem. In contrast to the majority of tasks in the literature that only make use of robust texture features, this method generates a graph from a set of fiducial landmarks of each face, which captures the texture clues that tend to be stable in a period as well as the common facial geometry configuration. The nodes of the graph denote the texture of a face area around a landmark, and the edges correspond to the geometry topology of the face. For each area, the age invariant texture information is extracted by a discriminative and compact feature encoded in the Local Gabor Binary Pattern Histogram Sequence (LGBPHS) projected in an LDA subspace. An objective function is then designed to match graphs for the purpose of registration and identification. Experiments are carried out on the FG-NET Aging database, and the results achieved outperform the state of the art ones, which clearly demonstrate the effectiveness and robustness of the proposed method in face recognition across age variations.
“The mosquitoes that destroy your face”. Social impact of Cutaneous Leishmaniasis in South-eastern Morocco, A qualitative study

Objective To document the psychosocial burden of Cutaneous Leishmaniasis (CL) in rural communities in Southeastern Morocco. Method Between March and April 2015, we conducted qualitative research in communities exposed to Leishmania major or L. tropica in Errachidia and Tinghir provinces. Twenty-eight focus groups discussions (FGDs) were realized, with a stratification by gender and tradition of medicine (users of folk versus professional medicine). Data were analyzed using content analysis. Results This rural population most exposed to CL in Morocco lacks access to health care in general and clearly points out there are other major public health issues that need to be resolved. Nonetheless, respondents consider the impact of CL lesions and scars as important and similar to that of burn scar tissue. Young women with CL scars in the face are stigmatized and will often be rejected for marriage in these communities. People usually try a long list of folk remedies on the active lesions, but none was felt adequate. There was a clear demand for better treatment as well as for treatment of the scars. Conclusions The psycho-social impact of CL due to L.major and L.tropica is substantial, especially for young single women with facial scars. These generate social and self-stigma and diminish their marriage prospects. CL is well known, but not considered as a major health priority by these poor rural communities in South-eastern Morocco where gender discrimination is still an issue and access to basic health care is as neglected as CL. Early CL diagnosis and new treatment options with better skin outcomes are urgently needed.
Serum TRACP 5b Is a Useful Marker for Monitoring Alendronate Treatment: Comparison With Other Markers of Bone Turnover

We studied clinical performance of serum TRACP 5b and other bone turnover markers, including S‐CTX, U‐DPD, S‐PINP, S‐BALP, and S‐OC, for monitoring alendronate treatment. TRACP 5b had higher clinical sensitivity, area under the ROC curve, and signal‐to‐noise ratio than the other markers.
A practical algorithm for turbo-decoding enhancement

It has been demonstrated that the BER (bit error rate) performance of turbo codes may be enhanced by applying an adaptive control technique to suppress transient dynamics in the turbo-decoding algorithm. In this work, we extend the method to a suboptimal decoding scheme, which is more suitable for practical implementation, and discuss the effect of metrics quantization.
Neuropsychological Functioning and Psychopathology in Children with Epilepsy

Summary: Fifty children with epilepsy, aged 8–12, were classified into two groups on the basis of their performance on a standardized battery of neuropsychological measures. Children with good neuropsychological function (n = 25) were compared to a closely matched group of children with poor neuropsychological function (n = 25) on measures of aggression, overall behavioral pathology, and overall social competence which were derived from a standardized behavioral assessment inventory. Children with poor neuropsychological function manifested significantly more aggression, overall psychopathology, and less overall social competence compared to the children with relatively good neuropsychological functioning. These results are related to the larger literature concerned with the relationship between epilepsy and psychopathology.
High-Performance 3D Image Processing Architectures for Image-Guided Interventions

Abstract : Minimally invasive image-guided interventions (IGIs) are time and cost efficient, minimize unintended damage to healthy tissues, and lead to faster patient recovery. Advanced three-dimensional (3D) image processing is a critical need for navigation during IGIs. However, achieving on-demand performance, as required by IGIs, for these image processing operations using software-only implementations is challenging because of the sheer size of the 3D images, and memory and compute intensive nature of the operations. This dissertation, therefore, is geared toward developing high-performance 3D image processing architectures, which will enable improved intraprocedural visualization and navigation capabilities during IGIs.
Clinical usefulness of a cluster of sacroiliac joint tests in patients with and without low back pain.

STUDY DESIGN Observation to examine the clinical usefulness of a cluster of sacroiliac joint tests. OBJECTIVES To find the sensitivity, specificity, and positive and negative predictive values (4 commonly used epidemiologic measures) for a cluster of sacroiliac joint tests in a group of subjects with and without low back pain. BACKGROUND Sacroiliac joint testing is commonly used by orthopaedic physical therapists in the evaluation of patients with low back pain. METHODS AND MEASURES Two hundred nineteen patients who either were being treated for low back pain or were being treated for some other condition not related to the low back participated in the study. The diagnosis of low back pain was obtained from the physician's prescription, which included low back strain, low back pain, or sacroiliac joint dysfunction, and the patient's pain drawing. RESULTS The results were a finding of 0.82 for sensitivity, 0.88 for specificity, 0.86 for positive predictive value of a test, and 0.84 for negative predictive value of the cluster of tests. CONCLUSIONS The results of this study show that using a cluster of sacroiliac joint tests can be useful in identifying sacroiliac joint dysfunction in patients with low back pain.
Multiagent-based processing and integration of system data

This paper presents a multiagent–based ETL (Extract, Transform, Load) unit for the processing and integration of system operational data in order to improve its value. Operational data plays a vital role in managing and optimising systems. Although KDD (Knowledge Discovery and Data Mining) techniques and concepts have long existed, it is only now that we are seeing real applications being extended onto network and systems management. However, the massive data pre–processing (e.g. feature extraction and data integration) which is needed prior to putting KDD tools in action, is still limiting the extent of exploitation. We propose and design the multiagent–based ETL unit which uses Support Vector Machine and Natural Language Processing techniques to efficiently extract information features from operational data. The unit uses an mSPIDER algorithm to discover INclusion Dependencies (INDs) which are used to integrate data across its peers within the system. We demonstrate efficiency of the unit and the used approaches using operational data from a mailing system.
De Novo Generation and Characterization of New Zika Virus Isolate Using Sequence Data from a Microcephaly Case

The major complications of an ongoing Zika virus outbreak in the Americas and Asia are congenital defects caused by the virus’s ability to cross the placenta and infect the fetal brain. The ability to generate molecular tools to analyze viral isolates from the current outbreak is essential for furthering our understanding of how these viruses cause congenital defects. The majority of existing viral isolates and infectious cDNA clones generated from them have undergone various numbers of passages in cell culture and/or suckling mice, which is likely to result in the accumulation of adaptive mutations that may affect viral properties. The approach described herein allows rapid generation of new, fully functional Zika virus isolates directly from deep sequencing data from virus-infected tissues without the need for prior virus passaging and for the generation and propagation of full-length cDNA clones. The approach should be applicable to other medically important flaviviruses and perhaps other positive-strand RNA viruses. ABSTRACT Zika virus (ZIKV) has recently emerged and is the etiological agent of congenital Zika syndrome (CZS), a spectrum of congenital abnormalities arising from neural tissue infections in utero. Herein, we describe the de novo generation of a new ZIKV isolate, ZIKVNatal, using a modified circular polymerase extension reaction protocol and sequence data obtained from a ZIKV-infected fetus with microcephaly. ZIKVNatal thus has no laboratory passage history and is unequivocally associated with CZS. ZIKVNatal could be used to establish a fetal brain infection model in IFNAR−/− mice (including intrauterine growth restriction) without causing symptomatic infections in dams. ZIKVNatal was also able to be transmitted by Aedes aegypti mosquitoes. ZIKVNatal thus retains key aspects of circulating pathogenic ZIKVs and illustrates a novel methodology for obtaining an authentic functional viral isolate by using data from deep sequencing of infected tissues. IMPORTANCE The major complications of an ongoing Zika virus outbreak in the Americas and Asia are congenital defects caused by the virus’s ability to cross the placenta and infect the fetal brain. The ability to generate molecular tools to analyze viral isolates from the current outbreak is essential for furthering our understanding of how these viruses cause congenital defects. The majority of existing viral isolates and infectious cDNA clones generated from them have undergone various numbers of passages in cell culture and/or suckling mice, which is likely to result in the accumulation of adaptive mutations that may affect viral properties. The approach described herein allows rapid generation of new, fully functional Zika virus isolates directly from deep sequencing data from virus-infected tissues without the need for prior virus passaging and for the generation and propagation of full-length cDNA clones. The approach should be applicable to other medically important flaviviruses and perhaps other positive-strand RNA viruses.
Political Expression and Action on Social Media: Exploring the Relationship Between Lower- and Higher-Threshold Political Activities Among Twitter Users in Italy

Scholars and commentators have debated whether lower-threshold forms of political engagement on social media should be treated as being conducive to higher-threshold modes of political participation or a diversion from them. Drawing on an original survey of a representative sample of Italians who discussed the 2013 election on Twitter, we demonstrate that the more respondents acquire political information via social media and express themselves politically on these platforms, the more they are likely to contact politicians via e-mail, campaign for parties and candidates using social media, and attend offline events to which they were invited online. These results suggest that lower-threshold forms of political engagement on social media do not distract from higher-threshold activities, but are strongly associated with them.
Concurrent synchronization of neural networks via excitatory-only coupling with different topologies

Concurrent synchronization of neural networks coupled via an excitatory-only protocol is addressed using contraction theory. Under certain conditions guaranteeing the existence of a flow-invariant subspace, coupling functions are designed so that both heterogeneous neural networks coupled via an excitatory-only protocol, and networks of nodes communicating over different media interconnected with an excitatory-only method spontaneously synchronize. Applications to networks of Fitzhugh-Nagumo oscillators illustrate how to deal with the proposed architecture in practice.
The Research of the Intelligent Device Management and Diagnostic

By our research and implementation of intelligent device management and diagnostic system which are based on Wireless HART Technology. In this essay we focus on the application of the wireless HART intelligent devices, explaining the wireless HART protocol and its four-level model, putting forward the wireless HART-USB potable gateway, by which the operating personnel at the scene can obtain data for diagnosis and modification directly from the PC. Then we briefly discuss the design module of intelligent device management system. In the end, we mainly emphasize on the introduction of the mathematical model which is based on the pneumatic control regulator and is used for diagnosis. And we represent the steps of verifying its correctness.
Mechanisms of cardiac potassium channel trafficking

The regulation of ion channels involves more than just modulation of their synthesis and kinetics, as controls on their trafficking and localization are also important. Although the body of knowledge is fairly large, the entire trafficking pathway is not known for any one channel. This review summarizes current knowledge on the trafficking of potassium channels that are expressed in the heart. Our knowledge of channel assembly, trafficking through the Golgi apparatus and on to the surface is covered, as are controls on channel surface retention and endocytosis.
Ultrasound in the diagnosis of ulnar neuropathy at the elbow.

The use of ultrasound to image peripheral nerves was pioneered in the 1990s and has shown promise in the evaluation of carpal tunnel syndrome. Ultrasonographic studies have demonstrated diffuse enlargement of the median nerve throughout the carpal tunnel, becoming most pronounced immediately proximal to the tunnel. This unexpected finding has been confirmed with other imaging modalities and cadaveric studies and could reflect edema or an increase in interstitial tissue. Fewer studies have been published regarding ultrasonography of the ulnar nerve but similar enlargement of the nerve occurs in ulnar neuropathy at the elbow (UNE). The following case report illustrates the ability of ultrasound to diagnose UNE with adequate sensitivity to distinguish between a lesion at the cubital tunnel versus the ulnar groove. Case Report
Follow up of patients presenting with fatigue to an infectious diseases clinic.

OBJECTIVES--To determine the symptomatic and functional status during follow up of patients referred to hospital with unexplained fatigue and to identify patient variables associated with persistent functional impairment. DESIGN--Follow up by postal questionnaire six weeks to four years (median 1 year) after initial clinical assessment of patients referred to hospital during 1984-8. SETTING--Infectious diseases outpatient clinic in a teaching hospital. PATIENTS--200 consecutive patients with fatigue of uncertain cause for at least six weeks; 177 fulfilled the inclusion criteria. MAIN OUTCOME MEASURES--Findings at initial assessment; current symptoms, beliefs about the cause of illness, coping behaviours emotional disorder, social variables including membership of self help organizations, and degrees of recovery and functional impairment from questionnaire responses. RESULTS--144 (81%) patients returned completed questionnaires. Initial assessment did not indicate the cause of fatigue, other than preceding infection. The proportion of patients with functional impairment was significantly smaller with longer follow up (33% (11/33) at two to four years, 73% (29/40) at six weeks to six months; chi 2 for trend = 12.5, df = 1; p less than 0.05). Functional impairment was significantly associated with belief in a viral cause of the illness (odds ratio = 3.9; 95% confidence interval 1.5 to 9.9), limiting exercise (3.2; 1.5 to 6.6), avoiding alcohol (4.5; 1.8 to 11.3), changing or leaving employment (3.1; 1.4 to 6.9), belonging to a self help organization (7.8; 2.5 to 23.9), and current emotional disorder (4.4; 2.0 to 9.3). CONCLUSIONS--Short term prognosis for recovery of function was poor but improved with time. Most patients had made a functional recovery by two years after initial clinic attendance. Impaired functioning was more likely with certain patient characteristics. Prospective studies are required to clarify whether these associations are the consequences of a more disabling illness or indicate factors contributing to impaired function.
PLDA-Based Clustering for Speaker Diarization of Broadcast Streams

This paper presents two approaches to speaker clustering based on Probabilistic Linear Discriminant Analysis (PLDA) in the speaker diarization task. We refer to the approaches as the multifold-PLDA approach and the onefold-PLDA approach. For both approaches, simple factor analysis model is employed to extract low-dimensional representation of a sequence of acoustic feature vectors – so called i-vectors – and these i-vectors are modeled using the PLDA model. Further, two-stage clustering with Bayesian Information Criterion (BIC) based approach applied in the ﬁrst stage and the PLDA-based approach in the second stage is examined. We carried out our experiments using the COST278 multilingual broadcast news database. The best evaluated system yielded 42 % relative improvement of the speaker error rate over a baseline BIC-based system.
Rapid classification based pedestrian detection in changing scenes

How to adapt to changing scenes in pedestrian detection is a difficult problem in visual monitoring. This paper proposed a pedestrian detection method in changing scenes. Response to the requirements of high detection speed and high detection rate of pedestrian detection method in changing scenes, this paper mainly consists of two parts: (1) proposing a general ternary classification framework. It is based on cascade classification framework and each stage is a ternary detection pattern, that is, through comparing stage threshold to exclude current pedestrians or non-pedestrians object and objects which is difficult determine will enter the next layer filtering. Such detection framework is faster than traditional method and is suitable for real time pedestrian detection system. (2) Considering the above mentioned detection framework relies on thresholds, the parameters of cascade classifier which trained in old scene require adaptive adjustment in a new scenario. We design a pedestrian method in changing scenes, using a small amount of data in new scene to assist the old scene classifier, taking cross entropy method to quickly optimizing these parameters combination so that the optimized classifier can be better adapt to pedestrian detection in changing scenes. The new classifier can receive high detection rate and high detection speed. Taking AHHF dataset as an old scene and NICTA dataset as the new scene, experiments show that the proposed method can apply to pedestrian detection in new scene and obtain good results.
Genomewide view of gene silencing by small interfering RNAs

RNA interference (RNAi) is an evolutionarily conserved mechanism in plant and animal cells that directs the degradation of messenger RNAs homologous to short double-stranded RNAs termed small interfering RNA (siRNA). The ability of siRNA to direct gene silencing in mammalian cells has raised the possibility that siRNA might be used to investigate gene function in a high throughput fashion or to modulate gene expression in human diseases. The specificity of siRNA-mediated silencing, a critical consideration in these applications, has not been addressed on a genomewide scale. Here we show that siRNA-induced gene silencing of transient or stably expressed mRNA is highly gene-specific and does not produce secondary effects detectable by genomewide expression profiling. A test for transitive RNAi, extension of the RNAi effect to sequences 5′ of the target region that has been observed in Caenorhabditis elegans, was unable to detect this phenomenon in human cells.
Security in Routing Protocol for Mobile Ad Hoc Network

Today's mobilizing world, corporation and government agencies are progressively used embedded and wireless technologies. Since the advent of wireless communication, the need for mobile ad hoc networks has been growing exponentially. MANET is a developing research area with applied applications. Due to fundamental characteristics of MANET, it is useful and more popular in mobilizing world. But these features such as open medium, dynamic topology,
Learner-centered web-based instruction in software engineering

During the past several years, there has been a growing demand for skilled software engineers, a demand that, unfortunately, has not been satisfied, resulting in a variety of problems for the discipline. This work presents a new approach called learner-centered Web-based instruction in software engineering that can be used to educate skilled engineers. The approach is based on three ideas. First, software engineering education must become more realistic. Second, software engineering education has to move closer to the learner. Finally, it must take advantage of the Web since this technology has the power of being a unique tool for implementing change in education. This work reports and discusses the results from the evaluation of the approach.