Miracle-dz/UniFAR-FTUs huggingface dataset:
Evidence for Policy Making: Clinical Appropriateness Study of Lumbar Spine MRI Prescriptions Using RAND Appropriateness Method.

BACKGROUND MRI is a new and expensive diagnostic technology, which has been used increasingly all over the world. Low back pain is a worldwide prevalent disorder and MRI technique is one of the several ways to diagnose it. This paper aims to identify the appropriateness of lumbar spine MRI prescriptions in Shiraz teaching hospitals using standardized RAND Appropriateness Method (RAM) criteria in 2012. METHODS This study consisted of two phases. The first phase involved a qualitative enquiry and the second phase had a quantitative cross-sectional nature. In the first phase RAM was used for developing lumbar spine MRI indications and scenarios. In the second phase, the finalized scenarios were compared with the history and physical examination of 300 patients with low back pain. The rate of appropriateness of lumbar spine MRI prescription was then calculated. RESULTS Of 300 cases of lumbar spine MRI prescriptions, approximately 167 (56%) were considered inappropriate, 72 (24%) were uncertain, and 61 (20%) were deemed to be appropriate. The economic burden of inappropriate prescriptions was calculated at 88,009,000 Rials. In addition, the types of expertise and physical examination were considered as related factors to appropriateness of prescriptions. CONCLUSION In conclusion, a large proportion of lumbar spine MRI prescriptions, which result in financial burden on the insurance companies and the patients alike is unnecessary. This study suggests that policy makers consider this evidence while decision-making. Our findings highlight the imperative role of Health Technology Assessment (HTA) and Clinical Practice Guidelines (CPGs). As a result, developing local clinical guidelines may create the commitment needed in physicians in prescribing appropriate prescriptions within the health sector. The study further recommends that appropriate scenarios should be considered as a criterion for payment and reimbursement.
Image collection summarization for search result overviewing on mobile devices

Due to small displays of mobile devices, overviewing an image search result that contains many and various images is difficult. To provide an overview of thousands of images, recent studies have tried to develop a framework for image collection summarization that extracts a smaller set of representative images from the original set. Most existing methods take (a) relevance and (b) coverage of each image into account. However, for the use on mobile devices, several important issues remain: generated summaries must be compact enough so as to suit the small mobile displays but the legibility of the summaries should be sufficient -- but how? Our focus in this paper is to extend the framework of image collection summarization to fit the context of overviewing image search results on mobile devices. The key advances of this paper are to introduce two primary factors of (c) compactness and (d) legibility when generating summaries. Our solution is a two-stage optimization method. Given a keyword query and display size, its first stage ranks the images by taking (a) relevance and (b) coverage into account. The second optimization stage takes into account (c) compactness and (d) legibility and determines the number and sizes of images included in the final summary so as to satisfy the display size constraint. Experiments conducted on over 240,000 images demonstrate the effectiveness of our method.
Drop Out Feature of Student Data for Academic Performance Using Decision Tree Techniques

Studentsâ€™ academic performance is critical for educational institutions because strategic programs can be planned in improving or maintaining studentsâ€™ performance during their period of studies in the institutions. The academic performance in this study is measured by their cumulative grade point average (CGPA) upon graduating. This study presents the work of data mining in predicting the drop out feature of students. This study applies decision tree technique to choose the best prediction and analysis. The list of students who are predicted as likely to drop out from college by data mining is then turned over to teachers and management for direct or indirect intervention.
Multicenter clinical laboratory evaluation of a beta-lactamase disk assay employing a novel chromogenic cephalosporin, S1

S1, a new chromogenic cephalosporin (International BioClinical, Inc., Portland, Oreg.), was used to detect beta-lactamase production among a variety of commonly encountered bacteria in a four-center collaborative study. Results of an S1 disk assay were compared with those obtained by a nitrocefin-based disk procedure (Cefinase; Becton-Dickinson Microbiology Systems, Cockeysville, Md.), with repetitive testing of five quality control organisms and with individual tests of recent clinical isolates of Neisseria gonorrhoeae (162 strains), Haemophilus influenzae (162 strains), Moraxella catarrhalis (155 strains), Staphylococcus aureus (161 strains), and Bacteroides fragilis (164 strains). The performances of the two beta-lactamase disk assays were comparable for the first three species cited above. However, the S1 assay appeared to be a more sensitive procedure than the Cefinase assay when applied to S. aureus and B. fragilis, with respect to both total numbers of positive results and length of time to a definitive positive endpoint.
Study of Greedy Search with Multiple Improvement Heuristics for Vehicle Routing Problems

Vehicle routing problems have been extensively studied using a variety of search methods and meta-heuristics. However, most searchmethods are carried out using only a single improvement heuristic. Here, we report on a study using four improvement heuristics embedded in a simple steepest descent search engine. We conclude that reasonable results can be produced quickly by this simple method. A small study of the effectiveness of the different improvement heuristics was also undertaken—it is shown that the RELOCATEoperatoris invaluable andthat solutions with longervehicle routes beneﬁted more from using a rich set of improvement heuristics.
Diusive Transport Enhanced by Thermal Velocity Fluctuations

We study the contribution of advection by thermal velocity fluctuations to the effective diffusion coefficient in a mixture of two identical fluids. We find good agreement between a simple fluctuating hydrodynamics theory and particle and finite-volume simulations. The enhancement of the diffusive transport depends on the system size L and grows as ln(L/L0) in quasi two-dimensional systems, while in three dimensions it scales as L−1 0 − L−1, where L0 is a reference length. Our results demonstrate that fluctuations play an important role in the hydrodynamics of small-scale systems.
User tweets based genre prediction and movie recommendation using LSI and SVD

The emerging popularity and raise in users' posts on social media gave birth to numerous research challenges. Out of all challenges users' centric context information based recommendation is one prime research area to recommend jobs, events and movies. Here in this research work we focus on movie context aware recommendation and for this purpose, we analyze users' posted movie tweets to understand their intentions for the same. Therefore, the objective of this research work is to predict genre of movies based on user's posted movie tweets and recommending movies to users' according to predicted genre. For this purpose, we pre-processed twitter extracted movie tweets using tokenization, porter stemming, stop word removal and use Word-Net dictionary for synonym matching. Further, we apply Latent Semantic Indexing technique which in turn involves Singular Value Decomposition on this pre-processed data and predicts genre on the basis of IMDb movie genre categorization. The predicted genre conveys the movie interest of the user and to recommend movie on the basis of predicted genre which is measured through euclidean distance. We have extracted IMdb given movie data and further predicted genre using our proposed technique. To validate this we divided our dataset using pareto principle and matched with IMDb given genre data set and achieved approximate 70% accuracy using our approach.
Segmentation of Speech Signals in Template-based Speech to Singing Conversion

Singing voice synthesis has found numerous applications in the entertainment industry over the recent years. The template-based personalized singing voice synthesis method is a new method of generating high quality singing voice, which synthesizes the singing voice by means of conversion from the narrated lyrics of a song. In this synthesis method, template speaking and singing voices are first recorded for the purpose of modeling the transformation from speech to singing. To improve its accuracy while reducing computational load, the template voices are divided into several segments so that fine alignment and subsequent conversion can be performed separately for each segment. To correctly generate singing voice, a new instance of speech has to be divided into similar segments, each containing the same stanza as in the template voices. In order to achieve this, an automatic segmentation method is proposed in this paper. The experiment results have shown that the segmentation of speech signals using our method is comparable to manual segmentation, with an accuracy of 98.24%. This performance is consistent even in the presence of noise.
Plant flavonoids target Pseudomonas syringae pv. tomato DC3000 flagella and type III secretion system.

Flavonoids are among the most abundant plant secondary metabolites involved in plant protection against pathogens, but micro-organisms have developed resistance mechanisms to those compounds. We previously demonstrated that the MexAB-OprM efflux pump mediates resistance of Pseudomonas syringae pv. tomato (Pto) DC3000 to flavonoids, facilitating its survival and the colonization of the host. Here, we have shown that tomato plants respond to Pto infection producing flavonoids and other phenolic compounds. The effects of flavonoids on key traits of this model plant-pathogen bacterium have also been investigated observing that they reduce Pto swimming and swarming because of the loss of flagella, and also inhibited the expression and assembly of a functional type III secretion system. Those effects were more severe in a mutant lacking the MexAB-OprM pump. Our results suggest that flavonoids inhibit the function of the GacS/GacA two-component system, causing a depletion of rsmY RNA, therefore affecting the synthesis of two important virulence factors in Pto DC3000, flagella and the type III secretion system. These data provide new insights into the flavonoid role in the molecular dialog between host and pathogen.
Discriminative vision-based recovery and recognition of human motion

The automatic analysis of human motion from images opens up the way for applications in the domains of security and surveillance, human-computer interaction, animation, retrieval and sports motion analysis. In this dissertation, the focus is on robust and fast human pose recovery and action recognition. The former is a regression task where the aim is to determine the locations of key joints in the human body, given an image of a human figure. The latter is the process of labeling image sequences with action labels, a classification task. An example-based pose recovery approach is introduced where histograms of oriented gradients (HOG) are used as the image descriptor. From a database containing thousands of HOG-pose pairs, the visually closest examples are selected. Weighted interpolation of the corresponding poses is used to obtain the pose estimate. This approach is fast due to the use of a low-cost distance function. To cope with partial occlusions of the human figure, the normalization and matching of the HOG descriptors was changed from global to the cell level. When occlusion areas in the image are predicted, only part of the descriptor can be used for recovery, thus avoiding adaptation of the database to the occlusion setting. For the recognition of human actions, simple functions are used to discriminate between two classes after applying a common spatial patterns (CSP) transform on sequences of HOG descriptors. In the transform, the difference in variance between two classes is maximized. Each of the discriminative functions softly votes into the two classes. After evaluation of all pairwise functions, the action class that receives most of the voting mass is the estimated class. By combining the two approaches, actions could be recognized by considering sequences of recovered, rotation-normalized poses. Thanks to this normalization, actions could be recognized from arbitrary viewpoints. By handling occlusions in the pose recovery step, actions could be recognized from image observations where occlusion was simulated.
A Human Keratinocyte Cell Line Produces Two Autocrine Growth Inhibitors, Transforming Growth Factor-β and Insulin-like Growth Factor Binding Protein-6, in a Calcium- and Cell Density-dependent Manner (*)

Two growth inhibitors were identified in culture medium conditioned by a human keratinocyte cell line, HaCat. TGF-β was detected in media conditioned by growing or confluent HaCat cells, as well as in media conditioned at physiological (1 mM) or low (0.03 mM) Ca2+ concentrations. However, a considerable part of transforming growth factor β (TGF-β) in media conditioned at a physiological Ca2+ concentration was in active form, whereas most TGF-β in media conditioned at a low Ca2+ concentration was latent. The other growth-inhibitory activity, which was detected only in media conditioned by confluent cells at a physiological Ca2+ concentration, was purified to homogeneity by a four-step procedure. The N-terminal amino acid sequence of the 33-kDa protein was identical with that of insulin-like growth factor binding protein-6 (IGFBP-6). Purified IGFBP-6 inhibited the growth of HaCat and Balb/MK keratinocyte cell lines, as well as Mv1Lu cells. The growth activity was also demonstrated by human recombinant IGFBP-6. In summary, HaCat cells secrete at least two possible autocrine growth inhibitors: TGF-β which is secreted constitutively, but activated in a Ca2+-dependent manner, and IGFBP-6 which is secreted in a cell density- and Ca2+-dependent manner.
Chronic expression of monocyte chemoattractant protein‐1 in the central nervous system causes delayed encephalopathy and impaired microglial function in mice

Increased central nervous system (CNS) levels of monocyte chemoattractant protein 1 [CC chemokine ligand 2 (CCL2) in the systematic nomenclature] have been reported in chronic neurological diseases such as human immunodeficiency virus type 1‐associated dementia, amyotrophic lateral sclerosis, and multiple sclerosis. However, a pathogenic role for CCL2 has not been confirmed, and there is no established model for the effects of chronic CCL2 expression on resident and recruited CNS cells. We report that aged (>6 months) transgenic (tg) mice expressing CCL2 under the control of the human glial fibrillary acidic protein promoter (huGFAP‐CCL2hi tg+ mice) manifested encephalopathy with mild perivascular leukocyte infiltration, impaired blood brain barrier function, and increased CD45‐immunoreactive microglia, which had morphologic features of activation. huGFAP‐CCL2hi tg+ mice lacking CC chemokine receptor 2 (CCR2) were normal, showing that chemokine action via CCR2 was required. Studies of cortical slice preparations using video confocal microscopy showed that microglia in the CNS of huGFAP‐CCL2hi tg+ mice were defective in expressing amoeboid morphology. Treatment with mutant CCL2 peptides, a receptor antagonist and an obligate monomer, also suppressed morphological transformation in this assay, indicating a critical role for CCL2 in microglial activation and suggesting that chronic CCL2 exposure desensitized CCR2 on microglia, which in the CNS of huGFAP‐CCL2hi tg+ mice, did not up‐regulate cell‐surface expression of major histocompatibility complex class II, CD11b, CD11c, or CD40, in contrast to recruited perivascular macrophages that expressed enhanced levels of these markers. These results indicate that huGFAP‐CCL2hi tg+ mice provide a useful model to study how chronic CNS expression of CCL2 alters microglial function and CNS physiology. —Huang, D. , Wujek, J., Kidd, G. , He, T. T. , Cardona, A. , Sasse, M. E. , Stein, E. J., Kish, J., Tani, M. , Charo, I. F. , Proudfoot, A. E. , Rollins, B. J., Handel, T. , Ransohoff, R. M. Chronic expression of monocyte chemoattractant protein‐1 in the central nervous system causes delayed encephalopathy and impaired microglial function in mice. FASEB J. 19, 761–772 (2005)
From Grey Scale B-Mode to Elastosonography: Multimodal Ultrasound Imaging in Meningioma Surgery—Pictorial Essay and Literature Review

The main goal in meningioma surgery is to achieve complete tumor removal, when possible, while improving or preserving patient neurological functions. Intraoperative imaging guidance is one fundamental tool for such achievement. In this regard, intra-operative ultrasound (ioUS) is a reliable solution to obtain real-time information during surgery and it has been applied in many different aspect of neurosurgery. In the last years, different ioUS modalities have been described: B-mode, Fusion Imaging with pre-operative acquired MRI, Doppler, contrast enhanced ultrasound (CEUS), and elastosonography. In this paper, we present our US based multimodal approach in meningioma surgery. We describe all the most relevant ioUS modalities and their intraoperative application to obtain precise and specific information regarding the lesion for a tailored approach in meningioma surgery. For each modality, we perform a review of the literature accompanied by a pictorial essay based on our routinely use of ioUS for meningioma resection.
ScienceDirect 20 th European Conference on Fracture ( ECF 20 ) Parametric study of edge crack of silicon steel strip in cold rolling based on a shear modified GTN damage model

Edge cracking is a commonly observed phenomenon during the cold rolling process of the silicon steel strip which may cause the rupture of strip and reduce the product quality and productivity. In this work, the damage behavior and edge cracking of steel strip in cold rolling is analyzed based on a shear modified Gurson model. Taguchi experimental design method is used to analyze the effects of reduction ratio, roll diameter, tension, friction coefficient on the initiation and propagation of edge cracks. The analysis results reveal that the possibility of edge crack for silicon steel increases with the increasing of reduction ratio, tension, friction coefficient and the decrease of roll diameter. © 2014 The Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of the Norwegian University of Science and Technology (NTNU), Department of Structural Engineering.
Improved Design of Shearing Sections with New Calculation Models Based on 3D Finite‐Element Simulations

New models for the Maddock and spiral shearing sections have been developed, employing three-dimensional finite element analysis (3D FEA). These models describe the pressure-throughput and power consumption behavior of the shearing sections for both the extrusion and the injection molding process and have been implemented in the REX 6.0 and PSI 4.0 simulation software. As a consequence it is now possible to describe the process behavior of these shearing sections within just a few seconds with the accuracy of FEA calculations. Actual Maddock shearing section (left) and actual spiral shearing section (right).
Triangles as basis to detect communities: an application to Twitter's network

Nowadays, the interest given by the scientific community to the investigation of the data generated by social networks is increasing as much as the exponential increasing of social network data. The data structure complexity is one among the snags, which slowdown their understanding. On the other hand, community detection in social networks helps the analyzers to reveal the structure and the underlying semantic within communities. In this paper we propose an interactive visualization approach relying on our application NLCOMS, which uses synchronous and related views for graph and community visualization. Additionally, we present our algorithm for community detection in networks. A computation study is conducted on instances generated with the LFR [9]-[10] benchmark. Finally, in order to assess our approach on real-world data, we consider the data of the ANR-Info-RSN project. The latter addresses community detection in Twitter.
Preparing Text Reports from Web Pages Employing Similarity Tests

The World Wide Web is the main source of information for many organizations and common users. However, the analysis and selection of the web content is still an arduous manual task in many cases. When a web query is sent towards a web search engine, a list of URLs is received, frequently ordered by popularity (such as Google's PageRank algorithm). Then, the user must read and analyze each URL in order to find out the convenient information. In this work a method that automatically constructs a text report induced by a web query from a set of URLs is presented. The method extracts text slices (excerpts) from web pages considering the most similar text w.r. t. a web query as slicing criterion. A slice is composed by document object model (DOM) nodes, whereas similarity is calculated using standard techniques employed in natural language processing.
Radiation therapy to the primary tumor in locally advanced prostate cancer is not "closing the barn door after the horse has bolted".

The National Cancer Institute of Canada (NCIC) Clinical Trials Group PR.3/Medical Research Council PR07/ Intergroup T94-0110 (1) was a randomized controlled trial (RCT) of radiation therapy (RT) and androgen deprivation therapy (ADT) vs. ADT alone, for men with locally advanced prostate cancer. The authors defined locally advanced as: (I) T3-4, N0/X, M0; or (II) T1-2 with prostate specific antigen (PSA) > 40 ng/mL; or (III) PSA 20-40 ng/mL and Gleason 8-10. Men were randomized to lifelong ADT vs. ADT + RT, 65-69 Gy in 1.8 Gy fractions, using 3D conformal RT, to the prostate and pelvis or prostate alone. Of the 1,205 patients treated between 1995 and 2005, 602 received ADT alone and 603 received ADT + RT. Overall survival (OS) was significantly improved in the patients allocated to ADT + RT [hazard ratio (HR) =0.70; 95% CI, 0.57-0.85; P<0.001]. Prostate cancer specific mortality (CSM) was improved in the patients allocated to ADT + RT (HR =0.46; 95% CI, 0.34-0.61; P<0.001). Although patients on ADT + RT arm reported a higher rate of gastrointestinal (GI) toxicity, only 2 of 589 patients had grade 3 or greater diarrhea at 24 months after RT.