LLukas22/scidocs huggingface dataset:
Community-based therapy for children with multidrug-resistant tuberculosis.

OBJECTIVES
The goals were to describe the management of multidrug-resistant tuberculosis among children, to examine the tolerability of second-line antituberculosis agents among children, and to report the outcomes of children treated for multidrug-resistant tuberculosis in poor urban communities in Lima, Peru, a city with high tuberculosis prevalence.


METHODS
A retrospective analysis of data for 38 children <15 years of age with multidrug-resistant tuberculosis, either documented with drug sensitivity testing of the child's tuberculosis isolate or suspected on the basis of the presence of clinical symptoms for a child with a household contact with documented multidrug-resistant tuberculosis, was performed. All 38 children initiated a supervised individualized treatment regimen for multidrug-resistant tuberculosis between July 1999 and July 2003. Each child received 18 to 24 months of therapy with > or =5 first- or second-line drugs to which their Mycobacterium tuberculosis strain was presumed to be sensitive.


RESULTS
Forty-five percent of the children had malnutrition or anemia at the time of diagnosis, 29% had severe radiographic findings (defined as bilateral or cavitary disease), and 13% had extrapulmonary disease. Forty-five percent of the children were hospitalized initially because of the severity of illness. Adverse events were observed for 42% of the children, but no events required suspension of therapy for >5 days. Ninety-five percent of the children (36 of 38 children) achieved cures or probable cures, 1 child (2.5%) died, and 1 child (2.5%) defaulted from therapy.


CONCLUSIONS
Multidrug-resistant tuberculosis disease among children can be treated successfully in resource-poor settings. Treatment is well tolerated by children, and severe adverse events with second-line agents are rare.
Algebraic computation for the masses

Powerful algebraic manipulation systems will be available at very low costs in this decade. We are thus close to achieving the goal many of us have been after for nearly two decades, namely, availability of our systems to the masses. In this talk we shall discuss the problems we still face in making our systems useful to the hordes of potential users.
Comparative proteomic analysis reveals that T3SS, Tfp, and xanthan gum are key factors in initial stages of Citrus sinensis infection by Xanthomonas citri subsp. citri

The bacteria Xanthomonas citri subsp. citri (Xac) is the causal agent of citrus canker. The disease symptoms are characterized by localized host cell hyperplasia followed by tissue necrosis at the infected area. An arsenal of bacterial pathogenicity- and virulence-related proteins is expressed to ensure a successful infection process. At the post-genomic stage of Xac, we used a proteomic approach to analyze the proteins that are displayed differentially over time when the pathogen attacks the host plant. Protein extracts were prepared from infectious Xac grown in inducing medium (XAM1) for 24 h or from host citrus plants for 3 or 5 days after infection, detached times to evaluate the adaptation and virulence of the pathogen. The protein extracts were proteolyzed, and the peptides derived from tryptic digestion were investigated using liquid chromatography and tandem mass spectrometry. Changes in the protein expression profile were compared with the Xac genome and the proteome recently described under non-infectious conditions. An analysis of the proteome of Xac under infectious conditions revealed proteins directly involved in virulence such as the type III secretion system (T3SS) and effector proteins (T3SS-e), the type IV pilus (Tfp), and xanthan gum biosynthesis. Moreover, four new mutants related to proteins detected in the proteome and with different functions exhibited reduced virulence relative to the wild-type proteins. The results of the proteome analysis of infectious Xac define the processes of adaptation to the host and demonstrate the induction of the virulence factors of Xac involved in plant–pathogen interactions.
How To Extract Fashion Trends From Social Media? A Robust Object Detector With Support For Unsupervised Learning

With the proliferation of social media, fashion inspired from celebrities, reputed designers as well as fashion influencers has shortned the cycle of fashion design and manufacturing. However, with the explosion of fashion related content and large number of user generated fashion photos, it is an arduous task for fashion designers to wade through social media photos and create a digest of trending fashion. Designers do not just wish to have fashion related photos at one place but seek search functionalities that can let them search photos with natural language queries such as ‘red dress’, ’vintage handbags’, etc in order to spot the trends. This necessitates deep parsing of fashion photos on social media to localize and classify multiple fashion items from a given fashion photo. While object detection competitions such as MSCOCO have thousands of samples for each of the object categories, it is quite difficult to get large labeled datasets for fast fashion items. Moreover, state-of-the-art object detectors [2, 7, 9] do not have any functionality to ingest large amount of unlabeled data available on social media in order to fine tune object detectors with labeled datasets. In this work, we show application of a generic object detector [11], that can be pretrained in an unsupervised manner, on 24 categories from recently released Open Images V4 dataset. We first train the base architecture of the object detector using unsupervisd learning on 60K unlabeled photos from 24 categories gathered from social media, and then subsequently fine tune it on 8.2K labeled photos from Open Images V4 dataset. On 300 × 300 image inputs, we achieve 72.7% mAP on a test dataset of 2.4K photos while performing 11% to 17% better as compared to the state-of-the-art object detectors. We show that this improvement is due to our choice of architecture that lets us do unsupervised learning and that performs significantly better in identifying small objects. 1
Toward Entity Retrieval over Structured and Text Data

Many real-world applications increasingly involve both structured data and text. Hence, managing both in an efficient and integrated manner has received much attention from both the IR and database communities. To date, however, little research has been devoted to semantic issues in the integration of text and data. In this paper we introduced a problem in this realm: entity retrieval. Given data fragments that describe various aspects of a real-world entity, find all other data fragments as well as text documents that describe that same entity. As such, entity retrieval is a novel retrieval problem, which differs from both regular text retrieval and database search in that it explicitly requires matching information at the semantic level; matching syntactically as done in the current search engines and relational databases would be inherently non-optimal. We define entity retrieval and conduct a case study of retrieving information about a researcher from both the Web and a bibliographic database (DBLP). We propose several methods for exploiting the structured information in the database to improve entity retrieval over the text collection. Specifically, we present a query expansion mechanism based on extracted information from structured data. Experiment results show that selectively using more structured information to expand the text query improves entity retrieval performance on text. We conclude the paper with future research directions for entity retrieval.
PORTFOLIO DECISIONS OF SMALL AGRIBUSINESSES: EVIDENCE FROM THE 1993 NATIONAL SURVEY OF SMALL BUSINESS FINANCE

This study develops a model for the financial portfolio allocations of small businesses and identifies the financial decisions of small agribusiness firms to develop optimal portfolio strategies. We will compare the performance of two econometric models in identifying firm and owner characteristics that influence asset and liability holdings in small agribusinesses.
Selective Retina Therapy in Acute and Chronic-Recurrent Central Serous Chorioretinopathy.

PURPOSE
Selective retina therapy (SRT), the confined laser heating and destruction of retinal pigment epithelial cells, has been shown to treat acute types of central serous chorioretinopathy (CSC) successfully without damaging the photoreceptors and thus avoiding laser-induced scotoma. However, a benefit of laser treatment for chronic forms of CSC is questionable. In this study, the efficacy of SRT by means of the previously used 1.7-µs and shorter 300-ns pulse duration was evaluated for both types of CSC, also considering re-treatment for nonresponders.


MATERIAL AND METHODS
In a two-center trial, 26 patients were treated with SRT for acute (n = 10) and chronic-recurrent CSC (n = 16). All patients presented with subretinal fluid (SRF) in OCT and leakage in fluorescein angiography (FA). SRT was performed using a prototype SRT laser system (frequency-doubled Q-switched Nd:YLF-laser, wavelength 527 nm) with adjustable pulse duration. The following irradiation settings were used: a train of 30 laser pulses with a repetition rate of 100 Hz and pulse durations of 300 ns and 1.7 µs, pulse energy 120-200 µJ, retinal spot size 200 µm. Because SRT lesions are invisible, FA was always performed 1 h after treatment to demonstrate laser outcome (5-8 single spots in the area of leakage). In cases where energy was too low, as indicated by missing FA leakage, energy was adjusted and the patient re-treated immediately. Observation intervals were after 4 weeks and 3 months. In case of nonimprovement of the disease after 3 months, re-treatment was considered.


RESULTS
Of 10 patients with active CSC that presents focal leakage in FA, 5 had completely resolved fluid after 4 weeks and all 10 after 3 months. Mean visual acuity increased from 76.6 ETDRS letters to 85.0 ETDRS letters 3 months after SRT. Chronic-recurrent CSC was characterized by less severe SRF at baseline in OCT and weaker leakage in FA than in acute types. Visual acuity changed from baseline 71.6 to 72.8 ETDRS letters after 3 months. At this time, SRF was absent in 3 out of 16 patients (19%), FA leakage had come to a complete stop in 6 out of 16 patients (38%). In 6 of the remaining chronic CSC patients, repeated SRT with higher pulse energy was considered because of persistent leakage activity. After the re-treatment, SRF resolved completely in 5 patients (83.3%) after only 25 days.


CONCLUSION
SRT showed promising results in treating acute CSC, but was less effective in chronic cases. Interestingly, re-treatment resulted in enhanced fluid resolution and dry conditions after a considerably shorter time in most patients. Therefore, SRT including re-treatment if necessary might be a valuable CSC treatment alternative even in chronic-recurrent cases.
Building Virtual Reality Environments for Distance Education on the Web: A Case Study in Medical Education

The paper presents an investigation into the role of virtual reality and web technologies in the field of distance education. Within this frame, special emphasis is given on the building of web-based virtual learning environments so as to successfully fulfill their educational objectives. In particular, basic pedagogical methods are studied, focusing mainly on the efficient preparation, approach and presentation of learning content, and specific designing rules are presented considering the hypermedia, virtual and educational nature of this kind of applications. The paper also aims to highlight the educational benefits arising from the use of virtual reality technology in medicine and study the emerging area of web-based medical simulations. Finally, an innovative virtual reality environment for distance education in medicine is demonstrated. The proposed environment reproduces conditions of the real learning process and enhances learning through a real-time interactive simulator. Keywords—Distance education, medicine, virtual reality, web.
Efficacy and safety of intraarticular hylan or hyaluronic acids for osteoarthritis of the knee: a randomized controlled trial.

OBJECTIVE
To compare the efficacy and safety of intraarticular hylan and 2 hyaluronic acids (HAs) in osteoarthritis (OA) of the knee.


METHODS
This was a multicenter, patient-blind, randomized controlled trial in 660 patients with symptomatic knee OA. Patients were randomly assigned to receive 1 cycle of 3 intraarticular injections per knee of 1 of 3 preparations: a high molecular weight cross-linked hylan, a non-cross-linked medium molecular weight HA of avian origin, or a non-cross-linked low molecular weight HA of bacterial origin. The primary outcome measure was the change in the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain score at 6 months. Secondary outcome measures included local adverse events (effusions or flares) in injected knees. During months 7-12, patients were offered a second cycle of viscosupplementation.


RESULTS
Pain relief was similar in all 3 groups. The difference in changes between baseline and 6 months between hylan and the combined HAs was 0.1 on the WOMAC pain score (95% confidence interval [95% CI] -0.2, 0.3). No relevant differences were observed in any of the secondary efficacy outcomes, and stratified analyses provided no evidence for differences in effects across different patient groups. There was a trend toward more local adverse events in the hylan group than in the HA groups during the first cycle (difference 2.2% [95% CI -2.4, 6.7]), and this trend became more pronounced during the second cycle (difference 6.4% [95% CI 0.6, 12.2]).


CONCLUSION
We found no evidence for a difference in efficacy between hylan and HAs. In view of its higher costs and potential for more local adverse events, we see no rationale for the continued use of hylan in patients with knee OA.
Stroke Rehabilitation Reaches a Threshold

Motor training with the upper limb affected by stroke partially reverses the loss of cortical representation after lesion and has been proposed to increase spontaneous arm use. Moreover, repeated attempts to use the affected hand in daily activities create a form of practice that can potentially lead to further improvement in motor performance. We thus hypothesized that if motor retraining after stroke increases spontaneous arm use sufficiently, then the patient will enter a virtuous circle in which spontaneous arm use and motor performance reinforce each other. In contrast, if the dose of therapy is not sufficient to bring spontaneous use above threshold, then performance will not increase and the patient will further develop compensatory strategies with the less affected hand. To refine this hypothesis, we developed a computational model of bilateral hand use in arm reaching to study the interactions between adaptive decision making and motor relearning after motor cortex lesion. The model contains a left and a right motor cortex, each controlling the opposite arm, and a single action choice module. The action choice module learns, via reinforcement learning, the value of using each arm for reaching in specific directions. Each motor cortex uses a neural population code to specify the initial direction along which the contralateral hand moves towards a target. The motor cortex learns to minimize directional errors and to maximize neuronal activity for each movement. The derived learning rule accounts for the reversal of the loss of cortical representation after rehabilitation and the increase of this loss after stroke with insufficient rehabilitation. Further, our model exhibits nonlinear and bistable behavior: if natural recovery, motor training, or both, brings performance above a certain threshold, then training can be stopped, as the repeated spontaneous arm use provides a form of motor learning that further bootstraps performance and spontaneous use. Below this threshold, motor training is "in vain": there is little spontaneous arm use after training, the model exhibits learned nonuse, and compensatory movements with the less affected hand are reinforced. By exploring the nonlinear dynamics of stroke recovery using a biologically plausible neural model that accounts for reversal of the loss of motor cortex representation following rehabilitation or the lack thereof, respectively, we can explain previously hard to reconcile data on spontaneous arm use in stroke recovery. Further, our threshold prediction could be tested with an adaptive train-wait-train paradigm: if spontaneous arm use has increased in the "wait" period, then the threshold has been reached, and rehabilitation can be stopped. If spontaneous arm use is still low or has decreased, then another bout of rehabilitation is to be provided.
Evaluating Nicotine Craving, Withdrawal, and Substance Use as Mediators of Smoking Cessation in Cocaine- and Methamphetamine-Dependent Patients.

INTRODUCTION
Smoking is highly prevalent in substance dependence, but smoking-cessation treatment (SCT) is more challenging in this population. To increase the success of smoking cessation services, it is important to understand potential therapeutic targets like nicotine craving that have meaningful but highly variable relationships with smoking outcomes. This study characterized the presence, magnitude, and specificity of nicotine craving as a mediator of the relationship between SCT and smoking abstinence in the context of stimulant-dependence treatment.


METHODS
This study was a secondary analysis of a randomized, 10-week trial conducted at 12 outpatient SUD treatment programs. Adults with cocaine and/or methamphetamine dependence (N = 538) were randomized to SUD treatment as usual (TAU) or TAU+SCT. Participants reported nicotine craving, nicotine withdrawal symptoms, and substance use in the week following a uniform quit attempt of the TAU+SCT group, and self-reported smoking 7-day point prevalence abstinence (verified by carbon monoxide) at end-of-treatment.


RESULTS
Bootstrapped regression models indicated that, as expected, nicotine craving following a quit attempt mediated the relationship between SCT and end-of-treatment smoking point prevalence abstinence (mediation effect = 0.09, 95% CI = 0.04% to 0.14%, P < .05, 14% of total effect). Nicotine withdrawal symptoms and substance use were not significant mediators (Ps > .05, <1% of total effect). This pattern held for separate examinations of cocaine and methamphetamine dependence.


CONCLUSIONS
Nicotine craving accounts for a small but meaningful portion of the relationship between smoking-cessation treatment and smoking abstinence during SUD treatment. Nicotine craving following a quit attempt may be a useful therapeutic target for increasing the effectiveness of smoking-cessation treatment in substance dependence.
Solid-State Transformer and MV Grid Tie Applications Enabled by 15 kV SiC IGBTs and 10 kV SiC MOSFETs Based Multilevel Converters

Medium-voltage (MV) SiC devices have been developed recently which can be used for three-phase MV grid tie applications. Two such devices, 15 kV SiC insulated-gate bipolar transistor (IGBT) and 10 kV SiC MOSFET, have opened up the possibilities of looking into different converter topologies for the MV distribution grid interface. These can be used in MV drives, active filter applications, or as the active front end converter for solid-state transformers (SSTs). The transformerless intelligent power substation (TIPS) is one such application for these devices. TIPS is proposed as a three-phase SST interconnecting a 13.8 kV distribution grid with a 480 V utility grid. It is an all SiC device-based multistage SST. This paper focuses on the advantages, design considerations, and challenges associated with the operation of converters using these devices keeping TIPS as the topology of reference. The efficiency of the TIPS topology is also calculated using the experimentally measured loss data of the devices and the high-frequency transformer. Experimental results captured on a developed prototype of TIPS along with its measured efficiency are also given.
Nudging guideline-concordant antibiotic prescribing: a randomized clinical trial.

IMPORTANCE
"Nudges" that influence decision making through subtle cognitive mechanisms have been shown to be highly effective in a wide range of applications, but there have been few experiments to improve clinical practice.


OBJECTIVE
To investigate the use of a behavioral "nudge" based on the principle of public commitment in encouraging the judicious use of antibiotics for acute respiratory infections (ARIs).


DESIGN, SETTING, AND PARTICIPANTS
Randomized clinical trial in 5 outpatient primary care clinics. A total of 954 adults had ARI visits during the study timeframe: 449 patients were treated by clinicians randomized to the posted commitment letter (335 in the baseline period, 114 in the intervention period); 505 patients were treated by clinicians randomized to standard practice control (384 baseline, 121 intervention).


INTERVENTIONS
The intervention consisted of displaying poster-sized commitment letters in examination rooms for 12 weeks. These letters, featuring clinician photographs and signatures, stated their commitment to avoid inappropriate antibiotic prescribing for ARIs.


MAIN OUTCOMES AND MEASURES
Antibiotic prescribing rates for antibiotic-inappropriate ARI diagnoses in baseline and intervention periods, adjusted for patient age, sex, and insurance status.


RESULTS
Baseline rates were 43.5% and 42.8% for control and poster, respectively. During the intervention period, inappropriate prescribing rates increased to 52.7% for controls but decreased to 33.7% in the posted commitment letter condition. Controlling for baseline prescribing rates, we found that the posted commitment letter resulted in a 19.7 absolute percentage reduction in inappropriate antibiotic prescribing rate relative to control (P = .02). There was no evidence of diagnostic coding shift, and rates of appropriate antibiotic prescriptions did not diminish over time.


CONCLUSIONS AND RELEVANCE
Displaying poster-sized commitment letters in examination rooms decreased inappropriate antibiotic prescribing for ARIs. The effect of this simple, low-cost intervention is comparable in magnitude to costlier, more intensive quality-improvement efforts.


TRIAL REGISTRATION
clinicaltrials.gov identifier: NCT01767064.
Recognition of Tables and Forms

Tables and forms are a very common way to organize information in structured documents. Their recognition is fundamental for the recognition of the documents. Indeed, the physical organization of a table or a form gives a lot of information concerning the logical meaning of the content. This chapter presents the different tasks that are related to the recognition of tables and forms and the associated well-known methods and remaining B. Coüasnon ( ) IRISA/INSA de Rennes, Rennes Cedex, France e-mail: couasnon@irisa.fr A. Lemaitre IRISA/Université Rennes 2, Rennes Cedex, France e-mail:couasnon@irisa.fr D. Doermann, K. Tombre (eds.), Handbook of Document Image Processing and Recognition, DOI 10.1007/978-0-85729-859-1 20, © Springer-Verlag London 2014 647 648 B. Coüasnon and A. Lemaitre challenges. Three main tasks are pointed out: the detection of tables in heterogeneous documents; the classification of tables and forms, according to predefined models; and the recognition of table and form contents. The complexity of these three tasks is related to the kind of studied document: image-based document or digital-born documents. At last, this chapter will introduce some existing systems for table and form analysis.