LLukas22/scidocs huggingface dataset:
Use of Vacuum Assisted Closure Therapy in the Treatment of Diabetic Foot Wounds

Diabetic foot disease is a major health problem, which affects up to 15% of the more than 200 million patients with diabetes worldwide and is associated with an increased risk of amputation. VacuumAssisted Closure (V.A.C.®) Therapy has been shown to be effective in the treatment of diabetic foot wounds. In two parallel randomized controlled trials we have evaluated the effectiveness of VAC Therapy in enhancing skin-graft take of diabetic foot wounds (study I) and the effectiveness in treatment of infected open minor amputations (study II). In study I, 70 patients were randomly assigned to either VAC Therapy (V1 group) or coverage of the grafts with non adherent gauze (C1 group). In study II, 130 diabetic subjects were randomized to either surgical debridement and VAC Therapy (V2 group) or surgical debridement and semi-occlusive silver dressing (C2 group). In study I the take rate was 80% in the V1 group versus 68% in the C1 group (p = 0.05). In study II a more rapid development of granulation tissue covering the exposed bone was shown in the V2 group when compared to the C2 group (41±8 vs 59±18 days, p = 0.03). Also a better and more rapid control of the infections (10±8 days in V2 group vs 19±13 days in C2 group; p = 0.05) and reduced time to complete closure of the wound was found with VAC Therapy (65±16 days in V2 group vs 98±45 days in C2 group, p = 0.005). Total time required for surgical procedures was reduced in the VAC group ( 2.5 hours versus 6 hours in the control group, p = 0.02). In conclusion, this study demonstrates that treating diabetic wounds with VAC Therapy can result in a faster wound bed preparation, a faster closure, and in a better graft take rate when compared to standard wound care.
Optimal design of superelastic‐friction base isolators for seismic protection of highway bridges against near‐field earthquakes

The seismic response of a multi-span continuous bridge isolated with novel superelasticfriction base isolator (S-FBI) is investigated under near-field earthquakes. The isolation system consists of a flat steel-Teflon sliding bearing and a superelastic NiTi shape memory alloy (SMA) device. The key design parameters of an S-FBI system are the natural period of the isolated bridge, the yielding displacement of the SMA device, and the friction coefficient of the sliding bearings. The goal of this study is to obtain optimal values for each design parameter by performing sensitivity analysis of a bridge isolated by an S-FBI system. First, a three-span continuous bridge is modeled as two-degrees-of-freedom with the S-FBI system. A neuro-fuzzy model is used to capture rateand temperature-dependent nonlinear behavior of the SMA device. Then, a set of nonlinear time history analyses of the isolated bridge is performed. The variation of the peak response quantities of interest is shown as a function of design parameters of the S-FBI system and the optimal values for each parameter are evaluated. Next, in order to assess the effectiveness of the S-FBI system, the response of the bridge isolated by the S-FBI system is compared with the response of the non-isolated bridge and the same bridge isolated by pure-friction (P-F) sliding isolation system. Finally, the influence of temperature variations on the performance of the S-FBI system is evaluated. The results show that the optimum design of a bridge with the S-FBI system can be achieved by a judicious specification of design parameters.
[Efficacy of a treatment program for sexually abused children].

OBJECTIVE
An evaluation study was conducted in order to evaluate the impact of the treatment program for sexually abused children.


METHOD
Forty-one (41) children (aged 6-17 years), victims of a sexual abuse by a family member, were assessed at pre- and post-treatment (16 months following the pre-test). The evolution of children's psychological well-being was measured by the Children's Depression Inventory (CDI), the Picturial Scale of Perceived Competence and Acceptance for Young Children (PSPCA), the Children's Nowicki-Strickland Internal-External control scale (CNS-IE), the Children's Action Tendency Scale (CATS), the Revised Children's Manifest Anxiety Scale (RCMAS), and the Pediatric Behavior Scale (PBS). A hierarchical multiple regression analysis was used to assess the strength of the relationship between the level of participation in both individual (including dyadic and family therapy) and group therapy and the evolution of Ss' psychological well-being.


RESULTS
Results indicate that the child's mental health was generally positively related to the level of participation in individual therapy but not related or negatively related with the level of participation in group sessions except for the PBS.


CONCLUSIONS
These results indicate the need: (a) to consider the adoption of a dose measurement in the appreciation of the therapeutic impact; (b) to have a better grasp of the nature and the effects of specific therapeutic activities included in a program; (c) to have a better understanding of the disparities observed between parents' and children's evaluation of the psychological status of the child.
Hybrid asymmetrically clipped OFDM-based IM/DD optical wireless system

In this paper, we present a hybrid asymmetrically clipped optical orthogonal frequency division multiplexing (OFDM) system. This system uses a combination of asymmetrically clipped optical OFDM (ACO-OFDM) and pulse amplitude modulated discrete multitone (PAM-DMT) techniques, which can be used in intensity modulated direct detection (IM/DD) optical wireless (OW) systems. In this hybrid scheme, ACO-OFDM and PAM-DMT signals are transmitted together. Clipping noise is estimated at the receiver and canceled to recover the PAM-DMT symbols. This scheme does not require any DC bias for transmission, which makes the transmitter less complex and very power efficient. With this system, we can increase the data rate of the ACO-OFDM system by almost twice. In addition, no bandwidth penalty is incurred. Extensive computer simulations show that the bit-error rate (BER) performance of ACO-OFDM in the additive white Gaussian noise environment is not affected by any kind of interference, but only due to half of the available transmit power, we see a 3 dB degradation. However, the BER performance of PAM-DMT shows some degradation at low signal-to-noise ratio (SNR) but is identical to the conventional scheme at higher SNR. We also see a slight improvement in peak-to-average power ratio (PAPR) of the output combined signal. Therefore, advantages such as increased data rate, DC-bias elimination, no bandwidth, and PAPR penalty make this scheme very attractive for OW systems using IM/DD.
Visibility culling using hierarchical occlusion maps

We present hierarchical occlusion maps (HOM) for visibility culling on complex models with high depth complexity. The culling algorithm uses an object space bounding volume hierarchy and a hierarchy of image space occlusion maps. Occlusion maps represent the aggregate of projections of the occluders onto the image plane. For each frame, the algorithm selects a small set of objects from the modelas occludersand renders them to form an initial occlusion map, from which a hierarchy of occlusion maps is built. The occlusion maps are used to cull away a portion of the model not visible from the current viewpoint. The algorithm is applicable to all models and makes no assumptions about the size, shape, or type of occluders. It supports approximate culling in which small holes in or among occluders can be ignored. The algorithm has been implemented on current graphics systems and has been applied to large models composed of hundreds of thousands of polygons. In practice, it achieves significant speedup in interactive walkthroughs of models with high depth complexity. CR
Efficient record-level wrapper induction

Web information is often presented in the form of record, e.g., a product record on a shopping website or a personal profile on a social utility website. Given a host webpage and related information needs, how to identify relevant records as well as their internal semantic structures is critical to many online information systems. Wrapper induction is one of the most effective methods for such tasks. However, most traditional wrapper techniques have issues dealing with web records since they are designed to extract information from a page, not a record. We propose a record-level wrapper system. In our system, we use a novel ``broom'' structure to represent both records and generated wrappers. With such representation, our system is able to effectively extract records and identify their internal semantics at the same time. We test our system on 16 real-life websites from four different domains. Experimental results demonstrate 99\% extraction accuracy in terms of F1-Value.
Text detection, recognition in images and video frames

This paper presents a new method for detecting and recognizing text in complex images and video frames. Text detection is performed in a two-step approach that combines the speed of a text localization step, enabling text size normalization, with the strength of a machine learning text veri3cation step applied on background independent features. Text recognition, applied on the detected text lines, is addressed by a text segmentation step followed by an traditional OCR algorithm within a multi-hypotheses framework relying on multiple segments, language modeling and OCR statistics. Experiments conducted on large databases of real broadcast documents demonstrate the validity of our approach. ? 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
Study of inclusive multi-ring events from atmospheric neutrinos

Abstract The current analysis of atmospheric neutrinos by the Super-Kamiokande Collaboration is based only on fully-contained one-ring events and partially contained events. We show that the up-down ratio of fully-contained, inclusive, multi-ring events gives an independent test of the atmospheric neutrino anomaly, without the need for particle identification. Moreover, this class of events is rich in neutral current events and hence gives crucial information for discriminating between oscillations of ν μ into ν e , τ and ν s .
Early Prediction of Cardiac Arrest (Code Blue) using Electronic Medical Records

Code Blue is an emergency code used in hospitals to indicate when a patient goes into cardiac arrest and needs resuscitation. When Code Blue is called, an on-call medical team staffed by physicians and nurses is paged and rushes in to try to save the patient's life. It is an intense, chaotic, and resource-intensive process, and despite the considerable effort, survival rates are still less than 20% [4]. Research indicates that patients actually start showing clinical signs of deterioration some time before going into cardiac arrest [1][2[][3], making early prediction, and possibly intervention, feasible. In this paper, we describe our work, in partnership with NorthShore University HealthSystem, that preemptively flags patients who are likely to go into cardiac arrest, using signals extracted from demographic information, hospitalization history, vitals and laboratory measurements in patient-level electronic medical records. We find that early prediction of Code Blue is possible and when compared with state of the art existing method used by hospitals (MEWS - Modified Early Warning Score)[4], our methods perform significantly better. Based on these results, this system is now being considered for deployment in hospital settings.
Combination lithium and divalproex sodium in pediatric bipolar symptom re-stabilization.

OBJECTIVE
It has been reported that bipolar disorder may become less responsive to previously effective treatment with each symptomatic relapse. The primary goal of this study was to assess the rate of re-stabilization after the resumption of lithium (Li) plus divalproex (DVPX) following relapse on either agent as monotherapy.


METHOD
This is a prospective, 8-week, open-label outpatient Li/DVPX combination therapy trial. Patients ages 5 to 17 years with bipolar disorder type I or II, who had achieved symptom remission with Li/DVPX combination therapy and subsequently relapsed during treatment with Li or DVPX monotherapy were enrolled between January 1999 and January 2003.


RESULTS
Thirty-eight patients with a mean age of 10.5 years entered the study. Thirty-four (89.5%) patients responded to treatment with Li/DVPX mood stabilizer therapy alone, but four patients required adjunctive antipsychotic treatment to address residual symptomatology. Overall, reinitiation of Li/DVPX combination therapy was well tolerated with no subjects discontinuing because of a medication-related adverse event.


CONCLUSIONS
It appears that most youths with bipolar disorder who stabilize on combination Li/DVPX therapy and subsequently relapse during monotherapy can safely and effectively be re-stabilized with the reinitiation of Li/DVPX combination treatment.
Language mapping with navigated repetitive TMS: Proof of technique and validation

OBJECTIVE
Lesion-based mapping of speech pathways has been possible only during invasive neurosurgical procedures using direct cortical stimulation (DCS). However, navigated transcranial magnetic stimulation (nTMS) may allow for lesion-based interrogation of language pathways noninvasively. Although not lesion-based, magnetoencephalographic imaging (MEGI) is another noninvasive modality for language mapping. In this study, we compare the accuracy of nTMS and MEGI with DCS.


METHODS
Subjects with lesions around cortical language areas underwent preoperative nTMS and MEGI for language mapping. nTMS maps were generated using a repetitive TMS protocol to deliver trains of stimulations during a picture naming task. MEGI activation maps were derived from adaptive spatial filtering of beta-band power decreases prior to overt speech during picture naming and verb generation tasks. The subjects subsequently underwent awake language mapping via intraoperative DCS. The language maps obtained from each of the 3 modalities were recorded and compared.


RESULTS
nTMS and MEGI were performed on 12 subjects. nTMS yielded 21 positive language disruption sites (11 speech arrest, 5 anomia, and 5 other) while DCS yielded 10 positive sites (2 speech arrest, 5 anomia, and 3 other). MEGI isolated 32 sites of peak activation with language tasks. Positive language sites were most commonly found in the pars opercularis for all three modalities. In 9 instances the positive DCS site corresponded to a positive nTMS site, while in 1 instance it did not. In 4 instances, a positive nTMS site corresponded to a negative DCS site, while 169 instances of negative nTMS and DCS were recorded. The sensitivity of nTMS was therefore 90%, specificity was 98%, the positive predictive value was 69% and the negative predictive value was 99% as compared with intraoperative DCS. MEGI language sites for verb generation and object naming correlated with nTMS sites in 5 subjects, and with DCS sites in 2 subjects.


CONCLUSION
Maps of language function generated with nTMS correlate well with those generated by DCS. Negative nTMS mapping also correlates with negative DCS mapping. In our study, MEGI lacks the same level of correlation with intraoperative mapping; nevertheless it provides useful adjunct information in some cases. nTMS may offer a lesion-based method for noninvasively interrogating language pathways and be valuable in managing patients with peri-eloquent lesions.
Natural skin color transformation based on color subspace learning

With the rapid spread of digital cameras, a growing interest has been seen in image processing for beautification. Pseudo make-up face can be generated by a variety of user's preferred make-up as the image processing method for beautification. But unnatural image be generated by this method because of different lighting conditions or skin colors between two images. Our proposed method can generate more natural images by transforming skin color which based on color subspace learning. We also developed a skin color transformation system, which can transform the effect of make-up rapidly and naturally.
ARMDN: Associative and Recurrent Mixture Density Networks for eRetail Demand Forecasting

Accurate demand forecasts can help on-line retail organizations better plan their supply-chain processes. The challenge, however, is the large number of associative factors that result in large, non-stationary shifts in demand, which traditional time series and regression approaches fail to model. In this paper, we propose a Neural Network architecture called AR-MDN, that simultaneously models associative factors, time-series trends and the variance in the demand. We first identify several causal features and use a combination of feature embeddings, MLP and LSTM to represent them. We then model the output density as a learned mixture of Gaussian distributions. The AR-MDN can be trained end-to-end without the need for additional supervision. We experiment on a dataset of an year’s worth of data over tens-of-thousands of products from Flipkart. The proposed architecture yields a significant improvement in forecasting accuracy when compared with existing alternatives. PVLDB Reference Format: Srayanta Mukherjee, Devashish Shankar, Atin Ghosh, Nilam Tathawadekar, Pramod Kompalli, Sunita Sarawagi, Krishnendu Chaudhury. AR-MDN: Associative and Recurrent Mixture Density Networks for eRetail Demand Forecasting. PVLDB, 11 (5): xxxxyyyy, 2018. DOI: https://doi.org/TBD
The (Perceived) Roles of Corporate Governance Reforms in Malaysia: The Views of Corporate Practitioners

Purpose - The purpose of this paper is to understand the roles of corporate governance reforms in Malaysia following the 1997/1998 Asian crisis from the perspectives of corporate managers. Design/methodology/approach - The primary evidence used is drawn from a series of in-depth semi-structured interviews with Malaysian corporate managers involved in the overseeing of the governance structures within their companies. Findings - This study shows that most interviewees believed that an appropriate corporate governance system could play a role in resolving the problems associated with the interlocking and concentrated corporate ownership structure in Malaysia. However, the effectiveness of the corporate governance reforms in dealing with this issue is questionable. It also reveals that Malaysian companies 'changed' their corporate governance practices predominantly to recover (foreign) investor confidence lost during the crisis and to fulfil the legal requirements enforced by the government, where the latter was under pressure from the international community (especially, the World Bank and IMF) to 'improve' the Malaysian corporate governance practices after the crisis. Originality/value of paper - This paper adds to the literature on corporate governance, especially in the context of developing countries. Prior research investigating corporate governance issues in developing countries has been limited, particularly the lack of in-depth examination of corporate governance practices from the perspectives of corporate managers. This paper will be of great value to researchers and practitioners seeking to gain a better understanding of the roles of corporate governance in Malaysia.
Process Engineer Training

The process engineer certification program has been structured to build on the existing competencies of the practitioner, but most importantly, with a main focus on developing new skills through the use of our unique engineering principles. Process engineers focus on the design, operation, control, and optimization of business, application, and technology processes. They use specific engineering principles to enable better enterprise-related processes.
A novel approach for integrating security policy enforcement with dynamic network virtualization

Network function virtualization (NFV) is a new networking paradigm that virtualizes single network functions. NFV introduces several advantages compared to classical approaches, such as the dynamic provisioning of functionality or the implementation of scalable and reliable services (e.g., adding a new instance to support demands). NFV also allows the deployment of security controls, like firewalls or VPN gateways, as virtualized network functions. However, currently there is not an automatic way to select the security functions to enable and to configure the selected ones according to a set of user's security requirements. This paper presents a first approach towards the integration of network and security policy management into the NFV framework. By adding to the NFV architecture a new software component, the Policy Manager, we provide NFV with an easy and effective way for users to specify their security requirements and a process that hides all the details of the correct deployment and configuration of security functions. To perform its tasks, the Policy Manager uses policy refinement techniques.
Object-Class Segmentation using Deep Convolutional Neural Networks

After successes at image classification, segmentation is the next step towards image understanding for neural networks. We propose a convolutional network architecture that outperforms current methods on the challenging INRIA-Graz02 dataset with regards to accuracy and speed.
Perinatal human immunodeficiency virus-1 transmission and intrauterine growth: a cohort study in Butare, Rwanda.

OBJECTIVE
To study the association of perinatal human immunodeficiency virus (HIV)-1 transmission with birth outcomes, including birth weight, gestational age, ponderal index, head circumference, and weight/head ratio.


METHODS
Data from a prospective cohort study of 627 pregnant women and their infants in Butare, Rwanda, from October 1989 until April 1994 were analyzed. A total of 318 HIV-1-infected and 309 seronegative women were enrolled during pregnancy and gave birth to 590 live singletons. Multiple linear regression modeling was used to assess the association of mother-child HIV status with several birth outcome measures.


RESULTS
Unadjusted mean birth weight of HIV- infected infants was 235 g (95% confidence interval [CI] = 94 to 376 g) less than that of HIV-uninfected infants born to HIV-positive mothers (the reference group). After adjustment for gestational age, socioeconomic factors, maternal age, parity, hematocrit, and anthropomorphic measures, mean birth weight of HIV-infected infants was 154 g (95% CI = 38 to 271 g) lower than that of the reference group. When infants born to HIV-seronegative mothers were compared with the reference group, mean birth weights did not differ. Adjusted models resulted in estimates of mean head circumference 0.6 cm smaller (95% CI = 0.2 to 1.1 cm), ponderal index 0.14 lower (95% CI = 0.05 to 0.23), weight/head ratio 3.5 lower (95% CI = 0.5 to 6.4), and gestational age 0.5 weeks shorter (95% CI = 0.1 to 0.9 weeks) for HIV-infected infants than for the reference group.


CONCLUSIONS
After adjustment for potential confounding variables, this study showed statistically significant differences in birth weight, gestational age, ponderal index, and weight/head ratio when HIV-infected infants were compared with noninfected infants born to HIV-positive mothers. HIV-1, mother-to-child transmission, Africa, intrauterine growth, birth weight, gestational age, ponderal index.