nils-herrmann/clean_scirepeval huggingface dataset:
Method of delivery and pregnancy outcomes in Asia: the WHO global survey on maternal and perinatal health 2007–08

There has been concern about rising rates of caesarean section worldwide. This Article reports the third phase of the WHO global survey, which aimed to estimate the rate of different methods of delivery and to examine the relation between method of delivery and maternal and perinatal outcomes in selected facilities in Africa and Latin America in 2004-05, and in Asia in 2007-08.



Nine countries participated in the Asia global survey: Cambodia, China, India, Japan, Nepal, Philippines, Sri Lanka, Thailand, and Vietnam. In each country, the capital city and two other regions or provinces were randomly selected. We studied all women admitted for delivery during 3 months in institutions with 6000 or fewer expected deliveries per year and during 2 months in those with more than 6000 deliveries. We gathered data for institutions to obtain a detailed description of the health facility and its resources for obstetric care. We obtained data from women's medical records to summarise obstetric and perinatal events.



We obtained data for 109 101 of 112 152 deliveries reported in 122 recruited facilities (97% coverage), and analysed 107 950 deliveries. The overall rate of caesarean section was 27.3% (n=29 428) and of operative vaginal delivery was 3.2% (n=3465). Risk of maternal mortality and morbidity index (at least one of: maternal mortality, admission to intensive care unit [ICU], blood transfusion, hysterectomy, or internal iliac artery ligation) was increased for operative vaginal delivery (adjusted odds ratio 2.1, 95% CI 1.7-2.6) and all types of caesarean section (antepartum without indication 2.7, 1.4-5.5; antepartum with indication 10.6, 9.3-12.0; intrapartum without indication 14.2, 9.8-20.7; intrapartum with indication 14.5, 13.2-16.0). For breech presentation, caesarean section, either antepartum (0.2, 0.1-0.3) or intrapartum (0.3, 0.2-0.4), was associated with improved perinatal outcomes, but also with increased risk of stay in neonatal ICU (2.0, 1.1-3.6; and 2.1, 1.2-3.7, respectively).



To improve maternal and perinatal outcomes, caesarean section should be done only when there is a medical indication.



US Agency for International Development (USAID); UNDP/UNFPA/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction (HRP), WHO, Switzerland; Ministry of Health, Labour and Welfare of Japan; Ministry of Public Health, China; and Indian Council of Medical Research.
A mobile diabetes management and educational system for type-2 diabetics in Saudi Arabia (SAED).

Diabetes is a chronic disease, with high prevalence across many nations, which is characterized by elevated level of blood glucose and risk of acute and chronic complication. The Kingdom of Saudi Arabia (KSA) has one of the highest levels of diabetes prevalence globally. It is well-known that the treatment of diabetes is complex process and requires both lifestyle change and clear pharmacologic treatment plan. To avoid the complication from diabetes, the effective behavioural change and extensive education and self-management is one of the key approaches to alleviate such complications. However, this process is lengthy and expensive. The recent studies on the user of smart phone technologies for diabetes self-management have proven to be an effective tool in controlling hemoglobin (HbA1c) levels especially in type-2 diabetic (T2D) patients. However, to date no reported study addressed the effectiveness of this approach in the in Saudi patients. This study investigates the impact of using mobile health technologies for the self-management of diabetes in Saudi Arabia.



In this study, an intelligent mobile diabetes management system (SAED), tailored for T2D patients in KSA was developed. A pilot study of the SAED system was conducted in Saudi Arabia with 20 diabetic patients for 6 months duration. The patients were randomly categorized into a control group who did not use the SAED system and an intervention group whom used the SAED system for their diabetes management during this period. At the end of the follow-up period, the HbA1c levels in the patients in both groups were measure together with a diabetes knowledge test was also conducted to test the diabetes awareness of the patients.



The results of SAED pilot study showed that the patients in the intervention group were able to significantly decrease their HbA1c levels compared to the control group. The SAED system also enhanced the diabetes awareness amongst the patients in the intervention group during the trial period. These outcomes confirm the global studies on the effectiveness of smart phone technologies in diabetes management. The significance of the study is that this was one of the first such studies conducted on Saudi patients and of their acceptance for such technology in their diabetes self-management treatment plans.



The pilot study of the SAED system showed that a mobile health technology can significantly improve the HbA1C levels among Saudi diabetic and improve their disease management plans. The SAED system can also be an effective and low-cost solution in improving the quality of life of diabetic patients in the Kingdom considering the high level of prevalence and the increasing economic burden of this disease.
Classifying the Autonomy and Morality of Artificial Agents

As we outsource more of our decisions and activities to machines with various degrees of autonomy, the question of clarifying the moral and legal status of their autonomous behaviour arises. There is also an ongoing discussion on whether artificial agents can ever be liable for their actions or become moral agents. Both in law and ethics, the concept of liability is tightly connected with the concept of ability. But as we work to develop moral machines, we also push the boundaries of existing categories of ethical competency and autonomy. This makes the question of responsibility particularly difficult. Although new classification schemes for ethical behaviour and autonomy have been discussed, these need to be worked out in far more detail. Here we address some issues with existing proposals, highlighting especially the link between ethical competency and autonomy, and the problem of anchoring classifications in an operational understanding of what we mean by a moral
MobiFace: A Lightweight Deep Learning Face Recognition on Mobile Devices

Deep neural networks have been widely used in numerous computer vision applications, particularly in face recognition. However, deploying deep neural network face recognition on mobile devices is still limited since most highaccuracy deep models are both time and GPU consumption in the inference stage. Therefore, developing a lightweight deep neural network is one of the most promising solutions to deploy face recognition on mobile devices. Such the lightweight deep neural network requires efficient memory with small number of weights representation and low cost operators. In this paper a novel deep neural network named MobiFace, which is simple but effective, is proposed for productively deploying face recognition on mobile devices. The experimental results have shown that our lightweight MobiFace is able to achieve high performance with 99.7% on LFW database and 91.3% on large-scale challenging Megaface database. It is also eventually competitive against large-scale deep-networks face recognition while significant reducing computational time and memory consumption.
Diversity of sharp-wave-ripple LFP signatures reveals differentiated brain-wide dynamical events.

Sharp-wave-ripple (SPW-R) complexes are believed to mediate memory reactivation, transfer, and consolidation. However, their underlying neuronal dynamics at multiple scales remains poorly understood. Using concurrent hippocampal local field potential (LFP) recordings and functional MRI (fMRI), we study local changes in neuronal activity during SPW-R episodes and their brain-wide correlates. Analysis of the temporal alignment between SPW and ripple components reveals well-differentiated SPW-R subtypes in the CA1 LFP. SPW-R-triggered fMRI maps show that ripples aligned to the positive peak of their SPWs have enhanced neocortical metabolic up-regulation. In contrast, ripples occurring at the trough of their SPWs relate to weaker neocortical up-regulation and absent subcortical down-regulation, indicating differentiated involvement of neuromodulatory pathways in the ripple phenomenon mediated by long-range interactions. To our knowledge, this study provides the first evidence for the existence of SPW-R subtypes with differentiated CA1 activity and metabolic correlates in related brain areas, possibly serving different memory functions.
Tight Bra in a 34-Year-Old Woman: An Unusual Cause of Mondor's Disease.

Mondor's disease is characterized by thrombophlebitis of the superficial veins of the breast and the chest wall. The list of causes is long. Various types of clothing, mainly tight bras and girdles, have been postulated as causes. We report a case of a 34-year-old woman who referred typical symptoms and signs of Mondor's disease, without other possible risk factors, and showed the cutaneous findings of the tight bra. Therefore, after distinguishing benign causes of Mondor's disease from hidden malignant causes, the clinicians should consider this clinical entity.
Seakeeping response of a surface effect ship in near-shore transforming seas

Scale-model laboratory tests of a surface effect ship (SES) conducted in a near-shore transforming wave field are discussed. Waves approaching a beach in a wave tank were used to simulate transforming sea conditions and a series of experiments were conducted with a 1:30 scale model SES traversing in heads seas. Pitch and heave motion of the vehicle were recorded in support of characterizing the seakeeping response of the vessel in developing seas. The aircushion pressure and the vessel speed were varied over a range of values and the corresponding vehicle responses were analyzed to identify functional dependence on these parameters. The results show a distinct correlation between the air-cushion pressure and the response amplitude of both pitch and heave.
Estimation of remaining useful life of ball bearings using data driven methodologies

This paper describes the three methodologies used by CALCE in their winning entry for the IEEE 2012 PHM Data Challenge competition. An experimental data set from seventeen ball bearings was provided by the FEMTO-ST Institute. The data set consisted of data from six bearings for algorithm training and data from eleven bearings for testing. The authors developed prognostic algorithms based on the data from the training bearings to estimate the remaining useful life of the test bearings. Three methodologies are presented in this paper. Result accuracies of the winning methodology are presented.
Virtual Reality for Enhanced Ecological Validity and Experimental Control in the Clinical, Affective and Social Neurosciences

An essential tension can be found between researchers interested in ecological validity and those concerned with maintaining experimental control. Research in the human neurosciences often involves the use of simple and static stimuli lacking many of the potentially important aspects of real world activities and interactions. While this research is valuable, there is a growing interest in the human neurosciences to use cues about target states in the real world via multimodal scenarios that involve visual, semantic, and prosodic information. These scenarios should include dynamic stimuli presented concurrently or serially in a manner that allows researchers to assess the integrative processes carried out by perceivers over time. Furthermore, there is growing interest in contextually embedded stimuli that can constrain participant interpretations of cues about a target's internal states. Virtual reality environments proffer assessment paradigms that combine the experimental control of laboratory measures with emotionally engaging background narratives to enhance affective experience and social interactions. The present review highlights the potential of virtual reality environments for enhanced ecological validity in the clinical, affective, and social neurosciences.
Brazilian version of the Functional Status Score for the ICU:
translation and cross-cultural adaptation

The aim of the present study was to translate and cross-culturally adapt the Functional Status Score for the intensive care unit (FSS-ICU) into Brazilian Portuguese.



This study consisted of the following steps: translation (performed by two independent translators), synthesis of the initial translation, back-translation (by two independent translators who were unaware of the original FSS-ICU), and testing to evaluate the target audience's understanding. An Expert Committee supervised all steps and was responsible for the modifications made throughout the process and the final translated version.



The testing phase included two experienced physiotherapists who assessed a total of 30 critical care patients (mean FSS-ICU score = 25 ± 6). As the physiotherapists did not report any uncertainties or problems with interpretation affecting their performance, no additional adjustments were made to the Brazilian Portuguese version after the testing phase. Good interobserver reliability between the two assessors was obtained for each of the 5 FSS-ICU tasks and for the total FSS-ICU score (intraclass correlation coefficients ranged from 0.88 to 0.91).



The adapted version of the FSS-ICU in Brazilian Portuguese was easy to understand and apply in an intensive care unit environment.
25 years of neuroimaging in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease for which a precise cause has not yet been identified. Standard CT or MRI evaluation does not demonstrate gross structural nervous system changes in ALS, so conventional neuroimaging techniques have provided little insight into the pathophysiology of this disease. Advanced neuroimaging techniques—such as structural MRI, diffusion tensor imaging and proton magnetic resonance spectroscopy—allow evaluation of alterations of the nervous system in ALS. These alterations include focal loss of grey and white matter and reductions in white matter tract integrity, as well as changes in neural networks and in the chemistry, metabolism and receptor distribution in the brain. Given their potential for investigation of both brain structure and function, advanced neuroimaging methods offer important opportunities to improve diagnosis, guide prognosis, and direct future treatment strategies in ALS. In this article, we review the contributions made by various advanced neuroimaging techniques to our understanding of the impact of ALS on different brain regions, and the potential role of such measures in biomarker development.
Towards Self-explanatory Ontology Visualization with Contextual Verbalization

Ontologies are one of the core foundations of the Semantic Web. To participate in Semantic Web projects, domain experts need to be able to understand the ontologies involved. Visual notations can provide an overview of the ontology and help users to understand the connections among entities. However, the users first need to learn the visual notation before they can interpret it correctly. Controlled natural language representation would be readable right away and might be preferred in case of complex axioms, however, the structure of the ontology would remain less apparent. We propose to combine ontology visualizations with contextual ontology verbalizations of selected ontology (diagram) elements, displaying controlled natural language (CNL) explanations of OWL axioms corresponding to the selected visual notation elements. Thus, the domain experts will benefit from both the high-level overview provided by the graphical notation and the detailed textual explanations of particular elements in the diagram.
Seeded Region Growing

We present here a new algorithm for segmentation of intensity images which is robust, rapid, and free of tuning parameters. The method, however, requires the input of a number of seeds, either individual pixels or regions, which will control the formation of regions into which the image will be segmented. In this correspondence, we present the algorithm, discuss briefly its properties, and suggest two ways in which it can be employed, namely, by using manual seed selection or by automated procedures.
Posterosuperior and anterosuperior impingement of the shoulder in overhead athletes—evolving concepts

During throwing motion the athlete puts enormous stress on both the dynamic and the static stabilisers of the shoulder. Repetitive forces cause adaptive soft tissue and bone changes that initially improve performance but ultimately may lead to shoulder pathologies. Although a broad range of theories have been suggested for the pathophysiology of internal impingement, the reasons are obviously multifactorial. This review aims to critically analyse the current literature and to summarise clinically important information. The cardinal lesions of internal impingement, articular-sided rotator cuff tears and posterosuperior labral lesions, have been shown to occur in association with a number of other findings, most importantly glenohumeral internal rotation deficit and SICK scapula syndrome, but also with posterior humeral head lesions, posterior glenoid bony injury and, rarely, with Bankart and inferior glenohumeral ligament lesions. Extensive biomechanical and clinical research is necessary before a complete understanding and reconciliation of the varying theories of the pathomechanisms of injury can be developed.
"Answer ka type kya he?": Learning to Classify Questions in Code-Mixed Language

Code-Mixing (CM) is defined as the embedding of linguistic units such as phrases, words, and morphemes of one language into an utterance of another language. CM is a natural phenomenon observed in many multilingual societies. It helps in speeding-up communication and allows wider variety of expression due to which it has become a popular mode of communication in social media forums like Facebook and Twitter. However, current Question Answering (QA) research and systems only support expressing a question in a single language which is an unrealistic and hard proposition especially for certain domains like health and technology. In this paper, we take the first step towards the development of a full-fledged QA system in CM language which is building a Question Classification (QC) system. The QC system analyzes the user question and infers the expected Answer Type (AType). The AType helps in locating and verifying the answer as it imposes certain type-specific constraints. In this paper, we present our initial efforts towards building a full-fledged QA system for CM language. We learn a basic Support Vector Machine (SVM) based QC system for English-Hindi CM questions. Due to the inherent complexities involved in processing CM language and also the unavailability of language processing resources such POS taggers, Chunkers, Parsers, we design our current system using only word-level resources such as language identification, transliteration and lexical translation. To reduce data sparsity and leverage resources available in a resource-rich language, in stead of extracting features directly from the original CM words, we translate them commonly into English and then perform featurization. We created an evaluation dataset for this task and our system achieves an accuracy of 63% and 45% in coarse-grained and fine-grained categories of the question taxanomy. The idea of translating features into English indeed helps in improving accuracy over the unigram baseline.
Towards a Dataset for Natural Language Requirements Processing

The current breakthrough of natural language processing (NLP) techniques can provide the requirements engineering (RE) community with powerful tools that can help addressing specific tasks of natural language (NL) requirements analysis, such as traceability, ambiguity detection and requirements classification, to name a few.  However, modern NLP techniques are mainly statistical, and need large NL requirements datasets, to support appropriate training, test and validation of the techniques. The RE community has experimented with NLP since long time, but datasets were often proprietary, or limited to few software projects for which requirements were publicly available. Hence, replication of the experiments and generalization have always been an issue.  Our near future commitment is to provide a publicly available NL requirements dataset.  To this end, we are collecting requirements documents from the Web, and we are representing them in a common XML format. In this paper, we present the current version of the dataset, together with our agenda concerning formatting, extension, and annotation of the dataset.
Ultra-Lightweight Cryptography for Low-Cost RFID Tags : Hummingbird Algorithm and Protocol

Motivated by the design of the well-known Enigma machine, we present a novel ultra-lightweight encryption scheme, referred to as Hummingbird, and its applications to a privacy-preserving identification and mutual authentication protocol for RFID applications. Hummingbird can provide the designed security with a small block size and is therefore expected to meet the stringent response time and power consumption requirements described in the ISO protocol without any modification of the current standard. We show that Hummingbird is resistant to the most common attacks such as linear and differential cryptanalysis. Furthermore, we investigate some properties for integrating the Hummingbird into a privacypreserving identification and mutual authentication protocol.
Issues in cybersecurity; understanding the potential risks associated with hackers/crackers

Issues in cybersecurity; understanding the potential risks associated with hackers/crackers Alan D. Smith William T. Rupp Article information: To cite this document: Alan D. Smith William T. Rupp, (2002),"Issues in cybersecurity; understanding the potential risks associated with hackers/ crackers", Information Management & Computer Security, Vol. 10 Iss 4 pp. 178 183 Permanent link to this document: http://dx.doi.org/10.1108/09685220210436976
Comparison of Physical, Chemical and Biological Methods of Controlling Garlic White Rot

Treatment of garlic cloves with tebuconazole (at 1 ml of Folicur 25% l−1) achieved a significant reduction in the rate of disease progress and the final incidence of plant death by Sclerotium cepivorum: garlic yields were improved. Although soil solarization provided the best control of garlic white rot, bringing soil populations of S. cepivorum to negligible levels, similar levels of disease control and garlic yields were achieved when tebuconazole was sprayed to stem bases of plants grown from cloves also treated with tebuconazole. This double treatment almost doubled the yield compared with untreated plants and significantly increased bulb quality under high disease pressure conditions. Soil solarization was also highly effective in a second consecutive crop of garlic, with significant improvements in yield and garlic quality. In contrast, lower levels of disease control were obtained when selected isolates of Trichoderma harzianum and Bacillus subtilis were applied to the soil and cloves respectively.