nils-herrmann/clean_scirepeval huggingface dataset:
Methods: Using Three-Dimensional Culture (Spheroids) as an In Vitro Model of Tumour Hypoxia.

Regions of hypoxia in tumours can be modelled in vitro in 2D cell cultures with a hypoxic chamber or incubator in which oxygen levels can be regulated. Although this system is useful in many respects, it disregards the additional physiological gradients of the hypoxic microenvironment, which result in reduced nutrients and more acidic pH. Another approach to hypoxia modelling is to use three-dimensional spheroid cultures. In spheroids, the physiological gradients of the hypoxic tumour microenvironment can be inexpensively modelled and explored. In addition, spheroids offer the advantage of more representative modelling of tumour therapy responses compared with 2D culture. Here, we review the use of spheroids in hypoxia tumour biology research and highlight the different methodologies for spheroid formation and how to obtain uniformity. We explore the challenge of spheroid analyses and how to determine the effect on the hypoxic versus normoxic components of spheroids. We discuss the use of high-throughput analyses in hypoxia screening of spheroids. Furthermore, we examine the use of mathematical modelling of spheroids to understand more fully the hypoxic tumour microenvironment.
A unified foundation for business analytics

a r t i c l e i n f o Synthesizing prior research, this paper designs a relatively comprehensive and holistic characterization of business analytics – one that serves as a foundation on which researchers, practitioners, and educators can base their studies of business analytics. As such, it serves as an initial ontology for business analytics as a field of study. The foundation has three main parts dealing with the whence and whither of business analytics: identification of dimensions along which business analytics possibilities can be examined, derivation of a six-class taxonomy that covers business analytics perspectives in the literature, and design of an inclusive framework for the field of business analytics. In addition to unifying the literature, a major contribution of the designed framework is that it can stimulate thinking about the nature, roles, and future of business analytics initiatives. We show how this is done by deducing a host of unresolved issues for consideration by researchers, practitioners, and educators. We find that business analytics involves issues quite aside from data management, number crunching, technology use, systematic reasoning, and so forth. According to a study by Gartner, the technology category of " analyt-ics and business intelligence " is the top priority of chief information officers, and comprises a $12.2B market . It is seen as a higher priority than such categories as mobile technology, cloud computing, and collaboration technology. Further, Gartner finds that the top technology priority of chief financial officers is analytics . Similarly, in studies involving interviews with thousands of chief information officers, worldwide, IBM asked, " which visionary plan do you have to increase competitiveness over the next 3 to 5 years? " In both 2011 and 2009, 83% of respondents identify " Business Intelligence and Analytics " as their number-one approach for achieving greater competitiveness. Among all types of plans, this is the top percentage for both years. To put this in perspective, consider 2011 results, in which business intelligence and analytics exceeds such other competitiveness plans as mobility solutions (ranked 2nd at74%), cloud computing (ranked 4th at 60%), and social networking (ranked 8th at 55%) . IDC reports that the business analytics software market grew by 13.8% during 2011 to $32B, and predicts it to be at $50.7B in revenue by 2016 . It appears that a driver for this growth is the perception or realization that such investments yield value. Across a …
Automatic Question Paper Generator System

Information and intelligence are two vital columns on which development of humankind rise and knowledge has significant impact on operating of society. Student assessment is a crucial part of teaching and is done through the process of examinations and preparation of exam question papers has consistently been a matter of interest. Present-day technologies assist the teacher to stock the questions in a computer databases but the problem which emerges is how the present day technologies would also assist the teachers to automatically create the variety sets of questions from every now and then without worry about replication and duplication from the previous exam while the question bank keeps growing, so a non-automatic path for conniving a exam paper would not be able to serve to this need so in this paper we introduce an automated way which would permit the operation of conniving exam paper to be further well organized and productive and it would also aid in developing a database of questions which could be further classified for blending of exam question paper, currently there is no systematic procedure to fortify quality of exam question paper. Hence there appears a requirement to have a system which will automatically create the question paper from teacher entered description within few
Behavioural interventions for the prevention of sexually transmitted infections in young people aged 13-19 years: a systematic review.

We systematically reviewed school-based skills building behavioural interventions for the prevention of sexually transmitted infections. References were sought from 15 electronic resources, bibliographies of systematic reviews/included studies and experts. Two authors independently extracted data and quality-assessed studies. Fifteen randomized controlled trials (RCTs), conducted in the United States, Africa or Europe, met the inclusion criteria. They were heterogeneous in terms of intervention length, content, intensity and providers. Data from 12 RCTs passed quality assessment criteria and provided evidence of positive changes in non-behavioural outcomes (e.g. knowledge and self-efficacy). Intervention effects on behavioural outcomes, such as condom use, were generally limited and did not demonstrate a negative impact (e.g. earlier sexual initiation). Beneficial effect on at least one, but never all behavioural outcomes assessed was reported by about half the studies, but this was sometimes limited to a participant subgroup. Sexual health education for young people is important as it increases knowledge upon which to make decisions about sexual behaviour. However, a number of factors may limit intervention impact on behavioural outcomes. Further research could draw on one of the more effective studies reviewed and could explore the effectiveness of 'booster' sessions as young people move from adolescence to young adulthood.
A Hierarchical Compositional Model for Face Representation and Sketching

This paper presents a hierarchical-compositional model of human faces, as a three-layer AND-OR graph to account for the structural variabilities over multiple resolutions. In the AND-OR graph, an AND-node represents a decomposition of certain graphical structure, which expands to a set of OR-nodes with associated relations; an OR-node serves as a switch variable pointing to alternative AND-nodes. Faces are then represented hierarchically: The first layer treats each face as a whole, the second layer refines the local facial parts jointly as a set of individual templates, and the third layer further divides the face into 15 zones and models detail facial features such as eye corners, marks, or wrinkles. Transitions between the layers are realized by measuring the minimum description length (MDL) given the complexity of an input face image. Diverse face representations are formed by drawing from dictionaries of global faces, parts, and skin detail features. A sketch captures the most informative part of a face in a much more concise and potentially robust representation. However, generating good facial sketches is extremely challenging because of the rich facial details and large structural variations, especially in the high-resolution images. The representing power of our generative model is demonstrated by reconstructing high-resolution face images and generating the cartoon facial sketches. Our model is useful for a wide variety of applications, including recognition, nonphotorealisitc rendering, superresolution, and low-bit rate face coding.
Effect of predicted protein-truncating genetic variants on the human transcriptome

Accurate prediction of the functional effect of genetic variation is critical for clinical genome interpretation. We systematically characterized the transcriptome effects of protein-truncating variants, a class of variants expected to have profound effects on gene function, using data from the Genotype-Tissue Expression (GTEx) and Geuvadis projects. We quantitated tissue-specific and positional effects on nonsense-mediated transcript decay and present an improved predictive model for this decay. We directly measured the effect of variants both proximal and distal to splice junctions. Furthermore, we found that robustness to heterozygous gene inactivation is not due to dosage compensation. Our results illustrate the value of transcriptome data in the functional interpretation of genetic variants.
Gut microorganisms as promising targets for the management of type 2 diabetes

Each human intestine harbours not only hundreds of trillions of bacteria but also bacteriophage particles, viruses, fungi and archaea, which constitute a complex and dynamic ecosystem referred to as the gut microbiota. An increasing number of data obtained during the last 10 years have indicated changes in gut bacterial composition or function in type 2 diabetic patients. Analysis of this ‘dysbiosis’ enables the detection of alterations in specific bacteria, clusters of bacteria or bacterial functions associated with the occurrence or evolution of type 2 diabetes; these bacteria are predominantly involved in the control of inflammation and energy homeostasis. Our review focuses on two key questions: does gut dysbiosis truly play a role in the occurrence of type 2 diabetes, and will recent discoveries linking the gut microbiota to host health be helpful for the development of novel therapeutic approaches for type 2 diabetes? Here we review how pharmacological, surgical and nutritional interventions for type 2 diabetic patients may impact the gut microbiota. Experimental studies in animals are identifying which bacterial metabolites and components act on host immune homeostasis and glucose metabolism, primarily by targeting intestinal cells involved in endocrine and gut barrier functions. We discuss novel approaches (e.g. probiotics, prebiotics and faecal transfer) and the need for research and adequate intervention studies to evaluate the feasibility and relevance of these new therapies for the management of type 2 diabetes.
Vasopressin and desmopressin in central diabetes insipidus: adverse effects and clinical considerations.

The management of central diabetes insipidus has been greatly simplified by the introduction of desmopressin (DDAVP). Its ease of administration, safety and tolerability make DDAVP the first line agent for outpatient treatment of central diabetes insipidus. The major complication of DDAVP therapy is water intoxication and hyponatremia. The risk of hyponatremia can be reduced by careful dose titration when initiating therapy and by close monitoring of serum osmolality when DDAVP is used with other medications affecting water balance. Herein we review the adverse effects of DDAVP and its predecessor, vasopressin, as well as discuss important clinical considerations when using these agents to treat central diabetes insipidus.
Face Recognition in Low Quality Images: A Survey

Low-resolution face recognition (LRFR) has received increasing attention over the past few years. Its applications lie widely in the real-world environment when highresolution or high-quality images are hard to capture. One of the biggest demands for LRFR technologies is video surveillance. As the the number of surveillance cameras in the city increases, the videos that captured will need to be processed automatically. However, those videos or images are usually captured with large standoffs, arbitrary illumination condition, and diverse angles of view. Faces in these images are generally small in size. Several studies addressed this problem employed techniques like super resolution, deblurring, or learning a relationship between different resolution domains. In this paper, we provide a comprehensive review of approaches to low-resolution face recognition in the past five years. First, a general problem definition is given. Later, systematically analysis of the works on this topic is presented by catogory. In addition to describing the methods, we also focus on datasets and experiment settings. We further address the related works on unconstrained lowresolution face recognition and compare them with the result that use synthetic low-resolution data. Finally, we summarized the general limitations and speculate a priorities for the future effort.
Duloxetine, pregabalin, and duloxetine plus gabapentin for diabetic peripheral neuropathic pain management in patients with inadequate pain response to gabapentin: an open-label, randomized, noninferiority comparison.

To determine whether duloxetine is noninferior to (as good as) pregabalin in the treatment of pain associated with diabetic peripheral neuropathy.



We performed a 12-week, open-label study of patients with diabetic peripheral neuropathic pain who had been treated with gabapentin (≥ 900 mg/d) and had an inadequate response (defined as a daily pain score of ≥ 4 on a numerical rating scale [0-10 points]). The first patient was enrolled on September 28, 2006, and the last patient visit occurred on August 26, 2009. Patients were randomized to duloxetine monotherapy (n=138), pregabalin monotherapy (n=134), or a combination of duloxetine and gabapentin (n=135). The primary objective was a noninferiority comparison between duloxetine and pregabalin on improvement in the weekly mean of the diary-based daily pain score (0- to 10-point scale) at end point. Noninferiority would be declared if the mean improvement for duloxetine was no worse than the mean improvement for pregabalin, within statistical variability, by a margin of -0.8 unit.



The mean change in the pain rating at end point was -2.6 for duloxetine and -2.1 for pregabalin. The 97.5% lower confidence limit was a -0.05 difference in means, establishing noninferiority. As to adverse effects, nausea, insomnia, hyperhidrosis, and decreased appetite were more frequent with duloxetine than pregabalin; insomnia, more frequent with duloxetine than duloxetine plus gabapentin; peripheral edema, more frequent with pregabalin than with duloxetine; and nausea, hyperhidrosis, decreased appetite, and vomiting, more frequent with duloxetine plus gabapentin than with pregabalin.



Duloxetine was noninferior to pregabalin for the treatment of pain in patients with diabetic peripheral neuropathy who had an inadequate pain response to gabapentin.
A vacuum flash–assisted solution process for high-efficiency large-area perovskite solar cells

Metal halide perovskite solar cells (PSCs) currently attract enormous research interest because of their high solar-to-electric power conversion efficiency (PCE) and low fabrication costs, but their practical development is hampered by difficulties in achieving high performance with large-size devices. We devised a simple vacuum flash–assisted solution processing method to obtain shiny, smooth, crystalline perovskite films of high electronic quality over large areas. This enabled us to fabricate solar cells with an aperture area exceeding 1 square centimeter, a maximum efficiency of 20.5%, and a certified PCE of 19.6%. By contrast, the best certified PCE to date is 15.6% for PSCs of similar size. We demonstrate that the reproducibility of the method is excellent and that the cells show virtually no hysteresis. Our approach enables the realization of highly efficient large-area PSCs for practical deployment.
INTERSEX AND GENDER IDENTITY DISORDERS Male Gender Identity in an XX Individual with Congenital Adrenal Hyperplasia

In spite of significant changes in the management policies of intersexuality, clinical evidence show that not all pubertal or adult individuals live according to the assigned sex during infancy.  The purpose of this study was to analyze the clinical management of an individual diagnosed as a female pseudohermaphrodite with congenital adrenal hyperplasia (CAH) simple virilizing form four decades ago but who currently lives as a monogamous heterosexual male.  We studied the clinical files spanning from 1965 to 1991 of an intersex individual. In addition, we conducted a magnetic resonance imaging (MRI) study of the abdominoplevic cavity and a series of interviews using the oral history method.  Our analysis is based on the clinical evidence that led to the CAH diagnosis in the 1960s in light of recent clinical testing to confirm such diagnosis.  Analysis of reported values for 17-ketosteroids, 17-hydroxycorticosteroids, from 24-hour urine samples during an 8-year period showed poor adrenal suppression in spite of adherence to treatment. A recent MRI study confirmed the presence of hyperplastic adrenal glands as well as the presence of a prepubertal uterus. Semistructured interviews with the individual confirmed a life history consistent with a male gender identity.  Although the American Academy of Pediatrics recommends that XX intersex individuals with CAH should be assigned to the female sex, this practice harms some individuals as they may self-identify as males. In the absence of comorbid psychiatric factors, the discrepancy between infant sex assignment and gender identity later in life underlines the need for a reexamination of current standards of care for individuals diagnosed with CAH. Jorge JC, Echeverri C, Medina Y, and Acevedo P. Male gender identity in an xx individual with congenital adrenal hyperplasia.
Flow-Based Anomaly Detection Using Neural Network Optimized with GSA Algorithm

Reliable high-speed networks are essential to provide quality services to ever growing Internet applications. A Network Intrusion Detection System (NIDS) is an important tool to protect computer networks from attacks. Traditional packet-based NIDSs are time-intensive as they analyze all network packets. A state-of-the-art NIDS should be able to handle a high volume of traffic in real time. Flow-based intrusion detection is an effective method for high speed networks since it inspects only packet headers. The existence of new attacks in the future is another challenge for intrusion detection. Anomaly-based intrusion detection is a well-known method capable of detecting unknown attacks. In this paper, we propose a flow-based anomaly detection system. Artificial Neural Network (ANN) is an important approach for anomaly detection. We used a Multi-Layer Perceptron (MLP) neural network with one hidden layer. We investigate the use of a Gravitational Search Algorithm (GSA) in optimizing interconnection weights of a MLP network. Our proposed GSA-based flow anomaly detection system (GFADS) is trained with a flow-based data set. The trained system can classify benign and malicious flows with 99.43% accuracy. We compare the performance of GSA with traditional gradient descent training algorithms and a particle swarm optimization (PSO) algorithm. The results show that GFADS is effective in flow-based anomaly detection. Finally, we propose a four-feature subset as the optimal set of features.
Performance evaluation in content-based image retrieval: overview and proposals

Evaluation of retrieval performance is a crucial problem in content-based image retrieval (CBIR). Many different methods for measuring the performance of a system have been created and used by researchers. This article discusses the advantages and shortcomings of the performance measures currently used. Problems such as a common image database for performance comparisons and a means of getting relevance judgments (or ground truth) for queries are explained. The relationship between CBIR and information retrieval (IR) is made clear, since IR researchers have decades of experience with the evaluation problem. Many of their solutions can be used for CBIR, despite the differences between the fields. Several methods used in text retrieval are explained. Proposals for performance measures and means of developing a standard test suite for CBIR, similar to that used in IR at the annual Text REtrieval Conference (TREC), are presented. MULLER, Henning, et al. Performance Evaluation in Content-Based Image Retrieval: Overview and Proposals. Genève : 1999
Visualisation and 'diagnostic classifiers' reveal how recurrent and recursive neural networks process hierarchical structure

We investigate how neural networks can learn and process languages with hierarchical, compositional semantics. To this end, we define the artificial task of processing nested arithmetic expressions, and study whether different types of neural networks can learn to compute their meaning. We find that recursive neural networks can implement a generalising solution to this problem, and we visualise this solution by breaking it up in three steps: project, sum and squash. As a next step, we investigate recurrent neural networks, and show that a gated recurrent unit, that processes its input incrementally, also performs very well on this task: the network learns to predict the outcome of the arithmetic expressions with high accuracy, although performance deteriorates somewhat with increasing length. To develop an understanding of what the recurrent network encodes, visualisation techniques alone do not suffice. Therefore, we develop an approach where we formulate and test multiple hypotheses on the information encoded and processed by the network. For each hypothesis, we derive predictions about features of the hidden state representations at each time step, and train ‘diagnostic classifiers’ to test those predictions. Our results indicate that the networks follow a strategy similar to our hypothesised ‘cumulative strategy’, which explains the high accuracy of the network on novel expressions, the generalisation to longer expressions than seen in training, and the mild deterioration with increasing length. This is turn shows that diagnostic classifiers can be a useful technique for opening up the black box of neural networks. We argue that diagnostic classification, unlike most visualisation techniques, does scale up from small networks in a toy domain, to larger and deeper recurrent networks dealing with real-life data, and may therefore contribute to a better understanding of the internal dynamics of current state-of-the-art models in natural language processing.
Ten Years of iCTF: The Good, The Bad, and The Ugly

Security competitions have become a popular way to foster security education by creating a competitive environment in which participants go beyond the effort usually required in traditional security courses. Live security competitions (also called “Capture The Flag,” or CTF competitions) are particularly well-suited to support handson experience, as they usually have both an attack and a defense component. Unfortunately, because these competitions put several (possibly many) teams against one another, they are difficult to design, implement, and run. This paper presents a framework that is based on the lessons learned in running, for more than 10 years, the largest educational CTF in the world, called iCTF. The framework’s goal is to provide educational institutions and other organizations with the ability to run customizable CTF competitions. The framework is open and leverages the security community for the creation of a corpus of educational security challenges.