nils-herrmann/clean_scirepeval huggingface dataset:
Design and manufactering of an X-band horn antenna using 3-D printing technology

Herein, design and manufacturing of an X-band pyramid horn antenna using 3-D printer is studied with its experimental results. X-band is used for the military purposes with the marine and satellite technology based on the geographic discovery. Horn antennas are especially very preferable in these applications since they can be built easily at the different types depending on their utilizations and provide low voltage standing wave ratios. This work is focused on a pyramid horn antenna design and its manufacturing method with 3-D printer technology. The measurement results of the 3-D printed antenna are also compared with the simulation results.
Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013

In 2010, overweight and obesity were estimated to cause 3·4 million deaths, 3·9% of years of life lost, and 3·8% of disability-adjusted life-years (DALYs) worldwide. The rise in obesity has led to widespread calls for regular monitoring of changes in overweight and obesity prevalence in all populations. Comparable, up-to-date information about levels and trends is essential to quantify population health effects and to prompt decision makers to prioritise action. We estimate the global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013.



We systematically identified surveys, reports, and published studies (n=1769) that included data for height and weight, both through physical measurements and self-reports. We used mixed effects linear regression to correct for bias in self-reports. We obtained data for prevalence of obesity and overweight by age, sex, country, and year (n=19,244) with a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs).



Worldwide, the proportion of adults with a body-mass index (BMI) of 25 kg/m(2) or greater increased between 1980 and 2013 from 28·8% (95% UI 28·4-29·3) to 36·9% (36·3-37·4) in men, and from 29·8% (29·3-30·2) to 38·0% (37·5-38·5) in women. Prevalence has increased substantially in children and adolescents in developed countries; 23·8% (22·9-24·7) of boys and 22·6% (21·7-23·6) of girls were overweight or obese in 2013. The prevalence of overweight and obesity has also increased in children and adolescents in developing countries, from 8·1% (7·7-8·6) to 12·9% (12·3-13·5) in 2013 for boys and from 8·4% (8·1-8·8) to 13·4% (13·0-13·9) in girls. In adults, estimated prevalence of obesity exceeded 50% in men in Tonga and in women in Kuwait, Kiribati, Federated States of Micronesia, Libya, Qatar, Tonga, and Samoa. Since 2006, the increase in adult obesity in developed countries has slowed down.



Because of the established health risks and substantial increases in prevalence, obesity has become a major global health challenge. Not only is obesity increasing, but no national success stories have been reported in the past 33 years. Urgent global action and leadership is needed to help countries to more effectively intervene.



Bill & Melinda Gates Foundation.
Acroangiodermatitis of mali: a rare vascular phenomenon.

Acroangiodermatitis (synonym pseudo-Kaposi sarcoma) is an unusual, benign condition which clinically presents as purple-colored patches, plaques or nodules, mostly on the extensor surfaces of lower extremities in patients with chronic venous insufficiency and arteriovenous malformations. It resembles aggressive conditions like Kaposi's sarcoma and requires histopathological examination for its diagnosis. We report two such cases of acroangiodermatitis. Histopathology of both the cases showed dilated capillaries in the dermis with extravasated red blood corpuscles (RBCs), hemosiderin deposits, and hyperplastic granulation tissue. Both were treated with oral antibiotics and topical steroids. The ulcers showed a good response within 2 months of treatment.
Operant conditioning in invertebrates

Learning to anticipate future events on the basis of past experience with the consequences of one's own behavior (operant conditioning) is a simple form of learning that humans share with most other animals, including invertebrates. Three model organisms have recently made significant contributions towards a mechanistic model of operant conditioning, because of their special technical advantages. Research using the fruit fly Drosophila melanogaster implicated the ignorant gene in operant conditioning in the heat-box, research on the sea slug Aplysia californica contributed a cellular mechanism of behavior selection at a convergence point of operant behavior and reward, and research on the pond snail Lymnaea stagnalis elucidated the role of a behavior-initiating neuron in operant conditioning. These insights demonstrate the usefulness of a variety of invertebrate model systems to complement and stimulate research in vertebrates.
Infrared stabilization of rice bran and its effects on γ-oryzanol content, tocopherols and fatty acid composition.

Rice bran is a nutritionally valuable by-product of paddy milling. In this study an experimental infrared (IR) stabilization system was developed to prevent rice bran rancidity. The free fatty acid content of raw and IR-stabilized rice bran samples was monitored every 15 days during 6 months of storage. In addition, energy consumption was determined.



The free fatty acid content of rice bran stabilized at 600 W IR power for 5 min remained below 5% for 165 days. No significant change in γ-oryzanol content or fatty acid composition but a significant decrease in tocopherol content was observed in stabilized rice bran compared with raw bran. IR stabilization was found to be comparable to extrusion with regard to energy consumption.



IR stabilization was effective in preventing hydrolytic rancidity of rice bran. By optimizing the operational parameters of IR stabilization, this by-product has the potential for use in the food industry in various ways as a value-added commodity.
ADAGIO: Interactive Experimentation with Adversarial Attack and Defense for Audio

Adversarial machine learning research has recently demonstrated the feasibility to confuse automatic speech recognition (ASR) models by introducing acoustically imperceptible perturbations to audio samples. To help researchers and practitioners gain better understanding of the impact of such attacks, and to provide them with tools to help them more easily evaluate and craft strong defenses for their models, we present Adagio, the first tool designed to allow interactive experimentation with adversarial attacks and defenses on an ASR model in real time, both visually and aurally. Adagio incorporates AMR and MP3 audio compression techniques as defenses, which users can interactively apply to attacked audio samples. We show that these techniques, which are based on psychoacoustic principles, effectively eliminate targeted attacks, reducing the attack success rate from 92.5% to 0%. We will demonstrate Adagio and invite the audience to try it on the Mozilla Common Voice dataset.
The one comparing narrative social network extraction techniques

Correspondence: michelle.edwards@adelaide.edu.au University of Adelaide, Adelaide, SA 5005, Australia Full list of author information is available at the end of the article  Analysing narratives through their social networks is an expanding field in quantitative literary studies. Manually extracting a social network from any narrative can be time consuming, so automatic extraction methods of varying complexity have been developed. However, the effect of different extraction methods on the analysis is unknown. Here we model and compare three extraction methods for social networks in narratives: manual extraction, co-occurrence automated extraction and automated extraction using machine learning. Although the manual extraction method produces more precise results in the network analysis, it is much more time consuming and the automatic extraction methods yield comparable conclusions for density, centrality measures and edge weights. Our results provide evidence that social networks extracted automatically are reliable for many analyses. We also describe which aspects of analysis are not reliable with such a social network. We anticipate that our findings will make it easier to analyse more narratives, which help us improve our understanding of how stories are written and evolve, and how people interact with each other.
An assist-as-needed control scheme for robot-assisted rehabilitation

This paper addresses the assist-as-needed (AAN) control problem for robotic orthoses. The objective is to design a stable AAN controller with an adjustable assistance level. The controller aims to follow a desired trajectory while allowing an adjustable tracking error with low control effort to provide a freedom zone for the user. By ensuring the stability of the system and providing the freedom zone, the controller combines the advantages of both model-based and non-model-based AAN controllers existing in the literature. Furthermore, the controller provides a priori bounded control command, and includes an adaptive neural network term to compensate for the uncertainties of dynamic model of the system, mainly when a precise tracking is of interest. The stability of the closed-loop system is well analysed based on the Lyapunov method. The effectiveness of the proposed control scheme is validated through experiments using a lower extremity robotic exoskeleton.
Topic-dependent sentiment analysis of financial blogs

While most work in sentiment analysis in the financial domain has focused on the use of content from traditional finance news, in this work we concentrate on more subjective sources of information, blogs. We aim to automatically determine the sentiment of financial bloggers towards companies and their stocks. To do this we develop a corpus of financial blogs, annotated with polarity of sentiment with respect to a number of companies. We conduct an analysis of the annotated corpus, from which we show there is a significant level of topic shift within this collection, and also illustrate the difficulty that human annotators have when annotating certain sentiment categories. To deal with the problem of topic shift within blog articles, we propose text extraction techniques to create topic-specific sub-documents, which we use to train a sentiment classifier. We show that such approaches provide a substantial improvement over full documentclassification and that word-based approaches perform better than sentence-based or paragraph-based approaches.
Large-scale recording of neuronal ensembles

How does the brain orchestrate perceptions, thoughts and actions from the spiking activity of its neurons? Early single-neuron recording research treated spike pattern variability as noise that needed to be averaged out to reveal the brain's representation of invariant input. Another view is that variability of spikes is centrally coordinated and that this brain-generated ensemble pattern in cortical structures is itself a potential source of cognition. Large-scale recordings from neuronal ensembles now offer the opportunity to test these competing theoretical frameworks. Currently, wire and micro-machined silicon electrode arrays can record from large numbers of neurons and monitor local neural circuits at work. Achieving the full potential of massively parallel neuronal recordings, however, will require further development of the neuron–electrode interface, automated and efficient spike-sorting algorithms for effective isolation and identification of single neurons, and new mathematical insights for the analysis of network properties.
pTCP: An End-to-End Transport Layer Protocol for Striped Connections

The TCP transport layer protocol is designed for connections that traverse a single path between the sender and receiver. However, there are several environments in which multiple paths can be used by a connection simultaneously. In this paper we consider the problem of supporting striped connections that operate over multiple paths. We propose an end-to-end transport layer protocol called pTCP that allows connections to enjoy the aggregate bandwidths offered by the multiple paths, irrespective of the individual characteristics of the paths. We show that pTCP can have a varied range of applications through instantiations in three different environments: (a) bandwidth aggregation on multihomed mobile hosts, (b) service differentiation using purely end-to-end mechanisms, and (c) end-systems based network striping. In each of the applications we demonstrate the applicability of pTCP and how its efficacy compares with existing approaches through simulation results.
Wegener granulomatosis: an analysis of 158 patients.

To prospectively study the clinical features, pathophysiology, treatment and prognosis of Wegener granulomatosis.



Of the 180 patients with Wegener granulomatosis referred to the National Institute of Allergy and Infectious Diseases during the past 24 years, 158 have been followed for 6 months to 24 years (a total of 1229 patient-years).



Characteristics of clinical presentation, surgical pathology, course of illness, laboratory and radiographic findings, and the results of medical and surgical treatment have been recorded in a computer-based information retrieval system.



The Warren Magnuson Clinical Center of the National Institutes of Health.



Men and women were equally represented; 97% of patients were white, and 85% were more than 19 years of age. The mean period of follow-up was 8 years. One hundred and thirty-three patients (84%) received "standard" therapy with daily low-dose cyclophosphamide and glucocorticoids. Eight (5.0%) received only low-dose cyclophosphamide. Six (4.0%) never received cyclophosphamide and were treated with other cytotoxic agents and glucocorticoids. Ten patients (6.0%) were treated with only glucocorticoids. Ninety-one percent of patients experienced marked improvement, and 75% achieved complete remission. Fifty percent of remissions were associated with one or more relapses. Of 99 patients followed for greater than 5 years, 44% had remissions of greater than 5 years duration. Thirteen percent of patients died of Wegener granulomatosis, treatment-related causes, or both. Almost all patients had serious morbidity from irreversible features of their disease (86%) or side effects of treatment (42%).



The course of Wegener granulomatosis has been dramatically improved by daily treatment with cyclophosphamide and glucocorticoids. Nonetheless, disease- and treatment-related morbidity is often profound. Alternative forms of therapy have not yet achieved the high rates of remission induction and successful maintenance that have been reported with daily cyclophosphamide treatment. Despite continued therapeutic success with cyclophosphamide, our long-term follow-up of patients with Wegener granulomatosis has led to increasing concerns about toxicity resulting from prolonged cyclophosphamide therapy and has encouraged investigation of other therapeutic regimens.
Trusted D2D-based data uploading in in-band narrowband-IoT with social awareness

Fifth generation (5G) systems are expected to introduce a revolution in the ICT domain with innovative networking features, such as device-to-device (D2D) communications. Accordingly, in-proximity devices directly communicate with each other, thus avoiding routing the data across the network infrastructure. This innovative technology is deemed to be also of high relevance to support effective heterogeneous objects interconnection within future IoT ecosystems. However, several open challenges shall be solved to achieve a seamless and reliable deployment of proximity-based communications. In this paper, we give a contribution to trust and security enhancements for opportunistic hop-by-hop forwarding schemes that rely on cellular D2D communications. To tackle the presence of malicious nodes in the network, reliability and reputation notions are introduced to model the level of trust among involved devices. To this aim, social-awareness of devices is accounted for, to better support D2D-based multihop content uploading. Our simulative results in small-scale IoT environments, demonstrate that data loss due to malicious nodes can be drastically reduced and gains in uploading time be reached with the proposed solution.
Assessment of vulnerabilities of web applications of Bangladesh: A case study of XSS & CSRF

In a sophisticated and coordinated cyber-attack $100 million has been stolen from Bangladesh's account. Attackers introduced malicious code remotely into the Bangladesh Bank's server, which allowed them to process and authorize the transactions. Advanced attack techniques poses threats to all web application systems. Cross Site Scripting (XSS) and Cross Site Request Forgery (CSRF) are two vulnerabilities which have techniques that are similar to those of the Bangladesh Bank heist. XSS and CSRF are third and eighth of the top ten web application vulnerabilities on OWASP list from 2013 till now. Both these attacks violate the users trust for the websites and web browsers. Because of the severity of these vulnerabilities, security specialists have always shared their concern and warned the web developers. Yet Bangladesh government's and developers' reluctance to address the severity of the attacks resulted in Bangladesh Bank heist. In this paper, we aim to study and conduct an investigation of the vulnerabilities of similar attacks as these of the Bangladesh Bank heist on web applications of Bangladesh. We would focus on XSS and CSRF vulnerabilities due to their high ranking on the OWASP list. We analyze the data collected during the investigation and provide a summary of the current state and a guideline for the future web developers.
Mitigating Address Spoofing Attacks in Hybrid SDN

Address spoofing attacks like ARP spoofing and DDoS attacks are mostly launched in a networking environment to degrade the performance. These attacks sometimes break down the network services before the administrator comes to know about the attack condition. Software Defined Networking (SDN) has emerged as a novel network architecture in which date plane is isolated from the control plane. Control plane is implemented at a central device called controller. But, SDN paradigm is not commonly used due to some constraints like budget, limited skills to control SDN, the flexibility of traditional protocols. To get SDN benefits in a traditional network, a limited number of SDN devices can be deployed among legacy devices. This technique is called hybrid SDN. In this paper, we propose a new approach to automatically detect the attack condition and mitigate that attack in hybrid SDN. We represent the network topology in the form of a graph. A graph based traversal mechanism is adopted to indicate the location of the attacker. Simulation results show that our approach enhances the network efficiency and improves the network security Keywords—Communication system security; Network Security; ARP Spoofing
Trace elements and cancer risk: a review of the epidemiologic evidence

Worldwide, there are more than 10 million new cancer cases each year, and cancer is the cause of approximately 12% of all deaths. Given this, a large number of epidemiologic studies have been undertaken to identify potential risk factors for cancer, amongst which the association with trace elements has received considerable attention. Trace elements, such as selenium, zinc, arsenic, cadmium, and nickel, are found naturally in the environment, and human exposure derives from a variety of sources, including air, drinking water, and food. Trace elements are of particular interest given that the levels of exposure to them are potentially modifiable. In this review, we focus largely on the association between each of the trace elements noted above and risk of cancers of the lung, breast, colorectum, prostate, urinary bladder, and stomach. Overall, the evidence currently available appears to support an inverse association between selenium exposure and prostate cancer risk, and possibly also a reduction in risk with respect to lung cancer, although additional prospective studies are needed. There is also limited evidence for an inverse association between zinc and breast cancer, and again, prospective studies are needed to confirm this. Most studies have reported no association between selenium and risk of breast, colorectal, and stomach cancer, and between zinc and prostate cancer risk. There is compelling evidence in support of positive associations between arsenic and risk of both lung and bladder cancers, and between cadmium and lung cancer risk.
Machine Learning and Images for Malware Detection and Classification

Detecting malicious code with exact match on collected datasets is becoming a large-scale identification problem due to the existence of new malware variants. Being able to promptly and accurately identify new attacks enables security experts to respond effectively.
 My proposal is to develop an automated framework for identification of unknown vulnerabilities by leveraging current neural network techniques. This has a significant and immediate value for the security field, as current anti-virus software is typically able to recognize the malware type only after its infection, and preventive measures are limited.
 Artificial Intelligence plays a major role in automatic malware classification: numerous machine-learning methods, both supervised and unsupervised, have been researched to try classifying malware into families based on features acquired by static and dynamic analysis.
 The value of automated identification is clear, as feature engineering is both a time-consuming and time-sensitive task, with new malware studied while being observed in the wild.
Aquaponics: integrating fish feeding rates and ion waste production for strawberry hydroponics.

Aquaponics is the science of integrating intensive fish aquaculture with plant production in recirculating water systems. Although ion waste production by f ish cannot satisfy all plant requirements, less is known about the relationship between total feed provided for f ish and the production of milliequivalents (mEq) of different macronutrients for plants, especially for nutrient flow hydroponics used for strawberry production in Spain. That knowledge is essential to consider the amount of macronutrients available in aquaculture systems so that farmers can estimate how much nutrient needs to be supplemented in the waste water from fish, to produce viable plant growth. In the present experiment, tilapia (Oreochromis niloticus L.) were grown in a small-scale recirculating system at two different densities while growth and feed consumption were noted every week for five weeks. At the same time points, water samples were taken to measure pH, EC25, HCO3, Cl, NH4, NO2, NO3, H2PO4, SO4, Na, K, Ca and Mg build up. The total increase in mEq of each ion per kg of feed provided to the fish was highest for NO3, followed, in decreasing order, by Ca, H2PO4, K, Mg and SO4. The total amount of feed required per mEq ranged from 1.6113.1 kg for the four most abundant ions (NO3, Ca, H2PO4 and K) at a density of 2 kg fish m, suggesting that it would be rather easy to maintain small populations of fish to reduce the cost of hydroponic solution supplementation for strawberries.  nutrients; recirculating system; tilapia; water quality.