nils-herrmann/clean_scirepeval huggingface dataset:
Brightness-Based Convolutional Neural Network for Thermal Image Enhancement

In this paper, we propose a convolutional neural network for thermal image enhancement by incorporating the brightness domain with a residual-learning technique, which improves the performance of enhancement and speed of convergence. Typically, the training domain uses the same domain as that of the target image; however, we evaluated several domains to determine the most suitable one for the network. In the analyses, we first compared the performance of networks that were trained by the corresponding regions of color-based and aligned infrared-based images, respectively, including thermal, far, and near spectra. Then, four RGB-based domains, namely, gray, lightness, intensity, and brightness were evaluated. Finally, the proposed network architecture was determined by considering the residual and brightness domains. The results of the analyses indicated that the brightness domain was the best training domain for enhancing the thermal images. The experimental results confirm that the proposed network, which can be trained in approximately one hour, outperforms the conventional learning-based approaches for thermal image enhancement, in terms of several image quality metrics and a qualitative evaluation. Furthermore, the results demonstrate that the brightness domain is effective as the training domain and can be used to increase the performance of existing networks.
THE CRIMINAL AND LABOR MARKET IMPACTS OF INCARCERATION

This paper investigates the preand post-release impacts of incarceration on criminal behavior, economic wellbeing and family formation using new data from Harris County, Texas. The research design identifies exogenous variation in the extensive and intensive margins of incarceration by leveraging the random assignment of defendants to courtrooms. I develop a new data-driven estimation procedure to address multidimensional and non-monotonic sentencing patterns observed in the courtrooms in my data. My findings indicate that incarceration generates modest incapacitation effects, which are offset in the long-run by an increased likelihood of defendants reoffending after being released. Additional evidence finds that incarceration reduces post-release employment and wages, increases take-up of food stamps, decreases likelihood of marriage and increases the likelihood of divorce. Based on changes in defendant behavior alone, I estimate that a one-year prison term for marginal defendants conservatively generates $56,200 to $66,800 in social costs, which would require substantial general deterrence in the population to at least be welfare neutral.
A quantitative real-time assessment of Buerger exercise on dorsal foot peripheral skin circulation in patients with diabetes foot

Buerger exercise can improve the peripheral circulation of lower extremities. However, the evidence and a quantitative assessment of skin perfusion immediately after this exercise in patients with diabetes feet are still rare.We recruited 30 patients with unilateral or bilateral diabetic ulcerated feet in Chang Gung Memorial Hospital, Chia-Yi Branch, from October 2012 to December 2013. Real-time dorsal foot skin perfusion pressures (SPPs) before and after Buerger exercise were measured and analyzed. In addition, the severity of ischemia and the presence of ulcers before exercise were also stratified.A total of 30 patients with a mean age of 63.4 ± 13.7 years old were enrolled in this study. Their mean duration of diabetes was 13.6 ± 8.2 years. Among them, 26 patients had unilateral and 4 patients had bilateral diabetes foot ulcers. Of the 34 wounded feet, 23 (68%) and 9 (27%) feet were classified as Wagner class II and III, respectively. The real-time SPP measurement indicated that Buerger exercise significantly increased the level of SPP by more than 10 mm Hg (n = 46, 58.3 vs 70.0 mm Hg, P < 0.001). In terms of pre-exercise dorsal foot circulation condition, the results showed that Buerger exercise increased the level of SPP in severe ischemia (n = 5, 22.1 vs 37.3 mm Hg, P = 0.043), moderate ischemia (n = 14, 42.2 vs 64.4 mm Hg, P = 0.001), and borderline-normal (n = 7, 52.9 vs 65.4 mm Hg, P = 0.028) groups, respectively. However, the 20 feet with SPP levels more than 60 mm Hg were not improved significantly after exercise (n = 20, 58.3 vs 71.5 mm Hg, P = 0.239). As to the presence of ulcers, Buerger exercise increased the level of SPP in either unwounded feet (n = 12, 58.5 vs 66.0 mm Hg, P = 0.012) or wounded feet (n = 34, 58.3 vs 71.5 mm Hg, P < 0.001). The majority of the ulcers was either completely healed (9/34 = 27%) or still improving (14/34 = 41%).This study quantitatively demonstrates the evidence of dorsal foot peripheral circulation improvement after Buerger exercise in patients with diabetes.
Double-polysilicon self-aligned SiGe HBT architecture based on nonselective epitaxy and polysilicon reflow

This paper describes a self-aligned SiGe heterojunction bipolar transistor (HBT) based on a standard double-polysilicon architecture and nonselective epitaxial growth (i.e. DPSA-NSEG). Emitter-base self-alignment is realized by polysilicon reflow in a hydrogen ambient after emitter window patterning. The fabricated self-aligned SiGe HBTs, with emitter widths of 0.3-0.4 μm, exhibit 20% lower base resistance and 15% higher maximum oscillation frequency fmax than non-self-aligned reference devices. The minimum noise figure of a Ku-band low-noise amplifier is reduced from 0.9 to 0.8 dB by emitter-base self-alignment.
Social Media and Mobile Apps for Health Promotion in Australian Indigenous Populations: Scoping Review

Health promotion organizations are increasingly embracing social media technologies to engage end users in a more interactive way and to widely disseminate their messages with the aim of improving health outcomes. However, such technologies are still in their early stages of development and, thus, evidence of their efficacy is limited.



The study aimed to provide a current overview of the evidence surrounding consumer-use social media and mobile software apps for health promotion interventions, with a particular focus on the Australian context and on health promotion targeted toward an Indigenous audience. Specifically, our research questions were: (1) What is the peer-reviewed evidence of benefit for social media and mobile technologies used in health promotion, intervention, self-management, and health service delivery, with regard to smoking cessation, sexual health, and otitis media? and (2) What social media and mobile software have been used in Indigenous-focused health promotion interventions in Australia with respect to smoking cessation, sexual health, or otitis media, and what is the evidence of their effectiveness and benefit?



We conducted a scoping study of peer-reviewed evidence for the effectiveness of social media and mobile technologies in health promotion (globally) with respect to smoking cessation, sexual health, and otitis media. A scoping review was also conducted for Australian uses of social media to reach Indigenous Australians and mobile apps produced by Australian health bodies, again with respect to these three areas.



The review identified 17 intervention studies and seven systematic reviews that met inclusion criteria, which showed limited evidence of benefit from these interventions. We also found five Australian projects with significant social media health components targeting the Indigenous Australian population for health promotion purposes, and four mobile software apps that met inclusion criteria. No evidence of benefit was found for these projects.



Although social media technologies have the unique capacity to reach Indigenous Australians as well as other underserved populations because of their wide and instant disseminability, evidence of their capacity to do so is limited. Current interventions are neither evidence-based nor widely adopted. Health promotion organizations need to gain a more thorough understanding of their technologies, who engages with them, why they engage with them, and how, in order to be able to create successful social media projects.
A Comprehensive Approach Towards Data Preprocessing Techniques & Association Rules

Data pre-processing is an important and critical step in the data mining process and it has a huge impact on the success of a data mining ) Data pre-processing is a step of the Knowledge discovery in databases (KDD) process that reduces the complexity of the data and offers better conditions to subsequent analysis. Through this the nature of the data is better understood and the data analysis is performed more accurately and efficiently. Data pre-processing is challenging as it involves extensive manual effort and time in developing the data operation scripts. There are a number of different tools and methods used for pre-processing, including: sampling, which selects a representative subset from a large population of data; transformation, which manipulates raw data to produce a single input; denoising, which removes noise from data; normalization, which organizes data for more efficient access; and feature extraction, which pulls out specified data that is significant in some particular context. Pre-processing technique is also useful for association rules algo. LikeAprior, Partitioned, Princer-search algo. and many more algos.
Inhibition of GSK-3 Ameliorates Aβ Pathology in an Adult-Onset Drosophila Model of Alzheimer's Disease

Abeta peptide accumulation is thought to be the primary event in the pathogenesis of Alzheimer's disease (AD), with downstream neurotoxic effects including the hyperphosphorylation of tau protein. Glycogen synthase kinase-3 (GSK-3) is increasingly implicated as playing a pivotal role in this amyloid cascade. We have developed an adult-onset Drosophila model of AD, using an inducible gene expression system to express Arctic mutant Abeta42 specifically in adult neurons, to avoid developmental effects. Abeta42 accumulated with age in these flies and they displayed increased mortality together with progressive neuronal dysfunction, but in the apparent absence of neuronal loss. This fly model can thus be used to examine the role of events during adulthood and early AD aetiology. Expression of Abeta42 in adult neurons increased GSK-3 activity, and inhibition of GSK-3 (either genetically or pharmacologically by lithium treatment) rescued Abeta42 toxicity. Abeta42 pathogenesis was also reduced by removal of endogenous fly tau; but, within the limits of detection of available methods, tau phosphorylation did not appear to be altered in flies expressing Abeta42. The GSK-3-mediated effects on Abeta42 toxicity appear to be at least in part mediated by tau-independent mechanisms, because the protective effect of lithium alone was greater than that of the removal of tau alone. Finally, Abeta42 levels were reduced upon GSK-3 inhibition, pointing to a direct role of GSK-3 in the regulation of Abeta42 peptide level, in the absence of APP processing. Our study points to the need both to identify the mechanisms by which GSK-3 modulates Abeta42 levels in the fly and to determine if similar mechanisms are present in mammals, and it supports the potential therapeutic use of GSK-3 inhibitors in AD.
Knowledge Extraction Using Rule Based Decision Tree Approach

Text mining has been defined as “the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources” . Many other industries and areas can also benefit from the text mining tools that are being developed by a number of companies. This paper provides an overview of the text mining tools and technologies that are being developed and is intended to be a guide for organizations who are looking for the most appropriate text mining techniques for their situation. This paper also concentrates to design text and data mining tool to extract the valuable information from curriculum vitae according to concerned requirements. The tool clusters the curriculum vitae into several segments which will help the public and private concerns for their recruitment. Rule based approach is used to develop the algorithm for mining and also it is implemented to extract the valuable information from the curriculum vitae on the web. Analysis of Curriculum vitae is until now, a costly and manual activity. It is subject to all typical variations and limitations in its quality, depending of who is doing it. Automating this analysis using algorithms might deliver much more consistency and preciseness to support the human experts. The experiments involve cooperation with many people having their CV online, as well as several recruiters etc. The algorithms must be developed and improved for processing of existing sets of semi-structured documents information retrieval under uncertainity about quality of the sources.
Multi-fragment effects on the GPU using the k-buffer

Many interactive rendering algorithms require operations on multiple fragments (i.e., ray intersections) at the same pixel location: however, current Graphics Processing Units (GPUs) capture only a single fragment per pixel. Example effects include transparency, translucency, constructive solid geometry, depth-of-field, direct volume rendering, and isosurface visualization. With current GPUs, programmers implement these effects using multiple passes over the scene geometry, often substantially limiting performance. This paper introduces a generalization of the Z-buffer, called the k-buffer, that makes it possible to efficiently implement such algorithms with only a single geometry pass, yet requires only a small, fixed amount of additional memory. The k-buffer uses framebuffer memory as a read-modify-write (RMW) pool of k entries whose use is programmatically defined by a small k-buffer program. We present two proposals for adding k-buffer support to future GPUs and demonstrate numerous multiple-fragment, single-pass graphics algorithms running on both a software-simulated k-buffer and a k-buffer implemented with current GPUs. The goal of this work is to demonstrate the large number of graphics algorithms that the k-buffer enables and that the efficiency is superior to current multipass approaches.
Analysis of brute force attack using TG — Dataset

In this paper we compare and evaluate the effectiveness of the brute force methodology using dataset of known password. It is a known fact that user chosen passwords are easily recognizable and crackable, by using several password recovery techniques; Brute force attack is one of them. For rescuing such attacks several organizations proposed the password creation rules which stated that password must include number and special characters for strengthening it and protecting against various password cracking attacks such as Dictionary attack, brute force attack etc. The result of this paper and proposed methodology helps in evaluating the system and account security for measuring the degree of authentication by estimating the password strength. The experiment is conducted on our proposed dataset (TG-DATASET) that contain an iterative procedure for creating the alphanumeric password string like a*, b*, c* and so on. The proposed dataset is prepared due to non-availability of iterative password in any existing password data sets.
Using Virtual Reality in Education

computers can not only create models, they can store Virtual Reality is a three-dimensional, computer-generated, information about these models -more data than ever simulated environment where data is literally transformed before. So the computer becomes a dynamic electronic into things we can see, feel, and even touch. Virtual reality encyclopedia that can be easily updated and easily tailored has significant implications in many areas such as business, to fit individual needs. industry, entertainment, and most importantly for educators, education. We have a responsibility to learn more about this Myron Krueger claims to have coined the term virtual new technology and investigate uses for our students. Then reality in 1991 to describe the type of experience possible in we need to encourage the continuing research, development, his VIDEOPLACE, a virtual room he created and explained and implementation of virtual reality environments for as “a graphic world that people could enter from different educational purposes. places to interact with each other and with graphic creatures”. (3) Spring examines the definitions for virtual (being in essence or effect, but not in fact) and reality (a real event, entity, or state of affairs), and uses these definitions to define virtual reality as, “a factor real event that appears in essence, but not in fact”. (4) Many other authors offer varying definitions, but each one follows the theme or virtual reality as the appearance of reality, Virtual Reality has become a much used, and often misused buzzwood in today’s society. Like so many buzzwords, it is sometimes used very loosely. It has been used to describe everything from computer games to the internet. But, what exactly is virtual reality, how is it developing, and most importantly for educators, what benefits could we derive from using virtual reality in education?
Effects of actinobacteria on plant disease suppression and growth promotion

Biological control and plant growth promotion by plant beneficial microbes has been viewed as an alternative to the use of chemical pesticides and fertilizers. Bacteria and fungi that are naturally associated with plants and have a beneficial effect on plant growth by the alleviation of biotic and abiotic stresses were isolated and developed into biocontrol (BCA) and plant growth-promoting agents (PGPA). Actinobacteria are a group of important plant-associated spore-forming bacteria, which have been studied for their biocontrol, plant growth promotion, and interaction with plants. This review summarizes the effects of actinobacteria as BCA, PGPA, and its beneficial associations with plants.
Using open educational resources on culture for the creation of MOOCs: A proposal of training for secondary education teachers

Because of their development in recent years Digital Humanities have been applied to the field of Education on an international level. In the field of Culture especially, a mere search online will reveal the great number of Massive Open Online Courses (MOOCs) that focus on Greek Arts. In Greece, on the contrary, despite the plethora of Greek sites, the digitalized material on culture they contain has not been systematically used in the field of education. In this paper we suggest a way to create Greek MOOCs for Greek Arts making use of digitalized resources of cultural material, mainly DARIA-GR. In this proposal we use University Open Courses so that the described platform will be able to form, on the one hand, a basis for the training of SE teachers who teach the relevant disciplines and on the other hand an area of enriched material aiding them in the teaching process. Finally, we recommend that TraMOOC be used for the creation of complete foreign-language MOOC for Digital Humanities.
SEMANTIC WEB LANGUAGES – STRENGTHS AND WEAKNESS

The current web suffers information overloading: it is increasingly difficult and time consuming to obtain information desired. Ontologies, the key concept behind the Semantic Web, will provide the means to overcome such problem by providing meaning to the available data. An ontology provides a shared and common understanding of a domain and information machine-processable semantics. To make the Semantic Web a reality and lift current Web to its full potential, powerful and expressive languages are required. Such web ontology languages must be able to describe and organize knowledge in the Web in a machine understandable way. However, organizing knowledge requires the facilities of a logical formalism which can deal with temporal, spatial, epistemic, and inferential aspects of knowledge. Implementations of Web ontology languages must provide these inference services, making them much more than just simple data storage and retrieval systems. This paper presents a state of the art for the most relevant Semantic Web Languages: XML, RDF(s), OIL, DAML+OIL, and OWL, together with a detailed comparison based on modeling primitives and language to language characteristics.
Uncovering periodic network signals of cyber attacks

This paper addresses the problem of detecting the presence of malware that leaveperiodictraces innetworktraffic. This characteristic behavior of malware was found to be surprisingly prevalent in a parallel study. To this end, we propose a visual analytics solution that supports both automatic detection and manual inspection of periodic signals hidden in network traffic. The detected periodic signals are visually verified in an overview using a circular graph and two stacked histograms as well as in detail using deep packet inspection. Our approach offers the capability to detect complex periodic patterns, but avoids the unverifiability issue often encountered in related work. The periodicity assumption imposed on malware behavior is a relatively weak assumption, but initial evaluations with a simulated scenario as well as a publicly available network capture demonstrate its applicability.
Immunopathology of chronic rhinosinusitis.

Chronic rhinosinusitis (CRS) is a heterogeneous disease characterized by local inflammation of the upper airways and sinuses which persists for at least 12 weeks. CRS can be divided into two phenotypes dependent on the presence of nasal polyps (NPs); CRS with NPs (CRSwNP) and CRS without NPs (CRSsNP). Immunological patterns in the two diseases are known to be different. Inflammation in CRSsNP is rarely investigated and limited studies show that CRSsNP is characterized by type 1 inflammation. Inflammation in CRSwNP is well investigated and CRSwNP in Western countries shows type 2 inflammation and eosinophilia in NPs. In contrast, mixed inflammatory patterns are found in CRSwNP in Asia and the ratio of eosinophilic NPs and non-eosinophilic NPs is almost 50:50 in these countries. Inflammation in eosinophilic NPs is mainly controlled by type 2 cytokines, IL-5 and IL-13, which can be produced from several immune cells including Th2 cells, mast cells and group 2 innate lymphoid cells (ILC2s) that are all elevated in eosinophilic NPs. IL-5 strongly induces eosinophilia. IL-13 activates macrophages, B cells and epithelial cells to induce recruitment of eosinophils and Th2 cells, IgE mediated reactions and remodeling. Epithelial derived cytokines, TSLP, IL-33 and IL-1 can directly and indirectly control type 2 cytokine production from these cells in eosinophilic NPs. Recent clinical trials showed the beneficial effect on eosinophilic NPs and/or asthma by monoclonal antibodies against IL-5, IL-4Rα, IgE and TSLP suggesting that they can be therapeutic targets for eosinophilic CRSwNP.
Seven-switch five-level active neutral-point clamped converter and optimal modulation strategy

The five-level active-neutral-point-clamped (ANPC) converters are newly hybrid topologies which have the advantages of traditional neutral-point-clamped (NPC) and flying-capacitor (FC) multilevel converters. A novel seven-switch five-level ANPC (7S-5L-ANPC) inverter topology is proposed, which reduces the number of active semiconductor switches over traditional 5L-ANPC inverter topologies. It is capable of operating under any power factor conditions. The special modulation strategy for 7S-5L-ANPC is proposed and simulation shows only reactive current is flowing through the seventh switch. Thus, low current rating switch can be selected for the seventh switch. The proposed 7S-5L-ANPC inverter is very suitable for unity and high power factor applications such as photovoltaic (PV) application. A 1KW single-phase inverter prototype is built to verify the validity and flexibility of the proposed topology and modulation.