nils-herrmann/clean_scirepeval huggingface dataset:
Common pathological processes in Alzheimer disease and type 2 diabetes: A review

Alzheimer disease (AD) and type 2 diabetes mellitus (T2DM) are conditions that affect a large number of people in the industrialized countries. Both conditions are on the increase, and finding novel treatments to cure or prevent them are a major aim in research. Somewhat surprisingly, AD and T2DM share several molecular processes that underlie the respective degenerative developments. This review describes and discusses several of these shared biochemical and physiological pathways. Disturbances in insulin signalling appears to be the main common impairment that affects cell growth and differentiation, cellular repair mechanisms, energy metabolism, and glucose utilization. Insulin not only regulates blood sugar levels but also acts as a growth factor on all cells including neurons in the CNS. Impairment of insulin signalling therefore not only affects blood glucose levels but also causes numerous degenerative processes. Other growth factor signalling systems such as insulin growth factors (IGFs) and transforming growth factors (TGFs) also are affected in both conditions. Also, the misfolding of proteins plays an important role in both diseases, as does the aggregation of amyloid peptides and of hyperphosphorylated proteins. Furthermore, more general physiological processes such as angiopathic and cytotoxic developments, the induction of apoptosis, or of non-apoptotic cell death via production of free radicals greatly influence the progression of AD and T2DM. The increase of detailed knowledge of these common physiological processes open up the opportunities for treatments that can prevent or reduce the onset of AD as well as T2DM.
Deletion 3q22.1-q23 with blepharophimosis, ptosis and epicanthus inversus and an Albright hereditary osteodystrophy-like brachydactyly phenotype.

Blepharophimosis, ptosis and epicanthus inversus (BPES) is an autosomal dominant condition caused by mutations in the FOXL2 gene, located on chromosome 3q23 (Beysen et al., 2005). It has frequently been reported in association with 3q chromosomal deletions and rearrangements (Franceschini et al., 1983; Al-Awadi et al., 1986; Alvarado et al., 1987; Jewett et al., 1993; Costa et al., 1998). In a review of the phenotype associated with interstitial deletions of the long arm of chromosome 3, Alvarado et al. (1987) commented on brachydactyly and abnormalities of the hands and feet. A syndrome characterized by growth and developmental delay, microcephaly, ptosis, blepharophimosis, large abnormally shaped ears, and a prominent nasal tip was suggested to be associated with deletion of the 3q2 region.
Can Facebook Aid Sustainability ? An Investigation of Empathy Expression within the Humans of New York Blog

This qualitative study offers a novel exploration of the links between social media, virtual intergroup contact, and empathy by examining how empathy is expressed through interactions on a popular social media blog. Global leaders are encouraging individuals to engage in behaviors and support policies that provide basic social foundations. It is difficult to motivate people to undertake such actions. However, research shows that empathy intensifies motivation to help others. It can cause individuals to see the world from the perspective of stigmatized group members and increase positive feelings. Social media offers a new pathway for virtual intergroup contact, providing opportunities to increase conversation about disadvantaged others and empathy. We examined expressions of empathy within a popular blog, Humans of New York (HONY), and engaged in purposeful case selection by focusing on (1) events where specific prosocial action was taken corresponding to interactions on the HONY blog and (2) presentation of people in countries other than the United States. Nine overarching themes; (1) perspective taking, (2) fantasy, (3) empathic concern, (4) personal distress, (5) relatability, (6) prosocial action, (7) community appreciation, (8) anti-empathy, and (9) rejection of anti-empathy, exemplify how the HONY community expresses and shares empathic thoughts and feelings.
Indoor localization without the pain

While WiFi-based indoor localization is attractive, the need for a significant degree of pre-deployment effort is a key challenge. In this paper, we ask the question: can we perform indoor localization with no pre-deployment effort? Our setting is an indoor space, such as an office building or a mall, with WiFi coverage but where we do not assume knowledge of the physical layout, including the placement of the APs. Users carrying WiFi-enabled devices such as smartphones traverse this space in normal course. The mobile devices record Received Signal Strength (RSS) measurements corresponding to APs in their view at various (unknown) locations and report these to a localization server. Occasionally, a mobile device will also obtain and report a location fix, say by obtaining a GPS lock at the entrance or near a window. The centerpiece of our work is the EZ Localization algorithm, which runs on the localization server. The key intuition is that all of the observations reported to the server, even the many from unknown locations, are constrained by the physics of wireless propagation. EZ models these constraints and then uses a genetic algorithm to solve them. The results from our deployment in two different buildings are promising. Despite the absence of any explicit pre-deployment calibration, EZ yields a median localization error of 2m and 7m, respectively, in a small building and a large building, which is only somewhat worse than the 0.7m and 4m yielded by the best-performing but calibration-intensive Horus scheme [29] from prior work.
A 32-KB Standard CMOS Antifuse One-Time Programmable ROM Embedded in a 16-bit Microcontroller

A 32-KB standard CMOS antifuse one-time programmable (OTP) ROM embedded in a 16-bit microcontroller as its program memory is designed and implemented in 0.18-mum standard CMOS technology. The proposed 32-KB OTP ROM cell array consists of 4.2 mum2 three-transistor (3T) OTP cells where each cell utilizes a thin gate-oxide antifuse, a high-voltage blocking transistor, and an access transistor, which are all compatible with standard CMOS process. In order for high density implementation, the size of the 3T cell has been reduced by 80% in comparison to previous work. The fabricated total chip size, including 32-KB OTP ROM, which can be programmed via external I 2C master device such as universal I2C serial EEPROM programmer, 16-bit microcontroller with 16-KB program SRAM and 8-KB data SRAM, peripheral circuits to interface other system building blocks, and bonding pads, is 9.9 mm2. This paper describes the cell, design, and implementation of high-density CMOS OTP ROM, and shows its promising possibilities in embedded applications
Obsessive-compulsive spectrum disorders

The obsessive-compulsive spectrum is an important concept referring to a number of disorders drawn from several diagnostic categories that share core obsessive-compulsive features. These disorders can be grouped by the focus of their symptoms: bodily preoccupation, impulse control, or neurological disorders. Although the disorders are clearly distinct from one another, they have intriguing similarities in phenomenology, etiology, pathophysiology, patient characteristics, and treatment response. In combination with the knowledge gained through many years of research on obsessive-compulsive disorder (OCD), the concept of a spectrum has generated much fruitful research on the spectrum disorders. It has become apparent that these disorders can also be viewed as being on a continuum of compulsivity to impulsivity, characterized by harm avoidance at the compulsive end and risk seeking at the impulsive end. The compulsive and impulsive disorders differ in systematic ways that are just beginning to be understood. Here, we review these concepts and several representative obsessive-compulsive spectrum disorders including both compulsive and impulsive disorders, as well as the three different symptom clusters: OCD, body dysmorphic disorder, pathological gambling, sexual compulsivity, and autism spectrum disorders.
Cu-Sn based die attach material for power semiconductor with stress control

This paper describes development of joint materials using only base metals (Cu and Sn) for power semiconductor assembly. The preform sheet of the joint material is made by two kinds of particles such as Cu source and Cu-Sn IMC source. Optimized ratio of Cu source: IMC source provides robust skeleton structure in joint area. The particles' mixture control (Cu density and thickness) affects stress control to eliminate cracks and delamination of the joint area. As evaluation, Thermal Cycling Test (TCT, −40°C∼+200°C, 1,000cycles) of Cu-Cu joint resulted no critical cracks / delamination / voids. We confirmed the material also applicable for attaching SiC die on the DCB substrate on bare Cu heatsink.
Ensuring rigour and trustworthiness of qualitative research in clinical pharmacy

The use of qualitative research methodology is well established for data generation within healthcare research generally and clinical pharmacy research specifically. In the past, qualitative research methodology has been criticized for lacking rigour, transparency, justification of data collection and analysis methods being used, and hence the integrity of findings. Demonstrating rigour in qualitative studies is essential so that the research findings have the “integrity” to make an impact on practice, policy or both. Unlike other healthcare disciplines, the issue of “quality” of qualitative research has not been discussed much in the clinical pharmacy discipline. The aim of this paper is to highlight the importance of rigour in qualitative research, present different philosophical standpoints on the issue of quality in qualitative research and to discuss briefly strategies to ensure rigour in qualitative research. Finally, a mini review of recent research is presented to illustrate the strategies reported by clinical pharmacy researchers to ensure rigour in their qualitative research studies.
Structure and Encapsulation in Distributed Systems: The Proxy Principle

We present a novel view of the structuring of distributed systems, and a few examples of its utilization in an object-oriented context. In a distributed system, the structure of a service or subsystem may be complex, being implemented as a set of communicating server objects; however, this complexity of structure should not be apparent to the client. In our proposal, a client must first acquire a local object, called a proxy, in order to use such a service. The proxy represents the whole set of servers. The client directs all its communication to the proxy. The proxy, and all the objects it represents, collectively form one distributed object, which is not decomposable by the client. Any higher-level communication protocols are internal to this distributed object. Such a view provides a powerful structuring framework for distributed systems; it can be implemented cheaply without sacrificing much flexibility. It subsumes may previous proposals, but encourages better information-hiding and encapsulation.
Optimizing Neuropsychological Assessments for Cognitive, Behavioral, and Functional Impairment Classification: A Machine Learning Study

Subjects with Alzheimer's disease (AD) show loss of cognitive functions and change in behavioral and functional state affecting the quality of their daily life and that of their families and caregivers. A neuropsychological assessment plays a crucial role in detecting such changes from normal conditions. However, despite the existence of clinical measures that are used to classify and diagnose AD, a large amount of subjectivity continues to exist. Our aim was to assess the potential of machine learning in quantifying this process and optimizing or even reducing the amount of neuropsychological tests used to classify AD patients, also at an early stage of impairment. We investigated the role of twelve state-of-the-art neuropsychological tests in the automatic classification of subjects with none, mild, or severe impairment as measured by the clinical dementia rating (CDR). Data were obtained from the ADNI database. In the groups of measures used as features, we included measures of both cognitive domains and subdomains. Our findings show that some tests are more frequently best predictors for the automatic classification, namely, LM, ADAS-Cog, AVLT, and FAQ, with a major role of the ADAS-Cog measures of delayed and immediate memory and the FAQ measure of financial competency.
Large-scale user modeling with recurrent neural networks for music discovery on multiple time scales

The amount of content on online music streaming platforms is immense, and most users only access a tiny fraction of this content. Recommender systems are the application of choice to open up the collection to these users. Collaborative filtering has the disadvantage that it relies on explicit ratings, which are often unavailable, and generally disregards the temporal nature of music consumption. On the other hand, item co-occurrence algorithms, such as the recently introduced word2vec-based recommenders, are typically left without an effective user representation. In this paper, we present a new approach to model users through recurrent neural networks by sequentially processing consumed items, represented by any type of embeddings and other context features. This way we obtain semantically rich user representations, which capture a user’s musical taste over time. Our experimental analysis on large-scale user data shows that our model can be used to predict future songs a user will likely listen to, both in the short and long term.
Introduction: digital literacies: concepts, policies and practices

Th is book supports an emerging trend toward emphasizing the plurality of digital literacy; recognizing the advantages of understanding digital literacy as digital literacies. In the book world this trend is still marginal. In December 2007, Allan Martin and Dan Madigan’s collection Digital Literacies for Learning (2006) was the only English-language book with “digital literacies” in the title to show up in a search on Amazon.com. Th e plural form fares better among English-language journal articles (e.g., Anderson & Henderson, 2004; Ba, Tally, & Tsikalas, 2002; Bawden, 2001; Doering et al., 2007;  2006; Snyder, 1999; Th omas, 2004) and conference presentations (e.g., Erstad, 2007; Lin & Lo, 2004; Steinkeuhler, 2005), however, and is now reasonably common in talk on blogs and wikis (e.g., Couros, 2007; Davies, 2007). Nonetheless, talk of digital literacy, in the singular, remains the default mode. Th e authors invited to contribute to this book were chosen in light of three reasons we (the editors) identify as important grounds for promoting the idea of digital literacies in the plural. Th is, of course, does not mean the contributing authors would necessarily subscribe to some or all of these reasons. Th at was
INTEGRATING FUZZY LOGIC WITH DATA MINING METHODS FOR INTRUSION DETECTION

This report explores integrating fuzzy logic with two data mining methods (association rules and frequency episodes) for intrusion detection. Data mining methods are capable of extracting patterns automatically from a large amount of data. The integration with fuzzy logic can produce more abstract and flexible patterns for intrusion detection, since many quantitative features are involved in intrusion detection and security itself is fuzzy. In this report, Chapter I introduces the concept of intrusion detection and the practicality of applying fuzzy logic to intrusion detection. In Chapter II, two types of intrusion detection systems, host-based systems and network-based systems, are briefly reviewed. Some important artificial intelligence techniques that have been applied to intrusion detection are also reviewed here, including data mining methods for anomaly detection. Chapter III summarizes a set of desired characteristics for the Intelligent Intrusion Detection Model (IIDM) being developed at Mississippi State University. A preliminary architecture which we have developed for integrating machine learning methods with other intrusion detection methods is also described. Chapter IV discusses basic fuzzy logic theory, traditional algorithms for mining association rules, and an original algorithm for mining frequency episodes. In Chapter V, the algorithms we have extended for mining fuzzy association rules and fuzzy frequency episodes are described. We add a normalization step to the procedure for mining fuzzy association rules in order to prevent one data instance from contributing more than others. We also modify the procedure for mining frequency episodes to learn fuzzy frequency episodes. Chapter VI describes a set of experiments of applying fuzzy association rules and fuzzy episode rules for off-line anomaly detection and real-time intrusion detection. We use fuzzy association rules and fuzzy frequency episodes to extract patterns for temporal statistical measurements at a higher level than the data level. We define a modified similarity evaluation function which is continuous and monotonic for the application of fuzzy association rules and fuzzy frequency episodes in anomaly detection. We also present a new real-time intrusion detection method using fuzzy episode rules. The experimental results show the utility of fuzzy association rules and fuzzy frequency episodes in intrusion detection. The conclusions are included in Chapter VII. ii DEDICATION I would like to dedicate this research to my family and my wife. iii ACKNOWLEDGMENTS I am deeply grateful to Dr. Susan Bridges for expending much time to direct me in this entire research project and directing my graduate study and research work …
Vision-Based Mobile Robot Localization with Simple Artificial Landmarks

This article presents a vision-based method for mobile robot localization in partially known environments. Simple, unobtrusive artificial landmarks are used as external localization aids. The landmarks are labelled with unique code patterns, what enables unambiguous global localization. The analysis is presented which enables prediction of the uncertainty of the position and orientation of the robot relative to the landmark. Experimental evidence is provided, demonstrating that the proposed method can be reliably used over a wide range of relative positions between the camera and the landmark.
Optimized fast convolution based filtered-OFDM processing for 5G

This paper investigates the application of flexible fast-convolution (FC) filtering scheme for multiplexing orthogonal frequency-division multiplexing (OFDM) physical resource blocks (PRBs) in a spectrally well-localized manner. This scheme is able to suppress interference leakage between adjacent PRBs, thus supporting independent waveform parametrization and numerologies for different PRBs, as well as asynchronous multiuser operation. These are considered as important features in the 5G waveform development. This contribution focuses on optimizing FC based OFDM transmultiplexers such that the in-band interference is minimized subject to the given out-of-band emission constraint. The performance of the optimized designs is demonstrated using resource block groups (RBGs) of different sizes and with various design parameters. The proposed scheme has great flexibility in tuning the filtering bandwidths dynamically according the resource allocation to different users with different requirements regarding the OFDM waveform numerology. Also the computational complexity is competitive with existing time-domain windowing approaches and becomes superior when the number of filtering bands is increased.
Design And Optimization Of Planar Waveguide Magic Tee At W-band

Conventionally, the sum and difference signals of a tracking system are fixed up by sum and difference network and the network is often composed of four or more magic tees whose arms direct at four different directions, which give inconveniences to assemble. In this paper, a waveguide side-wall slot directional coupler and a double dielectric slab filled waveguide phase shifter is used to form a planar magic tee with four arms in the same H-plane. Four planar magic tees can be used to construct the W-band planar monopulse comparator. The planar magic tee is analyzed exactly with Ansoft HFSS software, and is optimized by genetic algorithm. Simulation results are presented, which show good performance.
Feed study for a wideband 18 to 45 GHz luneburg lens antenna

This paper evaluates quad-ridged horn, tapered slot, and planar spiral antennas as a manifold feed of an 18–45 GHz Luneburg lens (LL). Since a greater number of feed elements can be accommodated when the feeds are farther from the lens, the effect of feed displacement from the lens focal point on far-field performance is evaluated. As expected, the displacement reduces directivity and worsens side lobe level; however, the horn and spiral antennas demonstrate encouraging results for wideband LL applications.
A MultiView Dense Point Cloud Generation Algorithm Based on Low-Altitude Remote Sensing Images

This paper presents a novel multi-view dense point cloud generation algorithm based on low-altitude remote sensing images. The proposed method was designed to be especially effective in enhancing the density of point clouds generated by Multi-View Stereo (MVS) algorithms. To overcome the limitations of MVS and dense matching algorithms, an expanded patch was set up for each point in the point cloud. Then, a patch-based Multiphoto Geometrically Constrained Matching (MPGC) was employed to optimize points on the patch based on least square adjustment, the space geometry relationship, and epipolar line constraint. The major advantages of this approach are twofold: (1) compared with the MVS method, the proposed algorithm can achieve denser three-dimensional (3D) point cloud data; and (2) compared with the epipolar-based dense matching method, the proposed method utilizes redundant measurements to weaken the influence of occlusion and noise on matching results. Comparison studies and experimental results have validated the accuracy of the proposed algorithm in low-altitude remote sensing image dense point cloud generation.
A randomised study evaluating the use of pyridoxine to avoid capecitabine dose modifications

Pyridoxine is frequently used to treat capecitabine-induced hand–foot syndrome (HFS), although the evidence of benefit is lacking. We performed a randomised placebo-controlled trial to determine whether pyridoxine could avoid the need for capecitabine dose modifications and improve outcomes.A total of 106 patients planned for palliative single-agent capecitabine (53 in each arm, 65%/ 35% colorectal/breast cancer) were randomised to receive either concomitant pyridoxine (50 mg po) or matching placebo three times daily.Compared with placebo, pyridoxine use was associated with an increased rate of avoiding capecitabine dose modifications (37% vs 23%, relative risk 0.59, 95% CI 0.29, 1.20, P=0.15) and fewer grade 3/4 HFS-related adverse events (9% vs 17%, odds ratio 0.51, 95% CI 0.15–1.6, P=0.26). Use of pyridoxine did not improve response rate or progression-free survival.Pyridoxine may reduce the need for capecitabine dose modifications and the incidence of severe HFS, but does not impact on antitumour effect.
NuDetective: A Forensic Tool to Help Combat Child Pornography through Automatic Nudity Detection

With the recent amendment in Brazilian law, where possession of files containing child pornography is now considered a crime, the need to detect this type of content at crime scenes increased. This paper presents the NuDetective Forensic Tool, which was developed in order to assist forensic examiners to conduct such analysis in a timely manner at the crime scene. This Tool performs automatic detection of nudity in images and also performs analysis of file names. Two evaluation experiments of the Tool were performed and showed detection rates around 95%, with low rates of false positives, combined with fast processing.