nils-herrmann/clean_scirepeval huggingface dataset:
A sulfated galactans supplemented diet enhances the expression of immune genes and protects against Vibrio parahaemolyticus infection in shrimp.

A sulfated galactans (SG) supplemented diet was evaluated for the potential to stimulate immune activity in shrimp Penaeus vannamei (P. vannamei). Shrimp given the SG supplemented diet (0.5, 1 and 2% w/w) for 7 days showed enhanced expression of the downstream signaling mediator of lipopolysaccharide and β-1,3-glucan binding protein (LGBP) and immune related genes including p-NF-κB, IMD, IKKβ and IKKε, antimicrobial peptide PEN-4, proPO-I and II. Following immersion with Vibrio parahaemolyticus (V. parahaemolyticus) for 14 days, the shrimp given the SG supplemented diet (1 and 2% w/w) showed a decrease in bacterial colonies and bacterial toxin gene expression, compared to shrimp given a normal diet, and they reached 50% mortality at day 14. However, shrimp given the normal diet and challenged with the bacteria reached 100% mortality at day 6. SG-fed shrimp increased expression of immune genes related to LGBP signaling at day 1 after the bacterial immersion compared to control (no immersion), which later decreased to control levels. Shrimp on the normal diet also increased expression of immune related genes at day 1 after immersion which however decreased below control levels by day 3. Taken together, the results indicate the efficacy of the SG supplemented diet to enhance the immune activity in shrimp which could offer protection from V. parahaemolyticus infection.
A new approach to line and line segment clipping in homogeneous coordinates

The clipping operation is still the bottleneck of the graphics pipeline in spite of the latest developments in graphical hardware and a significant increase in performance. Algorithms for line and line segment clipping have been studied for a long time and many research papers have been published so far. This paper presents a new robust approach to line and line segment clipping using a rectangular window. A simple extension for the case of convex polygon clipping is presented as well. The presented approach does not require a division operation and uses homogeneous coordinates for input and output point representation. The proposed algorithms can take advantage of operations supported by vector–vector hardware. The main contribution of this paper is a new approach to intersection computations applied to line and line segment clipping. This approach leads to algorithms that are simpler, robust, and easy to implement.
Cloud-Computing in Banking Influential Factors, Benefits and Risks from a Decision Maker's Perspective

In 2008 Gartner Group listed "Cloud-Computing (CC)" in its Hype-Cycle (Gartner, 2008). Since these day s, enterprises in different industries discuss the utilization of clo ud-computing for their own benefit. The banking industry traditionally is heavily depen d t on information technology. Therefore, it can b e assumed that cloudcomputing could be of particular interesting for ba nks. This paper investigates the use of cloud-compu ting in German banks and the associated benefits and risks as senior man agement perceives them. Grounded in the TOE-Framewo rk ten expert interviews with senior decision makers German banks have been conducted to evaluate the decision crite ria pro and con cloud computing. Several factors influencing the cloud-computing dec ision have been detected, amongst them the technolo gy supporting infrastructure, government regulations and security and compliance requirements. Furthermore the finan cial benefits came up as the most important perceived benefit and governm nt regulation (esp. privacy/security regulations) are the most important risks perceived by senior management.
Chunking based malayalam paraphrase identification using unfolding recursive autoencoders

Paraphrase Detection is the task of examining if two sentences convey the same meaning or not. Here, in this paper, we have chosen a sentence embedding by unsupervised RAE vectors for capturing syntactic as well as semantic information. The RAEs learn features from the nodes of the parse tree and chunk information along with unsupervised word embedding. These learnt features are used for measuring phrase wise similarity between two sentences. Since sentences are of varying length, we use dynamic pooling for getting a fixed sized representation for sentences. This fixed sized sentence representation is the input to the classifier. The DPIL (Detecting Paraphrases in Indian Languages) dataset is used for paraphrase identification here. Initially, paraphrase identification is defined as a 2-class problem and then later, it is extended to a 3-class problem. Word2vec and Glove embedding techniques producing 100, 200 and 300 dimensional vectors are used to check variation in accuracies. The baseline system accuracy obtained using word2vec for 2-class problem is 77.67% and the same for 3-class problem is 66.07%. Glove gave an accuracy of 77.33% for 2-class and 65.42% for 3-classproblem. The results are also compared with the existing open source word embedding and our system using Word2vec embedding is found to outperform better. This is a first attempt using chunking based approach for identification of Malayalam paraphrases.
Analyzing Adaptive Cache Replacement Strategies

Adaptive Replacement Cache (Arc) and Clock with Adaptive Replacement (Car) are stateof-the-art “adaptive” cache replacement algorthms invented to improve on the shortcomings of classical cache replacement policies such as Lru and Clock. Both Arc and Car have been shown to outperform their classical and popular counterparts in practice. However, for over a decade, no theoretical proof of the competitiveness of Arc and Car is known. We prove that for a cache of size N , (a) Arc is 4N -competitive, and (b) Car is 21N -competitive, thus proving that no “pathological” worst-case request sequence exists that could make them perform much worse than Lru.
Movement skill assessment of typically developing preschool children: a review of seven movement skill assessment tools.

The importance of movement is often overlooked because it is such a natural part of human life. It is, however, crucial for a child's physical, cognitive and social development. In addition, experiences support learning and development of fundamental movement skills. The foundations of those skills are laid in early childhood and essential to encourage a physically active lifestyle. Fundamental movement skill performance can be examined with several assessment tools. The choice of a test will depend on the context in which the assessment is planned. This article compares seven assessment tools which are often referred to in European or international context. It discusses the tools' usefulness for the assessment of movement skill development in general population samples. After a brief description of each assessment tool the article focuses on contents, reliability, validity and normative data. A conclusion outline of strengths and weaknesses of all reviewed assessment tools focusing on their use in educational research settings is provided and stresses the importance of regular data collection of fundamental movement skill development among preschool children. Key pointsThis review discusses seven movement skill assessment tool's test content, reliability, validity and normative samples.The seven assessment tools all showed to be of great value. Strengths and weaknesses indicate that test choice will depend on specific purpose of test use.Further data collection should also include larger data samples of able bodied preschool children.Admitting PE specialists in assessment of fundamental movement skill performance among preschool children is recommended.The assessment tool's normative data samples would benefit from frequent movement skill performance follow-up of today's children.



MOT 4-6: Motoriktest fur vier- bis sechsjährige Kinder, M-ABC: Movement Assessment Battery for Children, PDMS: Peabody Development Scales, Koordinationtest für Kinder,  Test of Gross Motor Development, MMT: Maastrichtse Motoriektest, BOTMP: Bruininks-Oseretsky Test of Motor Proficiency. ICC: intraclass correlation coefficient, NR: not reported, GM: gross motor, LV: long version, SV: short version, LF: long form, SF: short form, STV: subtest version, SEMs: standard errors of measurement, TMQ: Total Motor Quotient, TMC: Total Motor Composite, CSSA: Comprehensive Scales of Student Abilities MSEL: Mullen Scales of Early learning: AGS Edition AUC: Areas under curve BC: Battery composite ROC: Receiver operating characteristic.
Effects of sleep deprivation on performance and EEG spectral analysis in young adults.

Nine totally sleep deprived (TSD) and nine control subjects were evaluated with a complete battery for attention and memory performance. Frontal and temporal EEGs (5 min, eyes closed) were also recorded before and after the night. TSD subjects exhibited three performance deficits: learning the Pursuit Rotor Task, implicit recall of paired words, and distractibility on the Brown-Peterson Test. Relative to evening recordings, control subjects showed decreased morning absolute powers in all electrodes for all frequencies except for Frontal delta; TSD subjects showed increased Frontal and Temporal theta and Frontal beta. These results show that motor procedural, implicit memory, and working memory are sensitive to one night of TSD, and that Frontal and Temporal theta spectral power seem to discriminate between a night with sleep from a night without.
Caudal duplication (monocephalus tripus dibrachius) in a kid goat

Dipygus is a congenital duplication in the caudal region of the body. According to the extension of the anomaly, duplicated cases are classified as monoceophalus tripus dibrachius, monocephalus tetrapus dibrachius and cephalothoracopagus. A newborn five-legged male kid was referred to the veterinary teaching hospital of Shahid Bahonar University of Kerman, Iran. In ventrodorsal radiography, normal pelvic symphysis was not observed between middle and left or right limbs. Necropsy findings included duplication of the bony pelvic girdle, alimentary tract from the jejunum downward, bladder and urethra. We hereby describe the first report of monocephalus tripus dibrachius in a kid goat.
CpG islands and the regulation of transcription.

Vertebrate CpG islands (CGIs) are short interspersed DNA sequences that deviate significantly from the average genomic pattern by being GC-rich, CpG-rich, and predominantly nonmethylated. Most, perhaps all, CGIs are sites of transcription initiation, including thousands that are remote from currently annotated promoters. Shared DNA sequence features adapt CGIs for promoter function by destabilizing nucleosomes and attracting proteins that create a transcriptionally permissive chromatin state. Silencing of CGI promoters is achieved through dense CpG methylation or polycomb recruitment, again using their distinctive DNA sequence composition. CGIs are therefore generically equipped to influence local chromatin structure and simplify regulation of gene activity.
Effect of Seed Roasting Conditions on the Antioxidant Activity of Defatted Sesame Meal Extracts

Antioxidant activities of defatted sesame meal extract increased as the roasting temperature of sesame seed increased, but the maximum antioxidant activity was achieved when the seeds were roasted at 200 °C for 60 min. Roasting sesame seeds at 200 °C for 60 min significantly increased the total phenolic content, radical scavenging activity (RSA), reducing powers, and antioxidant activity of sesame meal extract; and several low-molecularweight phenolic compounds such as 2-methoxyphenol, 4-methoxy-3-methylthio-phenol, 5-amino-3-oxo-4hexenoic acid, 3,4-methylenedioxyphenol (sesamol), 3-hydroxy benzoic acid, 4-hydroxy benzoic acid, vanillic acid, filicinic acid, and 3,4-dimethoxy phenol were newly formed in the sesame meal after roasting sesame seeds at 200 °C for 60 min. These results indicate that antioxidant activity of defatted sesame meal extracts was significantly affected by roasting temperature and time of sesame seeds.
More Than a Tick Box: Medical Checklist Development, Design, and Use.

Despite improving patient safety in some perioperative settings, some checklists are not living up to their potential and complaints of "checklist fatigue" and outright rejection of checklists are growing. Problems reported often concern human factors: poor design, inadequate introduction and training, duplication with other safety checks, poor integration with existing workflow, and cultural barriers. Each medical setting-such as an operating room or a critical care unit-and different clinical needs-such as a shift handover or critical event response-require a different checklist design. One size will not fit all, and checklists must be built around the structure of medical teams and the flow of their work in those settings. Useful guidance can be found in the literature; however, to date, no integrated and comprehensive framework exists to guide development and design of checklists to be effective and harmonious with the flow of medical and perioperative tasks. We propose such a framework organized around the 5 stages of the checklist life cycle: (1) conception, (2) determination of content and design, (3) testing and validation, (4) induction, training, and implementation, and (5) ongoing evaluation, revision, and possible retirement. We also illustrate one way in which the design of checklists can better match user needs in specific perioperative settings (in this case, the operating room during critical events). Medical checklists will only live up to their potential to improve the quality of patient care if their development is improved and their designs are tailored to the specific needs of the users and the environments in which they are used.
Toward Postgenomics Ophthalmology: A Proteomic Map of the Human Choroid-Retinal Pigment Epithelium Tissue.

Ophthalmology and visual health research have received relatively limited attention from the personalized medicine community, but this trend is rapidly changing. Postgenomics technologies such as proteomics are being utilized to establish a baseline biological variation map of the human eye and related tissues. In this context, the choroid is the vascular layer situated between the outer sclera and the inner retina. The choroidal circulation serves the photoreceptors and retinal pigment epithelium (RPE). The RPE is a layer of cuboidal epithelial cells adjacent to the neurosensory retina and maintains the outer limit of the blood-retina barrier. Abnormal changes in choroid-RPE layers have been associated with age-related macular degeneration. We report here the proteome of the healthy human choroid-RPE complex, using reverse phase liquid chromatography and mass spectrometry-based proteomics. A total of 5309 nonredundant proteins were identified. Functional analysis of the identified proteins further pointed to molecular targets related to protein metabolism, regulation of nucleic acid metabolism, transport, cell growth, and/or maintenance and immune response. The top canonical pathways in which the choroid proteins participated were integrin signaling, mitochondrial dysfunction, regulation of eIF4 and p70S6K signaling, and clathrin-mediated endocytosis signaling. This study illustrates the largest number of proteins identified in human choroid-RPE complex to date and might serve as a valuable resource for future investigations and biomarker discovery in support of postgenomics ophthalmology and precision medicine.
The Brief Obsessive–Compulsive Scale (BOCS): A self-report scale for OCD and obsessive–compulsive related disorders

The Brief Obsessive Compulsive Scale (BOCS), derived from the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) and the children's version (CY-BOCS), is a short self-report tool used to aid in the assessment of obsessive-compulsive symptoms and diagnosis of obsessive-compulsive disorder (OCD). It is widely used throughout child, adolescent and adult psychiatry settings in Sweden but has not been validated up to date.



The aim of the current study was to examine the psychometric properties of the BOCS amongst a psychiatric outpatient population.



The BOCS consists of a 15-item Symptom Checklist including three items (hoarding, dysmorphophobia and self-harm) related to the DSM-5 category "Obsessive-compulsive related disorders", accompanied by a single six-item Severity Scale for obsessions and compulsions combined. It encompasses the revisions made in the Y-BOCS-II severity scale by including obsessive-compulsive free intervals, extent of avoidance and excluding the resistance item. 402 adult psychiatric outpatients with OCD, attention-deficit/hyperactivity disorder, autism spectrum disorder and other psychiatric disorders completed the BOCS.



Principal component factor analysis produced five subscales titled "Symmetry", "Forbidden thoughts", "Contamination", "Magical thoughts" and "Dysmorphic thoughts". The OCD group scored higher than the other diagnostic groups in all subscales (P < 0.001). Sensitivities, specificities and internal consistency for both the Symptom Checklist and the Severity Scale emerged high (Symptom Checklist: sensitivity = 85%, specificities = 62-70% Cronbach's α = 0.81; Severity Scale: sensitivity = 72%, specificities = 75-84%, Cronbach's α = 0.94).



The BOCS has the ability to discriminate OCD from other non-OCD related psychiatric disorders. The current study provides strong support for the utility of the BOCS in the assessment of obsessive-compulsive symptoms in clinical psychiatry.
A Survey on Wi-Fi Based Contactless Activity Recognition

Providing accurate information about human's state, activity is one of the most important elements in Ubiquitous Computing. Various applications can be enabled if one's state, activity can be recognized. Due to the low deployment cost, non-intrusive sensing nature, Wi-Fi based activity recognition has become a promising, emerging research area. In this paper, we survey the state-of-the-art of the area from four aspects ranging from historical overview, theories, models, key techniques to applications. In addition to the summary about the principles, achievements of existing work, we also highlight some open issues, research directions in this emerging area.
MMALFM: Explainable Recommendation by Leveraging Reviews and Images

Personalized rating prediction is an important research problem in recommender systems. Although the latent factor model (e.g., matrix factorization) achieves good accuracy in rating prediction, it suffers from many problems including cold-start, non-transparency, and suboptimal results for individual user-item pairs. In this article, we exploit textual reviews and item images together with ratings to tackle these limitations. Specifically, we first apply a proposed multi-modal aspect-aware topic model (MATM) on text reviews and item images to model users’ preferences and items’ features from different aspects, and also estimate the aspect importance of a user toward an item. Then, the aspect importance is integrated into a novel aspect-aware latent factor model (ALFM), which learns user’s and item’s latent factors based on ratings. In particular, ALFM introduces a weight matrix to associate those latent factors with the same set of aspects in MATM, such that the latent factors could be used to estimate aspect ratings. Finally, the overall rating is computed via a linear combination of the aspect ratings, which are weighted by the corresponding aspect importance. To this end, our model could alleviate the data sparsity problem and gain good interpretability for recommendation. Besides, every aspect rating is weighted by its aspect importance, which is dependent on the targeted user’s preferences and the targeted item’s features. Therefore, it is expected that the proposed method can model a user’s preferences on an item more accurately for each user-item pair. Comprehensive experimental studies have been conducted on the Yelp 2017 Challenge dataset and Amazon product datasets. Results show that (1) our method achieves significant improvement compared to strong baseline methods, especially for users with only few ratings; (2) item visual features can improve the prediction performance—the effects of item image features on improving the prediction results depend on the importance of the visual features for the items; and (3) our model can explicitly interpret the predicted results in great detail.
Adepts: Advanced peptide de novo Sequencing with a Pair of Tandem Mass Spectra

De novo sequencing is an important task in proteomics to identify novel peptide sequences. Traditionally, only one MS/MS spectrum is used for the sequencing of a peptide; however, the use of multiple spectra of the same peptide with different types of fragmentation has the potential to significantly increase the accuracy and practicality of de novo sequencing. Research into the use of multiple spectra is in a nascent stage. We propose a general framework to combine the two different types of MS/MS data. Experiments demonstrate that our method significantly improves the de novo sequencing of existing software.
Personalized Spell Checking using Neural Networks

Spell checkers are one of the most widely recognized and heavily employed features of word processing applications in existence today. This remains true despite the many problems inherent in the spell checking methods employed by all modern spell checkers. In this paper we present a proof-ofconcept spell checking system that is able to intrinsically avoid many of these problems. In particular, it is the actual corrections performed by the typist that provides the basis for error detection. These corrections are used to train a feed-forward neural network so that if the same error is remade, the network can flag the offending word as a possible error. Since these corrections are the observations of a single typist’s behavior, a spell checker employing this system is essentially specific to the typist that made the corrections. A discussion of the benefits and deficits of the system is presented with the conclusion that the system is most effective as a supplement to current spell checking methods.
Design FOPID Control of an Automatic Voltage Regulator ( AVR ) System Imperialist Competitive Algorithm

This paper addresses a robust method for optimal Fractional order PID (FOPID) control of automatic Voltage Regulation (AVR) system to damp terminal voltage oscillation following disturbances in power systems. The optimization is carried out by the Imperialist Competitive algorithm Optimization (ICA) to improve their situation. The optimal tuning problem of the FOPID gains to control of AVR system against parametric uncertainties is formulated as an optimization problem according to time domain based objective function. It is carried out under multiple operation conditions to achieve the desired level of terminal voltage regulation. The results analysis reveals that the ICA based FOPID type AVR control system is effective and provides good terminal voltage oscillations damping ability.