nils-herrmann/clean_scirepeval huggingface dataset:
LABOUR TURNOVER : CAUSES , CONSEQUENCES AND PREVENTION Oladele

Employees’ turnover poses a recurrent challenge to most business organization globally. There is virtually no organization that is immune to employees’ turnover; be it small size or big size organizations, they are all exposed to employees’ turnover. Although, it may not be feasible for any organization to totally eliminate employees’ turnover due to several reasons, nevertheless it could be reduced to the barest minimum. Many of the prior studies only focused on the causes of employees’ turnover without considering the remedies. In bridging this gap, the current study examines the causes, costs consequences and prevention of employees’ turnover. The study provides theoretical foundation underpinning employees’ turnover. The causes of employees’ turnover are also provided among which we have poor work environment and poor remuneration packages. The study further indicates that employees’ turnover has cost implications to the organization; such costs include but not limited to vacancy advertisement, interview, recruitment and training of new hire, loss of productivity, and cost of inefficiency of the new staff. Strategies that can help in addressing employees’ turnover include favourable working environment, and improved remuneration packages, amongst others.
SABER: Window-Based Hybrid Stream Processing for Heterogeneous Architectures

Modern servers have become heterogeneous, often combining multi-core CPUs with many-core GPGPUs. Such heterogeneous architectures have the potential to improve the performance of data-intensive stream processing applications, but they are not supported by current relational stream processing engines. For an engine to exploit a heterogeneous architecture, it must execute streaming SQL queries with sufficient data-parallelism to fully utilise all available heterogeneous processors, and decide how to use each in the most effective way. It must do this while respecting the semantics of streaming SQL queries, in particular with regard to window handling.
 We describe Saber, a hybrid high-performance relational stream processing engine for CPUs and GPGPUs. Saber executes window-based streaming SQL queries in a data-parallel fashion using all available CPU and GPGPU cores. Instead of statically assigning query operators to heterogeneous processors, Saber employs a new adaptive heterogeneous lookahead scheduling strategy, which increases the share of queries executing on the processor that yields the highest performance. To hide data movement costs, Saber pipelines the transfer of stream data between CPU and GPGPU memory. Our experimental comparison against state-of-the-art engines shows that Saber increases processing throughput while maintaining low latency for a wide range of streaming SQL queries with both small and large window sizes.
Understanding Cancer Mutations by Genome Editing

Ali, M. A. 2014. Understanding Cancer Mutations by Genome Editing. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1054. 37  Acta Universitatis Upsaliensis. ISBN 978-91-554-9106-2. Mutational analyses of cancer genomes have identified novel candidate cancer genes with hitherto unknown function in cancer. To enable phenotyping of mutations in such genes, we have developed a scalable technology for gene knock-in and knock-out in human somatic cells based on recombination-mediated construct generation and a computational tool to design gene targeting constructs. Using this technology, we have generated somatic cell knock-outs of the putative cancer genes ZBED6 and DIP2C in human colorectal cancer cells. In ZBED6 cells complete loss of functional ZBED6 was validated and loss of ZBED6 induced the expression of IGF2. Whole transcriptome and ChIP-seq analyses revealed relative enrichment of ZBED6 binding sites at upregulated genes as compared to downregulated genes. The functional annotation of differentially expressed genes revealed enrichment of genes related to cell cycle and cell proliferation and the transcriptional modulator ZBED6 affected the cell growth and cell cycle of human colorectal cancer cells. In DIP2Ccells, transcriptome sequencing revealed 780 differentially expressed genes as compared to their parental cells including the tumour suppressor gene CDKN2A. The DIP2C regulated genes belonged to several cancer related processes such as angiogenesis, cell structure and motility. The DIP2Ccells were enlarged and grew slower than their parental cells. To be able to directly compare the phenotypes of mutant KRAS and BRAF in colorectal cancers, we have introduced a KRAS allele in RKO BRAF cells. The expression of the mutant KRAS allele was confirmed and anchorage independent growth was restored in KRAS cells. The differentially expressed genes both in BRAF and KRAS mutant cells included ERBB, TGFB and histone modification pathways. Together, the isogenic model systems presented here can provide insights to known and novel cancer pathways and can be used for drug discovery.
On the Complexity of the Extended String-to-String Correction Problem

The Extended String-to-String Correction  is defined as the problem of determining, for given strings A and B over alphabet V, a minimum-cost sequence S of edit operations such that S(A) &equil; B. The sequence S may make use of the operations: <underline>Change, Insert, Delete</underline> and <underline>Swaps</underline>, each of constant cost W<subscrpt>C</subscrpt>, W<subscrpt>I</subscrpt>, W<subscrpt>D</subscrpt>, and W<subscrpt>S</subscrpt> respectively. Swap permits any pair of adjacent characters to be interchanged.
 The principal results of this paper are:
 (1) a brief presentation of an algorithm (the CELLAR algorithm) which solves ESSCP in time Ø(¦A¦* ¦B¦* ¦V¦<supscrpt>s</supscrpt>*s), where s &equil; min(4W<subscrpt>C</subscrpt>, W<subscrpt>I</subscrpt>+W<subscrpt>D</subscrpt>)/W<subscrpt>S</subscrpt> + 1;
 (2) presentation of polynomial time algorithms for the cases (a) W<subscrpt>S</subscrpt> &equil; 0, (b) W<subscrpt>S</subscrpt> > 0, W<subscrpt>C</subscrpt>&equil; W<subscrpt>I</subscrpt>&equil; W<subscrpt>D</subscrpt>&equil; @@@@;
 (3) proof that ESSCP, with W<subscrpt>I</subscrpt> < W<subscrpt>C</subscrpt> &equil; W<subscrpt>D</subscrpt> &equil; @@@@, 0 < W<subscrpt>S</subscrpt> < @@@@, suitably encoded, is NP-complete. (The remaining case, W<subscrpt>S</subscrpt>&equil; @@@@, reduces ESSCP to the string-to-string correction problem of , where an Ø( ¦A¦* ¦B¦) algorithm is given.) Thus, “almost all” ESSCP's can be solved in deterministic polynomial time, but the general problem is NP-complete.
Stability Analysis and Stabilization Methods of DC Microgrid With Multiple Parallel-Connected DC–DC Converters Loaded by CPLs

Constant power loads may yield instability due to the well-known negative impedance characteristic. This paper analyzes the factors that cause instability of a dc microgrid with multiple dc–dc converters. Two stabilization methods are presented for two operation modes: 1) constant voltage source mode; and 2) droop mode, and sufficient conditions for the stability of the dc microgrid are obtained by identifying the eigenvalues of the Jacobian matrix. The key is to transform the eigenvalue problem to a quadratic eigenvalue problem. When applying the methods in practical engineering, the salient feature is that the stability parameter domains can be estimated by the available constraints, such as the values of capacities, inductances, maximum load power, and distances of the cables. Compared with some classical methods, the proposed methods have wider stability region. The simulation results based on MATLAB/simulink platform verify the feasibility of the methods.
Motion doodles: an interface for sketching character motion

In this paper we present a novel system for sketching the motion of a character. The process begins by sketching a character to be animated. An animated motion is then created for the character by drawing a continuous sequence of lines, arcs, and loops. These are parsed and mapped to a parameterized set of output motions that further reflect the location and timing of the input sketch. The current system supports a repertoire of 18 different types of motions in 2D and a subset of these in 3D. The system is unique in its use of a cursive motion specification, its ability to allow for fast experimentation, and its ease of use for non-experts.
A tutorial on the operational validation of simulation models

This tutorial discusses in depth the operational validation of simulation models after a brief overview of verification and validation of simulation models. The discussion of operational validation first covers the different approaches used for observable and non-observable systems. Next, various types of graphical displays of model output behavior are presented; this is followed by how these displays can be used in determining model validity by the model developers, subject matter experts, and others when no system data are available; and how these displays can be used as reference distributions for operational validation when system data are available. Lastly, the use of the “interval hypothesis test” is covered for operational validation when sufficient system data are available. Various examples are presented.
Factored Neural Machine Translation Architectures

In this paper we investigate the potential of the neural machine translation (NMT) when taking into consideration the linguistic aspect of target language. From this standpoint, the NMT approach with attention mechanism  is extended in order to produce several linguistically derived outputs. We train our model to simultaneously output the lemma and its corresponding factors (e.g. part-of-speech, gender, number). The word level translation is built with a mapping function using a priori linguistic information. Compared to the standard NMT system, factored architecture increases significantly the vocabulary coverage while decreasing the number of unknown words. With its richer architecture, the Factored NMT approach allows us to implement several training setup that will be discussed in detail along this paper. On the IWSLT’15 English-to-French task, FNMT model outperforms NMT model in terms of BLEU score. A qualitative analysis of the output on a set of test sentences shows the effectiveness of the FNMT model.
Formalization in Practice

Formalizations are used in systems development to support the description of artifacts and to shape and regulate developer behavior. The limits to applying formalizations in these two ways are discussed based on examples from systems development practice. It is argued that formalizations, for example in the form of methods, are valuable in some situations, but inappropriate in others. The alternative to uncritically using formalizations is that systems developers reflect on the situations in which they find themselves and manage based on a combination of formal and informal approaches.
Weakly Supervised Coupled Networks for Visual Sentiment Analysis

Automatic assessment of sentiment from visual content has gained considerable attention with the increasing tendency of expressing opinions on-line. In this paper, we solve the problem of visual sentiment analysis using the high-level abstraction in the recognition process. Existing methods based on convolutional neural networks learn sentiment representations from the holistic image appearance. However, different image regions can have a different influence on the intended expression. This paper presents a weakly supervised coupled convolutional network with two branches to leverage the localized information. The first branch detects a sentiment specific soft map by training a fully convolutional network with the cross spatial pooling strategy, which only requires image-level labels, thereby significantly reducing the annotation burden. The second branch utilizes both the holistic and localized information by coupling the sentiment map with deep features for robust classification. We integrate the sentiment detection and classification branches into a unified deep framework and optimize the network in an end-to-end manner. Extensive experiments on six benchmark datasets demonstrate that the proposed method performs favorably against the state-of-the-art methods for visual sentiment analysis.
Complete long-term recovery of beta-cell function in autoimmune type 1 diabetes after insulin treatment.

A 13-year-old Caucasian boy (BMI 26.4 kg/m) presented with 3 weeks’ history of polyuria, polydipsia, and weight loss. His serum glucose (26.8 mmol/l), HbA1c (9.4%, normal 3.2–5.5) and fructosamine (628 mol/l, normal 205–285) levels were highly elevated , and urinalysis showed glucosuria ( ) and ketonuria ( ) . He was HLA-DRB1* 0101,*0901, DRB4*01, DQA1*0101,03, and DQB1*0303,0501. Plasma Cpeptide, determined at a blood glucose of 17.0 mmol/l, was low (0.18 nmol/l). His previous history was unremarkable, and he did not take any medication. The patient received standard treatment with insulin, fluid, and electrolyte replacement and diabetes education. After an uneventful clinical course he was discharged on multiple-injection insulin therapy (total 0.9 units kg 1 day ) after 10 days. Subsequently, insulin doses were gradually reduced to 0.3 units kg 1 day , and insulin treatment was completely stopped after 11 months. Without further treatment, HbA1c and fasting glucose levels remained normal throughout the entire follow-up of currently 4.5 years. During oral glucose tolerance testing performed 48 months after diagnosis, he had normal fasting and 2-h levels of glucose (3.7 and 5.6 mmol/l, respectively), insulin (60.5 and 217.9 pmol/l, respectively), and C-peptide (0.36 and 0.99 nmol/l, respectively). His insulin sensitivity, as determined by insulin sensitivity index (composite) and homeostasis model assessment, was normal, and BMI remained unchanged. Serum autoantibodies to GAD65, insulin autoantibody-2, insulin, and islet cell antibodies were initially positive but showed a progressive decline or loss during follow-up.  T-cell antigen recognition and cytokine profiles were studied using a library of 21 preproinsulin (PPI) peptides (2). In the patient’s peripheral blood mononuclear cells (PBMCs), a high cumulative interleukin (IL)-10) secretion (201 pg/ml) was observed in response to PPI peptides, with predominant recognition of PPI44–60 and PPI49–65, while interferon (IFN)secretion was undetectable. In contrast, in PBMCs from a cohort of 12 type 1 diabetic patients without long-term remission (2), there was a dominant IFNresponse but low IL-10 secretion to PPI. Analysis of CD4 T–helper cell subsets revealed that IL-10 secretion was mostly attributable to the patient’s naı̈ve/recently activated CD45RA cells, while a strong IFNresponse was observed in CD45RA cells. CD45RA T-cells have been associated with regulatory T-cell function in diabetes, potentially capable of suppressing
The iNaturalist Species Classification and Detection Dataset

Existing image classification datasets used in computer vision tend to have a uniform distribution of images across object categories. In contrast, the natural world is heavily imbalanced, as some species are more abundant and easier to photograph than others. To encourage further progress in challenging real world conditions we present the iNaturalist species classification and detection dataset, consisting of 859,000 images from over 5,000 different species of plants and animals. It features visually similar species, captured in a wide variety of situations, from all over the world. Images were collected with different camera types, have varying image quality, feature a large class imbalance, and have been verified by multiple citizen scientists. We discuss the collection of the dataset and present extensive baseline experiments using state-of-the-art computer vision classification and detection models. Results show that current non-ensemble based methods achieve only 67% top one classification accuracy, illustrating the difficulty of the dataset. Specifically, we observe poor results for classes with small numbers of training examples suggesting more attention is needed in low-shot learning.
An NFC transceiver with RF-powered RFID transponder mode

A single chip NFC transceiver supporting not only NFC active and passive mode but also 13.56 MHz RFID reader and tag mode was designed and fabricated. The proposed NFC transceiver can operate as a RFID tag even without external power supply thanks to a dual antenna structure for initiator and target. The area increment due to additional target antenna is negligible because the target antenna is constructed by using a shielding layer of initiator antenna.
The Heterotaxy gene, GALNT11, glycosylates Notch to orchestrate cilia type and laterality

Heterotaxy is a disorder of left–right body patterning, or laterality, that is associated with major congenital heart disease. The aetiology and mechanisms underlying most cases of human heterotaxy are poorly understood. In vertebrates, laterality is initiated at the embryonic left–right organizer, where motile cilia generate leftward flow that is detected by immotile sensory cilia, which transduce flow into downstream asymmetric signals. The mechanism that specifies these two cilia types remains unknown. Here we show that the N-acetylgalactosamine-type O-glycosylation enzyme GALNT11 is crucial to such determination. We previously identified GALNT11 as a candidate disease gene in a patient with heterotaxy, and now demonstrate, in Xenopus tropicalis, that galnt11 activates Notch signalling. GALNT11 O-glycosylates human NOTCH1 peptides in vitro, thereby supporting a mechanism of Notch activation either by increasing ADAM17-mediated ectodomain shedding of the Notch receptor or by modification of specific EGF repeats. We further developed a quantitative live imaging technique for Xenopus left–right organizer cilia and show that Galnt11-mediated Notch1 signalling modulates the spatial distribution and ratio of motile and immotile cilia at the left–right organizer. galnt11 or notch1 depletion increases the ratio of motile cilia at the expense of immotile cilia and produces a laterality defect reminiscent of loss of the ciliary sensor Pkd2. By contrast, Notch overexpression decreases this ratio, mimicking the ciliopathy primary ciliary dyskinesia. Together our data demonstrate that Galnt11 modifies Notch, establishing an essential balance between motile and immotile cilia at the left–right organizer to determine laterality, and reveal a novel mechanism for human heterotaxy.
The medical evaluation of the sexually abused child: lessons from a decade of research.

The problem of child sexual abuse (CSA) has engendered lively interest among physicians and other health care providers for more than 20 years. The number of cases of sexual abuse known to child protection service agencies in the United States rose sharply from 1977 to 1988, then leveled off and declined between 1988 and 1996  Several investigators have provided comprehensive reviews of CSA and of the role of the physician in diagnosis and management.2–4 A partial list of epidemiologic, psychological, and legal topics in the area of CSA that have been investigated and reviewed during the past decade includes the effectiveness and accuracy of various techniques for obtaining histories of sexual abuse (repeated interviews, standardized questionnaires, drawings, anatomically correct dolls)5–7; the sexual abuse of boys8,9; the impact of sexual abuse on children’s subsequent psychosocial wellbeing10,11; the relationship of CSA to sexual aggression in children and appropriate treatment for offending children12,13; the criminal prosecution of CSA cases14; and the effectiveness of CSA prevention programs.2 In this article, we will highlight research published during the past decade that deals particularly with topics in the medical evaluation of sexually abused children and that has advanced our understanding of those topics. We have divided our discussion into three sections: the conduct of the physical examination, the interpretation of physical examination findings, and selected sexually transmitted infections in children. CONDUCTING THE PHYSICAL EXAMINATION
A Simple Deterministic Model for the Spread of Hand, Foot and Mouth Disease (HFMD) in Sarawak

Hand, foot and mouth disease (HFMD) is considered a common disease among children. However, HFMD recent outbreaks in Sarawak had caused many death particularly children below the age of ten. In this study we are building a simple deterministic model based on the SIR (Susceptible-Infected-Recovered) model to predict the number of infected and the duration of an outbreak when it occurs. Our findings show that the disease spread quite rapidly and the parameter that may be able to control that would be the number of susceptible persons. We hope the model will allow public health personnel to plan intervention in an effective manner in order to reduce the effect of the disease in the coming outbreak.
A Fast, Efficient Domain Adaptation Technique for Cross-Domain Electroencephalography(EEG)-Based Emotion Recognition

Electroencephalography (EEG)-based emotion recognition is an important element in psychiatric health diagnosis for patients. However, the underlying EEG sensor signals are always non-stationary if they are sampled from different experimental sessions or subjects. This results in the deterioration of the classification performance. Domain adaptation methods offer an effective way to reduce the discrepancy of marginal distribution. However, for EEG sensor signals, both marginal and conditional distributions may be mismatched. In addition, the existing domain adaptation strategies always require a high level of additional computation. To address this problem, a novel strategy named adaptive subspace feature matching (ASFM) is proposed in this paper in order to integrate both the marginal and conditional distributions within a unified framework (without any labeled samples from target subjects). Specifically, we develop a linear transformation function which matches the marginal distributions of the source and target subspaces without a regularization term. This significantly decreases the time complexity of our domain adaptation procedure. As a result, both marginal and conditional distribution discrepancies between the source domain and unlabeled target domain can be reduced, and logistic regression (LR) can be applied to the new source domain in order to train a classifier for use in the target domain, since the aligned source domain follows a distribution which is similar to that of the target domain. We compare our ASFM method with six typical approaches using a public EEG dataset with three affective states: positive, neutral, and negative. Both offline and online evaluations were performed. The subject-to-subject offline experimental results demonstrate that our component achieves a mean accuracy and standard deviation of 80.46% and 6.84%, respectively, as compared with a state-of-the-art method, the subspace alignment auto-encoder (SAAE), which achieves values of 77.88% and 7.33% on average, respectively. For the online analysis, the average classification accuracy and standard deviation of ASFM in the subject-to-subject evaluation for all the 15 subjects in a dataset was 75.11% and 7.65%, respectively, gaining a significant performance improvement compared to the best baseline LR which achieves 56.38% and 7.48%, respectively. The experimental results confirm the effectiveness of the proposed method relative to state-of-the-art methods. Moreover, computational efficiency of the proposed ASFM method is much better than standard domain adaptation; if the numbers of training samples and test samples are controlled within certain range, it is suitable for real-time classification. It can be concluded that ASFM is a useful and effective tool for decreasing domain discrepancy and reducing performance degradation across subjects and sessions in the field of EEG-based emotion recognition.