nils-herrmann/clean_scirepeval huggingface dataset:
Inkjet-Printed Small-Molecule Organic Light-Emitting Diodes: Halogen-Free Inks, Printing Optimization, and Large-Area Patterning.

Manufacturing small-molecule organic light-emitting diodes (OLEDs) via inkjet printing is rather attractive for realizing high-efficiency and long-life-span devices, yet it is challenging. In this paper, we present our efforts on systematical investigation and optimization of the ink properties and the printing process to enable facile inkjet printing of conjugated light-emitting small molecules. Various factors on influencing the inkjet-printed film quality during the droplet generation, the ink spreading on the substrates, and its solidification processes have been systematically investigated and optimized. Consequently, halogen-free inks have been developed and large-area patterning inkjet printing on flexible substrates with efficient blue emission has been successfully demonstrated. Moreover, OLEDs manufactured by inkjet printing the light-emitting small molecules manifested superior performance as compared with their corresponding spin-cast counterparts.
Is Multipath TCP (MPTCP) Beneficial for Video Streaming over DASH?

HTTP-based adaptive protocols dominate today's video streaming over the Internet, and operate using multiple quality levels that video players request one segment at a time. Despite their popularity, studies have shown that performance of video streams still suffers from stalls, quality switches and startup delay. In wireless networks, it is well-known that high variability in network bandwidth affects video streaming. MultiPath TCP (MPTCP) is an emerging paradigm that could offer significant benefits to video streaming by combining bandwidth on multiple network interfaces, in particular for mobile devices that typically support both WiFi and cellular networks. In this paper, we explore whether MPTCP always benefits mobile video streaming. Our experimental study on video streaming using two wireless interfaces yields mixed results. While beneficial to user experience under ample and stable bandwidth, MPTCP may not offer any advantage under some network conditions. We find that when additional bandwidth on the secondary path is not sufficient to sustain an upgrade in video quality, it is generally better not to use MPTCP. We also identify that MPTCP can harm user experience when an unstable secondary path is added to the stable primary path.
Two-Stage Convolutional Neural Network for Breast Cancer Histology Image Classification

This paper explores the problem of breast tissue classification of microscopy images. Based on the predominant cancer type the goal is to classify images into four categories of normal, benign, in situ carcinoma, and invasive carcinoma. Given a suitable training dataset, we utilize deep learning techniques to address the classification problem. Due to the large size of each image in the training dataset, we propose a patch-based technique which consists of two consecutive convolutional neural networks. The first “patch-wise” network acts as an auto-encoder that extracts the most salient features of image patches while the second “image-wise” network performs classification of the whole image. The first network is pre-trained and aimed at extracting local information while the second network obtains global information of an input image. We trained the networks using the ICIAR 2018 grand challenge on BreAst Cancer Histology (BACH) dataset. The proposed method yields 95% accuracy on the validation set compared to previously reported 77% accuracy rates in the literature. Our code is publicly available at https://github.com/ImagingLab/ICIAR2018.
Effects of 12-week core stabilization exercise on the Cobb angle and lumbar muscle strength of adolescents with idiopathic scoliosis

To identify the effects of core stabilization exercise on the Cobb angle and lumbar muscle strength of adolescent patients with idiopathic scoliosis. Subjects in the present study consisted of primary school students who were confirmed to have scoliosis on radiologic examination performed during their visit to the National Fitness Center in Seoul, Korea. Depending on whether they participated in a 12-week core stabilization exercise program, subjects were divided into the exercise (n=14, age 12.71±0.72 years) or control (n=15, age 12.80±0.86 years) group. The exercise group participated in three sessions of core stabilization exercise per week for 12 weeks. The Cobb angle, flexibility, and lumbar muscle strength tests were performed before and after core stabilization exercise. Repeated-measure two-way analysis of variance was performed to compare the treatment effects between the exercise and control groups. There was no significant difference in thoracic Cobb angle between the groups. The exercise group had a significant decrease in the lumbar Cobb angle after exercise compared to before exercise (P<0.001). The exercise group also had a significant increase in lumbar flexor and extensor muscles strength after exercise compared to before exercise (P<0.01 and P<0.001, respectively). Core stabilization exercise can be an effective therapeutic exercise to decrease the Cobb angle and improve lumbar muscle strength in adolescents with idiopathic scoliosis.
Complement-Related Regulates Autophagy in Neighboring Cells

Autophagy degrades cytoplasmic components and is important for development and human health. Although autophagy is known to be influenced by systemic intercellular signals, the proteins that control autophagy are largely thought to function within individual cells. Here, we report that Drosophila macroglobulin complement-related (Mcr), a complement ortholog, plays an essential role during developmental cell death and inflammation by influencing autophagy in neighboring cells. This function of Mcr involves the immune receptor Draper, suggesting a relationship between autophagy and the control of inflammation. Interestingly, Mcr function in epithelial cells is required for macrophage autophagy and migration to epithelial wounds, a Draper-dependent process. This study reveals, unexpectedly, that complement-related from one cell regulates autophagy in neighboring cells via an ancient immune signaling program.
Online convolutional dictionary learning for multimodal imaging

Computational imaging methods that can exploit multiple modalities have the potential to enhance the capabilities of traditional sensing systems. In this paper, we propose a new method that reconstructs multimodal images from their linear measurements by exploiting redundancies across different modalities. Our method combines a convolutional group-sparse representation of images with total variation (TV) regularization for high-quality multimodal imaging. We develop an online algorithm that enables the unsupervised learning of convolutional dictionaries on large-scale datasets that are typical in such applications. We illustrate the benefit of our approach in the context of joint intensity-depth imaging.
Deep Affect Prediction in-the-Wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond

Automatic understanding of human affect using visual signals is of great importance in everyday human–machine interactions. Appraising human emotional states, behaviors and reactions displayed in real-world settings, can be accomplished using latent continuous dimensions (e.g., the circumplex model of affect). Valence (i.e., how positive or negative is an emotion) and arousal (i.e., power of the activation of the emotion) constitute popular and effective representations for affect. Nevertheless, the majority of collected datasets this far, although containing naturalistic emotional states, have been captured in highly controlled recording conditions. In this paper, we introduce the Aff-Wild benchmark for training and evaluating affect recognition algorithms. We also report on the results of the First Affect-in-the-wild Challenge (Aff-Wild Challenge) that was recently organized in conjunction with CVPR 2017 on the Aff-Wild database, and was the first ever challenge on the estimation of valence and arousal in-the-wild. Furthermore, we design and extensively train an end-to-end deep neural architecture which performs prediction of continuous emotion dimensions based on visual cues. The proposed deep learning architecture, AffWildNet, includes convolutional and recurrent neural network layers, exploiting the invariant properties of convolutional features, while also modeling temporal dynamics that arise in human behavior via the recurrent layers. The AffWildNet produced state-of-the-art results on the Aff-Wild Challenge. We then exploit the AffWild database for learning features, which can be used as priors for achieving best performances both for dimensional, as well as categorical emotion recognition, using the RECOLA, AFEW-VA and EmotiW 2017 datasets, compared to all other methods designed for the same goal. The database and emotion recognition models are available at http://ibug.doc.ic.ac.uk/resources/first-affect-wild-challenge .
Cultures of Agility – Agile Software Development in Practice

Agile Software Development (ASD) has gained much attention as an approach that provides values and principles for dealing with turbulent environments and change as they are now common for many systems development projects. Literature stresses the importance of organizational culture for agile development, but only little empirical research about their relationship has been conducted. On this background we carried out a cultural analysis in 3 organizations which perform systems and software development according to agile principles. We found that agile development thrives in different organizational cultures as long as the 4 core values are present to a significant extent. This is possible because agile methods bear to compromise even with central elements of the agile approach; this is the essence of agility.
A collaboration platform for data sharing among heterogeneous relief organizations for disaster management

Recently, we are witnessing the progressive increase in the occurrence of largescale disasters, characterized by an overwhelming scale and number of causalities. After 72 hours from the disaster occurrence, the damaged area is interested by assessment, reconstruction and recovery actions from several heterogeneous organizations, which need to collaborate and being orchestrated by a centralized authority. This situation requires an effective data sharing by means of a proper middleware platform able to let such organizations to interoperate despite of their differences. Although international organizations have defined collaboration frameworks at the higher level, there is no ICT supporting platform at operational level able to realize the data sharing demanded by such collaborative frameworks. This work proposes a layered architecture and a preliminary implementation of such a middleware for messaging, data and knowledge management. We also illustrate a demonstration of the usability of such an implementation, so as to show the achievable interoperability.
Genetic variations of live attenuated plague vaccine strains (Yersinia pestis EV76 lineage) during laboratory passages in different countries.

Plague, one of the most devastating infectious diseases in human history, is caused by the bacterial species Yersinia pestis. A live attenuated Y. pestis strain (EV76) has been widely used as a plague vaccine in various countries around the world. Here we compared the whole genome sequence of an EV76 strain used in China (EV76-CN) with the genomes of Y. pestis wild isolates to identify genetic variations specific to the EV76 lineage. We identified 6 SNPs and 6 Indels (insertions and deletions) differentiating EV76-CN from its counterparts. Then, we screened these polymorphic sites in 28 other strains of EV76 lineage that were stored in different countries. Based on the profiles of SNPs and Indels, we reconstructed the parsimonious dissemination history of EV76 lineage. This analysis revealed that there have been at least three independent imports of EV76 strains into China. Additionally, we observed that the pyrE gene is a mutation hotspot in EV76 lineages. The fine comparison results based on whole genome sequence in this study provide better understanding of the effects of laboratory passages on the accumulation of genetic polymorphisms in plague vaccine strains. These variations identified here will also be helpful in discriminating different EV76 derivatives.
Episakral lipoma: Bel ağrisinin tedavi edilebilir bir nedeni Episacral lipoma: a treatable cause of low back pain

Episacral lipoma is a small, tender subcutaneous nodule primarily occurring over the posterior iliac crest. Episacral lipoma is a significant and treatable cause of acute and chronic low back pain. Episacral lipoma occurs as a result of tears in the thoracodorsal fascia and subsequent herniation of a portion of the underlying dorsal fat pad through the tear. This clinical entity is common, and recognition is simple. The presence of a painful nodule with disappearance of pain after injection with anaesthetic, is diagnostic. Medication and physical therapy may not be effective. Local injection of the nodule with a solution of anaesthetic and steroid is effective in treating the episacral lipoma. Here we describe 2 patients with painful nodules over the posterior iliac crest. One patient complained of severe lower back pain radiating to the left lower extremity and this patient subsequently underwent disc operation. The other patient had been treated for greater trochanteric pain syndrome. In both patients, symptoms appeared to be relieved by local injection of anaesthetic and steroid. Episacral lipoma should be considered during diagnostic workup and in differential diagnosis of acute and chronic low back pain.
Uniqueness in the forensic identification sciences--fact or fiction?

Fingerprint analysts, firearms and toolmark examiners, and forensic odontologists often rely on the uniqueness proposition in order to support their theory of identification. However, much of the literature claiming to have proven uniqueness in the forensic identification sciences is methodologically weak, and suffers flaws that negate any such conclusion being drawn. The finding of uniqueness in any study appears to be an overstatement of the significance of its results, and in several instances, this claim is made despite contrary data being presented. The mathematical and philosophical viewpoint regarding this topic is that obtaining definitive proof of uniqueness is considered impossible by modern scientific methods. More importantly, there appears to be no logical reason to pursue such research, as commentators have established that uniqueness is not the essential requirement for forming forensic conclusions. The courts have also accepted this in several recent cases in the United States, and have dismissed the concept of uniqueness as irrelevant to the more fundamental question of the reliability of the forensic analysis.
TRPV4-associated skeletal dysplasias.

Dominant mutations in the TRPV4 gene result in a bone dysplasia family and form a continuous phenotypic spectrum that includes, in decreasing severity, lethal, and nonlethal metatropic dysplasia (MD), spondylometaphyseal dysplasia Kozlowski type (SMDK), and autosomal dominant brachyolmia. Several rare variant phenotypes that have some overlap but deviate in some ways from the general pattern have also been described. The known variant phenotypes are spondyloepiphyseal dysplasia Maroteaux type (Pseudo-Morquio type 2), parastremmatic dysplasia, and familial digital arthropathy with brachydactyly. Interestingly, different TRPV4 mutations have been associated with dominantly inherited neurologic disorders such as congenital spinal muscular atrophy and hereditary motor and sensory neuropathy. Finally, a small number of patients have been identified in whom a TRPV4 mutation results in a phenotype combining skeletal dysplasia with peripheral neuropathy. The TRPV4 gene encodes a regulated calcium channel implicated in multiple and diverse cellular processes. Over 50 different TRPV4 mutations have been reported, with two codons appearing to be mutational hot spots: P799 in exon 15, mostly associated with MD, and R594 in exon 11, associated with SMDK. While most pathogenic mutations tested so far result in activation of the calcium channel in vitro, the mechanisms through which TRPV4 activation results in skeletal dysplasia and/or peripheral neuropathy remain unclear and the genotype-phenotype correlations in this group of disorders remains somewhat mysterious. Since the phenotypic expression of most mutations seems to be relatively constant, careful clinical and radiographic assessment is useful in directing molecular analysis.
Design of a 300-mV 2.4-GHz Receiver Using Transformer-Coupled Techniques

This paper presents a 1.6-mW 2.4-GHz receiver that operates from a single supply of 300 mV allowing direct powering from various energy harvesting sources. We extensively utilize transformer coupling between stages to reduce headroom requirements. We forward-bias bulk-source junctions to lower threshold voltages where appropriate. A single-ended 2.4 GHz RF input is amplified and converted to a differential signal before down-converting to a low IF of 1 to 10 MHz. A chain of IF amplifiers and narrowband filters are interleaved to perform programmable channel selection. The chip is fabricated in a 65-nm CMOS process. The receiver achieves -91.5-dBm sensitivity for a BER of 10e-3.
Survey of Multiobjective Evolutionary Algorithms for Data Mining: Part II

This paper is the second part of a two-part paper, which is a survey of multiobjective evolutionary algorithms for data mining problems. In Part I , multiobjective evolutionary algorithms used for feature selection and classification have been reviewed. In this part, different multiobjective evolutionary algorithms used for clustering, association rule mining, and other data mining tasks are surveyed. Moreover, a general discussion is provided along with scopes for future research in the domain of multiobjective evolutionary algorithms for data mining.
Microglial P2 Purinergic Receptor and Immunomodulatory Gene Transcripts Vary By Region, Sex, and Age in the Healthy Mouse CNS.

Inflammatory damage in many neurodegenerative diseases is restricted to certain regions of the CNS, and while microglia have long been implicated in the pathology of many of these disorders, information comparing their gene expression in different CNS regions is lacking. Here we tested the hypothesis that the expression of purinergic receptors, estrogen receptors and other neuroprotective and pro-inflammatory genes differed among CNS regions in healthy mice. Because neurodegenerative diseases vary in incidence by sex and age, we also examined the regional distribution of these genes in male and female mice of four different ages between 21 days and 12 months. We postulated that pro-inflammatory gene expression would be higher in older animals, and lower in young adult females. We found that microglial gene expression differed across the CNS. Estrogen receptor alpha (Esr1) mRNA levels were often lower in microglia from the brainstem/spinal cord than from the cortex, whereas tumor necrosis factor alpha (Tnfα) expression was several times higher. In addition, the regional pattern of gene expression often changed with animal age; for example, no regional differences in P2X7 mRNA levels were detected in 21 day-old animals, but at 7 weeks and older, expression was highest in cerebellar microglia. Lastly, the expression of some genes was sexually dimorphic. In microglia from 12 month-old animals, mRNA levels of inducible nitric oxide synthase, but not Tnfα, were higher in females than males. These data suggest that microglial gene expression is not uniformly more pro-inflammatory in males or older animals. Moreover, microglia from CNS regions in which neuronal damage predominates in neurodegenerative disease do not generally express more pro-inflammatory genes than microglia from regions less frequently affected. This study provides an in-depth assessment of regional-, sex- and age-dependent differences in key microglial transcripts from the healthy mouse CNS.
Automated reprojection-based pixel shader optimization

We present a framework and supporting algorithms to automate the use of temporal data reprojection as a general tool for optimizing procedural shaders. Although the general strategy of caching and reusing expensive intermediate shading calculations across consecutive frames has previously been shown to provide an effective trade-off between speed and accuracy, the critical choices of what to reuse and at what rate to refresh cached entries have been left to a designer. The fact that these decisions require a deep understanding of a procedure's semantic structure makes it challenging to select optimal candidates among possibly hundreds of alternatives. Our automated approach relies on parametric models of the way possible caching decisions affect the shader's performance and visual fidelity. These models are trained using a sample rendering session and drive an interactive profiler in which the user can explore the error/performance trade-offs associated with incorporating temporal reprojection. We evaluate the proposed models and selection algorithm with a prototype system used to optimize several complex shaders and compare our approach to current alternatives.
A 6.4-Gb/s Voltage-Mode Near-Ground Receiver With a One-Tap Data and Edge DFE

A low-power receiver with a one-tap data and edge decision-feedback equalizer (DFE) and a clock recovery circuit is presented. The receiver employs analog adders for the tap-weight summation in both the data and the edge path to simultaneously optimize both the voltage and timing margins. A switched-capacitor input stage allows the receiver to be fully compatible with near-GND input levels without extra level conversion circuits. Furthermore, the critical path of the DFE is simplified to relax the timing margin. Fabricated in the 65-nm CMOS technology, a prototype DFE receiver shows that the data-path DFE extends the voltage and timing margins from 40 mVpp and 0.3 unit interval (UI), respectively, to 70 mVpp and 0.6 UI, respectively. Likewise, the edge-path equalizer reduces the uncertain sampling region (the edge region), which results in 17% reduction of the recovered clock jitter. The DFE core, including adders and samplers, consumes 1.1 mW from a 1.2-V supply while operating at 6.4 Gb/s.
High Speed and High Resolution Self Biased Differential Amplifier based Latch Comparator

In high speed ADC, comparator influences the overall performance of ADC directly. This paper describes a very high speed and high resolution preamplifier comparator. The comparator use a self biased differential amp to increase the output current sinking and sourcing capability. The threshold and width of the new comparator can be reduced to the millivolt (mV) range, the resolution and the dynamic characteristics are good. Based on UMC 0. 18um CMOS process model, simulated results show the comparator can work under a 25dB gain, 55MHz speed and 210. 10μW power .
Process Control Cyber-Attacks and Labelled Datasets on S7Comm Critical Infrastructure

Cyber-security of their critical infrastructure is the current grand challenge facing nation-states. Development and research of cyber-security solutions for operational technology environments of critical infrastructure is being inhibited by the lack of publically available datasets. This paper provides a collection of labelled datasets containing attacks on the widely used STEP 7 (S7) protocol. To achieve this goal, we designed and executed a series of process-control attacks, using our physical critical infrastructure test-bed. The created labelled datasets, and the associated process logs, will directly aid in the development and assessment of intrusion detection systems (IDSs). We validate our dataset using Snort, configured with openly available S7 rule-sets.