nils-herrmann/clean_scirepeval huggingface dataset:
The cancer cell map initiative: defining the hallmark networks of cancer.

Progress in DNA sequencing has revealed the startling complexity of cancer genomes, which typically carry thousands of somatic mutations. However, it remains unclear which are the key driver mutations or dependencies in a given cancer and how these influence pathogenesis and response to therapy. Although tumors of similar types and clinical outcomes can have patterns of mutations that are strikingly different, it is becoming apparent that these mutations recurrently hijack the same hallmark molecular pathways and networks. For this reason, it is likely that successful interpretation of cancer genomes will require comprehensive knowledge of the molecular networks under selective pressure in oncogenesis. Here we announce the creation of a new effort, The Cancer Cell Map Initiative (CCMI), aimed at systematically detailing these complex interactions among cancer genes and how they differ between diseased and healthy states. We discuss recent progress that enables creation of these cancer cell maps across a range of tumor types and how they can be used to target networks disrupted in individual patients, significantly accelerating the development of precision medicine.
Batch Processing for Incremental FP-tree Construction

Frequent Patterns are very important in knowledge discovery and data mining process such as mining of association rules, correlations etc. Prefix-tree based approach is one of the contemporary approaches for mining frequent patterns. FP-tree is a compact representation of transaction database that contains frequency information of all relevant Frequent Patterns (FP) in a dataset. Since the introduction of FP-growth algorithm for FP-tree construction, three major algorithms have been proposed, namely AFPIM, CATS tree, and CanTree, that have adopted FP-tree for incremental mining of frequent patterns. All of the three methods perform incremental mining by processing one transaction of the incremental database at a time and updating it to the FP-tree of the initial (original) database. Here in this paper we propose a novel method to take advantage of FP-tree representation of incremental transaction database for incremental mining. We propose “Batch Incremental Tree (BIT)” algorithm to merge two small consecutive duration FP-trees to obtain a FP-tree that is equivalent of FP-tree obtained when the entire database is processed at once from the beginning of the first duration
The riddle of “life,” a biologist’s critical view

To approach the question of what life is, we first have to state that life exists exclusively as the “being-alive” of discrete spatio-temporal entities. The simplest “unit” that can legitimately be considered to be alive is an intact prokaryotic cell as a whole. In this review, I discuss critically various aspects of the nature and singularity of living beings from the biologist’s point of view. In spite of the enormous richness of forms and performances in the biotic realm, there is a considerable uniformity in the chemical “machinery of life,” which powers all organisms. Life represents a dynamic state; it is performance of a system of singular kind: “life-as-action” approach. All “life-as-things” hypotheses are wrong from the beginning. Life is conditioned by certain substances but not defined by them. Living systems are endowed with a power to maintain their inherent functional order (organization) permanently against disruptive influences. The term organization inherently involves the aspect of functionality, the teleonomic, purposeful cooperation of structural and functional elements. Structures in turn require information for their specification, and information presupposes a source. This source is constituted in living systems by the nucleic acids. Organisms are unique in having a capacity to use, maintain, and replicate internal information, which yields the basis for their specific organization in its perpetuation. The existence of a genome is a necessary condition for life and one of the absolute differences between living and non-living matter. Organization includes both what makes life possible and what is determined by it. It is not something “implanted” into the living beings but has its origin and capacity for maintenance within the system itself. It is the essence of life. The property of being alive we can consider as an emergent property of cells that corresponds to a certain level of self-maintained complex order or organization.
Context-Aware Attention for Understanding Twitter Abuse

The original goal of any social media platform is to facilitate users to indulge in healthy and meaningful conversations. But more often than not, it has been found that it becomes an avenue for wanton attacks. We want to alleviate this issue and hence we try to provide a detailed analysis of how abusive behavior can be monitored in Twitter. The complexity of the natural language constructs makes this task challenging. We show how applying contextual attention to Long Short Term Memory networks help us give near state of art results on multiple benchmarks abuse detection data sets from Twitter.
A 2D-fractional derivative mask for image feature edge detection

Feature extraction is a classic problem of machine vision and image processing. Edges are often detected using integer-order differential operators. In this paper, a one-dimensional digital fractional-order Charef differentiator (1D-FCD) is introduced and extended to 2D by a multi-directional operator. The obtained 2D-fractional differentiation (2D-FCD) is a new edge detection operation. The computed multi-directional mask coefficients are computed in a way that image details are detected and preserved. Experiments on texture images have demonstrated the efficiency of the proposed filter compared to existing techniques.
Automatic Skin Color Beautification

In this paper, we propose an automatic skin beautification framework based on color-temperature-insensitive skin-color detection. To polish selected skin region, we apply bilateral filter to smooth the facial flaw. Last, we use Poisson image cloning to integrate the beautified parts into the original input. Experimental results show that the proposed method can be applied in varied light source environment. In addition, this method can naturally beautify the portrait skin.
Acceptability of Smartphone Application-Based HIV Prevention Among Young Men Who Have Sex With Men

Young men who have sex with men (YMSM) are increasingly using mobile smartphone applications (“apps”), such as Grindr, to meet sex partners. A probability sample of 195 Grindr-using YMSM in Southern California were administered an anonymous online survey to assess patterns of and motivations for Grindr use in order to inform development and tailoring of smartphone-based HIV prevention for YMSM. The number one reason for using Grindr (29 %) was to meet “hook ups.” Among those participants who used both Grindr and online dating sites, a statistically significantly greater percentage used online dating sites for “hook ups” (42 %) compared to Grindr (30 %). Seventy percent of YMSM expressed a willingness to participate in a smartphone app-based HIV prevention program. Development and testing of smartphone apps for HIV prevention delivery has the potential to engage YMSM in HIV prevention programming, which can be tailored based on use patterns and motivations for use. Los hombres que mantienen relaciones sexuales con hombres (YMSM por las siglas en inglés de Young Men Who Have Sex with Men) están utilizando más y más aplicaciones para teléfonos inteligentes (smartphones), como Grindr, para encontrar parejas sexuales. En el Sur de California, se administró de forma anónima un sondeo en internet a una muestra de probabilidad de 195 YMSM usuarios de Grindr, para evaluar los patrones y motivaciones del uso de Grindr, con el fin de utilizar esta información para el desarrollo y personalización de prevención del VIH entre YMSM con base en teléfonos inteligentes. La principal razón para utilizar Grindr (29 %) es para buscar encuentros sexuales casuales (hook-ups). Entre los participantes que utilizan tanto Grindr como otro sitios de citas online, un mayor porcentaje estadísticamente significativo utilizó los sitios de citas online para encuentros casuales sexuales (42 %) comparado con Grindr (30 %). Un setenta porciento de los YMSM expresó su disposición para participar en programas de prevención del VIH con base en teléfonos inteligentes. El desarrollo y evaluación de aplicaciones para teléfonos inteligentes para el suministro de prevención del VIH tiene el potencial de involucrar a los YMSM en la programación de la prevención del VIH, que puede ser adaptada según los patrones y motivaciones de uso.
Conceptual Survey on Data Stream Processing Systems

The present paper gives an overview about the state of the art technology within the area of data stream processing systems. Although the area of stream processing systems is not new, it is receiving a greater interest in the light of current business trends like the Internet of Things (IoT). The comparison of systems thereby includes several aspects such as a look into their architectures as well as into the responsibilities of the corresponding system components. A ranking or recommendations for one or more system(s) is not part of the work.
A Step Beyond Local Observations with a Dialog Aware Bidirectional GRU Network for Spoken Language Understanding

Architectures of Recurrent Neural Networks (RNN) recently become a very popular choice for Spoken Language Understanding (SLU) problems; however, they represent a big family of different architectures that can furthermore be combined to form more complex neural networks. In this work, we compare different recurrent networks, such as simple Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM) networks, Gated Memory Units (GRU) and their bidirectional versions, on the popular ATIS dataset and on MEDIA, a more complex French dataset. Additionally, we propose a novel method where information about the presence of relevant word classes in the dialog history is combined with a bidirectional GRU, and we show that combining relevant word classes from the dialog history improves the performance over recurrent networks that work by solely analyzing the current sentence.
Mutual Coupling Reduction for UWB MIMO Antennas With a Wideband Neutralization Line

A wideband neutralization line is proposed to reduce the mutual coupling of a compact ultrawideband (UWB) multiple-input-multiple-output (MIMO) antenna. With the introduced decoupling method, the designed UWB MIMO antenna covers the band of 3.1-5 GHz with an isolation of higher than 22 dB. The proposed wideband neutralization line is not necessarily placed in the clearance area between two MIMO elements and can be put above the copper ground. A small clearance (antenna area) of 35 ×16 mm2 is achieved. The designed UWB MIMO antenna is fabricated. Sparameters, radiation patterns, total efficiency, and realized gain of the prototype are measured and compared to the simulations.
Classification and regression trees

Classification and regression trees are machine-learning methods for constructing prediction models from data. The models are obtained by recursively partitioning the data space and fitting a simple prediction model within each partition. As a result, the partitioning can be represented graphically as a decision tree. Classification trees are designed for dependent variables that take a finite number of unordered values, with prediction error measured in terms of misclassification cost. Regression trees are for dependent variables that take continuous or ordered discrete values, with prediction error typically measured by the squared difference between the observed and predicted values. This article gives an introduction to the subject by reviewing some widely available algorithms and comparing their capabilities, strengths, and weakness in two examples.
Achieving quality assurance functionality in the food industry using a hybrid case-based reasoning and fuzzy logic approach

Quality control of food inventories in the warehouse is complex as well as challenging due to the fact that food can easily deteriorate. Currently, this difficult storage problem is managed mostly by using a human dependent quality assurance and decision making process. This has however, occasionally led to unimaginative, arduous and inconsistent decisions due to the injection of subjective human intervention into the process. Therefore, it could be said that current practice is not powerful enough to support high-quality inventory management. In this paper, the development of an integrative prototype decision support system, namely, Intelligent Food Quality Assurance System (IFQAS) is described which will assist the process by automating the human based decision making process in the quality control of food storage. The system, which is composed of a Case-based Reasoning (CBR) engine and a Fuzzy rule-based Reasoning (FBR) engine, starts with the receipt of incoming food inventory. With the CBR engine, certain quality assurance operations can be suggested based on the attributes of the food received. Further of this, the FBR engine can make suggestions on the optimal storage conditions of inventory by systematically evaluating the food conditions when the food is receiving. With the assistance of the system, a holistic monitoring in quality control of the receiving operations and the storage conditions of the food in the warehouse can be performed. It provides consistent and systematic Quality Assurance Guidelines for quality control which leads to improvement in the level of customer satisfaction and minimization of the defective rate.
General background on the hypothalamic-pituitary-thyroid (HPT) axis.

This article reviews the thyroid system, mainly from a mammalian standpoint. However, the thyroid system is highly conserved among vertebrate species, so the general information on thyroid hormone production and feedback through the hypothalamic-pituitary-thyroid (HPT) axis should be considered for all vertebrates, while species-specific differences are highlighted in the individual articles. This background article begins by outlining the HPT axis with its components and functions. For example, it describes the thyroid gland, its structure and development, how thyroid hormones are synthesized and regulated, the role of iodine in thyroid hormone synthesis, and finally how the thyroid hormones are released from the thyroid gland. It then progresses to detail areas within the thyroid system where disruption could occur or is already known to occur. It describes how thyroid hormone is transported in the serum and into the tissues on a cellular level, and how thyroid hormone is metabolized. There is an in-depth description of the alpha and beta thyroid hormone receptors and their functions, including how they are regulated, and what has been learned from the receptor knockout mouse models. The nongenomic actions of thyroid hormone are also described, such as in glucose uptake, mitochondrial effects, and its role in actin polymerization and vesicular recycling. The article discusses the concept of compensation within the HPT axis and how this fits into the paradigms that exist in thyroid toxicology/endocrinology. There is a section on thyroid hormone and its role in mammalian development: specifically, how it affects brain development when there is disruption to the maternal, the fetal, the newborn (congenital), or the infant thyroid system. Thyroid function during pregnancy is critical to normal development of the fetus, and several spontaneous mutant mouse lines are described that provide research tools to understand the mechanisms of thyroid hormone during mammalian brain development. Overall this article provides a basic understanding of the thyroid system and its components. The complexity of the thyroid system is clearly demonstrated, as are new areas of research on thyroid hormone physiology and thyroid hormone action developing within the field of thyroid endocrinology. This review provides the background necessary to review the current assays and endpoints described in the following articles for rodents, fishes, amphibians, and birds.
Learning Transferable Features for Speech Emotion Recognition

Emotion recognition from speech is one of the key steps towards emotional intelligence in advanced human-machine interaction. Identifying emotions in human speech requires learning features that are robust and discriminative across diverse domains that differ in terms of language, spontaneity of speech, recording conditions, and types of emotions. This corresponds to a learning scenario in which the joint distributions of features and labels may change substantially across domains. In this paper, we propose a deep architecture that jointly exploits a convolutional network for extracting domain-shared features and a long short-term memory network for classifying emotions using domain-specific features. We use transferable features to enable model adaptation from multiple source domains, given the sparseness of speech emotion data and the fact that target domains are short of labeled data. A comprehensive cross-corpora experiment with diverse speech emotion domains reveals that transferable features provide gains ranging from 4.3% to 18.4% in speech emotion recognition. We evaluate several domain adaptation approaches, and we perform an ablation study to understand which source domains add the most to the overall recognition effectiveness for a given target domain.
Twenty-year follow-up of children with and without speech-language impairments: family, educational, occupational, and quality of life outcomes.

Parents, professionals, and policy makers need information on the long-term prognosis for children with communication disorders. Our primary purpose in this report was to help fill this gap by profiling the family, educational, occupational, and quality of life outcomes of young adults at 25 years of age (N = 244) from the Ottawa Language Study, a 20-year, prospective, longitudinal study of a community sample of individuals with (n = 112) and without (n = 132) a history of early speech and/or language impairments. A secondary purpose of this report was to use data from earlier phases of the study to predict important, real-life outcomes at age 25.



Participants were initially identified at age 5 and subsequently followed at 12, 19, and 25 years of age. Direct assessments were conducted at all 4 time periods in multiple domains (demographic, communicative, cognitive, academic, behavioral, and psychosocial).



At age 25, young adults with a history of language impairments showed poorer outcomes in multiple objective domains (communication, cognitive/academic, educational attainment, and occupational status) than their peers without early communication impairments and those with early speech-only impairments. However, those with language impairments did not differ in subjective perceptions of their quality of life from those in the other 2 groups. Objective outcomes at age 25 were predicted differentially by various combinations of multiple, interrelated risk factors, including poor language and reading skills, low family socioeconomic status, low performance IQ, and child behavior problems. Subjective well-being, however, was primarily associated with strong social networks of family, friends, and others.



This information on the natural history of communication disorders may be useful in answering parents' questions, anticipating challenges that children with language disorders might encounter, and planning services to address those issues.
A Meta-Learning Approach for Custom Model Training

Transfer-learning and meta-learning are two effective methods to apply knowledge learned from large data sources to new tasks. In few-class, few-shot target task settings (i.e. when there are only a few classes and training examples available in the target task), meta-learning approaches that optimize for future task learning have outperformed the typical transfer approach of initializing model weights from a pre-trained starting point. But as we experimentally show, meta-learning algorithms that work well in the few-class setting do not generalize well in many-shot and many-class cases. In this paper, we propose a joint training approach that combines both transfer-learning and meta-learning. Benefiting from the advantages of each, our method obtains improved generalization performance on unseen target tasks in both fewand many-class and fewand manyshot scenarios.
A 0.7dB insertion loss CMOS&#8211;SOI antenna switch with more than 50dB isolation over the 2.5 to 5GHz band

Taking full advantage of the high resistivity substrate and underlying oxide of SOI technology, a high performance CMOS SPDT T/R switch has been designed and fabricated in a partially depleted, 0.25µm SOI process. The targeted Bluetooth class II specifications have been fully fitted. The switch over the high resistivity substrate exhibits a 0.7dB insertion loss and a 50dB isolation at 2.4GHz; at 5GHz insertion loss and isolation are 1dB and 47dB respectively. The measured ICP1dBis +12dBm.
Mathematical modeling of microRNA-mediated mechanisms of translation repression.

MicroRNAs can affect the protein translation using nine mechanistically different mechanisms, including repression of initiation and degradation of the transcript. There is a hot debate in the current literature about which mechanism and in which situations has a dominant role in living cells. The worst, same experimental systems dealing with the same pairs of mRNA and miRNA can provide ambiguous evidences about which is the actual mechanism of translation repression observed in the experiment. We start with reviewing the current knowledge of various mechanisms of miRNA action and suggest that mathematical modeling can help resolving some of the controversial interpretations. We describe three simple mathematical models of miRNA translation that can be used as tools in interpreting the experimental data on the dynamics of protein synthesis. The most complex model developed by us includes all known mechanisms of miRNA action. It allowed us to study possible dynamical patterns corresponding to different miRNA-mediated mechanisms of translation repression and to suggest concrete recipes on determining the dominant mechanism of miRNA action in the form of kinetic signatures. Using computational experiments and systematizing existing evidences from the literature, we justify a hypothesis about co-existence of distinct miRNA-mediated mechanisms of translation repression. The actually observed mechanism will be that acting on or changing the sensitive parameters of the translation process. The limiting place can vary from one experimental setting to another. This model explains the majority of existing controversies reported.
A benchmark for 3D mesh segmentation

This paper describes a benchmark for evaluation of 3D mesh segmentation salgorithms. The benchmark comprises a data set with 4,300 manually generated segmentations for 380 surface meshes of 19 different object categories, and it includes software for analyzing 11 geometric properties of segmentations and producing 4 quantitative metrics for comparison of segmentations. The paper investigates the design decisions made in building the benchmark, analyzes properties of human-generated and computer-generated segmentations, and provides quantitative comparisons of 7 recently published mesh segmentation algorithms. Our results suggest that people are remarkably consistent in the way that they segment most 3D surface meshes, that no one automatic segmentation algorithm is better than the others for all types of objects, and that algorithms based on non-local shape features seem to produce segmentations that most closely resemble ones made by humans.