Miracle-dz/UniFAR-FTUs huggingface dataset:
A framework for formalizing inconsistencies and deviations in human-centered systems

Most modern business activities are carried out by a combination of computerized tools and human agents. Typical examples are engineering design activities, office procedures, and banking systems. All these human-centered systems are characterized by the interaction among people, and between people and computerized tools. This interaction defines a process, whose effectiveness is essential to ensure the quality of the delivered products and/or services. To support these systems, process-centered environments and workflow management systems have been recently developed. They can be collectively identified with the term process technology. This technology is based on the explicit definition of the process to be followed (the process model). The model specifies the kind of support that has to be provided to human agents. An essential property that process technology mut exhibit is the ability of tolerating, controlling, and supporting deviations and inconsistencies of the real-world behaviors with respect to the proocess model. This is necessary to provide consistent and effective support to the human-centered system, still maintaining a high degree of flexibility and adaptability to the evolving needs, preferences, an expertise of the the human agents. This article presents a formal framework to characterize the interaction between a human-centered system and its automated support. It does not aim at introducing a new language or system to describe processes. Rather, it aims at identifying the basic properties and features that make it possible to formally define the concepts of inconsistency and deviation. This formal framework can then be used to compare existing solutions and guide future research work.
Engineering stress tolerance of Escherichia coli by stress‐induced mutagenesis (SIM)‐based adaptive evolution

Microbial tolerance to toxic products and biomass hydrolysates is a challenge for the production of fuels and chemicals from renewable resources. To improve cellular tolerance to these environmental stresses, a novel adaptive evolutionary strategy based on stress‐induced mutagenesis (SIM) was developed using non‐dividing cells. The concept of this method was proved using Escherichia coli FC40 as a model strain, which was used to quantitatively evaluate the rate of SIM. By deleting either the mutL or mutS gene to disturb the mismatch repair activity of the host cells, the SIM rate under stressful conditions increased by 92‐ and 57‐fold, respectively. A periodic SIM‐based adaptive evolution procedure, which synchronized the mutagenesis and the selection process in a single plate‐incubation step, was then developed using the mutL‐deleted mutant. E. coli mutants tolerant to high concentrations of butanol (13 g/L), NaCl (95 g/L), and high temperature (50°C) were obtained. These results indicate that stress‐induced adaptive evolution in non‐dividing cells is an effective approach that can improve microbial tolerance against various stresses and generate robust microbial strains suitable for production of fuels and chemicals.
A PARTIALLY PARAMETRIC MODEL

In this paper we propose a model which includes both a known (potentially) nonlinear parametric component and an unknown nonparametric component. This approach is feasible given that we estimate the finite sample parameter vector and the bandwidths simultaneously. We show that our objective function is asymptotically equivalent to the individual objective criteria for the parametric parameter vector and the nonparametric function. In the special case where the parametric component is linear in parameters, our single-step method is asymptotically equivalent to the two-step partially linear model estimator in Robinson (1988). Monte Carlo simulations support the asymptotic developments and show impressive finite sample performance. We apply our method to the case of a partially constant elasticity of substitution production function for an unbalanced sample of 134 countries from 1955-2011 and find that the parametric parameters are relatively stable for different nonparametric control variables in the full sample. However, we find substantial parameter heterogeneity between developed and developing countries which results in important differences when estimating the elasticity of substitution.
Sparse Representations-Based Super-Resolution of Key-Frames Extracted from Frames-Sequences Generated by a Visual Sensor Network

Visual sensor networks (VSNs) usually generate a low-resolution (LR) frame-sequence due to energy and processing constraints. These LR-frames are not very appropriate for use in certain surveillance applications. It is very important to enhance the resolution of the captured LR-frames using resolution enhancement schemes. In this paper, an effective framework for a super-resolution (SR) scheme is proposed that enhances the resolution of LR key-frames extracted from frame-sequences captured by visual-sensors. In a VSN, a visual processing hub (VPH) collects a huge amount of visual data from camera sensors. In the proposed framework, at the VPH, key-frames are extracted using our recent key-frame extraction technique and are streamed to the base station (BS) after compression. A novel effective SR scheme is applied at BS to produce a high-resolution (HR) output from the received key-frames. The proposed SR scheme uses optimized orthogonal matching pursuit (OOMP) for sparse-representation recovery in SR. OOMP does better in terms of detecting true sparsity than orthogonal matching pursuit (OMP). This property of the OOMP helps produce a HR image which is closer to the original image. The K-SVD dictionary learning procedure is incorporated for dictionary learning. Batch-OMP improves the dictionary learning process by removing the limitation in handling a large set of observed signals. Experimental results validate the effectiveness of the proposed scheme and show its superiority over other state-of-the-art schemes.
The Effects of Granularity and Adaptivity on Private/Shared Classification for Coherence

Classification of data into private and shared has proven to be a catalyst for techniques to reduce coherence cost, since private data can be taken out of coherence and resources can be concentrated on providing coherence for shared data. In this article, we examine how granularity—page-level versus cache-line level—and adaptivity—going from shared to private—affect the outcome of classification and its final impact on coherence. We create a classification technique, called Generational Classification, and a coherence protocol called Generational Coherence, which treats data as private or shared based on cache-line generations. We compare two coherence protocols based on self-invalidation/self-downgrade with respect to data classification. Our findings are enlightening: (i) Some programs benefit from finer granularity, some benefit further from adaptivity, but some do not benefit from either. (ii) Reducing the amount of shared data has no perceptible impact on coherence misses caused by self-invalidation of shared data, hence no impact on performance. (iii) In contrast, classifying more data as private has implications for protocols that employ write-through as a means of self-downgrade, resulting in network traffic reduction—up to 30%—by reducing write-through traffic.
Distinct and Shared Transcriptomes Are Regulated by Microphthalmia-Associated Transcription Factor Isoforms in Mast Cells1

The Microphthalmia-associated transcription factor (Mitf) is an essential basic helix-loop-helix leucine zipper transcription factor for mast cell development. Mice deficient in Mitf harbor a severe mast cell deficiency, and Mitf-mutant mast cells cultured ex vivo display a number of functional defects. Therefore, an understanding of the genetic program regulated by Mitf may provide important insights into mast cell differentiation. Multiple, distinct isoforms of Mitf have been identified in a variety of cell types; we found that Mitf-a, Mitf-e, and Mitf-mc were the major isoforms expressed in mast cells. To determine the physiologic function of Mitf in mast cells, we restored expression of these isoforms in primary mast cells from Mitf−/− mice. We found that these isoforms restored granular morphology and integrin-mediated migration. By microarray analysis, proteases, signaling molecules, cell surface receptor, and transporters comprised the largest groups of genes up-regulated by all isoforms. Furthermore, we found that isoforms also regulated distinct genes sets, suggesting separable biological activities. This work defines the transcriptome regulated by Mitf in mast cells and supports its role as master regulator of mast cell differentiation. Expression of multiple isoforms of this transcription factor may provide for redundancy of biological activities while also allowing diversity of function.
A LTE Receiver Framework Implementation in GNU Radio

—We present an open source LTE receiver framework. Using GNU Radio‘s block-based signal processing capabilities, various LTE baseband speciﬁc functionality has been implemented in dedicated easily reconﬁgurable blocks. These can be used to decode and analyze arbitrary channels in the LTE downlink signal. As an example we decode the Master Information Block (MIB) transmitted on the Broadcast Channel (BCH). Our work is focused on performance measurements in order to identify critical processing operations on a General Purpose Processor (GPP). By optimizing critical components, e.g. channel estimation, synchronization, we can improve the overall system performance and therefore the system‘s real-time capabilities.
Compressed domain speech enhancement based on the joint modification of codebook gains

A compressed domain speech enhancement method based on the joint modification of adaptive and algebraic codebook gains for the codec of ITU-T G.722. 2 is proposed in this paper. First the power of excitation signal corresponding to the noise is estimated by the method of minimum statistics. Then the decision-directed approach is used to get an estimate of the a priori SNR. And the algebraic codebook gain is modified by multiplying a Wiener-type modification factor. In order to solve the problem of power loss in voiced segment, the modified adaptive codebook gain is got by keeping the power of the modified excitation signal equal to the scaled version of the noisy one. The result of performance evaluation under ITU-T G.160 shows that, in comparison with the method that only modifies the algebraic codebook gain, the proposed method could provide larger amount of noise reduction in both white and colored noise with smaller attenuation on the speech level, and the objective speech quality is improved evidently.
Discovery of Cyrtospirifer (Late Devonian Brachiopoda) from Choanji in the South Kitakami Belt, northeastern Japan

©The Geological Society of Japan 2017 101 Abstract: Three Cyrtospirifer species (Cyrtospirifer choanjiensis sp. nov., Cyrtospirifer sp. 1 and Cyrtospirifer sp. 2) are described for the first time from Choanji, eastern part of the South Kitakami Belt, northeastern Japan. The occurrence of the Late Devonian brachiopod Cyrtospirifer from Choanji indicates the presence of Upper Devonian rocks in the Choanji area. Report
Heterogeneous Representation Learning with Structured Sparsity Regularization

Motivated by real applications, heterogeneous learning has emerged as an important research area, which aims to model the co-existence of multiple types of heterogeneity. In this paper, we propose a HEterogeneous REpresentation learning model with structured Sparsity regularization (HERES) to learn from multiple types of heterogeneity. HERES aims to leverage two kinds of information to build a robust learning system. One is the rich correlations among heterogeneous data such as task relatedness, view consistency, and label correlation. The other is the prior knowledge of the data in the form of, e.g., the soft-clustering of the tasks. HERES is a generic framework for heterogeneous learning, which integrates multi-task, multi-view, and multi-label learning into a principled framework based on representation learning. The objective of HERES is to minimize the reconstruction loss of using the factor matrices to recover the input matrix for heterogeneous data, regularized by the structured sparsity constraint. The resulting optimization problem is challenging due to the non-smoothness and non-separability of structured sparsity. We develop an iterative updating method to solve the problem. Furthermore, we prove that the reformulation of structured sparsity is separable, which leads to a family of efficient and scalable algorithms for solving structured sparsity penalized problems. The experimental results in comparison with state-of-the-art methods demonstrate the effectiveness of the proposed approach.
In Vitro Metabolism Study of Combretastatin A-4 in Rat and Human Liver Microsomes

The phase I biotransformation of combretastatin A-4 (CA-4) 1, a potent tubulin polymerization inhibitor with antivascular and antitumoral properties, was studied using rat and human liver subcellular fractions. The metabolites were separated by high-performance liquid chromatography and detected with simultaneous UV and electrospray ionization (ESI) mass spectrometry. The assignment of metabolite structures was based on ESI-tandem mass spectrometry experiments, and it was confirmed by comparison with reference samples obtained by synthesis. O-Demethylation and aromatic hydroxylation are the two major phase I biotransformation pathways, the latter being regioselective for phenyl ring B of 1. Indeed, incubation with rat and human microsomal fractions led to the formation of a number of metabolites, eight of which were identified. The regioselectivity of microsomal oxidation was also demonstrated by the lack of metabolites arising from stilbenic double bond epoxidation. Alongside the oxidative metabolism, Z-E isomerization during in vitro study was also observed, contributing to the complexity of the metabolite pattern. Moreover, when 1 was incubated with a cytosolic fraction, metabolites were not observed. Aromatic hydroxylation at the C-6′ of phenyl ring B and isomerization led to the formation of M1 and M2 metabolites, which were further oxidized to the corresponding para-quinone (M7 and M8) species whose role in pharmacodynamic activity is unknown. Metabolites M4 and M5, arising from O-demethylation of phenyl ring B, did not form the ortho-quinones. O-Demethylation of phenyl ring A formed the metabolite M3 with a complete isomerization of the stilbenic double bond.
Desmosomes exhibit site‐specific features in human palm skin

Abstract: Hereditary skin disorders resulting from desmosome gene pathology may preferentially involve the palms and soles. Why this is so is not clear. Moreover, even in normal control skin it is unknown whether there are differences in desmosome number, size or structural organization in palmoplantar sites compared with skin from other body regions. Therefore, we sought evidence for such differences by examining desmosome expression in relation to epidermal differentiation in both epidermis and cultured keratinocytes from normal human palm and breast skin samples. Confocal microscopy of skin biopsy material showed relative differences in the expression profiles of several desmosomal proteins (desmogleins, desmocollins, desmoplakin, plakoglobin and plakophilin 1) between the two sites. Western blotting revealed a higher expression level of all five proteins in palm compared with breastcultured keratinocytes. Staining for the differentiation‐associated component, involucrin, suggested an earlier onset of synthesis of this protein in palm epidermis, and a suspension‐induced differentiation assay showed that involucrin synthesis began earlier in palm keratinocytes than in breast cells. At 4–8 h, the number of involucrin‐positive cells in palm keratinocytes was almost twice that in breast. Morphometric analysis showed that, overall, desmosomes were larger but of similar population density in the palm compared with breast skin. These findings demonstrate differences in desmosome structure and protein expression between the two sites, possibly reflecting the needs of palms and soles to withstand constant mechanical stress. They may also help to explain the preferential involvement of this region in certain hereditary disorders (palmoplantar keratodermas), associated with mutations in desmoplakin or desmoglein 1.
Automatic Building Detection from Satellite Images using Internal Gray Variance and Digital Surface Model

Automatic building extraction is considered recently as an active research in remote sensing operation. It has been going on for more than 20 years but the automated extractions still encounter problems due to image resolution, variation and level of details. Because of high-object density and scene complexity this is going to be an even greater challenge especially in urban areas. This paper is going to present an ideal framework for high-resolution panchromatic images which helps in reliable and accurate building extraction operation. Proposed framework along with the consideration of domain knowledge (spatial and spectral characteristics) provides features like the nature of objects in the scene, their optical interactions and their impact on the resulting image. To analyze geometric nature of scene in better way we are using Digital Surface Model (DSM). Proposed algorithm has been evaluated using a variety of images from IKONOS and QuickBird satellites. The results demonstrate that the proposed algorithm is accurate and efficient in comparison with the state of art methods.
A Top Down Approach for Describing the Acquaintace Organisation of Multiagent Systems

When the protocol of a complex Multi-Agent System (MAS) needs to be developed, the top-down approach emphasises to start with abstract descriptions that should be refined incrementally until we achieve the detail level necessary to implement it. Unfortunately, there exist a semantic gap in interaction protocol methodologies because most of them first, identify which tasks has to be performed, and then use low level description such as sequences of messages to detail them. In this paper, we propose an approach to bridge this gap proposing a set of techniques that are integrated in a methodology called MaCMAS (Methodology for Analysing Complex Multiagent Systems). We model MAS protocols using several abstract views of the tasks to be performed, and provide a systematic method to reach message sequences descriptions from task descriptions. These tasks are represented by means of interactions that shall be refined systematically into lower-level interactions with the techniques proposed in this paper (simpler interactions are easier to describe and implement using message passing.) Unfortunately, deadlocks may appear due to protocol design mistakes or due to the refinement process that we present. Thus, we also propose an algorithm to ensure that protocols are deadlock free.
A Common CYFIP1 Variant at the 15q11.2 Disease Locus Is Associated with Structural Variation at the Language-Related Left Supramarginal Gyrus

Copy number variants (CNVs) at the Breakpoint 1 to Breakpoint 2 region at 15q11.2 (BP1-2) are associated with language-related difficulties and increased risk for developmental disorders in which language is compromised. Towards underlying mechanisms, we investigated relationships between single nucleotide polymorphisms (SNPs) across the region and quantitative measures of human brain structure obtained by magnetic resonance imaging of healthy subjects. We report an association between rs4778298, a common variant at CYFIP1, and inter-individual variation in surface area across the left supramarginal gyrus (lh.SMG), a cortical structure implicated in speech and language in independent discovery (n = 100) and validation cohorts (n = 2621). In silico analyses determined that this same variant, and others nearby, is also associated with differences in levels of CYFIP1 mRNA in human brain. One of these nearby polymorphisms is predicted to disrupt a consensus binding site for FOXP2, a transcription factor implicated in speech and language. Consistent with a model where FOXP2 regulates CYFIP1 levels and in turn influences lh.SMG surface area, analysis of publically available expression data identified a relationship between expression of FOXP2 and CYFIP1 mRNA in human brain. We propose that altered CYFIP1 dosage, through aberrant patterning of the lh.SMG, may contribute to language-related difficulties associated with BP1-2 CNVs. More generally, this approach may be useful in clarifying the contribution of individual genes at CNV risk loci.
Energy-efficient power allocation for WDM/OCDM networks with particle swarm optimization

In this paper, an optical network optimization based on particle swarm intelligence is described. The particle swarm optimization (PSO) algorithm is evocated in order to solve the problem of resource allocation (RA) based on the signal-to-noise plus interference ratio optimization in a hybrid wavelength division multiplexing/optical code division multiplexing network with quality-of-service restrictions. The RA optimization based on the PSO strategy allows the regulation of the transmitted power in order to maximize the energy efficiency. For the network optimization context, a system model is described, figures of merit are presented, and a suitable model for the heuristic optimization approach is developed, with emphasis on the optimization of input parameters and network performance. Afterward, extensive numerical results for both optimization problems are discussed, taking into account realistic network operation scenarios.
Design and implementation of a personal health monitoring system with an effective SVM-based PVC detection algorithm in cardiology

In this paper, we present a bio-health monitoring system prototype specialized in capturing the Premature Ventricular Contraction (PVC) event, one of the major cardiac disorder events. The proposed bio-health system comprises three parts: (1) the Electrocardiograph (ECG) sensing hardware, (2) the Android-based processing and communication device, and (3) the expert system on the cloud to detect PVC events. The expert system on the cloud is designed and implemented based on the support vector machine (SVM). The effective identification of PVC can help patients take care of the health quickly. The main purpose of recording information is to track the patient's health status, and allow the medical team to keep tracking the recovery status.
Channelization Issues with Fairness Considerations for MU-MIMO Precoding Based UTRA-LTE/TDD Systems

In a pre-coded Multi User Multiple Input Multiple Output (MU-MIMO) system, the channelization can be done either by using any of the two basic access techniques, namely Orthogonal Frequency Division Multiple Access (OFDMA) and Space Division Multiple Access (SDMA), or by combining them. From resource allocation point of view, choice of any technique will require different fairness conditions among users. In this paper, we have studied these different fairness conditions when combined with basic or joint access schemes mentioned above, while applied in a MU-MIMO based UTRA-LTE system. We have evaluated the resource allocation fairness issue when two well-known linear MU-MIMO precoding is used on a UTRA-LTE system. User grouping issue is dealt with when SDMA component is considered in the system. The results in this work provides an indicative analysis of the usability of different channelization techniques for considered system.