Miracle-dz/UniFAR-FTUs huggingface dataset:
Major histocompatibility complex class I presentation of exogenous soluble tumor antigen fused to the B‐fragment of Shiga toxin

Targeting exogenous antigen into the MHC class I‐restricted presentation pathway is a prerequisite for the induction of cytotoxic T lymphocytes (CTL) which have been shown to represent an important component of the protective and therapeutic immune response to viral infections and tumors. In this study, we produced recombinant proteins composed of the receptor‐binding non‐toxic B‐fragment of bacterial Shiga toxin derived from Shigella dysenteriae associated with an epitope from a model tumor antigen, Mage 1. We show that Shiga B‐Mage 1 fusion proteins carrying an active or inactive endoplasmic reticulum retrieval signal (the C‐terminal peptides KDEL or KDELGL, respectively) could be presented by peripheral blood mononuclear cells in an MHC class I‐restricted manner to Mage 1‐specific CTL. After pulsing B lymphoblastoid cells or dendritic cells with Shiga B‐Mage 1 fusion protein, activation of the MHC class I‐restricted Mage 1‐specific CTL was also demonstrated. In further analysis, we showed that treatment with brefeldin A or paraformaldehyde fixation of Epstein‐Barr virus‐transformed B cells prevented the presentation of the Mage 1 T cell epitope, which excluded extracellular processing of the antigen. Immunofluorescence analysis also revealed that the Shiga B‐Mage 1 fusion protein was largely excluded from Lamp‐2‐positive lysosomal structures. Therefore, the ability of Shiga toxin B‐fragment to target dendritic cells and B cells and to direct antigen into the exogenous class I‐restricted pathway makes it an attractive non‐living and non‐toxic vaccine vector.
Interactive comment on “ Analyzing numerics of bulk microphysics schemes in Community models : warm rain processes ” by I . Sednev and S .

First, we thank the reviewer for the review of our paper entitled "Analyzing numerics of bulk microphysics schemes in Community models: Warm rain processes". Additional thanks for crediting us with ". an excellent point or two regarding numerical stability unrelated to dynamics" as well as for the evaluation that ". The criticism regarding "mass conservation" as a technique to prevent negative mixing ratios appears valid".
Bibliometric Analysis and Research Management

Traditional research managements were mostly driven by expert opinions (i.e. bottomup up decision making system). In the last ten years, however, citation metrics provided by search systems for scholarly literature, like Web of Knowledge (Thomson Reuters), Scopus (Elsevier) and Google Scholar gain interest in boardrooms of research laboratories and universities. This bibliometric analysis can develop to serve research managements and science and technology strategy building. This paper provides and discusses some examples of such citation metrics and methodology of identifying and ranking research fronts. As a result,100 hottest world research fronts are introduced. The corresponding situation is reported for Vietnam and proposals for changes in research managements, policies and decision making are suggested for Vietnam and other developing countries.
Task Interruption in Software Development Projects: What Makes some Interruptions More Disruptive than Others?

Multitasking has always been an inherent part of software development and is known as the primary source of interruptions due to task switching in software development teams. Developing software involves a mix of analytical and creative work, and requires a significant load on brain functions, such as working memory and decision making. Thus, task switching in the context of software development imposes a cognitive load that causes software developers to lose focus and concentration while working thereby taking a toll on productivity. To investigate the disruptiveness of task switching and interruptions in software development projects, and to understand the reasons for and perceptions of the disruptiveness of task switching we used a mixed-methods approach including a longitudinal data analysis on 4,910 recorded tasks of 17 professional software developers, and a survey of 132 software developers. We found that, compared to task-specific factors (e.g. priority, level, and temporal stage), contextual factors such as interruption type (e.g. self/external), time of day, and task type and context are a more potent determinant of task switching disruptiveness in software development tasks. Furthermore, while most survey respondents believe external interruptions are more disruptive than self-interruptions, the results of our retrospective analysis reveals otherwise. We found that self-interruptions (i.e. voluntary task switchings) are more disruptive than external interruptions and have a negative effect on the performance of the interrupted tasks. Finally, we use the results of both studies to provide a set of comparative vulnerability and interaction patterns which can be used as a mean to guide decision-making and forecasting the consequences of task switching in software development teams.
High-Technology Employment and Transportation: Evidence from the European Regions

Albalate D. and Fageda X. High-technology employment and transportation: evidence from the European regions, Regional Studies. High-technology sectors are typically open to external inputs, resources and knowledge spillovers. This paper studies the impact of transportation, which is essential for providing external links to regional and global markets, on high-tech employment. It draws on a sample of 182 European regions for the period 2002–10. By implementing a dynamic panel-data estimator, it is found that the density of motorways and the number of air services promote employment growth, yet only the latter remains consistent. Interestingly, network carriers have a greater impact than low-cost carriers. In contrast, high-speed rail does not seem to impact on employment.
Geometric Algorithms with Limited Workspace: A Survey

In the limited workspace model, we consider algorithms whose input resides in read-only memory and that use only a constant or sublinear amount of writable memory to accomplish their task. We survey recent results in computational geometry that fall into this model and that strive to achieve the lowest possible running time. In addition to discussing the state of the art, we give some illustrative examples and mention open problems for further research.
Mining Timed Regular Specifications from System Traces

Temporal properties define the order of occurrence and timing constraints on event occurrence. Such specifications are important for safety-critical real-time systems. We propose a framework for automatically mining temporal properties that are in the form of timed regular expressions (TREs) from system traces. Using an abstract structure of the property, the framework constructs a finite state machine to serve as an acceptor. We analytically derive speedup for the fragment and confirm the speedup using empirical validation with synthetic traces. The framework is evaluated on industrial-strength safety-critical real-time applications using traces with more than 1 million entries.
Proteomic screening identifies the zonula occludens protein ZO-1 as a new partner for ADAM12 in invadopodia-like structures

The epithelial mesenchymal transition (EMT) is a key process for cancer cell invasion and migration. This complex program whereby epithelial tumor cells loose polarity and acquire mesenchymal phenotype is driven by the regulation of cell-cell adhesion and cell-substrate interactions. We recently described the association of ADAM12 with EMT and we now use immunoprecipitation and proteomic approaches to identify interacting partners for ADAM12 during EMT. We identify twenty proteins that are involved in molecular mechanisms associated with adhesion/invasion processes. Integrative network analyses point out the zonula occludens protein ZO-1, as a new potential partner for ADAM12. In silico screening demonstrates that ZO-1 and ADAM12 are coexpressed in breast cancer cell lines sharing EMT signature. We validate the interaction between ZO-1 and ADAM12 in invasive breast cancer cell lines and show that ZO-1 and ADAM12 co-localize in actin- and cortactin-rich structures. Silencing either ADAM12 or ZO-1 inhibits gelatin degradation demonstrating that both proteins are required for matrix degradation. We further show that matrix metalloprotease 14, known to mediate degradation of collagen in invadopodia-like structures interacts with ZO-1. Depletion of PKCε that regulates the recruitment of ADAM12 and ZO-1 to cell membranes induces a decrease in ADAM12 and ZO-1 at invadopodia-like structures and degradation activity. Together our data provide evidence for a new interaction between ADAM12, a mesenchymal marker induced during TGF-β-dependent EMT and ZO-1, a scaffolding protein expressed in tight junctions of epithelial cells, both proteins being redistributed at the invadopodia-like structures of mesenchymal invasive cells to promote PKCε-dependent matrix degradation.
Rethinking value creation from the resource based view: the case of human capital in moroccan hotels

The growth of the modern knowledge-based economy is becoming less and less dependent on tangible assets and more on intangible ones. In this context, the role of human capital in the value creation process has become central. Despite the large amount of scientific work on human capital phenomena, little research has revealed the role of human capital in the process of creating value. The purpose of this article is to evaluate the impact of human capital on value creation within 31 classified hotels in Morocco for the period 2013-2015. This paper is organized into four sections. First, we return to the main conceptualization of value creation. The goal of this first section is to synthesize prior work on this construct and highlight the main role of the resource based view (RBV) in explaining it. This view presents the point that links value creation to human capital given that this latter concept is one of the most resources of the firm. Next, we present the main definition of human capital. To do so, we make use of concepts from psychology, economy and strategic human resource management. Then, we shed light on the existing relationship between the two concepts of our research. Finally, we present the methodology of this research as well as the results. The required data to calculate value creation is obtained mainly from the annual reports of Moroccan hotels. Whereas, human capital is assessed by a questionnaire using the scale of Subramaniam and Youndt (2005). Data is examined using linear regression by PASW statistics software. The results of this study give a more concrete picture on the creation of value in this context and refute any link between these two concepts.
Adaptive User-Oriented Direct Load-Control of Residential Flexible Devices

Demand Response (DR) schemes are effective tools to maintain a dynamic balance in energy markets with higher integration of fluctuating renewable energy sources. DR schemes can be used to harness residential devices' flexibility and to utilize it to achieve social and financial objectives. However, existing DR schemes suffer from low user participation as they fail at taking into account the users' requirements. First, DR schemes are highly demanding for the users, as users need to provide direct information, e.g. via surveys, on their energy consumption preferences. Second, the user utility models based on these surveys are hard-coded and do not adapt over time. Third, the existing scheduling techniques require the users to input their energy requirements on a daily basis. As an alternative, this paper proposes a DR scheme for user-oriented direct load-control of residential appliances operations. Instead of relying on user surveys to evaluate the user utility, we propose an online data-driven approach for estimating user utility functions, purely based on available load consumption data, that adaptively models the users' preference over time. Our scheme is based on a day-ahead scheduling technique that transparently prescribes the users with optimal device operation schedules that take into account both financial benefits and user-perceived quality of service. To model day-ahead user energy demand and flexibility, we propose a probabilistic approach for generating flexibility models under uncertainty. Results on both real-world and simulated datasets show that our DR scheme can provide significant financial benefits while preserving the user-perceived quality of service.
Predictable Performance and Fairness Through Accurate Slowdown Estimation in Shared Main Memory Systems

This paper summarizes the ideas and key concepts in MISE (Memory Interference-induced Slowdown Estimation), which was published in HPCA 2013 [97], and examines the work's significance and future potential. Applications running concurrently on a multicore system interfere with each other at the main memory. This interference can slow down different applications differently. Accurately estimating the slowdown of each application in such a system can enable mechanisms that can enforce quality-of-service. While much prior work has focused on mitigating the performance degradation due to inter-application interference, there is little work on accurately estimating slowdown of individual applications in a multi-programmed environment. Our goal is to accurately estimate application slowdowns, towards providing predictable performance. To this end, we first build a simple Memory Interference-induced Slowdown Estimation (MISE) model, which accurately estimates slowdowns caused by memory interference. We then leverage our MISE model to develop two new memory scheduling schemes: 1) one that provides soft quality-of-service guarantees, and 2) another that explicitly attempts to minimize maximum slowdown (i.e., unfairness) in the system. Evaluations show that our techniques perform significantly better than state-of-the-art memory scheduling approaches to address the same problems. Our proposed model and techniques have enabled significant research in the development of accurate performance models [35, 59, 98, 110] and interference management mechanisms [66, 99, 100, 108, 119, 120].
Aire-deficient mice provide a model of corneal and lacrimal gland neuropathy in Sjögren's syndrome

Sjögren’s syndrome (SS) is a chronic, autoimmune exocrinopathy that leads to severe dryness of the mouth and eyes. Exocrine function is highly regulated by neuronal mechanisms but little is known about the link between chronic inflammation, innervation and altered exocrine function in the diseased eyes and exocrine glands of SS patients. To gain a better understanding of neuronal regulation in the immunopathogenesis of autoimmune exocrinopathy, we profiled a mouse model of spontaneous, autoimmune exocrinopathy that possess key characteristics of peripheral neuropathy experienced by SS patients. Mice deficient in the autoimmune regulator (Aire) gene developed spontaneous, CD4+ T cell-mediated exocrinopathy and aqueous-deficient dry eye that were associated with loss of nerves innervating the cornea and lacrimal gland. Changes in innervation and tear secretion were accompanied by increased proliferation of corneal epithelial basal cells, limbal expansion of KRT19-positive progenitor cells, increased vascularization of the peripheral cornea and reduced nerve function in the lacrimal gland. In addition, we found extensive loss of MIST1+ secretory acinar cells in the Aire -/- lacrimal gland suggesting that acinar cells are a primary target of the disease, Finally, topical application of ophthalmic steroid effectively restored corneal innervation in Aire -/- mice thereby functionally linking nerve loss with local inflammation in the aqueous-deficient dry eye. These data provide important insight regarding the relationship between chronic inflammation and neuropathic changes in autoimmune-mediated dry eye. Peripheral neuropathies characteristic of SS appear to be tightly linked with the underlying immunopathological mechanism and Aire -/- mice provide an excellent tool to explore the interplay between SS-associated immunopathology and peripheral neuropathy.
The First Attempt at Non-Linear in Silico Prediction of Sampling Rates for Polar Organic Chemical Integrative Samplers (POCIS)

Modeling and prediction of polar organic chemical integrative sampler (POCIS) sampling rates (Rs) for 73 compounds using artificial neural networks (ANNs) is presented for the first time. Two models were constructed: the first was developed ab initio using a genetic algorithm (GSD-model) to shortlist 24 descriptors covering constitutional, topological, geometrical and physicochemical properties and the second model was adapted for Rs prediction from a previous chromatographic retention model (RTD-model). Mechanistic evaluation of descriptors showed that models did not require comprehensive a priori information to predict Rs. Average predicted errors for the verification and blind test sets were 0.03 ± 0.02 L d–1 (RTD-model) and 0.03 ± 0.03 L d–1 (GSD-model) relative to experimentally determined Rs. Prediction variability in replicated models was the same or less than for measured Rs. Networks were externally validated using a measured Rs data set of six benzodiazepines. The RTD-model performed best in comparison to the GSD-model for these compounds (average absolute errors of 0.0145 ± 0.008 L d–1 and 0.0437 ± 0.02 L d–1, respectively). Improvements to generalizability of modeling approaches will be reliant on the need for standardized guidelines for Rs measurement. The use of in silico tools for Rs determination represents a more economical approach than laboratory calibrations.
Application of Sliding Nest Window Control Chart in Data Stream Anomaly Detection

Since data stream anomaly detection algorithms based on sliding windows are sensitive to the abnormal deviation of individual interference data, this paper presents a sliding nest window chart anomaly detection based on the data stream (SNWCAD-DS) by employing the concept of the sliding window and control chart. By nesting a small sliding window in a large sliding window and analyzing the deviation distance between the small window and the large sliding window, the algorithm increases the out-of-bounds detection ratio and classifies the conceptual drift data stream online. The designed algorithm is simulated on the industrial data stream of drilling engineering. The proposed algorithm SNWCAD is compared with Automatic Outlier Detection for Data Streams (A-ODDS) and Distance-Based Outline Detection for Data Stream (DBOD-DS). The experimental results show that the new algorithm can obtain higher detection accuracy than the compared algorithms. Furthermore, it can shield the influence of individual interference data and satisfy actual engineering needs.
Latent Variable Approach to Modelling Dependence of Credit Risks: Application to French Firms and Implications for Regulatory Capital

This paper extends the analysis in Migration Correlation: Estimation Method and Application to the French Companies Rated by the Banque de France and provides a methodology for valuing dependent defaults based on the latent variable approach. This methodology underlies all models derived from the Merton's structural model and includes in particular the Basel II proposition. The latent correlation is calibrated by developing factor models that relate changes in unobservable variable to changes in a small number of economic factors. Our model exploits the relationship between the default correlation and the latent correlation throughout the joint probability of default. Using a comprehensive rating database managed by the Banque de France, we employ this relationship to calibrate latent correlations and finally to compute credit risk charges at a portfolio level.
hBRAG, a novel B cell lineage cDNA encoding a type II transmembrane glycoprotein potentially involved in the regulation of recombination activating gene 1 (RAG1)

The different display reverse transcription‐PCR (DD RT‐PCR) technique was used to identify novel cDNA detecting mRNA transcripts co‐expressed with human recombination activating gene‐1 (RAG1). A 5.0‐kb transcript detected by the differential display amplicon 3G1 was found to correlate strongly with RAG1 mRNA expression in various human cell lines. Subsequent screenings of a pre‐B cDNA library with 3G1 led to the identification of a complete cDNA we have termed hBRAG (human B‐cell RAG‐Associated Gene). The hBRAG cDNA encodes a 503‐amino acid (aa) protein with no known homology to any nucleotide or protein sequence. The predicted molecular mass of 55 kDa was confirmed by in vitro translation. Based on sequence analysis, the predicted open reading frame encodes for a type II transmembrane spanning glycoprotein with the N‐terminal 81‐aa in the cytoplasm, a 17‐aa transmembrane domain, and a C‐terminal 405‐aa extracellular domain with four potential N‐glycosylation sites. Northern blot analysis indicated a close association of the 5.0‐kb hBRAG mRNA transcript with RAG1 in numerous human pro‐B, pre‐B and mature B cell lines assessed, but not in human T cell lines. In human tissues, hBRAG is expressed at highest levels in B cell‐enriched tissues, but is not expressed in fetal or adult thymus. Southern blotting analysis revealed that this gene is conserved across eukaryotes, is expressed as a single copy in the human genome, and is likely not a multigene family member. The hBRAG gene was localized to the long arm of chromosome 10 (10q26). Transfection of the full‐length hBRAG cDNA increased levels of human RAG1 transcripts in the B cell line OCI LY8‐C3P, but not in the non‐lymphoid line K562, suggesting a B cell‐specific role for the hBRAG product in regulating RAG expression.
Image Resolution Enhancement via Multi Surface Fitting

A new method of image resolution enhancement via multi-surface fitting is proposed. Image resolution generally results in loss of image quality. Therefore image resolution requires interpolation to read between the pixels. By the use of spatial structure information, the idea of multi-surface fitting is implemented. The fusion of multi-sampling values on these surfaces in the maximum a posteriori fashion by fitting low resolution pixels on one surface. The reconstructed high-resolution images preserve image details effectively without any hypothesis on image prior. Although the main concern of image resolution algorithm is to reconstruct HR images from under sampled LR images, it covers image restoration techniques that produce high quality images from noisy, blurred images. Therefore, the goal of image resolution techniques is to restore an HR image from several degraded and aliased LR images. The proposed system provides error-free high resolution for real images.