Miracle-dz/UniFAR-FTUs huggingface dataset:
SPC-Cre-ERT2 Transgenic Mouse for Temporal Gene Deletion in Alveolar Epithelial Cells

Although several Cre-loxP-based gene knockout mouse models have been generated for the study of gene function in alveolar epithelia in the lung, their applications are still limited. In this study, we developed a SPC-Cre-ERT2 mouse model, in which a tamoxifen-inducible Cre recombinase (Cre-ERT2) is under the control of the human surfactant protein C (SPC) promoter. The specificity and efficiency of Cre-ERT2 activity was first evaluated by crossing SPC-Cre-ERT2 mouse with ROSA26R mouse, a β-galactosidase reporter strain. We found that Cre-ERT2 was expressed in 30.7% type II alveolar epithelial cells of SPC-Cre-ERT2/ROSA26R mouse lung tissues in the presence of tamoxifen. We then tested the tamoxifen-inducible recombinase activity of Cre-ERT2 in a mouse strain bearing TSC1 conditional knockout alleles (TSC1fx/fx). TSC1 deletion was detected in the lungs of tamoxifen treated SPC-Cre-ERT2/TSC1fx/fx mice. Therefore this SPC-Cre-ERT2 mouse model may be a valuable tool to investigate functions of genes in lung development, physiology and disease.
SOEPpapers 409: Neighborhood Effects and Individual Unemployment

Using a unique dataset for Germany that links individual longitudinal data from the GSOEP to regional data from the federal employment agency and data of real estate prices, we evaluate the impact of neighborhood unemployment on individual employment propects. The panel setup and richness of the data allows us to overcome some of the identification problems which are present in this strand of literature. The empirical results indicate that there is a significant negative impact of neighborhood unemployment on the individual employment probability. JEL: J64, R23
Cloud computing in education and student's needs

Cloud computing is not just a buzz-word, it represents a strong direction of IT industry development. Speaking of cloud computing we should distinguish three different service models: Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). The scope of this work is a model of Software as a Service. This represents the lease of computing resources on a network of remote servers where applications are executed and data is stored. The application of cloud computing is very broad and growing daily because of many advantages to the users, and is driven by the increasing use of various mobile devices (laptops, tablets and smartphones) and mobile Internet access being more available. Cloud computing is applicable in education, but it implies the acceptance of these services by all involved in the educational process. Therefore, the aim of this paper is to investigate whether there is a need between our students for applications and services in the “cloud” (SaaS), the extent to which they use them and what types of applications and services are leading. The paper analyzes and interprets the results of this study which provides indications of students' willingness to “move to the cloud”.
VR Applications for reducing time and cost of Vehicle Development Process

In the last decades the competition in the automotive market, in all segments, has become very strong. This motivation has pushed all OEM (Original Equipment Manufacturers) to develop complex and high technical products, with more and more variants, that satisfy the increasing customer requirements on style, quality, safety, comfort and environmental protection. OEM have tried to shorten the time-to-market of new products in order to better interpret the voice of the customers and implement these needs in the new product. They have also redefined their Vehicle Development Process (VDP), based on the use of a digital approach in the product development. Starting from the conceptual stage of a new product, a conceptual Digital Mock-Up (DMU) of the product is built and it represents the reference model for all the following phases of VDP, down to the market launch and its use. CAE ( Computer Aided Engineering) engineers use DMU data to create their simulation models in order to analyse and monitor the performances of the new product. Another important technology is Virtual Reality (VR) that today seems to be very integrated in the VDP. In fact VR is used in the fields of Styling, DMU and Physical Mock Up (PMU), Design, Ergonomics, Simulation, Digital Plant, Marketing and Sales. The VR Centre is becoming the place where the designer chooses the car style model, where the car development team executes DMU design reviews, analyses alternative solutions and deliberates product and process validation. VR represents a user interface technology that enables the interaction of the engineer with the virtual models of the car, thanks also to the immersion feature. VR allows, in fact, intuitive analysis and simple presentation of complex three-dimensional systems. Furthermore with immersive virtual environment, ergonomist can study the “man-car-environment” interaction and evaluate the comfort of a new car. The expected benefits of using Virtual Technologies are, therefore, the reduction of development time (it enables the concurrent engineering), the reduction of development costs (better design through virtual pre-checks, less modifications and less PMUs) and increasing quality. In the following paper we will describe the current use of VR in the development of new car models.
Disco: a computing platform for large-scale data analytics

We describe the design and implementation of Disco, a distributed computing platform for MapReduce style computations on large-scale data. Disco is designed for operation in clusters of commodity server machines, and provides both a fault-tolerant scheduling and execution layer as well as a distributed and replicated storage layer. Disco is implemented in Erlang and Python; Erlang is used for the implementation of the core aspects of cluster monitoring, job management, task scheduling and distributed filesystem, while Python is used to implement the standard Disco library. Disco has been used in production for several years at Nokia, to analyze tens of terabytes of data daily on a cluster of over 100 nodes. With a small but very functional codebase, it provides a free, proven, and effective component of a full-fledged data analytics stack.
Development of an Interactive, Hands-on Learning Experience of the Google Maps API

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Agent-based modeling of language evolution

Agent-based models of language evolution have received a lot of attention in the last two decades. Researchers wish to understand the origin of language, and aim to compensate for the lacking empirical evidence by utilizing methods from computer science and artificial life. The paper looks at the main theories of language evolution: biological evolution, learning, and cultural evolution. In particular, the Baldwin effect in a naming game model is elaborated on by describing a set of experimental simulations. This is on-going work and ideas for further investigating the social aspects of language evolution are also discussed.
Bootstrapping Noun Groups Using Closed-Class Elements Only

The identification of noun groups in text is a well researched task and serves as a pre-step for other natural language processing tasks, such as the extraction of keyphrases or technical terms. We present a first version of a noun group chunker that, given an unannotated text corpus, adapts itself to the domain at hand in an unsupervised way. Our approach is inspired by findings from cognitive linguistics, in particular the division of language into open-class elements and closedclass elements. Our system extracts noun groups using lists of closed-class elements and one linguistically inspired seed extraction rule for each open class. Supplied with raw text, the system creates an initial validation set for each open class based on the seed rules and applies a bootstrapping procedure to mutually expand the set of extraction rules and the validation sets. Possibly domain-dependent information about open-class elements, as for example provided by a part-of speech lexicon, is not used by the system in order to ensure the domain-independency of the approach. Instead, the system adapts itself automatically to the domain of the input text by bootstrapping domain-specific validation lists. An evaluation of our system on the Wall Street Journal training corpus used for the CONLL 2000 shared task on chunking shows that our bootstrapping approach can be successfully applied to the task of noun group chunking.
Variables Related to Working Capability among Swiss Patients with Multiple Sclerosis—A Cohort Study

Introduction Reduced working capability is one of the most devastating consequences of multiple sclerosis (MS). We aimed to study working capability and related variables in Swiss MS patients. Materials and Methods A cross-sectional analysis of employment status and risk factors for reduced working capability among MS patients treated at our outpatient clinic. A questionnaire was mailed to 644 MS patients and returned by 69.7%. 405 patients (66% female, mean age 44.2 years (SD±10.2), median EDSS 3.0 (SD±1.8)) were eligible for subsequent analysis. Results After a mean disease duration of 12.3 years (SD±8.25), full or part time employment was declared by 26.7% and 25.7%, respectively. Incapacity to work was reported by 27.1%. A total of 52.8% specified MS as the cause for altered working capability, whereas 20.5% cited reasons unrelated to the disorder. Even with minimal disability (EDSS<3) a significant proportion of patients (24%) reported reduced working capability. Among the MS-specific restricting factors were fatigue (47.6%), sensorimotor deficits (31.1%), impaired vision (3.3%) and pain (2.8%). Conclusion MS continues to takes its toll on the professional life of the patients early in the course. While complete incapacity becomes relevant with moderate to severe disability, many patients scale down to part-time even with minimal impairment.
Multilingualism in legal space: the issue of mutual understanding in ELF communication between defendants and interpreters

ABSTRACT Owing to its economic growth and social changes in the past two decades, China has become a popular destination for tourists, investors, and diverse communities of migrants. When foreign-language-speaking migrants interact with Chinese criminal justice system, they rely on interpreters to participate in the proceedings. Based on four-month trial observations in a Chinese city that is reported to have the highest concentration of foreign migrants in the country, this paper attempts to empirically explore the communicative complexity between foreign defendants and interpreters when they use English as a lingua franca. Drawing upon discourse analysis of recordings of seven criminal hearings that involve defendants from African countries, this paper shows how intercultural communication in the legal setting becomes challenging when primary participants in the interaction have divergent linguistic repertoires and speak different varieties of English. Variations in pronunciation become barriers to intelligibility; different legal culture and legal systems further complicate mutual understanding. This paper highlights how linguistic differences in interpreter-defendant communication disadvantage defendants in participating in judicial proceedings, which may undermine their legal rights and result in inequality and injustice.
Age-Related Changes in Segmental Body Composition by Ethnicity and History of Weight Change across the Adult Lifespan

This study assessed age-related changes in body composition (specifically in trunk fat and appendicular lean masses), with consideration of body mass index (BMI) at age 20 years (BMI reference age, “BMIref”), ethnicity and lifetime weight change history. A cross-sectional dual-energy X-ray absorptiometry-based dataset was extracted from the U.S. National Health and Nutrition Examination Survey (NHANES) 1999–2004. Only European-American and African-American subjects were used (2705 men, 2527 women). For each gender and ethnicity, 6 analytic cases were considered, based on three BMIref categories (normal, overweight and obese, being 22, 27 and 30 kg/m2, respectively) and two weight contexts (stable weight or weight gain across the lifespan). A nonparametric model was developed to investigate age-related changes in body composition. Then, parametric modelling was developed for assessing BMIref- and ethnicity-specific effects during aging. In the stable weight, both genders’ and ethnicities’ trunk fat (TF) increased gradually; body fat (BF) remained stable until 40 years and increased thereafter; trunk lean (TL) remained stable, but appendicular lean (APL) and body lean (BL) declined from 20 years. In the weight gain context, TF and BF increased at a constant rate, while APL, TL and BL increased until 40–50 years, and then declined slightly. Compared with European-American subjects of both genders, African-American subjects had lower TF and BF masses. Ethnic differences in body composition were quantified and found to remain constant across the lifespan.
Decreased Cd47 Expression during Spontaneous Apoptosis Targets Neutrophils for Phagocytosis by Monocyte-derived Macrophages

a r t i c l e i n f o Background: Neutrophils (PMN) are the primary leukocyte responders during acute inflammation. After migrating into the tissues, PMN undergo programmed cell death (apoptosis) and are subsequently removed via phagocytosis by resident macrophages during the resolution phase. Efficient phagocytosis of apoptotic neutrophils is necessary for successful resolution. CD47 plays a critical role in mediating the phagocytic response, although its role in the phagocytosis of apoptotic PMN is incompletely understood. Aims: In the present study we tested the hypotheses that CD47 modulates the targeting of apoptotic PMN for phagocytosis, and that this process is altered in neonatal PMN. Study design: Adult and neonatal PMN were examined for their expression of CD47. To investigate CD47-mediated functions, apoptotic adult and neonatal PMN were co-cultured with monocyte-derived macrophages (MDM) and the phagocytic index was determined using a flow cytometry-based assay. Results: We observed lower basal surface CD47 levels on neonatal vs. adult PMN. In both groups, spontaneous apoptosis led to decreased surface and total cellular CD47 expression. Adult and neonatal MDM ingested apoptotic neonatal target PMN more avidly than apoptotic adult target PMN. Masking of surface CD47 on PMN with a monoclonal antibody enhanced MDM phagocytic activity. Conclusions: Our results suggest that age-dependent expression of CD47 on PMN may account for differences in their ingestion by macrophages and in the resolution of inflammation. Following migration into the tissues during active inflammation, PMN must be removed by resident phagocytes during the resolution phase. Resolution of inflammation involves several steps including: cessation of PMN recruitment, initiation of PMN apoptosis and clearance of apoptotic PMN by resident macrophages [1]. Impairment of one or more of these processes could potentially prolong inflammation and exacerbate host tissue injury. The process of apoptosis, in addition to initiating systematic cell death, targets PMN for removal by macrophages. If apoptotic PMN within the tissues are not removed in an efficient and timely manner, they will become necrotic and release cytotoxic granule proteins that may perpetuate host tissue damage. Thus, PMN apoptosis is a critical limiting factor for the successful resolution of inflammation. In addition, we reported that apoptotic neonatal PMN retain their potent cytotoxic phenotype [2]. It is these inherent characteristics that promote the persistence of neonatal PMN at sites of inflammation. Recent studies have uncovered three key concerted signaling mechanisms that facilitate phagocytosis of apoptotic cells. These signals, " come and get …
Gobblin: Unifying Data Ingestion for Hadoop

Data ingestion is an essential part of companies and organizations that collect and analyze large volumes of data. This paper describes Gobblin, a generic data ingestion framework for Hadoop and one of LinkedIn's latest open source products. At LinkedIn we need to ingest data from various sources such as relational stores, NoSQL stores, streaming systems, REST endpoints, filesystems, etc. into our Hadoop clusters. Maintaining independent pipelines for each source can lead to various operational problems. Gobblin aims to solve this issue by providing a centralized data ingestion framework that makes it easy to support ingesting data from a variety of sources. Gobblin distinguishes itself from similar frameworks by focusing on three core principles: generality, extensibility, and operability. Gobblin supports a mixture of data sources out-of-the-box and can be easily extended for more. This enables an organization to use a single framework to handle different data ingestion needs, making it easy and inexpensive to operate. Moreover, with an end-to-end metrics collection and reporting module, Gobblin makes it simple and efficient to identify issues in production.
Fibring Logics: Past, Present and Future

This paper is a guided tour through the theory of fibring as a general mechanism for combining logics. We present the main ideas, constructions and difficulties of fibring, from both a model and a proof-theoretic perspective, and give an outline of soundness, completeness and interpolation preservation results. Along the way, we show how the current algebraic semantics of fibring relates with the original ideas of Dov Gabbay. We also analyze the collapsing problem, the challenges it raises, and discuss a number of future research
Improving the accuracy of network intrusion detection systems under load using selective packet discarding

Under conditions of heavy traffic load or sudden traffic bursts, the peak processing throughput of network intrusion detection systems (NIDS) may not be sufficient for inspecting all monitored traffic, and the packet capturing subsystem inevitably drops excess arriving packets before delivering them to the NIDS. This impedes the detection ability of the system and leads to missed attacks. In this work we present selective packet discarding, a best effort approach that enables the NIDS to anticipate overload conditions and minimize their impact on attack detection. Instead of letting the packet capturing subsystem randomly drop arriving packets, the NIDS proactively discards packets that are less likely to affect its detection accuracy, and focuses on the traffic at the early stages of each network flow. We present the design of selective packet discarding and its implementation in Snort NIDS. Our experiments show that selective packet discarding significantly improves the detection accuracy of Snort under increased traffic load, allowing it to detect attacks that would have otherwise been missed.
IMPLICATIONS OF CHANGES IN INFORMATION TECHNOLOGY FOR CORPORATE STRATEGY

Management in the 1990s is an industry and governmental agency supported research program. Its aim is to develop a better understanding of the managerial issues of the 1990s and how to deal most effectively with them, particularly as these issues revolve around anticipated advances in Information Technology. Assisting the work of the Sloan School scholars with financial support and as working partners in research are: The conclusions or opinions expressed in this paper are those of the author(s) and do not necessarily reflect the opinion of the Massachussetts Institute of Technology, the Management in the 1990s Research Program, or its sponsoring organizations. Introduction This paper is deliberately narrowly focused. It does not deal with a large number of important issues in the fascinating and constantly evolving field of corporate strategy. It contributes, as do the other papers in this issue, to the mosaic which somehow defines the elusive concept of corporate strategy. As is so often true in emerging fields, no one has yet been able to define the concept and identify the elements in a way that is satisfactory to all people who consider themselves to be in the field. Nonetheless, the substantive work represented by all the articles in this issue attests to the constantly evolving nature of the field and each contributes to this evolution. The work discussed in this paper is a small piece of the strategic planning domain and deals not at all with the process of planning but rather with one piece of substantive content that organizations are using to create strategic moves that will help them deal successfully with the future. The work discussed here is part of a project that is ongoing in the Sloan School. It logically follows from Chandler's 5 classic study "Strategy and Structure" written at MIT in 1962. Chandler's book, which has been through eleven printings in the intervening years, is an example of the richness and complexity of the field of corporate strategy. -2-In this work, among other things, Chandler developed omne of the first notions of causality and balance in organizational processes and structure. He observed that in his sample of organizations the organization structure of the firm was changed to follow the strategy the firm was pursuing. For example, as executives at DuPont in 1919 decided on a strategy of aggressively extending their business out of munitions and into industrial chemicals they changed DuPont's organization structure …
Reduce Meaningless Words for Joint Chinese Word Segmentation and Part-of-speech Tagging

Conventional statistics-based methods for joint Chinese word segmentation and part-of-speech tagging (S&T) have generalization ability to recognize new words that do not appear in the training data. An undesirable side effect is that a number of meaningless words will be incorrectly created. We propose an effective and efficient framework for S&T that introduces features to significantly reduce meaningless words generation. A general lexicon, Wikepedia and a large-scale raw corpus of 200 billion characters are used to generate word-based features for the wordhood. The word-lattice based framework consists of a character-based model and a word-based model in order to employ our word-based features. Experiments on Penn Chinese treebank 5 show that this method has a 62.9% reduction of meaningless word generation in comparison with the baseline. As a result, the F1 measure for segmentation is increased to 0.984.