Miracle-dz/UniFAR-FTUs huggingface dataset:
New CrH Opacities for the Study of L and Brown Dwarf Atmospheres

In this paper, we calculate new line lists and opacities for the 12 bands of the A 6Σ+-X 6Σ+ transitions of the CrH molecule. Identified in objects of the new L dwarf spectroscopic class (many of which are brown dwarfs), as well as in sunspots, the CrH molecule plays an important role in the diagnosis of low-temperature atmospheres. As a tentative first application of these opacities, we employ our new theoretical CrH data in an atmospheres code to obtain a CrH/H2 number ratio for the skin of the L5 dwarf 2MASSI J1507038-151648 of ~(2-4) × 10-9, in rough agreement with chemical equilibrium expectations. Since in previous compilations the oscillator strength was off by more than an order of magnitude, this agreement represents a modest advance. However, in order to fit the CrH abundance in the L dwarf spectral class, silicate clouds need to be incorporated into the model. Given that this subject is still in a primitive stage of development, one should view any spectral model in the L dwarf range as merely tentative. Nevertheless, a necessary first step in L dwarf modeling is a reliable CrH opacity algorithm, and this is what we have here attempted to provide.
Proteases at work: cues for understanding neural development and degeneration

Proteolytical processing of membrane bound molecules is a fundamental mechanism for the degradation of these proteins as well as for controlling cell-to-cell communication, which is at the basis of tissue development and homeostasis. Members of families of metalloproteinases and intra-membrane proteases are major effectors of these events. A recent workshop in Baeza, Spain, was devoted to discuss how this mechanism coordinates brain development and how its dysfunction leads to brain pathologies. Herein we summarize the findings presented during this workshop, which illuminate the role of metalloproteinases, including matrix metalloproteinase, A Disintegrin and Metalloproteinase-proteases and intra-membrane proteases, in the regulation of neurogenesis, axon guidance, and synaptogenesis as well as in neurodegeneration. Indeed, there is increasing evidence that proteolysis at the membrane is directly linked to neuropathologies such as Alzheimer Disease and autism spectrum or prion disorders. These proteolytic events are tightly regulated and we are just at the beginning of understanding how these processes could be exploited to design therapeutic treatments aimed at alleviating psychiatric and neurodegenerative pathologies.
Test automation for kernel code and disk arrays with virtual devices

In this work, we discuss testing automation issues for kernel code on a high-capacity network-attached storage (NAS) in early development phases when the hardware may not be ready. We propose to construct a high-fidelity versatile emulator for hard disks for the fast configuration of virtual disk arrays. To test kernel libraries, we not only have to figure out the proper values for the kernel procedure parameters, but also have to overcome the rigid resource limitations in kernel space. We propose techniques to profile kernel procedure parameters, drive the kernel procedures from the user space, and construct the testing interface between kernel SUTs (software-under-test) and user space test plans. We have experimented to test the multiple devices driver library used in the NAS server by Quanta Computer Inc. Our techniques support rapid NAS configurations and have been proven useful in locating a proven bug in the Linux kernel
Joint Link Prediction in Temporal Networks

Predicting the evolution of a network through time – how a network adds or removes edges – is a challenging task that has had limited exploration. Keeping with the established link prediction problem, we expand upon previous efforts to predict which nodes will gain or lose their edges at a later point in time. We develop more complex metrics to identify how topographical features of a graph can suggest its evolution. Most importantly, we remove the assumption that edges of a graph form independent of each other and attempt to predict links jointly.
DNS Prefetching and Its Privacy Implications: When Good Things Go Bad

A recent trend in optimizing Internet browsing speed is to optimistically pre-resolve (or prefetch) DNS resolutions. While the practical benefits of doing so are still being debated, this paper attempts to raise awareness that current practices could lead to privacy threats that are ripe for abuse. More specifically, although the adoption of several browser optimizations have already raised security concerns, we examine how prefetching amplifies disclosure attacks to a degree where it is possible to infer the likely search terms issued by clients using a given DNS resolver. The success of these inference attacks relies on the fact that prefetching inserts a significant amount of context into a resolver's cache, allowing an adversary to glean far more detailed insights than when this feature is turned off.
iPreviews : Abstracting Multimedia Content Collaboratively in Peer-to-Peer Networks

Users need an attractive mean of retrieving movies of choice from VOD providers that provide thousands of digital movies. The paper presents a framework within peer-to-peer recommenders system to recommend personalized movie trailer, thereby condensing digital content, by using a novel collaborative algorithm. Personalized trailers can provide abstracted and succinct representation of digital movies through a combination of video segments. Movie previews that match user’s tastes tend to stimulate online movie-buying, enrich the users’ experience and improve content providers business. Further, we use a distributed incentive scheme for collaborating users, in which users obtain incentive that is proportional to user’s contribution in content preview development. Our work builds upon prior research on recommender systems, by adding information in recommendation list exchanges rather than specifically focusing on the accuracy of individual recommendations. Our pilot analysis showed the merits of our approach. We present simulation based on Matlab to show results of our novel model.
Dietary Intake of Carotenoids and Their Antioxidant and Anti-Inflammatory Effects in Cardiovascular Care

Cardiovascular disease related to atherosclerosis represents nowadays the largest cause of morbidity and mortality in developed countries. Due to inflammatory nature of atherosclerosis, several studies had been conducted in order to search for substances with anti-inflammatory activity on arterial walls, able to exert beneficial roles on health. Researches investigated the role of dietary carotenoids supplementation on cardiovascular disease, due to their free radicals scavenger properties and their skills in improving low-density lipoprotein cholesterol resistance to oxidation. Nevertheless, literature data are conflicting: although some studies found a positive relationship between carotenoids supplementation and cardiovascular risk reduction, others did not find any positive effects or even prooxidant actions. This paper aimed at defining the role of carotenoids supplementation on cardiovascular risk profile by reviewing literature data, paying attention to those carotenoids more present in our diet (β-carotene, α-carotene, β-cryptoxanthin, lycopene, lutein, zeaxanthin, and astaxanthin).
Performance Improvement Technique in Column-Store

Column-oriented database has gained popularity as Data Warehousing data and performance issues for Analytical Queries have increased. Each attribute of a relation is physically stored as a separate column, which will help analytical queries to work fast. The overhead is incurred in tuple reconstruction for multi attribute queries. Each tuple reconstruction is joining of two columns based on tuple IDs, making it significant cost component. For reducing cost, physical design have multiple presorted copies of each base table, such that tuples are already appropriately organized in different orders across the various columns. This paper proposes a novel design, called partitioning, that minimizes the tuple reconstruction cost. It achieves performance similar to using presorted data, but without requiring the heavy initial presorting step. In addition, it handles dynamic, unpredictable workloads with no idle time and frequent updates. Partitioning provides the direct loading of the data in respective partitions. Partitions are created on the fly and depend on distribution of data, which will work nicely in limited storage space environments. General Terms: Algorithms, Performance, Design
An Othello evaluation function based on Temporal Difference Learning using probability of winning

This paper presents a new reinforcement learning method, called temporal difference learning with Monte Carlo simulation (TDMC), which uses a combination of Temporal Difference Learning (TD) and winning probability in each non-terminal position. Studies on self-teaching evaluation functions as applied to logic games have been conducted for many years, however few successful results of employing TD have been reported. This is perhaps due to the fact that the only reward observable in logic games is their final outcome, with no obvious rewards present in non-terminal positions. TDMC(lambda) attempts to compensate this problem by introducing winning probabilities, obtained through Monte Carlo simulation, as substitute rewards. Using Othello as a testing environment, TDMC(lambda), in comparison to TD(lambda), has been seen to yield better learning results.
Under the microscope: factors influencing student outcomes in a computer integrated classroom

Researchers continue to argue that more research is needed concerning how teachers actually integrate instructional technology into their curriculum. This qualitative study examined the incorporation of interactive multimedia science software into a grade two classroom over a six-week period. There was growth in various social and thinking skills that were developed and reinforced within the computer-supported learning environment. Several factors that contributed to these outcomes are identified: the software's instructional design, enthusiasm, on-task behavior, cooperation and collaboration among the students, improved cognitive learning outcomes, attitudes toward science, the teacher's pedagogical approach and attitudes toward incorporating technology into the curriculum, and an integrated curriculum. In addition, the results indicated increased positive attitudes to-wards science by the girls after using the software. Implications for computer integration are provided.
AN INTEGRATED FEATURE SELECTION STRATEGY FOR MONOCULAR SLAM

For feature-based monocular bearing-only SLAM, how to select useful features for SLAM process is crucial. The reason is overwhelming feature number will not only seriously slow down the system but produce erroneous SLAM result due to feature mismatching. In this paper, we propose a novel method for feature selection. The method combines both bottom-up (visual saliency) and top-down (learned object database) approaches to select versatile features. We argue that using human’s visual saliency to guide the robot’s visual SLAM feature selection is practicable. The experimental result after 10 runs attested our perspective. Compared with SLAM without feature selection, the running time here is reduced to 62% and the localization errors in the SLAM process decrease to 89% in mean and 89% in standard deviation.
The action synergies: Building blocks for understanding human behavior

Social signal processing is an emerging field that gains more and more attention. As a key element in the field, visual perception of human motion is important for understanding human behavior in social intelligence. Motivated by the hypothesis of muscle synergies, we proposed action synergies for automatically partitioning human motion into individual action segments in videos. Assuming the size of the human subject is reasonable and the background changes smoothly, the video sequence is represented by six latent variables, which we obtain using Gaussian Process Dynamical Models (GPDM). For each variable, the third order derivative and its local maxima are computed. Then by finding the consistent local maxima in all variables, the video is partitioned into action segments. We demonstrate the usefulness of the algorithm for periodic motion patterns as well as non-periodic ones, using videos of various qualities. Results show that the proposed algorithm partitions videos into meaningful action segments.
The beginnings of crop phosphoproteomics: exploring early warning systems of stress

This review examines why a knowledge of plant protein phosphorylation events is important in devising strategies to protect crops from both biotic and abiotic stresses, and why proteomics should be included when studying stress pathways. Most of the achievements in elucidating phospho-signaling pathways in biotic and abiotic stress are reported from model systems: while these are discussed, this review attempts mainly to focus on work done with crops, with examples of achievements reported from rice, maize, wheat, grape, Brassica, tomato, and soy bean after cold acclimation, hormonal and oxidative hydrogen peroxide treatment, salt stress, mechanical wounding, or pathogen challenge. The challenges that remain to transfer this information into a format that can be used to protect crops against biotic and abiotic stresses are enormous. The tremendous increase in the speed and ease of DNA sequencing is poised to reveal the whole genomes of many crop species in the near future, which will facilitate phosphoproteomics and phosphogenomics research.
User Interfaces for the Digital Home on the basis of Open Industrial Standards

In this paper we describe the design, development and evaluation of user interfaces for a modern digital home based on the ISO/IEC 24752 standard: Universal Remote Console—URC. Two target groups were addressed: seniors aged 65 years and above and people suffering from Alzheimer’s disease. Our goal is to design user interfaces (UI) for our target groups that make use of all available modalities, such as, graphics, voice, and video. We provide a set of recommendations and design patterns for developing UIs for seniors and Alzheimer’s disease patients. We present the results of tests of user interfaces designed for smart home environment.
Quantifying EEG synchrony using copulas

In this paper, we consider the problem of quantifying synchrony between multiple simultaneously recorded electroencephalographic signals. These signals exhibit nonlinear dependencies and non-Gaussian statistics. A copula based approach is presented to model the joint statistics. We then consider the application of copula derived synchrony measures for early diagnosis of Alzheimer's disease. Results on real data are presented.
Research in and through design: an interaction design research approach

This paper presents and discusses an approach to interaction design research entitled research in and through design. This denotes the study of the design process through the active involvement of the researcher in experimental design activities. The approach is exemplified by a case in which interaction design researchers engaged in the development of an interactive façade in order to generate insights into how to plan and carry out design for this type of interactive systems. This is followed by a discussion of the criteria by which the process and outcomes of research in and through design can be evaluated.
Leadership in Higher Education: The CIO Role and the Leadership Team.

In this study, I focus on higher education CIOs, their role in the organization, and how this role differs when the CIO is a member of the executive leadership team. Four hundred fifty (450) CIOs of mid-sized, private four-year colleges received a survey, and 51 respondents provided information about their role and perspectives. I interviewed six CIOs on the president's cabinet and six not on the president's cabinet, and used qualitative analysis to compare experiences of individuals in the two case groups. CIOs on the leadership team described different opportunities and approaches than CIOs not on the leadership team. Both groups reported significant benefit to being on the president's cabinet but cited the role of the president or supervisor as being more important.
A top-down driven, object-based approach to application-specific operating system design

Today, interconnected workstations provide sufficient computing power to execute complex distributed applications. But programming distributed applications is still a cumbersome and error prone task. Hence, bridging the gap between application programmers and hardware to provide completely transparent resource management is still a great challenge for operating system designers. We will present a top-down driven language-based approach to integrate application development and operating system design. Our approach results in a system which overcomes many deficiencies of existing systems. The system offers adaptable application programming interfaces as well as adaptive, distributed and transparent resource management services. <<ETX>>
CSMD: a context-based scheme for multimedia delivery in ubiquitous computing environment

A robust solution for context-aware multimedia delivery in the ubiquitous computing environment remains a challenging problem. Its heterogeneous and dynamic nature demands a more flexible and intelligent framework than Internet does. We propose a layered middleware solution to address this issue. The system responds to the condition of the network to offer extensibility and efficiency. Furthermore, we propose an active controlling scheme, in which the multimedia delivery is able to adapt to the environment variation in a timely fashion. In addition, we describe an application scenario of our framework, which opens out a wide prospect.
Towards a Hybrid Imputation Approach Using Web Tables

Data completeness is one of the most important data quality dimensions and an essential premise in data analytics. With new emerging Big Data trends such as the data lake concept, which provides a low cost data preparation repository instead of moving curated data into a data warehouse, the problem of data completeness is additionally reinforced. While traditionally the process of filling in missing values is addressed by the data imputation community using statistical techniques, we complement these approaches by using external data sources from the data lake or even the Web to lookup missing values. In this paper we propose a novel hybrid data imputation strategy that, takes into account the characteristics of an incomplete dataset and based on that chooses the best imputation approach, i.e. either a statistical approach such as regression analysis or a Web-based lookup or a combination of both. We formalize and implement both imputation approaches, including a Web table retrieval and matching system and evaluate them extensively using a corpus with 125M Web tables. We show that applying statistical techniques in conjunction with external data sources will lead to a imputation system which is robust, accurate, and has high coverage at the same time.
Design and Realization of On-line Bank Customer Management System Based on Mainframe

The paper proposed a system which combined on-line bank system with the customer relationship management system (CRM) for the bank to search trace and analyze every customer through the internet in the most convenient way. History record is used to get a general idea of the customer behavior and to dig the customer need. In this way, it can reduce much time that disturb the customer, to win a greater satisfaction of the customers. The system achieves the functions of a basic on-line payment business, customer information management, customer complaints management, customer allocation levels, personalized custom services and customer information analysis. The system uses the loosely coupled SOA solutions. The core business-critical applications run on the traditional mainframe platform, the other expansion of the application build on open platform. Data, business and logic are completely independent, so it is easy to maintain and extend for the system.
Growth and Disparity: A Decade of U.S. Public School Construction.

Under the leadership of the 21st Century School Fund and with support from the Ford Foundation, a group of local and national organizations working to improve public school facilities created Building Educational Success Together (BEST) in 2001. BEST is dedicated to identifying, developing and sharing experience and knowledge about policy and practices, to improve public school facilities but also to promote educational quality and community vitality.
A comparative analysis of current mode control techniques used in high power factor boost rectifier for electric/hybrid vehicle

This project proposes current mode control techniques for high power factor operation of boost rectifier. The current mode control techniques are linear peak current mode control (LPCM),non-linear carrier (NLC) and predictive switching modulator (PSM). The steady state stability analysis of the boost rectifier with the proposed switching modulators is analyzed and compared in this paper. The proposed modulators are realized by using a single-phase diode rectifier bridge with a Boost dc-dc converter for active power factor correction (PFC). The three current mode control techniques are simulated in MATLAB/ Simulink. Based on results, Predictive Switching Modulator(PSM)is considered as better modulator for improving power factor of Boost D.C- D.C converter.
Human sensitivity to face statistics computed on V1 similarity

In a biologically motivated recognition system we represent face images as convolution values with a set of multiscale and multiorientation Gabor wavelets (a simple model of V1). Based on their discriminative power on recognition tasks various face images were reconstructed from the Gabor wavelet representation to test whether the computed statistics had any psychophysical relevance. The result of our experiments indicate that human performance is sensitive to statistical information derived from our recognition system. The study provides evidence that higher face recognition areas, such as FFA in humans, potentially not only preserve, but also compute upon earlier V1 similarity space.