Miracle-dz/UniFAR-FTUs huggingface dataset:
Just Turn on the Faucet: A Content Analysis of PSAs About the Global Water Crisis on YouTube

ABSTRACT Water is essential for human life, yet safe drinking water is a limited resource. Critical to fighting the global water crisis are public awareness campaigns, including Public Service Announcements (PSAs). While YouTube has become a popular medium for disseminating prosocial content such as PSAs, environmental communication efforts on this platform remain largely uninvestigated. This study examines the content and characteristics of global water crisis PSAs on YouTube by applying two communication models: the Extended Parallel Process Model, and the Elaboration Likelihood Model. These models are used to evaluate the potential effectiveness of the PSAs. Content analysis reveals that threat messages often outweigh efficacy messages in the videos, central route processing cues are more prevalent than peripheral route cues, and a focus on quality or quantity issues differed by sponsoring organization (non-profit, for-profit, government). Implications and avenues for potential future research are discussed.
Globally maximizing, locally minimizing: Regularized Nonnegative Matrix Factorization for hyperspectral data feature extraction

In order to find a compact representation which uncovers the hidden topics and simultaneously respects the intrinsic geometric structure of hyperspectral data, a novel algorithm, named GLNMF (Globally maximizing, Locally minimizing, regularized Nonnegative Matrix Factorization) feature extraction algorithm, is proposed. The proposed algorithm is a linear approximation of a multi-manifolds-based learning framework which imposes an additional constraint on NMF that both the local and non-local quantities are considered. GLNMF characterizes the local scatter as well as the non-local scatter, seeking to find a projection that simultaneously maximizes the non-local scatter and minimizes the local scatter. This characteristic makes GLNMF more intuitive and more powerful than some up-to-date methods. An iterative multiplicative updating algorithm is proposed to optimize the objective. Experiments on a benchmark hyperspectral dataset demonstrate that the proposed method outperforms NMF as well as a few current dimensionality reduction methods.
Quantum-mechanical calculation of ionization potential lowering in dense plasmas

The charged environment within a dense plasma leads to the phenomenon of ionization potential depression (IPD) for ions embedded in the plasma. Accurate predictions of the IPD effect are of crucial importance for modeling atomic processes occurring within dense plasmas. Several theoretical models have been developed to describe the IPD effect, with frequently discrepant predictions. Only recently, first experiments on IPD in Al plasma have been performed with an x-ray free-electron laser (XFEL), where their results were found to be in disagreement with the widely-used IPD model by Stewart and Pyatt. Another experiment on Al, at the Orion laser, showed disagreement with the model by Ecker and Kr\"oll. This controversy shows a strong need for a rigorous and consistent theoretical approach to calculate the IPD effect. Here we propose such an approach: a two-step Hartree-Fock-Slater model. With this parameter-free model we can accurately and efficiently describe the experimental Al data and validate the accuracy of standard IPD models. Our model can be a useful tool for calculating atomic properties within dense plasmas with wide-ranging applications to studies on warm dense matter, shock experiments, planetary science, inertial confinement fusion and studies of non-equilibrium plasmas created with XFELs.
Isotopic evolution of snowmelt 1. A physically based one‐dimensional model

The 18O/16O ratio of snowmelt from a seasonal snowpack typically increases with time as the melting process progresses. This temporal evolution is caused by isotopic exchange between liquid and ice as meltwater percolates down the snow column. Consequently, hydrograph separations of spring runoff using the bulk snow composition as the new water end‐member will be erroneous. Accurate determinations of the new water input should take into account the temporal variation of the snowmelt. Here we present a one‐dimensional (1‐D) physically based model for the isotopic evolution of snowmelt. Two parameters, the effective rate of isotopic exchange between water and ice and the ice to liquid ratio of the exchange system, are important for controlling the range and temporal pattern of the isotopic variation in snowmelt. For all plausible values of these parameters the modeled isotopic signature of snowmelt changes by 1–4‰ as snowmelt progresses. These isotopic shifts will affect the results of hydrograph separations.
DISP: Practical, efficient, secure and fault-tolerant distributed data storage

DISP is a practical client-server protocol for the distributed storage of immutable data objects. Unlike most other contemporary protocols, DISP permits applications to make explicit tradeoffs between total storage space, computational overhead, and guarantees of availability, integrity, and privacy on a per-object basis. Applications specify the degree of redundancy with which each item is encoded, what level of integrity checks are computed and stored with each item, and whether items are stored in an encrypted format. At one extreme, clients willing to pay the overhead are guaranteed privacy, integrity, and availability of data stored in the system as long as fewer than half the servers are Byzantine. At the other extreme, objects that do not require privacy or integrity in the face of Byzantine servers can be stored with very low computational and storage overhead.DISP is efficient in terms of message count, message size, and storage requirements: even in the worst case, the read and write protocols require a number of messages that are linear with respect to the number of servers. In terms of message size, DISP requires transferring only marginally more than L bytes to correctly read an object of size L, even in the face of Byzantine server failures. In this article we provide a description of DISP and an analysis of its fault-tolerant properties. We also analyze the complexity of the protocol and discuss several potential applications. We conclude with a description of our prototype implementation and measurements of its performance on commodity hardware.
Intergalactic absorption and blazar gamma-ray spectra

The distribution of TeV spectral slopes versus redshift for currently known TeV blazars (16 sources with z ≤ 0.21, and one with z > 0.25) is essentially a scatter plot with hardly any hint of a global trend. We suggest that this is the outcome of two combined effects of intergalactic γγ absorption, plus an inherent feature of the SSC (synchro-self-Compton) process of blazar emission. First, flux dimming introduces a bias that favors detection of progressively more flaring sources at higher redshifts. According to mainstream SSC models, more flaring source states imply sources with flatter TeV slopes. This results in a structured relation between intrinsic TeV slope and redshift. The second effect, spectral steepening by intergalactic absorption, affects sources progressively with distance and effectively wipes out the intrinsic slope-redshift correlation.
Multicore computing--the state of the art

This document presents the current state of the art in multicore computing, in hardware and software, as well as ongoing activities, especially in Sweden. To a large extent, it draws on the presentations given at the Multicore Days 2008 organized by SICS, Swedish Multicore Initiative and Ericsson Software Research but the published literature and the experience of the authors has been equally important sources. It is clear that multicore processors will be with us for the foreseeable future; there seems to be no alternative way to provide substantial increases of microprocessor performance in the coming years. While processors with a few (2–8) cores are common today, this number is projected to grow as we enter the era of manycore computing. The road ahead for multicore and manycore hardware seems relatively clear, although some issues like the organization of the on-chip memory hierarchy remain to be settled. Multicore software is however much less mature, with fundamental questions of programming models, languages, tools and methodologies still outstanding.
Biomechanics of vascular mechanosensation and remodeling

Flowing blood exerts a frictional force, fluid shear stress (FSS), on the endothelial cells that line the blood and lymphatic vessels. The magnitude, pulsatility, and directional characteristics of FSS are constantly sensed by the endothelium. Sustained increases or decreases in FSS induce vessel remodeling to maintain proper perfusion of tissue. In this review, we discuss these mechanisms and their relevance to physiology and disease, and propose a model for how information from different mechanosensors might be integrated to govern remodeling.
Teach and try: A simple interaction technique for exploratory data modelling by end users

The modern economy increasingly relies on exploratory data analysis. Much of this is dependent on data scientists - expert statisticians who process data using statistical tools and programming languages. Our goal is to offer some of this analytical power to end-users who have no statistical training through simple interaction techniques and metaphors. We describe a spreadsheet-based interaction technique that can be used to build and apply sophisticated statistical models such as neural networks, decision trees, support vector machines and linear regression. We present the results of an experiment demonstrating that our prototype can be understood and successfully applied by users having no professional training in statistics or computing, and that the experience of interacting with the system leads them to acquire some understanding of the concepts underlying exploratory statistical modelling.
Growth Patterns of Signet Ring Cell Carcinoma of the Stomach for Endoscopic Resection

Background/Aims It is difficult to precisely detect the lateral margin during endoscopic submucosal dissection (ESD) for signet ring cell carcinoma (SRC) because SRC often expands to lateral direction through the lamina propria. Thus, the aim of this study was to classify the intramucosal spreading patterns of SRC and to analyze the patients’ clinicopathological findings according to the spreading patterns. Methods The intramucosal spreading patterns of SRC were classified as expansive or infiltrative types. A total of 100 surgical and 42 ESD specimens were reviewed. Results In the surgical specimens, the proportions of expansive and infiltrative types were 44% and 56%, respectively. The infiltrative type was more commonly associated with old age, atrophy, and intestinal metaplasia in surrounding mucosa and the absence of Helicobacter pylori compared with the expansive type. In ESD specimens, the proportions of expansive and infiltrative types were each 50%. When lateral margin-positive lesions were compared with -negative lesions, larger size, residual lesion, and the lack of a neutrophil infiltration were more significantly associated with lateral margin-positive lesions. All cases with residual tumors in lateral margin-positive lesions were classified as the infiltrative type. Conclusions SRC surrounded with atrophy and/or intestinal metaplasia often spreads subepithelially in the margin. This finding may suggest that a larger safety margin is necessary in this type during ESD.
Sensor fusion for airborne 3D data capture

One of the major tasks for the rectification and mono-plotting of remote sensing data and photogrammetric images is the determination of a digital terrain model (DTM). With the advent of airborne laser range scanners the direct acquisition of DTMs became feasible. In order to determine the terrain surface the distance data provided by a laser scanner have to be georeferenced. Within this step, the exterior orientation (position, attitude) of the laser scanner at the time of measurement is determined by a combined CPS/INS sensor system. Additionally overlapping strips of range data are matched. Thus the system is callibrated and remaining errors e.g. caused by misalignment of the different sensor components can be corrected. This paper is focused on the description of the concept and the components of an integrated airborne laser ranging system. Especially, the GPS/INS part for determination of the exterior orientation of the laser scanner and the calibration routine for the acquired laser data will be briefly reviewed and demonstrated. 9 refs., 5 figs., 3 tabs.
Clinical and developmental profile of children with Autism

Background: Autism spectrum disorders (ASD) are neurodevelopmental disorders characterized by deficits in reciprocal social interaction as well as communication and a restrictive repertoire of activities. Indian studies on this subject have been few. Objectives: The aim of this study was to assess clinical characteristics of children with ASD in Indian scenario. Methods: We conducted a cross-sectional observational survey in special schools involving diagnosed autistic children, and their parents using a pretested standardized questionnaire based on diagnostic and statistical manual IV criteria. Results: Males (n=25) outnumbered the females (n=11). Only 6 cases (16.7%) were diagnosed as autistic before 3 years of age. 39% cases were detected between ages of 3 and 4.11 years. 22% cases were diagnosed in each of 5-6.11 years and 7 years and above category. The must watch behavior characteristics that our study found were impaired eye to eye gaze, impaired peer relationships, poor facial expressions, language delay, lack of pretend play, and inflexible adherence to rituals. Conclusion: Clinicians should be educated and encouraged to make timely diagnosis of ASD so as to initiate early interventions for these children.
Design of High-speed low power Reversible Logic BCD Adder Using HNG gate

Reversibility plays a fundamental role when computations with minimal energy dissipation are considered. In recent years, reversible logic has emerged as one of the most important approaches for power optimization with its application in low power CMOS, optical information processing, quantum computing and nanotechnology. This research proposes a new implementation of Binary Coded Decimal (BCD) adder in reversible logic. The design reduces the number of gate operations compared to the existing BCD adder reversible logic implementations. So, this design gives rise to an implementation with a reduced area and delay. We can use it to construct more complex systems in
Portability Analysis for Axiomatic Memory Models. PORTHOS: One Tool for all Models

We present PORTHOS, the first tool that discovers porting bugs in performance-critical code. PORTHOS takes as input a program, the memory model of the source architecture for which the program has been developed, and the memory model of the targeted architecture. If the code is not portable, PORTHOS finds a porting bug in the form of an unexpected execution - an execution that is consistent with the target but inconsistent with the source memory model. Technically, PORTHOS implements a bounded model checking method that reduces portability analysis to the satisfiability modulo theories (SMT) problem with integer difference logic. There are two problems in the reduction that are unique to portability and that we present novel and efficient solutions for. First, the formulation of portability contains a quantifier alternation (consistent + inconsistent). We encode inconsistency as an existential query. Second, the memory models may contain recursive definitions. We compute the corresponding least fixed points efficiently in SMT. Interestingly, we are able to prove that our execution-based notion of portability is the most liberal one that admits an efficient algorithmic analysis: for state-based portability, a polynomial SAT encoding cannot exist. Experimentally, we applied PORTHOS to a number of case studies. It is able to check portability of non-trivial programs between interesting architectures. Notably, we present the first algorithmic analysis of portability from TSO to Power.
Integrating Heterogeneous Knowledge with FrameBase

Large-scale knowledge graphs such as those in the Linked Data cloud are typically represented as subject-predicateobject triples. However, many facts about the world involve more than two entities. While n-ary relations can be converted to triples in a number of ways, unfortunately, the structurally different choices made in different knowledge sources significantly impede our ability to connect them. They also increase semantic heterogeneity, making it impossible to query the data concisely and without prior knowledge of each individual source. This article presents FrameBase, a wide-coverage knowledge-base schema that uses linguistic frames to represent and query n-ary relations from other knowledge bases, providing also different levels of granularity connected by logical entailment. This altogether provides for flexible and expressive seamless semantic integration from heterogeneous sources. It also opens possibilities to draw on natural language processing techniques for querying and data mining.
Measure for degree heterogeneity in complex networks and its application to recurrence network analysis

We propose a novel measure of degree heterogeneity, for unweighted and undirected complex networks, which requires only the degree distribution of the network for its computation. We show that the proposed measure can be applied to all types of network topology with ease and increases with the diversity of node degrees in the network. The measure is applied to compute the heterogeneity of synthetic (both random and scale free (SF)) and real-world networks with its value normalized in the interval [0,1]. To define the measure, we introduce a limiting network whose heterogeneity can be expressed analytically with the value tending to 1 as the size of the network N tends to infinity. We numerically study the variation of heterogeneity for random graphs (as a function of p and N) and for SF networks with γ and N as variables. Finally, as a specific application, we show that the proposed measure can be used to compare the heterogeneity of recurrence networks constructed from the time series of several low-dimensional chaotic attractors, thereby providing a single index to compare the structural complexity of chaotic attractors.
Revisiting the Cache Interference Costs of Context Switching

The high cost of context switching is one reason that operating system performance is not keeping pace with hardware improvements. Besides the cost of saving and restoring registers, another component of context switch cost is the cache interference between multiple processes sharing the same cache. We measured kernel on user, user on kernel, and user on user cache interference from context switching using a complete machine simulator. While the resulting cache interference is noticeable, the time between process switches is generally sufficient to amortize this cost over a large number of instructions. Completely eliminating all context-switch cache interference would therefore have a minimal impact on total execution time.
The Novel Design for Global Stabilization of a Class of Complex Lower-Triangular Systems

A novel design method is proposed to solve the problem of global asymptotic stabilization for the nonlinear systems in high-order lower-triangular form via recursive design procedure, with one common assumption. This new approach simplifies the design process of the class of complex lower-triangular systems. Furthermore, the practical example and simulation are provided to show the effectiveness of the design method.
MyTrackingChoices: Pacifying the Ad-Block War by Enforcing User Privacy Preferences

Free content and services on the Web are often supported by ads. However, with the proliferation of intrusive and privacy-invasive ads, a significant proportion of users have started to use ad blockers. As existing ad blockers are radical (they block all ads) and are not designed taking into account their economic impact, ad-based economic model of the Web is in danger today. In this paper, we target privacy-sensitive users and provide them with fine-grained control over tracking. Our working assumption is that some categories of web pages (for example, related to health, religion, etc.) are more privacy-sensitive to users than others (education, science, etc.). Therefore, our proposed approach consists in providing users with an option to specify the categories of web pages that are privacy-sensitive to them and block trackers present on such web pages only. As tracking is prevented by blocking network connections of third-party domains, we avoid not only tracking but also third-party ads. Since users will continue receiving ads on web pages belonging to non-sensitive categories, our approach essentially provides a trade-off between privacy and economy. To test the viability of our solution, we implemented it as a Google Chrome extension, named MyTrackingChoices (available on Chrome Web Store). Our real-world experiments with MyTrackingChoices show that the economic impact of ad blocking exerted by privacy-sensitive users can be significantly reduced.
Web Server Performance Optimization using Prediction Prefetching Engine

The long-term success of the World Wide Web depends on fast response time. People use the Web to access information from remote sites, but do not like to wait long for their results. The rapid growth in the amount of information and the number of users has lead to difficulty in providing effective response time for the web users and this increased web latency; resulting in decreased web performance. Although several proposals have been made for reducing this latency, like it can be improved by caching, the benefit of using it is rather limited owing to filling the cache with documents without any prior knowledge.Predictive caching becomes an attractive solution wherein the forthcoming page likely to be requested soon are predicted based on user access logs information and pre-fetched ,while the user is browsing the current display pages. As web page prediction gained its importance, This paper proposes a bracing approach for increasing web server performance by analyzing user behavior, in this pre-fetching and prediction is done by pre-processing the user access log and integrating the three techniques i.e. Clustering, Markov model and association rules which achieves better web page access prediction accuracy;This work also overcomes the limitation of path completion i.e. by extracting web site structure paths are completed,which helps in better prediction, decreasing access time of user and improving web performance.
A Vocational Recovery Model for Young People With Mental Illness: A Pretest–Posttest

Purpose: This research project aims to evaluate the potential effectiveness of a vocational recovery model promoting both vocational and personal recovery for young people with mental illness. Methods: In this study, a one group pre–posttest design was conducted, involving 37 young people with mental illness who received a vocational recovery program that consisted of a psychoeducation group on recovery, social skills and job-related skills training, 3-month job internship, and individual follow-up services. Standardized assessment tools were used for outcomes assessment at baseline, 3 months after treatment began, and 6 months after treatment began. Results: Results indicated that the participants showed improved competitive employment rates, personal recovery, and social support at follow-up assessments. Conclusions: The present study supports the feasibility and effectiveness of a vocational recovery model for young people with mental illness, suggesting the importance of integrating recovery framework and strategies into community-based vocational service.