Miracle-dz/UniFAR-FTUs huggingface dataset:
Diverging Patterns of Satisfaction across Europe

Building on a decade-long comparative database of the European Social Survey the present study targets general aspects of satisfaction across larger regions of Europe with special regard to the socioeconomic changes in the recent decades. Conventionally cultivated measures like central tendency are supplemented by structural parameters of distribution based on a conceptual scheme distinguishing consensus and tightness of opinions. Dispersion-like indicators point to a stronger polarization of public mood under worse off contexts and, to a certain degree, conditions of vulnerability to economic downturn. A more rigid juncture of various mood components is also observable under less favourable circumstances. Disparities of income position in the first place, but features of cultural and ideological-political differentiation as well are intertwined with satisfaction polarization in a kind of stress syndrome exhibiting substantial divergences in both the East/West and the North/South regards.
A WS-Agreement Based Resource Negotiation Framework for Mobile Agents

Mobile agents require access to computing resources on heterogeneous systems across the Internet. They need to be able to negotiate their requirements with the systems on which they wish to be hosted. This paper presents a negotiation infrastructure with which agents acquire time-limited resource contracts through negotiation with one or more mediators instead of individual hosting systems. Mediators represent groups of autonomous hosts. The negotiation protocol and language are based on the WS-Agreement Specification, and have been implemented and tested within the AgentScape framework.
Automated Analysis of Background EEG and Reactivity During Therapeutic Hypothermia in Comatose Patients After Cardiac Arrest

Visual analysis of electroencephalography (EEG) background and reactivity during therapeutic hypothermia provides important outcome information, but is time-consuming and not always consistent between reviewers. Automated EEG analysis may help quantify the brain damage. Forty-six comatose patients in therapeutic hypothermia, after cardiac arrest, were included in the study. EEG background was quantified with burst-suppression ratio (BSR) and approximate entropy, both used to monitor anesthesia. Reactivity was detected through change in the power spectrum of signal before and after stimulation. Automatic results obtained almost perfect agreement (discontinuity) to substantial agreement (background reactivity) with a visual score from EEG-certified neurologists. Burst-suppression ratio was more suited to distinguish continuous EEG background from burst-suppression than approximate entropy in this specific population. Automatic EEG background and reactivity measures were significantly related to good and poor outcome. We conclude that quantitative EEG measurements can provide promising information regarding current state of the patient and clinical outcome, but further work is needed before routine application in a clinical setting.
Arabidopsis noncoding RNA mediates control of photomorphogenesis by red light

Significance The dynamic regulation of gene-expression programs is both critical to and regulated precisely in the light-mediated seedling photomorphogenesis of higher plants. Our work adds HIDDEN TREASURE 1 (HID1), a noncoding RNA that acts as a positive regulator of photomorphogenesis, to the current group of pivotal genetic factors known to control photomorphogenesis. Specifically, our data obtained by numerous approaches reveal that HID1 modulates red light-mediated photomorphogenesis by directly repressing PHYTOCHROME-INTERACTING FACTOR 3, which encodes a key transcription factor that inhibits red light responses. HID1 appears to be highly conserved among higher plants. Seedling photomorphogenesis is a sophisticated developmental process that is controlled by both the transcriptional and posttranscriptional regulation of gene expression. Here, we identify an Arabidopsis noncoding RNA, designated HIDDEN TREASURE 1 (HID1), as a factor promoting photomorphogenesis in continuous red light (cR). We show that HID1 acts through PHYTOCHROME-INTERACTING FACTOR 3 (PIF3), which encodes a basic helix–loop–helix transcription factor known to be a key repressor of photomorphogenesis. Knockdown of HID1 in hid1 mutants leads to a significant increase in the expression of PIF3, which in turn drives the development of elongated hypocotyls in cR. We identified two major stem-loops in HID1 that are essential for its modulation of hypocotyl growth in cR-grown seedlings. Furthermore, our data reveal that HID1 is assembled into large nuclear protein–RNA complex(es) and that it associates with the chromatin of the first intron of PIF3 to repress its transcription. Strikingly, phylogenetic analysis reveals that many land plants have conserved homologs of HID1 and that its rice homolog can rescue the mutant phenotype when expressed in Arabidopsis hid1 mutants. We thus concluded that HID1 is a previously uncharacterized noncoding RNA whose function represents another layer of regulation in the precise control of seedling photomorphogenesis.
Decreased knee adduction moment does not guarantee decreased medial contact force during gait

Excessive contact force is believed to contribute to the development of medial compartment knee osteoarthritis. The external knee adduction moment (KAM) has been identified as a surrogate measure for medial contact force during gait, with an abnormally large peak value being linked to increased pain and rate of disease progression. This study used in vivo gait data collected from a subject with a force‐measuring knee implant to assess whether KAM decreases accurately predict corresponding decreases in medial contact force. Changes in both quantities generated via gait modification were analyzed statistically relative to the subject's normal gait. The two gait modifications were a “medial thrust” gait involving knee medialization during stance phase and a “walking pole” gait involving use of bilateral walking poles. Reductions in the first (largest) peak of the KAM (32–33%) did not correspond to reductions in the first peak of the medial contact force. In contrast, reductions in the second peak and angular impulse of the KAM (15–47%) corresponded to reductions in the second peak and impulse of the medial contact force (12–42%). Calculated reductions in both KAM peaks were highly sensitive to rotation of the shank reference frame about the superior–inferior axis of the shank. Both peaks of medial contact force were best predicted by a combination of peak values of the external KAM and peak absolute values of the external knee flexion moment (R2 = 0.93). Future studies that evaluate the effectiveness of gait modifications for offloading the medial compartment of the knee should consider the combined effect of these two knee moments. Published by Wiley Periodicals, Inc. J Orthop Res 28:1348–1354, 2010
Robust Variational Inference

Variational inference is a powerful tool for approximate inference. However, it mainly focuses on the evidence lower bound as variational objective and the development of other measures for variational inference is a promising area of research. This paper proposes a robust modification of evidence and a lower bound for the evidence, which is applicable when the majority of the training set samples are random noise objects. We provide experiments for variational autoencoders to show advantage of the objective over the evidence lower bound on synthetic datasets obtained by adding uninformative noise objects to MNIST and OMNIGLOT. Additionally, for the original MNIST and OMNIGLOT datasets we observe a small improvement over the non-robust evidence lower bound.
Harvesting developer credentials in Android apps

Developers often integrate third-party services into their apps. To access a service, an app must authenticate itself to the service with a credential. However, credentials in apps are often not properly or adequately protected, and might be easily extracted by attackers. A leaked credential could pose serious privacy and security threats to both the app developer and app users. In this paper, we propose CredMiner to systematically study the prevalence of unsafe developer credential uses in Android apps. CredMiner can programmatically identify and recover (obfuscated) developer credentials unsafely embedded in Android apps. Specifically, it leverages data flow analysis to identify the raw form of the embedded credential, and selectively executes the part of the program that builds the credential to recover it. We applied CredMiner to 36,561 apps collected from various Android markets to study the use of free email services and Amazon AWS. There were 237 and 196 apps that used these two services, respectively. CredMiner discovered that 51.5% (121/237) and 67.3% (132/196) of them were vulnerable. In total, CredMiner recovered 302 unique email login credentials and 58 unique Amazon AWS credentials, and verified that 252 and 28 of these credentials were still valid at the time of the experiments, respectively.
The Cloud Access Control Based on Dynamic Feedback and Merkle Hash Tree

For cloud environment is an open, dynamic environment, analysed the lack of based on the Merkle hash tree architecture, we propose a high efficiency, flexible and dynamic feedback, remote authentication mechanisms. This paper describes TPM_ Trust command enhanced the functionality of the existing TPM (trusted platform module), and analyze the discussion of the advantages of the new mechanism, and proposes a measuring method based on subjective trust.
Who’s Been Served and How?

Child welfare systems were created to protect maltreated children. However, adolescents today can be involved with child welfare for reasons other than maltreatment, including behavior issues. Such youth are also commonly involved in the youth corrections system. This study examines youth characteristics and risk factors which predict attaining permanency at case closure for youth involved in child welfare primarily for behavioral reasons. The sample consists of 5,691 youth aged 10–17 served in Colorado between 2007 and 2013. A multinomial logit model identified predictors of nonpermanent outcomes and of placement with return home, compared to remaining home throughout case involvement. Results show that the following characteristics and risks have a positive relationship with nonpermanent outcomes: longer case duration, prior child welfare placement, felony involvement, crimes against persons or property, truancy, running away, and gang membership. Services provided by the child welfare system are negatively related to nonpermanent outcomes.
Time Series Data Mining in Real Time Surface Runoff Forecasting through Support Vector Machine

This study presents support vector machine based model for forecasting the runoff-rainfall events. A SVM based model is either implemented through Radial base or Gaussian based Kernel functions. SVM uses precipitation, temperature, sediment, rainfall, water level and discharge as input variable parameters. In this research the Sequential minimal optimization algorithm (SMO) has been implemented as an effective method for training support vector machines (SVMs) on classification tasks defined on large and sparse real time data sets. In this work, we generalized the SMO so that it can handle regression problem and by dividing datasets into test data and trained data performed future forecasting keeping four major evaluation parameters Root Mean Square Error (RMSE), Mean Absolute error (MAE), Mean Squared error (MSE) and correlation coefficient (CC). Study site for this research is Narmada basin reservoir hosahangabad catchment area and the experimental results on predicting the full natural flow of Narmada River indicates that support vector machine method performs far better and more accurate from the current forecasting practices (Artificial Neural Network).
C3: Internet-Scale Control Plane for Video Quality Optimization

As Internet video goes mainstream, we see increasing user expectations for higher video quality and new global policy requirements for content providers. Inspired by the case for centralizing network-layer control, we present C3, a control system for optimizing Internet video delivery. The design of C3 addresses key challenges in ensuring scalability and tackling data plane heterogeneity. First, to ensure scalability and responsiveness, C3 introduces a novel split control plane architecture that can tolerate a small increase in model staleness for a dramatic increase in scalability. Second, C3 supports diverse client-side platforms via a minimal clientside sensing/actuation layer and offloads complex monitoring and control logic to the control plane. C3 has been operational for eight years, and today handles more than 100M sessions per day from 244 countries for 100+ content providers and has improved the video quality significantly. In doing so, C3 serves as a proof point of the viability of fine-grained centralized control for Internetscale applications. Our experiences reinforce the case for centralizing control with the continued emergence of new use case pulls (e.g., client diversity) and technology pushes (e.g., big data platforms).
Non-traditional Strength Training

This study aimed to examine southern Chinese college student (N = 1983) stage of exercise behavior changes (SEBC) and their exercise self-efficacy (ESE). The SEBC and ESE scales were used to collect data. ANOVA was performed to investigate the differences in ESE by SEBC. Post Hoc Tukey tests were employed to determine which variables contributed to the differences. The data from the study indicated that those who maintained regular participation in exercise had significantly higher ESE than those who did not. It is concluded that improving college student ESE might lead to an increase in exercise.
Towards a physical model of dust tori in Active Galactic Nuclei

We explore physically self‐consistent models of dusty molecular tori in Active Galactic Nuclei (AGN) with the goal of interpreting VLTI observations and fitting high resolution mid‐infrared spectral energy distributions (SEDs). The input dust distribution is analytically calculated by assuming hydrostatic equilibrium between pressure forces — due to the turbulent motion of the gas clouds — and gravitational and centrifugal forces as a result of the contribution of the nuclear stellar distribution and the central black hole. For a fully three‐dimensional treatment of the radiative transfer problem through the tori we employ the Monte Carlo code MC3D. We find, that in homogeneous dust distributions the observed mid‐infrared emission is dominated by the inner funnel of the torus, even when observing along the equatorial plane. Our mean Seyfert galaxy model with a moderate density contrast fits well the available mean quasar SEDs. Also high spatial resolution data of special Seyfert galaxies are in good agree.
The Impact of Immigration on Native Poverty Through Labor Market Competition

In this paper I first analyze the wage effects of immigrants on native workers in the US economy and its top immigrant-receiving states and metropolitan areas. Then I quantify the consequences of these wage effects on the poverty rates of native families. The goal is to establish whether the labor market effects of immigrants have significantly affected the percentage of "poor" families among U.S.-born individuals. I consider the decade 2000-2009 during which poverty rates increased significantly in the U.S. As a reference, I also analyze the decade 1990-2000. To calculate the wage impact of immigrants I adopt a simple general equilibrium model of productive interactions, regulated by the elasticity of substitution across schooling groups, age groups and between US and foreign-born workers. Considering the inflow of immigrants by age, schooling and location I evaluate their impact in local markets (cities and states) assuming no mobility of natives and on the US market as a whole allowing for native internal mobility. Our findings show that for all plausible parameter values there is essentially no effect of immigration on native poverty at the national level. At the local level, only considering the most extreme estimates and only in some localities, we find non-trivial effects of immigration on poverty. In general, however, even the local effects of immigration bear very little correlation with the observed changes in poverty rates and they explain a negligible fraction of them.
Transient Signal Spaces and Decompositions

In this paper, we study the problem of transient signal analysis. A signal-dependent algorithm is proposed which sequentially identifies the countable sets of decay rates and expansion coefficients present in a given signal. We qualitatively compare our method to existing techniques such as orthogonal exponential transforms generated from orthogonal polynomial classes. The presented algorithm has immediate utility to signal processing applications wherein the decay rates and expansion coefficients associated with a transient signal convey information. We also provide a functional interpretation of our parameter extraction method via signal approximation using monomials over the unit interval from the perspective of biorthogonal constraint satisfaction.
Diffusion Kurtosis Imaging: A Possible MRI Biomarker for AD Diagnosis?

Abstract The purpose of this explorative study was to investigate whether diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) parameter changes are reliable measures of white matter integrity changes in Alzheimer’s disease (AD) patients using a whole brain voxel-based analysis (VBA). Therefore, age- and gender-matched patients with mild cognitive impairment (MCI) due to AD (n = 18), dementia due to AD (n = 19), and age-matched cognitively healthy controls (n = 14) were prospectively included. The magnetic resonance imaging protocol included routine structural brain imaging and DKI. Datasets were transformed to a population-specific atlas space. Groups were compared using VBA. Differences in diffusion and mean kurtosis measures between MCI and AD patients and controls were shown, and were mainly found in the splenium of the corpus callosum and the corona radiata. Hence, DTI and DKI parameter changes are suggestive of white matter changes in AD.
Development of a nerve model of eyeball motion nerves to simulate the disorders of eyeball movements for neurologic examination training

Cranial nerve examination takes an important role in the physical examination. All the medical staffs need to be trained to master the skills for examination. By now, several training methods have been carried out for medical training including training with the simulated patient (SP). However, considering the characters of eyeball, the involuntary actions cannot be simulated by Sp. With the developments of technology, more and more robot heads have been launched. However, these simulators only focus on mimicking the healthy human abilities, not simulating disorders for medical training. In this paper, we propose a novel eyeball motion nerve model which is used in the head robot named WKH-2(Waseda Kyotokagaku Head Robot No.2). This robot is designed to simulate the disorders of eyeball movements to give the trainee a full training on cranial examination. The motor nerve model is carried out from mimicking the real eyeball nerve structure. And the functions of each part are designed from analysis of the real functions of each organ. In this robot, the effects of eyeball motion nerve system, and various symptoms are simulated. Making use of this robot, a systematic training on the skills as well as the understanding of medical knowledge is provided. Finally, several experiments are carried out to verify our proposed system. The experimental results show that the approach is worth following in further research.
Speeded-up, relaxed spatial matching

A wide range of properties and assumptions determine the most appropriate spatial matching model for an application, e.g. recognition, detection, registration, or large scale image retrieval. Most notably, these include discriminative power, geometric invariance, rigidity constraints, mapping constraints, assumptions made on the underlying features or descriptors and, of course, computational complexity. Having image retrieval in mind, we present a very simple model inspired by Hough voting in the transformation space, where votes arise from single feature correspondences. A relaxed matching process allows for multiple matching surfaces or non-rigid objects under one-to-one mapping, yet is linear in the number of correspondences. We apply it to geometry re-ranking in a search engine, yielding superior performance with the same space requirements but a dramatic speed-up compared to the state of the art.
Mismatch negativity and auditory sensory memory evaluation: a new faster paradigm

A new faster paradigm to measure the duration of auditory sensory memory, as indexed by mismatch negativity (MMN) suppression to stimuli presented at increasing inter-stimulus intervals (ISI), is proposed. Trains of three stimuli were delivered at very short ISI (300 ms). The inter-train interval varied according to the memory probe interval (MPI) tested. Trains started randomly with a deviant or standard stimulus (50% each), with their event-related brain potentials subtracted to obtain the MMN. The new paradigm provided MMNs identical to the conventional one at MPIs of 0.4 and 4.0 s in young subjects, and revealed MMN suppression when the MPI was increased to 5.0 s in older subjects. The new paradigm estimates auditory sensory memory duration in one-third the time of conventional MMN.
Scalable Hierarchical Topic Detection Exploring a Sample Based Approach

Hierarchical topic detection is a new task in the TDT 2004 evaluation program, which aims to organize an unstructured news collection in a directed acyclic graph (DAG) structure, reflecting the topics discussed. We present a scalable architecture for HTD and compare several alternative choices for agglomerative clustering and DAG optimization in order to minimize the HTD cost metric.
EyeSketch: a drawing application for gaze control

We present a gaze-driven drawing application called EyeSketch. Contrary to earlier gaze-controlled drawing applications, our application utilizes drawing objects that can be moved and resized, and their colour attributes can be changed after drawing. Tool and object selections are implemented with dwell buttons. Tools for moving and resizing are controlled with gaze gestures and by closing the eyes. Our gaze gestures are simple, one-segment gestures that end outside the screen area. The gestures are used to give the direction for moving and also for the command to make the object either smaller or larger. Closing the eyes signals to the application to stop a moving object. In our evaluations, these gaze gestures were judged as a usable interaction style for the moving and resizing purpose.
Outlier-Robust Convex Segmentation

We derive a convex optimization problem for the task of segmenting sequential data, which explicitly treats presence of outliers. We describe two algorithms for solving this problem, one exact and one a top-down novel approach, and we derive a consistency results for the case of two segments and no outliers. Robustness to outliers is evaluated on two real-world tasks related to speech segmentation. Our algorithms outperform baseline segmentation algorithms.