Miracle-dz/UniFAR-FTUs huggingface dataset:
Technology use among adults who are deaf and hard of hearing: a national survey.

As society becomes increasingly more dependent on technology, information regarding the use, preference, and accessibility of commonly used devices and services among individuals who are deaf and hard of hearing (DHH) is crucial. Developing technologies that are functional and appropriately accessible allows persons who are DHH to fully participate in society, education, and business while also providing opportunities for personal and professional advancement. Although a few international studies have addressed the technology use of individuals who are DHH, none exist that focus on the needs, preferences, and accessibility of current Internet- and mobile-based technologies. Consequently, a national survey was conducted in the United States to determine the preference, frequency of use, and accessibility of various technologies (hardware, software, Web sites) by adults who are DHH and living in the United States. Findings indicate frequent use of smartphones and personal computers, specifically for text-based communication and web surfing, and little use of Teletypewriter/Telecommunications Device for the Deaf. Web site feature preferences include pictures and text, and captions over signed translations. Some results varied by demographics.
The Study on the Leaf Anatomy of Some Mangrove Species of China

A anatomical study was made of the leaves of seven mangrove species collected from Fugong Longhai of Fujian (24°54′ N, 117°23′ E). The tissue structure in each case was determined in terms of cell layers present and their relative thickness. Two species showed isobilateral leaf structure and the remaining five species dorsiventral. Leaf thickness was found to vary from 327.83 μm (Avicennia marina) to 666.60 μm (Kandelia candel) and an average of 514.50 μm. Sonneratia. apetala was found to have stomata on both surfaces of the lamina. The average of the stomatal complex dimension was found to be 31.1 μm by 17.9 μm. The average number of stomata per given area, and the average leaf area for each species were also determined. The ecophysiological significance of the present data like leaf area, the relative leaf thickness, and other anatomical characters is discussed with reference to the published literature.
Clustering the seoul metropolitan area by travel patterns based on a deep belief network

It is very useful to divide an urban area into several homogeneous zones when managing a city. Conventionally, clustering urban areas has depended upon the intuition and expertise of urban planners. On the other hand, the present study regards specific travel patterns of people living in an urban zone as a key variable to distinguish that zone from others. A K-means algorithm was adopted to cluster zones of the Seoul metropolitan area, after large dimensional origin-destination flows, which were elicited from smart-card data, were reduced by using a principal component analysis. A more elaborated approach, a deep belief network that stacked multiple restricted Boltzmann machines, was also used to reduce the dimension of origin-destination travel flows. The latter approach unveiled more hidden nonlinear aspects of clustering than provided by either the conventional zoning convention or the PCA-based approach.
Principal Component Image Analysis of MODIS for Volcanic Ash. Part II: Simulation of Current GOES and GOES-M Imagers

Abstract In Part I of this paper the infrared bands of the Moderate Resolution Imaging Spectroradiometer (MODIS) were analyzed using principal component image analysis for volcanic ash signals. The analyses performed determined that several of the thermal infrared bands of MODIS contributed significantly to detecting volcanic ash in the cases examined. Most, but not all, of these bands will be included in the next major upgrade to the Geostationary Operational Environmental Satellite (GOES) Imager scheduled for 2012. In Part II, MODIS data for the same volcanic cases examined in Part I (Popocatepetl near Mexico City and Cleveland in the Aleutian Islands) are used to simulate the impact of changes that will occur in spectral bands between current and near-term GOES imagery. The change from the 12.0-μm band to a 13.3-μm band on GOES-M (launched in 2001 and renamed GOES-12) was made to improve cloud-height determinations. However, when GOES-M becomes operational, the change in bands will have a potential neg.
Location-aware opportunistic forwarding in mobile opportunistic networks

In mobile opportunistic networks, the ad hoc nodes with high mobility are expected to have many opportunities of node contacts and serving message forwarding. Here we considering two typical mobility models, e.g., the RWP(Random WayPoint) model and Manhattan model, where the probabilistic characteristics of the node contact provided by the mobile nodes are explored. Furthermore we propose a Location-Aware Opportunistic Forwarding scheme, which exploits the location information of the messages and the node mobility for message forwarding. The message is forwarded to its destination regions or neighbor regions to improve the delivery ratio and reduce the network overhead. We construct a simulation environment, integrated with the RWP mobility trace and the city taxis' traces. Through extensive simulations, our scheme is demonstrated to outperform the best known opportunistic forwarding algorithms in terms of both delivery ratio/latency and transmission overhead.
Cloud service selection based on contextual subjective assessment and objective assessment

This paper proposes a novel cloud service selection model based on the comparison and aggregation of contextual subjective assessment and objective assessment of cloud services. In this model, objective assessment provided by some professional testing parties is used as a benchmark to dynamically filter out biased subjective assessment extracted from cloud user feedback according to assessment context similarity. Through this model, the overall quality of cloud services can be effectively reflected with less subjective bias for potential cloud consumers.
A novel optical tracking based tele-control system for tabletop object manipulation tasks

For a robot serving in a complex environment such as in a restaurant, it is difficult to perform a task like tabletop object manipulation completely by itself, in that some information may be missing. An approach to deal with this is to use a tele-control system and method to control the robot or demonstrate. In this paper, a LeapMotion sensor based non-contact tele-control method is developed for a robot to perform tabletop object manipulation tasks. A coordinate system for mapping from the operation space of the LeapMotion sensor to the workspace of the robot is established. A gesture recognition and action generating algorithm is proposed for control or to demonstrate the motion to the robot. To evaluate the performance of the LeapMotion sensor and proposed method for tele-control of a robot, a comprehensive assessment index based on entropy weighting is proposed. Three common tele-control modes, including demonstration mode, teleoperation mode and semi-teleoperation mode, are developed on a PR2 robot. The experimental results show that the proposed tele-control system is more appropriate for use in task demonstration.
Endothelial Cx40 limits myocardial ischaemia/reperfusion injury in mice.

AIMS Gap junctions are indispensable for the function of heart and blood vessels by providing electrical coupling and direct cell-to-cell transfer of small signalling molecules. Gap junction channels between neighbouring cells are composed of 12 connexins (Cx). Changes in Cx43 expression, localization, and channel properties in cardiomyocytes contribute to infarction and reperfusion injury of the heart. It is increasingly recognized that deleterious consequences of ischaemia/reperfusion (IR) are modulated by the inflammatory response and endothelial function. The role of the endothelial connexins, i.e. Cx40 and Cx37, in cardiac IR injury is, however, not known. METHODS AND RESULTS Following 30 min ischaemia and 24 h reperfusion, we found a significant increase in myocardial infarct size in mice with endothelial-specific deletion of Cx40 (Cx40del), but not in Cx37-deficient mice. The cardioprotective effect of endothelial Cx40 was associated with a decrease in neutrophil infiltration. Moreover, beneficial effects of endothelial Cx40 were not observed in isolated Langendorff-perfused hearts, suggesting direct involvement of endothelial-leucocyte interactions in the cardiac injury. Single-dose administration of methotrexate, a CD73 activator, reduced infarct size and neutrophil infiltration into the infarcted myocardium in Cx40del but not in control mice. Similar to Cx40del mice, CD73-deficient mice showed increased sensitivity to cardiac IR injury, which could not be conversed by methotrexate. CONCLUSION Endothelial Cx40, but not Cx37, is implicated in resistance of the heart to IR injury by activation of the CD73 pathway. Thus, the Cx40-CD73 axis may represent an interesting target for controlling reperfusion damage associated with revascularization in coronary disease.
ACTIVE phase-shift control of multi-phase converters to minimize input current sub-harmonics

Tolerance parameters limit the ripple cancellation phenomenon of an interleaving concept in multiphase converters. An analysis has been performed to demonstrate that coupled inductors help to reduce the influence of non-uniform inductances. Non-equal duty cycles and non-ideal phase-shifts are therefore more problematic in multi-phase converters with coupled inductors. This paper presents a control concept to optimize the phase-shifts and equalize the single pulse-widths especially for converters with coupled inductors. A prototype converter has been built and tested to show that filter components can be reduced with the proposed control technique. Theoretical predictions are compared with measurements on a full-size automotive dc-dc converter with six interleaved phases.
A novel multi-resolution SVM (MR-SVM) algorithm to detect ECG signal anomaly in WE-CARE project

Cardiovascular disease (CVD) has become the leading cause of human deaths today. In order to combat this disease, many professionals are using mobile electrocardiogram (ECG) remote monitoring system. While using mobile ECG systems, most of the cardiac anomalies can be observed, especially when serious myocardial ischemia, heart failure, and malignant arrhythmia occur. Thus, ECG anomaly detection and analysis have attracted more and more attention in the clinical and research communities. Currently, the existing solutions of ECG automatic detection and analysis technologies are challenged by an accuracy requirement. Based on this motivation, we propose a novel Multi-Resolution Support Vector Machine (MR-SVM) algorithm to detect ECG waveform anomaly. This proposal is tested in our WE-CARE (a Wearable Efficient telecardiology system) project. Clinical trials and experimental results show that the algorithm can successfully extract original QRS complex waves and T waves regardless of noise magnitude and distinguish the ST segment morphological anomalies. Compared with European standard ST-T database, our solution can achieve the average T wave recognition accuracy rate of 97.5% and ST anomaly detection accuracy rate of 93%.
Happy Like a Fish in Water? The Role of Personality–Situation Fit for Momentary Happiness in Social Interactions across the Adult Lifespan

Growing research on personality–relationship dynamics demonstrates that people's personality and their (enjoyment of) social relationships are closely intertwined. Using experience sampling data from 136 adults (aged 18–89 years) who reported on more than 50 000 social interactions, we zoom into everyday real–world social interactions to examine how Big Five personality traits and social context characteristics shape people's happiness in social encounters across the adult lifespan. Results revealed that interactions that were social (vs. task–oriented) and with close (vs. less close) others were associated with higher momentary happiness as were higher levels of the target person's extraversion, agreeableness, and conscientiousness, and lower neuroticism. Of the 10 personality × situation interactions tested, only one reached significance (with p = .041): Individuals with higher levels of neuroticism benefitted more from interactions with friends than did individuals low in neuroticism. The role of social context characteristics for momentary happiness changed with age, but the role of personality or personality × social context did not, suggesting that personality effects on happiness in social context manifest in similar ways across the adult lifespan. We discuss implications for personality–situation research and the understanding of affective dynamics in everyday social interactions. © 2019 European Association of Personality Psychology
Reducing HDAC6 ameliorates cognitive deficits in a mouse model for Alzheimer's disease

Histone deacetylases (HDACs) are currently being discussed as promising therapeutic targets to treat neurodegenerative diseases. However, the role of specific HDACs in cognition and neurodegeneration remains poorly understood. Here, we investigate the function of HDAC6, a class II member of the HDAC superfamily, in the adult mouse brain. We report that mice lacking HDAC6 are cognitively normal but reducing endogenous HDAC6 levels restores learning and memory and α‐tubulin acetylation in a mouse model for Alzheimer's disease (AD). Our data suggest that this therapeutic effect is, at least in part, linked to the observation that loss of HDAC6 renders neurons resistant to amyloid‐β‐mediated impairment of mitochondrial trafficking. Thus, our study suggests that targeting HDAC6 could be a suitable strategy to ameliorate cognitive decline observed in AD.
TR 15-009 Design and Evaluation of a Transaction Model with Multiple Consistency Levels for Replicated Data

We present here a transaction model which simultaneously supports different consistency levels, which include serializable transactions for strong consistency, and weaker consistency models such as causal snapshot isolation (CSI), CSI with commutative updates, and CSI with asynchronous concurrent updates. This model can be useful in managing replicated data with different consistency guarantees to make suitable tradeoffs between data availability, performance, and consistency of different data items. Data and the associated transactions are organized in a hierarchy which is based on consistency levels. Certain rules are imposed on transactions to constrain information flow across data at different levels in this hierarchy to ensure the required consistency guarantees. The building block for this transaction model is the snapshot isolation model. We present an example of an e-commerce application structured with data items and transactions defined at different consistency levels. We have implemented a testbed system for replicated data management based on the proposed multilevel consistency model. We present here the results of our experiments with this ecommerce application to demonstrate the benefits of this model.
Apple-CORE: Microgrids of SVP Cores -- Flexible, General-Purpose, Fine-Grained Hardware Concurrency Management

To harness the potential of CMPs for scalable, energy-efficient performance in general-purpose computers, the Apple-CORE project has co-designed a general machine model and concurrency control interface with dedicated hardware support for concurrency management across multiple cores. Its SVP interface combines dataflow synchronisation with imperative programming, towards the efficient use of parallelism in general-purpose workloads. The corresponding hardware implementation provides logic able to coordinate single-issue, in-order multi-threaded RISC cores into computation clusters on chip, called Microgrids. In contrast with the traditional "accelerator" approach, Microgrids are intended to be used as components in distributed systems on chip that consider both clusters of small cores and optional larger cores optimized towards sequential performance as system services shared between applications. The key aspects of the design are asynchrony, i.e. the ability to tolerate operations with irregular long latencies, a scale-invariant programming model, a distributed vision of the chip's structure, and the transparent performance scaling of a single program binary code across multiple cluster sizes. This paper describes the execution model, the core micro-architecture, its realization in a many-core, general-purpose processor chip and its software environment. The reference chip parameters include 128 cores, a 4 MB on-chip distributed cache network and four DDR3-1600 memory channels. This paper presents cycle-accurate simulation results for various key algorithmic and cryptographic kernels. The results show good efficiency in terms of the utilization of hardware despite the high-latency memory accesses and good scalability across relatively large clusters of cores.
Perceptual Evaluation of Speech Quality (PESQ), the new ITU standard for end-to-end speech quality assessment. Part II – Psychoacoustic model

A new model for perceptual evaluation of speech quality (PESQ) was recently standardised by the ITU-T as recommendation P.862. Unlike previous codec assessment models, such as PSQM and MNB (ITU-T P.861), PESQ is able to predict subjective quality with good correlation in a very wide range of conditions, that may include coding distortions, errors, noise, filtering, delay and variable delay. This paper introduces the psycho-acoustic model that is used in PESQ. An accompanying paper describes the time delay identification technique that is used in combination with the PESQ psychoacoustic model to predict the end-to-end perceived speech quality
Estimating state and Parameters in state space Models of Spike trains

Neural computations at all scales of evolutionary and behavioural complexity are carried out by recurrently connected networks of neurons that communicate with each other, with neurons elsewhere in the brain, and with muscles through the firing of action potentials or “spikes”. To understand how nervous tissue computes, it is therefore necessary to understand how the spiking of neurons is shaped both by inputs to the network and by the recurrent action of existing network activity. Whereas most historical spike data were collected one neuron at a time, new techniques including silicon multi-electrode array recording and scanning 2-photon, light-sheet or light-field fluorescence calcium imaging increasingly make it possible to record spikes from dozens, hundreds and potentially thousands of individual neurons simultaneously. These new data offer unprecedented empirical access to network computation, promising breakthroughs both in our understanding of neural coding and computation (Stevenson & Kording 2011), and our ability to build prosthetic neural interfaces (Santhanam, Ryu, Yu, Afshar & Shenoy 2006). Fulfilment of this promise will require powerful methods for data modelling and analysis, able to capture
Factors Affecting Automatic Genre Classification: An Investigation Incorporating Non-Western Musical Forms

The number of studies investigating automated genre classification is growing following the increasing amounts of digital audio data available. The underlying techniques to perform automated genre classification in general include feature extraction and classification. In this study, MARSYAS was used to extract audio features and the suite of tools available in WEKA was used for the classification. This study investigates the factors affecting automated genre classification. As for the dataset, most studies in this area work with western genres and traditional Malay music is incorporated in this study. Eight genres were introduced; Dikir Barat, Etnik Sabah, Inang, Joget, Keroncong, Tumbuk Kalang, Wayang Kulit, and Zapin. A total of 417 tracks from various Audio Compact Discs were collected and used as the dataset. Results show that various factors such as the musical features extracted, classifiers employed, the size of the dataset, excerpt length, excerpt location and test set parameters improve classification results.
Impact of Public R&D Financing on Employment. ENEPRI Working Paper No. 39, August 2005

This study analyses how public R&D financing impacts the labour demand of companies. To our knowledge, no previous studies have distinguished the impact between a firm’s global and domestic employment. Our company-level panel data covers a period from 1997 to 2002. The statistical method employed in the study takes into account the possibility that receiving public support may be an endogenous factor. Our results suggest that public R&D financing increases both group-level and domestic R&D employment. We also analysed the impact of public R&D funding on employment other than in the R&D area, and found that it is not affected by public funding. It is possible, however, that such funding has an impact in the longer term.
Assessing the effect of elevated carbon dioxide on soil carbon: a comparison of four meta‐analyses

Soil is the largest reservoir of organic carbon (C) in the terrestrial biosphere and soil C has a relatively long mean residence time. Rising atmospheric carbon dioxide (CO2) concentrations generally increase plant growth and C input to soil, suggesting that soil might help mitigate atmospheric CO2 rise and global warming. But to what extent mitigation will occur is unclear. The large size of the soil C pool not only makes it a potential buffer against rising atmospheric CO2, but also makes it difficult to measure changes amid the existing background. Meta‐analysis is one tool that can overcome the limited power of single studies. Four recent meta‐analyses addressed this issue but reached somewhat different conclusions about the effect of elevated CO2 on soil C accumulation, especially regarding the role of nitrogen (N) inputs. Here, we assess the extent of differences between these conclusions and propose a new analysis of the data. The four meta‐analyses included different studies, derived different effect size estimates from common studies, used different weighting functions and metrics of effect size, and used different approaches to address nonindependence of effect sizes. Although all factors influenced the mean effect size estimates and subsequent inferences, the approach to independence had the largest influence. We recommend that meta‐analysts critically assess and report choices about effect size metrics and weighting functions, and criteria for study selection and independence. Such decisions need to be justified carefully because they affect the basis for inference. Our new analysis, with a combined data set, confirms that the effect of elevated CO2 on net soil C accumulation increases with the addition of N fertilizers. Although the effect at low N inputs was not significant, statistical power to detect biogeochemically important effect sizes at low N is limited, even with meta‐analysis, suggesting the continued need for long‐term experiments.