Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating Management Training and Development in a Cross-cultural Context: A Stakeholder Approach

Purpose – This paper is to address the challenge in evaluating China’s overseas management training and development (MTD) in cross-cultural settings. It critically examines the evaluation practice of China’s overseas MTD interventions and to explore the cultural impact on training evaluation. Design/methodology/approach - This research presents an empirical study covering 526 participants who are the major stakeholders involved in China’s overseas MTD. A mix method approach is used to explore the perspectives of different stakeholders. Findings – The respondents from different stakeholder groups perceive purposes of evaluation and problems conducting evaluation differently. There are also different foci on the evaluation criteria and approaches by individual groups. The current evaluation system is based on segmented information collection and little joint effort has been found in training and evaluation. The judgement on the value and worth of China overseas MTD is culturally sensitive due to the diverse of stakeholders from different cultural background. Research limitations/implications – This study is limited to two countries between China and UK for China’s MTD cross-culture initiatives. The evaluation framework is based on China’s government initiated overseas MTD programs. It may not be applicable to situations where only two parties involved in training, e.g., trainees and training providers. Practical implications – This research proposes an evaluation framework which adopts stakeholders approach and takes into consideration the cross-cultural impact on managers’ learning and development. Originality/value – This paper contributes to the literature by investigating China’s overseas MTD activities and exploring the approaches of evaluation in the cross-cultural context.
Technical Innovations Deployed by the MERCI Project

The paper reviews some of the important recent developments within the MERCI project in the technical improvement and deployment of Multimedia conferencing. The developments address four of the known limitations of the Mbone technology heretofore: lack of security, absence of QoS guarantees, inability to interwork with conferences using the ITU-T standards and lack of good access over low bandwidth unicast links. Description of the developments is coupled with a discussion of future improvements and plans for further deployment.
Multi-pass algorithm of motion estimation in video encoding for generic GPU

The importance of video encoding has boomed rapidly since video data communication was widely needed. In this paper, we propose a multi-pass algorithm to accelerate the motion estimation (ME), the dominant part in video encoding, with the graphics processing unit (GPU). By the multi-pass method to unroll and rearrange the multiple nested loops, the complex ME can be implemented on GPU. Besides, ME can be executed efficiently with the built-in parallel processing and texture filter of GPU. Experimental results show that, by utilizing the computing power of GPU, about two times and 14 times speed-up can be achieved for integer-pel ME and MPEG-1/2 half-pel ME, respectively
A Deep Learning Neural Network for Number Cognition: A bi-cultural study with the iCub

The novel deep learning paradigm offers a highly biologically plausible way to train neural network architectures with many layers, inspired by the hierarchical organization of the human brain. Indeed, deep learning gives a new dimension to research modeling human cognitive behaviors, and provides new opportunities for applications in cognitive robotics. In this paper, we present a novel deep neural network architecture for number cognition by means of finger counting and number words. The architecture is composed of 5 layers and is designed in a way that allows it to learn numbers from one to ten by associating the sensory inputs (motor and auditory) coming from the iCub humanoid robotic platform. The architecture performance is validated and tested in two developmental experiments. In the first experiment, standard backpropagation is compared with a deep learning approach, in which weights and biases are pre-trained by means of a greedy algorithm and then refined with backpropagation. In the second experiment, six bi-cultural number learning conditions are compared to explore the impact of different languages (for number words) and finger counting strategies. The developmental experiments confirm the validity of the model and the increase in efficiency given by the deep learning approach. Results of the bi-cultural study are presented and discussed with respect to the neuro-psychological literature and implications of the results for learning situations are briefly outlined.
ℓ1-Sparse reconstruction of sharp point set surfaces

We introduce an ℓ1-sparse method for the reconstruction of a piecewise smooth point set surface. The technique is motivated by recent advancements in sparse signal reconstruction. The assumption underlying our work is that common objects, even geometrically complex ones, can typically be characterized by a rather small number of features. This, in turn, naturally lends itself to incorporating the powerful notion of sparsity into the model. The sparse reconstruction principle gives rise to a reconstructed point set surface that consists mainly of smooth modes, with the residual of the objective function strongly concentrated near sharp features. Our technique is capable of recovering orientation and positions of highly noisy point sets. The global nature of the optimization yields a sparse solution and avoids local minima. Using an interior-point log-barrier solver with a customized preconditioning scheme, the solver for the corresponding convex optimization problem is competitive and the results are of high quality.
Adaptive Insertion and Promotion Policies Based on Least Recently Used Replacement

To improve Last-Level Cache (LLC) management, numerous approaches have been proposed requiring additional hardware budget and increased overhead. A number of these approaches even change the organization of the existing cache design. In this letter, we propose Adaptive Insertion and Promotion (AIP) policies based on Least Recently Used (LRU) replacement. AIP dynamically inserts a missed line in the middle of the cache list and promotes a reused line several steps left, realizing the combination of LRU and LFU policies deliberately under a single unified scheme. As a result, it benefits workloads with high locality as well as with many frequently reused lines. Most importantly, AIP requires no additional hardware other than a typical LRU list, thus it can be easily integrated into the existing hardware with minimal changes. Other issues around LLC such as scans, thrashing and dead lines are all explored in our study. Experimental results on the gem5 simulator with SPEC CUP2006 benchmarks indicate that AIP outperforms LRU replacement policy by an average of 5.8% on the misses per thousand instructions metric. key words: last-level cache, replacement, insertion, promotion, thrashing
What is the True Rate of Social Mobility in Sweden? A Surname Analysis, 1700-2012

On conventional measures, modern Sweden has rapid social and economic mobility. Analyzing surname distributions among Swedish elites - attorneys, physicians, university students, and academicians this paper shows that conventional measures greatly overstate social mobility. The Swedish elite of 1700 is still an elite, and is becoming average only slowly. The b measuring status persistence across generations is 0.7-0.8, compared to the 0.25-0.40 found in conventional studies. This illustrates a general feature that conventional studies overstate generalized or long-term social mobility rates. True rates of mobility in Sweden are similar to those of the supposedly more socially immobile economies of the UK and USA. They are little higher than in the pre-industrial era.
Using complete machine simulation to understand computer system behavior

This dissertation describes complete machine simulation, a novel approach to understanding the behavior of modern computer systems. Complete machine simulation differs from existing simulation tools by modeling all of the hardware found in a typical computer system. As a result, it can help investigators better understand the behavior of machines running commercial operating systems as well as any applications designed for these operating systems. In contrast, most existing simulation tools model only limited portions of a computer's hardware and cannot support the accurate investigation of many workloads. In addition to extensive workload support, the complete machine simulation approach permits significant hardware modeling flexibility and provides detailed information regarding the behavior of this hardware. This combination of features has widespread applicability, providing benefits to such research domains as hardware design, operating system development, and application performance tuning. Complete machine simulation extends the applicability of traditional machine simulation techniques by addressing two difficult challenges. The first challenge is to achieve the speed needed to investigate complex, long-running workloads. To address this challenge, complete machine simulation allows an investigator to dynamically adjust the characteristics of its hardware simulation. There is an inherent trade-off between the level of detail that a hardware simulator models and the speed at which it runs, and complete machine simulation provides users with explicit control over this trade-off. An investigator can select a high-speed, low-detail simulation setting to quickly pass through uninteresting portions of a workload's execution. Once the workload has reached a more interesting execution state, an investigator can switch to slower, more detailed simulation to obtain behavioral information. The second challenge is to efficiently organize low-level hardware simulation data into information that is more meaningful to an investigation. Complete machine simulation addresses this challenge by providing mechanisms that allow a user to easily incorporate higher-level workload knowledge into the data management process. These mechanisms are efficient and further improve simulation speed by customizing all data collection and reporting to the specific needs of an investigation.
Attention During Argument Generation and Presentation

We describe the operation of our argumentation system, and discuss its use of attentional focus during both content planning and argument presentation. During content planning, attentional focus guides an abductive process used to build-up arguments. This process is applied to a model of a user's • beliefs and a normative model. During argument presentation, attentional focus supports the generation of enthymematic arguments.
Mitochondrial 16S rRNA gene-based evolutionary divergence and molecular phylogeny of Barilius spp.

Abstract Barilius is an important genus of fish family Cyprinidae, which comprises 22 species from Indian region. This study aimed to characterize five commonly occurring Bariline species, for example, Barilius bakeri. Barilius gatensis. Barilius vagra. Barilius bendelisis and Barilius tileo, across the country using partial mitochondrial 16 S rRNA gene, to estimate the order of inter- and intra-species divergence among these species and to establish phylogenetic and evolutionary relationships. The average inter-specific divergence was estimated as 7.10%. Intra-specific divergence of 0.20% and 0.10% was observed in B. gatensis and B. bendelisis that exhibited three and two haplotypes with 0.70 and 0.60 haplotype diversities, respectively. The NJ and MP phylogenetic trees were constructed using 16 S rRNA sequences along with sequences of the other five Indian cyprinid species retrieved from NCBI. Phylogenetic trees revealed five discrete branches each as a distinct species of the genus and exhibited identical phylogenetic relationship with other cyprinids. The study provided adequate information to distinguish the five Barilius species and indicated the suitability of 16S rRNA gene sequences in genetic divergence and phylogenetic studies.
Predictors of noninstitutionalized survival 1 year after hip fracture

Abstract Hip fractures are frequent fractures in geriatric patients. These fractures have great socioeconomic implications because of the significantly higher risk of mortality and institutionalization. The aim of this study was to develop a prognostic tool to predict survival without institutionalization within 1 year after hip fracture. A total of 402 hip fracture patients aged >60 years (84% community-dwelling) were included in a prospective observational cohort study. Multiple regression analyses determined independent predictors for noninstitutionalized 1-year survival. Finally, the Marburg Rehabilitation Tool for Hip fractures (MaRTHi) was developed based on these independent predictors. Of the 312 patients who were followed up for 1 year, 168 (54%) survived noninstitutionalized, 104 (33%) died, and 40 (13%) lived in nursing homes. Independent predictors for patients’ noninstitutionalized survival included the American Society of Anesthesiologists (ASA) score [ASA 1 or 2: odds ratio (OR) = 7.828; 95% confidence interval (CI) = 2.496–24.555 and ASA 3: OR = 8.098; 95% CI = 2.982–21.993 compared with ASA 4 or 5], the Mini Mental State Examination upon admission to the hospital (OR = 7.365; 95% CI = 2.967–18.282 for 27–30 compared with 0–10), patients’ age (OR = 2.814; 95% CI = 1.386–5.712 for 75–89 y and OR = 2.520; 95% CI = 0.984–6.453 for 90–99 y compared with 60–74 ys), and prefracture EQ-5D (OR = 2.163; 95% CI = 1.119–4.179 for EQ-5D >0.80 compared with <0.60). The area under the receiver-operating characteristic curve was 0.756 (95% CI = 0.703–0.809), and the sensitivity analysis yielded a MaRTHi score that ranged from 0 to 12 points. The MaRTHi score is the first instrument to predict noninstitutionalized survival with only 4 variables. In addition to 3 well-known factors influencing outcome (age, comorbidities, and cognitive ability), prefracture health-related quality of life was identified as an independent predictor of noninstitutionalized survival. Further studies must be conducted to validate the MaRTHi score and define cutoff scores. Health-related quality of life seems to be an important patient-reported outcome measurement and may play a role in determining patient prognosis.
Single Grain Boundary Break Junction for Suspended Nanogap Electrodes with Gapwidth Down to 1–2 nm by Focused Ion Beam Milling

Single grain boundary junctions are used for the fabrication of suspended nanogap electrodes with a gapwidth down to 1-2 nm through the break of such junctions by focused ion beam (FIB) milling. With advantages of stability and no debris, such nanogap electrodes are suitable for single molecular electronic device construction.
Spectrum Monitoring for Radar Bands Using Deep Convolutional Neural Networks

In this paper, we present a spectrum monitoring framework for the detection of radar signals in spectrum sharing scenarios. The core of our framework is a deep Convolutional Neural Network (CNN) model that enables Measurement Capable Devices (MCDs) to identify the presence of radar signals in the radio spectrum, even when these signals are overlapped with other sources of interference, such as commercial Long-Term Evolution (LTE) and Wireless Local Area Network (WLAN). We collected a large dataset of RF measurements, which include the transmissions of multiple radar pulse waveforms, downlink LTE, WLAN, and thermal noise. We propose a pre- processing data representation that leverages the amplitude and phase shifts of the collected samples. This representation allows our CNN model to achieve a classification accuracy of 99.6% on our testing dataset. The trained CNN model is then tested under various SNR values, outperforming other models, such as spectrogram-based CNN models.
Consumption and Real Exchange Rates in Professional Forecasts

Standard models of international risk sharing with complete asset markets predict a positive association between relative consumption growth and real exchange-rate depreciations across countries. The striking lack of evidence for this link - the consumption/real-exchange-rate anomaly or Backus-Smith puzzle - has prompted research on risk-sharing indicators with incomplete asset markets. That research generally implies that the association holds in forecasts, rather than realizations. Using professional forecasts for 28 countries for 1990-2008 we find no such association, thus deepening the puzzle. Independent evidence on the weak link between forecasts for consumption and real interest rates suggests that the presence of 'hand-to-mouth' consumers may help to explain the evidence.
How to achieve blocking resistance for existing systems enabling anonymous web surfing

We are developing a blocking resistant, practical and usable system for anonymous web surfing. This means, the system tries to provide as much reachability and availability as possible, even to users in countries where the free flow of information is legally, organizationally and physically restricted. The proposed solution is an add-on to existing anonymity systems. First we give a classification of blocking criteria and some general countermeasures. Using these techniques, we outline a concrete design, which is based on the JAP-Web Mixes (aka AN.ON).
Adding Redundancy to Replication in Window-aware Delay-tolerant Routing

This paper presents a resource-efficient protocol for opportunistic routing in delay-tolerant networks (DTN). First, our approach exploits the context of mobile nodes (speed, direction of movement and radio range) to estimate the size of a contact window. This knowledge is exploited to make better forwarding decisions and to minimize the probability of partially transmitted messages. Optimizing the use of bandwidth during overloads helps reduce energy consumption since partially transmitted messages are useless and waste transmission power. Second, we use a differentiation mechanism based on message utility. This allows allocating more resources for high utility messages. More precisely, messages are replicated in the order of highest utility first, and removed from the buffers in the reverse order. To illustrate the benefit of such a scheme, global accumulated utility is used as a system-wide performance metric. Third, we present a combined fragmentation/redundancy scheme which not only improves delivery ratio but also, if infrastructure is available, allows messages to be completed by pulling dropped fragments. Simulations illustrate the benefit of our model and show that our scheme provides lower overhead and higher delivery ratio, as well as higher accumulated utility compared to a number of well-known algorithms including Maxprop and SprayAndWait.
Depression : can we predict who will relapse?

This thesis addresses risk factors and proposed mechanisms to explain relapse to depression. Volume 1 comprises three parts: Part 1 is a literature review consisting of meta-reviews of systematic and non-systematic reviews of studies reporting on risk factors for relapse to depression, and a systematic-review of neuroimaging and experimental studies investigating risk factors for relapse and potential mechanisms of action of these risk factors. The reviews found that only residual symptoms of depression at the end of treatment and childhood maltreatment were sufficiently evidenced as predictors of relapse and neither have great clinical utility. A number of psychological and neuropsychological factors were suggested to play a role in conferring risk for relapse. Considering the inter-relationships between these factors the reviews were used to propose a conceptual framework which may be used to help guide future research into relapse to depression in adults. Part 2 is an empirical paper in which data were analysed from service users of a primary care mental health service to identify risk factors for relapse and for the presence of residual symptoms, and survival analysis methods were used to determine when relapses occur most often and what factors impact survival. In addition, a prospective cohort study was formed to investigate the relationship between cognitive control and depressive symptoms. The findings confirmed that cognitive control can be used to predict residual symptoms of depression post-treatment and therefore potentially to predict relapse. Part 3 is a critical appraisal focussing on the theoretical reasons as to why studying relapse in a manner as used in the prospective study is so important and discusses the logistical difficulties conducting such research in the current context of NHS services and of the D.Clin. Psy research project. Methodological decisions made that impacted upon the research process are discussed and reflective conclusions are offered.
HyQ - Design and Development of a Hydraulically Actuated Quadruped Robot

Legged machines promise greater mobility in rough and unstructured terrain then wheeled vehicles. In the future, especially quadruped robots are expected to be employed for a variety of dangerous and dirty tasks in fields like search and rescue, humanitarian demining etc. The objective of this dissertation is to make a significant contribution toward the development of a highly dynamic quadruped robot. This versatile platform is intended to serve as a tool to deepen the understanding of terrestrial locomotion, to assess the applicability of different hydraulic actuation systems to legged robots and to facilitate the future construction of useful robots for various tasks. To this end, this dissertation: 1. presents several design studies aimed at the creation of a quadruped robot. 2. describes the design and experimental testing of a hydraulically powered prototype leg with a focus on its actuator units. 3. explains the construction of the quadruped robot platform including all electric and hydraulic system components. The developed quadruped robot called HyQ features 12 active degrees of freedom and is designed to perform highly dynamic tasks like jumping and running. Therefore, the robot’s joints are either powered by hydraulic or electric actuators, depending on their particular performance and property requirements. While hydraulic cylinders have an excellent power to weight ratio and naturally absorb impact force peaks during running and jumping, electric motors have compact overall dimensions and exhibit a constant output torque profile. Therefore, hydraulic cylinders actuate the hip and knee
EXPLOITING ENTITY SEMANTICS FOR QUERY EXPANSION

Many user queries nowadays contain references to named entities, which has motivated the development of new methods that exploit entity semantics for query expansion. At the same time, Wikipedia has been widely recognized as a large network of named entities, where entity-related articles are organized into a comprehensive hierarchy of categories and present summarized information on these entities in the so-called infoboxes. In this paper, we present a new query expansion method that uses entity semantics derived from Wikipedia. The main appeal of our method is that, differently from previous methods in the literature, it exploits valuable human-refined information available in infoboxes to obtain candidate query expansion terms and to associate entities identified in queries with categories. Indeed, by taking advantage of the semantic structure implicitly provided by infoboxes templates, we leverage well-known term-selection functions, adapting them to deal properly with entities and ultimately improving their accuracy in selecting good query expansion terms. Experimental results show that our method presents gains of 19.05% (from 0.1370 to 0.1631) in terms of MAP and 77.99% (from 0.2381 to 0.4238) in terms of P@10. In addition, the two approaches for obtaining expansion terms based on information found in infoboxes present a better trade-off between quality of results and time required to process the expanded query.