Miracle-dz/UniFAR-FTUs huggingface dataset:
Off-Body Antenna Wireless Performance Evaluation in a Residential Environment

Modern body-centric communication systems require good link quality. Antenna performance is of primary importance when meeting this requirement. This paper contributes a method suited to the difficult task of quantifying antenna performance in a body-centric communications system. In a case study, a planar wrist wearable antenna, which provides radiation pattern switching across the 2.4 GHz operating band through an innovative technique that does not require an additional switching mechanism, is benchmarked against a monopole and a patch antenna in a residential setting. The performance of the antenna and subsequently the benefits of the pattern-switching technique are successfully quantified. The holistic method includes both antenna measurements and channel simulation with ray tracing. Results are verified against real-world measurements.
Neuron-Based Control Mechanisms for a Robotic Arm and Hand

A robotic arm and hand controlled by simulated neurons is presented. The robot makes use of a biological neuron simulator using a point neural model. The neurons and synapses are organised to create a finite state automaton including neural inputs from sensors, and outputs to effectors. The robot performs a simple pick-and-place task. This work is a proof of concept study for a longer term approach. It is hoped that further work will lead to more effective and flexible robots. As another benefit, it is hoped that further work will also lead to a better understanding of human and other animal neural processing, particularly for physical motion. This is a multidisciplinary approach combining cognitive neuroscience, robotics, and psychology.
Mobile Crowd Sensing for Internet of Things: A Credible Crowdsourcing Model in Mobile-Sense Service

Various types of micro-sensors in smart communication devices can measure a significant amount of potentially useful information. Mobile Crowd Sensing (MCS) between users with smart mobile devices is a new trend of development in Internet of Things. With the powerful sensing capability of smart device and user mobility, various services could be provided by building a trusted chain between service requesters and suppliers. In this paper, we first analyze and summarize the current status of the MCS technology, and a novel credible crowd sourcing service model is proposed based on MCS according to mobility, sociality and complexity of mobile users. Then, some key technologies of model are given in details. Finally, we give the focus of future research work.
Liquidity and Capital Structure: Evidence from a Bank-dominated Economy

We explore the impact of liquidity on capital structure decisions. Firms that enjoy more liquid equity experience a lower cost of equity and may be more motivated to adopt more equity and less debt in their capital structure. Consistent with this notion, the empirical evidence demonstrates an inverse relation between liquidity and leverage. Our results are especially interesting because we examine firms in Thailand, where capital markets are less sophisticated than the U.S., bank loans more prevalent, and corporate ownership much more concentrated. In spite of these differences, we document that Thai firms with more liquid equity are significantly less leveraged.
On the differentiation of memory beliefs from memory knowledge: the factor structure of the Metamemory in Adulthood Scale.

This study was designed to test the hypothesis that there are multiple factors of metamemory present in the Metamemory in Adulthood (MIA) questionnaire. Data on seven MIA scales from six separate studies on memory/metamemory relationships (total N = 750) were combined to yield two half-samples for cross-validation purposes. The samples were partitioned into young, middle-aged, and old groups. A multiple group confirmatory factor analysis was then conducted on the data, using the first half sample to develop a model and the second half sample to validate it. Although the models did not fully cross-validate, both analyses indicated that there are at least two higher-order factors in the MIA. The first involves beliefs about self-efficacy in using memory. The second factor combines knowledge about memory and affect concerning memory (e.g., achievement motivation). The analyses also indicated that the factor loadings for the second factor, tentatively labelled Knowledge, were invariant across the three age groups, but that there were age differences in the Self-Efficacy Beliefs factor loadings. The differences were localized to age-related increases in the loadings for the MIA Change and Locus scales. The two factor solution has potential for resolving conflicting results in the literature regarding age differences in both metamemory and metamemory/memory performance relationships.
Concatenative Resynthesis Using Twin Networks

Traditional noise reduction systems modify a noisy signal to make it more like the original clean signal. For speech, these methods suffer from two main problems: under-suppression of noise and over-suppression of target speech. Instead, synthesizing clean speech based on the noisy signal could produce outputs that are both noise-free and high quality. Our previous work introduced such a system using concatenative synthesis, but it required processing the clean speech at run time, which was slow and not scalable. In order to make such a system scalable, we propose here learning a similarity metric using two separate networks, one network processing the clean segments ofﬂine and another processing the noisy segments at run time. This system incorporates a ranking loss to optimize for the retrieval of appropriate clean speech segments. This model is compared against our original on the CHiME2-GRID corpus, measuring ranking performance and subjective listening tests of resyntheses.
A Bayesian Understanding of Information Uncertainty and the Cost of Capital

The term "information risk" or "information uncertainty" is defined as the risk of a misleading signal. This risk is understood Bayesianly in terms of the likelihood function f(S|φ). In Bayesian method, f(S|φ) captures the quality of signal S with respect to parameter φ. The Bayesian position is that even a highly informative signal (one with a very peaked likelihood function) can bring an increase in uncertainty, and hence an increase in the cost of capital. It can also occur that the cost of capital implied by a capital asset pricing model (CAPM) increases even when better information brings greater certainty. The role of financial reporting should be understood not in terms of its effect on the cost of capital per se, but as aiding investors to assess the probability distributions of future cash flows more accurately, thereby leading on average to higher expected utility portfolios. This is a technical version of the traditional view in accounting theory that financial disclosure should provide generally relevant information for asset valuation and other investment decisions.
Compact Dual-Band Filter Using Defected Stepped Impedance Resonator

This letter presents a novel approach for designing a dual-band bandpass filter by using defected stepped impedance resonator (DSIR). The resonant frequency of the DSIR is found to be much lower than that of the conventional microstrip stepped impedance resonator (SIR), which reduces the circuit size effectively. Two types of second-order DSIR microstrip bandpass filter operating at 1.85 and 2.35 GHz, respectively, are well designed according to the classical theory of coupled resonator filter. Then they are combined to construct a compact dual-band filter with a common parallel microstrip feed line, the measurement results of the fabricated filter have a good agreement with the simulation.
Assisting developers towards fault localization by analyzing failure reports

Large software applications encompass many components with complex interdependencies. When a failure occurs, developers usually have limited information and time in their disposal for localizing the root cause of the observed failure. The most common information developers have readily access to includes failure reports, stack traces, and event logs. In this context, a major challenge is to devise techniques that assist developers utilize this information in order to zero-in their focus on specific methods that have a high probability of containing the root cause of the observed failure. Once such an initial set of methods has been identified, other more elaborate, complex, and computationally expensive data flow analyses could be applied. In this paper, we present a technique which aims to identify such an initial set of suspicious methods by first, retrieving information from failure reports obtained from Bugzilla repositories, second by combining this information with graph models that denote actual dependencies obtained from the subject system's source code in order to create an hypothesis space and third, by applying a ranking score to identify methods that have high likelihood of containing the root cause. The technique is shown to be tractable when applied to systems with several thousands of source code methods and the results exhibit high accuracy.
Contagion effect of restatements through common directorships

We predict that when a restatement is disclosed, information on the lower monitoring quality of the directors at the restating firms (“tainted directors”) can transfer to other firms these directors also serve on (“contagion firms”), and that this information transfer causes investors to reassess the credibility of the contagion firms’ financial reporting. Consistent with our predictions, we find that restatements at the restating firms also induce negative stock price reactions at the contagion firms. The stock price reactions are more negative if the contagion firms have lower financial reporting quality or if the tainted directors serve on the audit committees of the contagion firms. Overall, our results are consistent with a contagion effect of restatements through common directorships. * Corresponding author: Chih-Ying Chen (cychen@smu.edu.sg). We thank Vincent Chen, Scott Liao, colleagues at Singapore Management University, and seminar participants at National Taiwan University for providing helpful comments and suggestions.
Localization of macular edema region from color retinal images for detection of diabetic retinopathy

Exudates are among the first signs of diabetic retinopathy and one of the main causes of vision loss in diabetic patients. In this study, an approach based on clustering and morphological image processing has been proposed for detection of retinal exudates. Contrast-limited adaptive histogram equalization technique is used to make the location of the exudate areas more specific. In addition, the k-means clustering algorithm determines the locations of candidate regions. According to experimental results, it was observed that a majority of the pixels of the exudate regions were detected.
Federated data centers as smart city stabilizing factors

The increasing demand for highly sophisticated cloud services and the consequent worldwide increase in the number of data centers (DC), make the need for energy efficient operation of DCs more actual than ever. Additionally, in the context of smart city and smart grid integration, flexible DCs can play a key role toward acting as grid-stabilization factors. In this paper, a review of the available techniques toward energy-efficient DC operation is performed. The available techniques give rise to four axes of flexibility within a federated DC network. Next, the applicability of the flexible, energy-efficient DC operation is highlighted, by proposing a simple scheduling algorithm, applicable to legacy DC equipment, for effective host and re-arrangement of the DC computing load. The proposed algorithm can provide substantial energy savings during periods of low computing load and improved Quality of Service during periods of high computing load. Concluding, the paper focuses on the grid-stabilization aspects of a federated DC network and the interoperability with the energy network via an Electronic Energy Marketplace in the context of a Smart City.
The influence of LTS-4, a saponoside from Lysimachia thyrsiflora L., on human skin fibroblasts and human melanoma cells

We investigated the effect of a triterpene saponoside from Lysimachia thyrsiflora L. upon the viability, proliferation, morphology and cell motility of human melanoma HTB-140 cells and human skin fibroblasts (HSFs). The compound, denoted LTS-4, decreased the viability and rate of cell growth of both cell types in a time-and dose-dependent manner, and proved cytotoxic against cancer cells at significantly lower concentrations than for fibroblasts. LTS-4 also affected the morphology of the examined cells, causing vacuolisation and actin cytoskeleton disintegration, and had an inhibitory effect on the tumour cell motility.
Socioeconomic Position and Health: The Differential Effects of Education versus Income on the Onset versus Progression of Health Problems

This article seeks to elucidate the relationship between socioeconomic position and health by showing how different facets of socioeconomic position (education and income) affect different stages (onset vs. progression) of health problems. The biomedical literature has generally treated socioeconomic position as a unitary construct. Likewise, the social science literature has tended to treat health as a unitary construct. To advance our understanding of the relationship between socioeconomic position and health, and ultimately to foster appropriate policies and practices to improve population health, a more nuanced approach is required—one that differentiates theoretically and empirically among dimensions of both socioeconomic position and health. Using data from the Americans' Changing Lives Study (1986 through 2001/2002), we show that education is more predictive than income of the onset of both functional limitations and chronic conditions, while income is more strongly associated than education with the progression of both.
Developing a Best Practice Model for Forecasting Annual Franchise Fee Revenue: The Case of the Lexington-Fayette Urban-County Government

Executive Summary: The LFUCG currently forecasts their revenues internally and has their forecasts validated by the Center for Business and Economic Research (CBER) at the University of Kentucky. However, it does not have a well-developed method of forecasting franchise fee revenue. They are not alone, as the literature on revenue forecasting that finds that between 50 and 75 percent of local governments rely on informal, judgmental approaches to forecast revenue instead of more formal, quantitative techniques. However, the literature also indicates that these judgmental approaches are less accurate.
A Comparison of Eleven Commercial Kits for the Determination of Serum Ferritin Levels

Eleven commercial kits for serum ferritin have been compared. Seven kits used RIA and four IRMA methodology. Seven kits used human liver ferritin, two human spleen ferritin and two undefined human ferritin as standard material. Incubation times varied between 30 minutes and 36 hours. Only four kits gave normal ranges determined with the kit in question. All values were compared with the kit in routine use. Although correlation of results was good in 10 cases, (r = 0.903-0.993) the numerical values varied greatly, (slope of the regression line b = 0.437-1.94). These values were obtained from at least 30 sera for each kit. Seven kits gave significantly different results from the routine kit (p less than 0.05 -- Wilcoxon matched pairs test -- two tail value). Inter and Intra-assay coefficients of variation were under 12.5% in all cases within the range of interest. Four kits showed a pronounced non-linear correlation with the routine kit, and one of the IRMA kits exhibited a high-dose hook effect within the standard curve. The other three IRMA kits showed no such effect up to 2000 micrograms . liter-1 (under assay conditions).
Diversity of fruit-feeding butterflies in a mountaintop archipelago of rainforest

We provide the first description of the effects of local vegetation and landscape structure on the fruit-feeding butterfly community of a natural archipelago of montane rainforest islands in the Serra do Espinhaço, southeastern Brazil. Butterflies were collected with bait traps in eleven forest islands through both dry and rainy seasons for two consecutive years. The influence of local and landscape parameters and seasonality on butterfly species richness, abundance and composition were analyzed. We also examined the partitioning and decomposition of temporal and spatial beta diversity. Five hundred and twelve fruit-feeding butterflies belonging to thirty-four species were recorded. Butterfly species richness and abundance were higher on islands with greater canopy openness in the dry season. On the other hand, islands with greater understory coverage hosted higher species richness in the rainy season. Instead, the butterfly species richness was higher with lower understory coverage in the dry season. Butterfly abundance was not influenced by understory cover. The landscape metrics of area and isolation had no effect on species richness and abundance. The composition of butterfly communities in the forest islands was not randomly structured. The butterfly communities were dependent on local and landscape effects, and the mechanism of turnover was the main source of variation in β diversity. The preservation of this mountain rainforest island complex is vital for the maintenance of fruit-feeding butterfly community; one island does not reflect the diversity found in the whole archipelago.
Emerging distribution systems in central and Eastern Europe

Purpose – The purpose of the research is to shed light on the evolution of distribution structures and its consequent implications for supply chain management (SCM) in the context of the emerging markets of Central and Eastern Europe (CEE). Design/methodology/approach – A structured literature review followed by two case studies, which combine qualitative and quantitative analysis. Mainly in‐depth interviews were used, with company sales data analysis in terms of variation and forecast accuracy.Findings – It was found that CEE distribution structures are overlapping, and along complex traditional structures there exists a possibility for a more direct approach. This modern key‐account approach improves supply chain performance, mainly due to echelon elimination and information sharing. The case studies also illustrate that supply chain demand distortion originating practices create uncertainty in demand, even in the case of modern key accounts. The findings therefore suggest that general SCM approaches of .
Calibration of SDR Circuit Imperfections

Software defined radio (SDR) transceivers comprising a single highly reconfigurable circuit have proven to enable multi-mode multi-band operation at low-cost. However, distortion induced by circuit imperfections hampers standard compliancy over the diverse modes and bands. In this paper, a solution is presented and implemented in hardware to eliminate this distortion by using digital in-system calibration. The proposed calibration scheme offers system performance improvements beyond standard compliancy, achieving e.g. an error vector magnitude (EVM) of 1.8%, a quadrature imbalance of -46 dBc and -42 dBc at the transmitter and receiver output respectively and a carrier feedthrough of -38 dBc. This calibration scheme is very efficient and directly applicable on most SDR transceivers, even in a multiple antenna (MIMO) configuration.
SvmFu : Software For SVMs

Motivation: Because theQ matrix in the SVM training problem is in general dense and of full rank, and has size equal to the number of data points squared, traditional “off the shelf” QP methods are not applicable for solving large problems (above 2,000 or so points). Nevertheless, there is a need to solve large instances: on many problems, SVMs have provided the best performance of any methods to date.
IT Governance Impact on Business Unit Performance

The main objective of this thesis is to investigate the impact and role of implementing information technology (IT) governance practices on the business value driven from IT. The proposed research model encompasses the use of configurational theory in order to find different gestalts of IT governance practices. This research also looks at the links between these gestalts and the performance of business units from a financial and non-financial perspective. To test the model, 57 matched surveys were collected from North America and the Middle East. Different clusters of IT governance practices have emerged from this study with distinct yet significant impact on business unit non-financial performance. However, no significant impact on the business unit financial performance was found. The findings show that implementing different sets of IT governance practices within organizations can result in different levels of performance at the business unit level in terms of business processes, decision making and legal and ethical compliance.
Performance Evaluation of EEG Based Mental Stress Assessment Approaches for Wearable Devices

Mental stress has been identified as the root cause of various physical and psychological disorders. Therefore, it is crucial to conduct timely diagnosis and assessment considering the severe effects of mental stress. In contrast to other health-related wearable devices, wearable or portable devices for stress assessment have not been developed yet. A major requirement for the development of such a device is a time-efficient algorithm. This study investigates the performance of computer-aided approaches for mental stress assessment. Machine learning (ML) approaches are compared in terms of the time required for feature extraction and classification. After conducting tests on data for real-time experiments, it was observed that conventional ML approaches are time-consuming due to the computations required for feature extraction, whereas a deep learning (DL) approach results in a time-efficient classification due to automated unsupervised feature extraction. This study emphasizes that DL approaches can be used in wearable devices for real-time mental stress assessment.
The direct chemical estimation of carbamino compounds of CO2 with hæmoglobin

THE "bound" C02 of blood is defined as the difference between (a) The total C02 which can be liberated by treatment with acid and vacuum extraction, and (b) The C02 present in simple physical solution. The bound C02 certainly consists, in large measure, of free bicarbonate ions, but in addition there may, under physiological conditions, be appreciable amounts of: (i) C02 bound to haemoglobin in the form of carbamino compounds, as suggested by Henriques [1928];
CULTURAL , MORPHOLOGICAL AND MOLECULAR CHARACTERIZATION OF VINCA ALKALOIDS PRODUCING ENDOPHYTIC FUNGUS FUSARIUM SOLANI ISOLATED FROM CATHARANTHUS ROSEUS

We have isolated fifty-two endophytic fungi (AA-CRL-1 to AA-CRL52) from the leaves of Catharanthus roseus plants collected from different parts of Pune (Maharashtra, India). These endophytic fungi represented different genera and were screened for vinca alkaloids production using TLC and ESI-MS analysis. Out of the 52 endophytic fungal cultures screened, the endophytic culture AA-CRL-20 was found to produce vinca alkaloids (Vinblastine and Vincristine) extracellularly. The endophytic fungal strain AA-CRL-20 which produced vinca alkaloids was identified as Fusarium solani based on its cultural and morphological characters and internal transcribed spacer (ITS) sequence analysis.