Miracle-dz/UniFAR-FTUs huggingface dataset:
Decontaminating pilots in cognitive massive MIMO networks

Cognitive radio has been lately suggested as a promising technology in order to improve spectrum utilization. This paper addresses the problem of channel estimation in an underlay interference-prone cognitive radio setup. We consider a primary and a secondary base station, both with multiple antenna capability and serving multiple users. Although previous studies propose the use of beamforming to handle secondary-caused interference, this cannot be done in practice unless channels are correctly estimated in the first place. However channel estimation itself is plagued by interference (pilot contamination effects). Therefore we propose a method to address channel estimation at the primary system while removing contamination caused by the secondary transmitter. The approach is twofold: (i) We develop a robust channel estimator which makes use of covariance information. We show analytically that the performance of this estimator is identical to the interference free scenario under certain when the number of antennas becomes large under a condition on the distribution of the multipath model. (ii) We build a pilot assignment algorithm which seeks to fulfill this condition. Significant gains are reported.
A direct comparison of presence levels in text-based and graphics-based virtual environments

We present results from an experiment (n=78) which used two presence measures to directly compare presence in text-based and graphics-based VEs of two levels of quality. The results show that text-based VEs produce less presence than graphics-based VEs, but the actual difference is less than 20%. This finding has implications for those wishing to implement VEs in impoverished devices or those working towards understanding the cognitive processing of VEs.
Planar center-fed leaky-wave antenna arrays for millimeter wave systems

Two kinds of planar center-fed leaky-wave antenna arrays for millimeter wave systems are presented. The antenna arrays consist of a printed one-dimensional periodic metal strip grating on a grounded dielectric waveguide and designed for broadside radiation. The first antenna array has a hybrid structure with a feeding device for the planar dielectric waveguide, represented by a center-fed linear slot waveguide array. The second antenna array has a simple single-layer structure with a feeding device, formed by a comb line using the central strip of the grating. The investigated examples of both kinds of arrays exhibit low return loss at frequencies of broadside radiation. The radiation efficiency of antennas exceeds 50 % at frequencies of up to 37-37.5 GHz, while the antenna gain is above 30 dBi.
Can C++ be made as safe as SPARK?

SPARK offers a way to develop formally-verified software in a language (Ada) that is designed with safety in mind and is further restricted by the SPARK language subset. However, much critical embedded software is developed in C or C++. We look at whether and how benefits similar to those offered by the SPARK language subset and associated tools can be brought to a C++ development environment.
Coexistence of Gait Disturbances and Chorea in Experimental Huntington's Disease

Huntington's disease (HD) is an autosomal dominant neurodegenerative disease caused by an expanded CAG repeat. The clinical features are progressive motor dysfunction, cognitive deterioration, and psychiatric disturbances. Unpredictable choreic movements, among the most characteristic hallmarks, may contribute to gait disturbances and loss of balance in HD individuals. In this study, we aimed to investigate and characterize the gait abnormalities and choreic movements in a transgenic rat model of HD (tgHD). TgHD presents typical neuropathological, neurophysiological, and behavioral aspects mimicking some of the key features of human HD and is the only described experimental model for HD that exhibits choreiform movements. We used the Catwalk, with emphasis on static and dynamic gait parameters, to test the hypothesis that at symptomatic age (9 months) the dynamic measures of gait in HD are altered and coexist with choreiform movements. Our results showed that the dynamic parameters seem to be more affected than static parameters at this age in tgHD rats. The number of steps and step cycles and swing speed of the paws were increased in tgHD rat in comparison to wild-type controls. Our study demonstrates that gait abnormalities coexist with chorea rather than being caused by it. These symptoms may originate from distinct networks in the basal ganglia and downstream connections.
Content-Based Social Network Analysis of Mailing Lists

Social Network Analysis (SNA) provides tools to examine relationships between people. Text Mining (TM) allows capturing the text they produce inWeb 2.0 applications, for example, however it neglects their social structure. This paper applies an approach to combine the two methods named "content-based SNA". Using the R mailing lists, R-help and R-devel, we show how this combination can be used to describe people's interests and to find out if authors who have similar interests actually communicate. We find that the expected positive relationship between sharing interests and communicating gets stronger as the centrality scores of authors in the communication networks increase.
Design on LVDS receiver with new delay-selecting technique for UXGA flat panel display applications

A LVDS receiver with new data recovery design for flat-panel-display (FPD) link is presented. The new delay-selecting technique is used in LVDS receiver to reduce the circuit complexity and to save chip power for cost-efficient applications. The proposed LVDS receiver with an operation data rate of 1.25 Gb/s has been successfully verified in a 0.13-mum CMOS process, which can fully support the operation of FPD link with UXGA resolution
Non-parametric speaker turn segmentation of meeting data

An extension of conventional speaker segmentation framework is presented for a scenario in which a number of microphones record the activity of speakers present at a meeting (one microphone per speaker). Although each microphone can receive speech from both the participant wearing the microphone (local speech) and other participants (cross-talk), the recorded audio can be broadly classiﬁed in three ways: local speech, cross-talk, and silence. This paper proposes a technique which takes into account cross-correlations, values of its maxima, and energy differences as features to identify and segment speaker turns. In particular, we have used classical cross-correlation functions, time smoothing and in part temporal constraints to sharpen and disambiguate timing differences between microphone channels that may be dominated by noise and reverberation. Experimental results show that proposed technique can be successively used for speaker segmentation of data collected from a number of different setups.
Factors associated with loneliness among the institutionalised elders in Shanghai, China: the role of social support

Abstract Studies have shown that loneliness is increasingly prevalent among the aged, especially those who live in institutions. This study examines the role of social support and differences in loneliness among institutionalised elders, using a face-to-face questionnaire interview in a Shanghai institution. Results show that the prevalence of loneliness among participants was relatively high. Gender, subjective appraisals of relationship with nurses, frequency of being visited by children, frequency of being visited by friends, and subjective appraisals of relationship with roommates were significant predictors of loneliness. The quality of social support was indicated as a significant factor for predicting loneliness rather than its quantity. It is striking that frequency of being visited by children was found to be positively associated with loneliness. This counterintuitive finding suggests that the function of family for those institutionalized elders may be negative under China’s cultural norms, beliefs, and perceptions, which is incongruent with theoretical assumptions in Western countries.
Developing a Bayesian Network for Clinical Diagnosis in Veterinary Medicine : from the Individual to the Herd

In close collaboration with two experts, we are building a Bayesian network for the early detection of classical swine fever in pigs. Although our network will ultimately be tailored to detecting the disease in pig herds, we decided to begin with modelling the pathogenesis of the disease in the individual animal. Having modelled the patterns of classical swine fever observed in individuals, we now are in the process of rendering our network applicable to herds. Upon doing so, we are confronted with various intriguing modelling issues. As an example, we focus in this paper on the issue of modelling diverging knowledge that pertains to the different types of pig in a herd.
ICF based automation system for spinal cord injuries rehabilitation

Disabilities, specially the ones caused by injuries of spinal cord, affect both people's behavior and participation in daily activities. Therefore, developing automated systems that monitor and assess the progress of Spinal Cord Injury (SCI) patients represents an accelerated need. In this paper we utilize the framework of the International Classification for Functioning, disability and health (ICF) in order to propose an automatic system for SCI patients progress monitoring and rehabilitation. The ICF is a reference classification system that aims at improving integration of health information and ensuring the collection of accurate health data. The proposed system is divided into three phases; namely (1) ICF code construction, (2) progress monitoring, and (3) progress assessment phases. Comparing the manual expert-based progress assessment to experimental results obtained by the proposed system in this article, an efficiency of 100% has been achieved by the three previously stated phases of the proposed system.
Monte carlo likelihood inference for missing data models

We describe a Monte Carlo method to approximate the maximum likelihood estimate (MLE), when there are missing data and the observed data likelihood is not available in closed form. This method uses simulated missing data that are independent and identically distributed and independent of the observed data. Our Monte Carlo approximation to the MLE is a consistent and asymptotically normal estimate of the minimizer θ* of the Kullback-Leibler information, as both Monte Carlo and observed data sample sizes go to infinity simultaneously. Plug-in estimates of the asymptotic variance are provided for constructing confidence regions for θ*. We give Logit-Normal generalized linear mixed model examples, calculated using an R package.
An Effective Application-Level QoS Routing Scheme for MANETs

In this research, our aim is to construct an effective quality of service (QoS) routing scheme for mobile ad hoc networks (MANET) that provides the service to satisfy required quality by absorbing dynamic changes of network resources. In this paper, we propose an application-level QoS routing scheme for MANETs (ALRS) as a novel QoS routing, that includes following three significant features: (1) estimation of consumed bandwidth on each node using 2-hop neighbors' traffic information, (2) route construction combined with admission control on each application session using (1), and (3) route maintenance based on (1) and (2). ALRS realizes control of generated traffic in MANET effectively and enables to provide the service to satisfy required quality for dynamic changes of network resources. By using our proposed scheme, it is expected that the availability of bandwidth would greatly improve for high-load communication, such as multimedia application on MANET. From our simulation results, it has shown, that our proposed scheme, by effective suppression of traffic, increased delivery ratio up to 40%, without any deterioration of throughput compared to traditional method. Results show that our proposed scheme enables to provide the service to satisfy the required quality
A Mechanistic Study of the Intestinal Absorption of Cryptotanshinone, the Major Active Constituent of Salvia miltiorrhiza

The nature of intestinal absorption of most herbal medicine is unknown. Cryptotanshinone (CTS) is the principal active constituent of the widely used cardiovascular herb Salvia miltiorrhiza (Danshen). We investigated the oral bioavailability of CTS in rats and the mechanism for its intestinal absorption using several in vitro and in vivo models: 1) Caco-2 cell monolayers; 2) monolayers of MDCKII cells overexpressing P-glycoprotein (PgP); and 3) single-pass rat intestinal perfusion with mesenteric vein cannulation. The systemic bioavailabilities of CTS after oral and intraperitoneal administration at 100 mg/kg were 2.05 and 10.60%, respectively. In the perfused rat intestinal model, permeability coefficients based on CTS disappearance from the luminal perfusate (Plumen) were 6.7- to 10.3-fold higher than permeability coefficients based on drug appearance in venous blood (Pblood). Pblood significantly increased in the presence of the P-gP inhibitor, verapamil. CTS transport across Caco-2 monolayers was pH-, temperature- and ATP-dependent. The transport from the apical (AP) to the basolateral (BL) side was 3- to 9-fold lower than that from the BL to the AP side. Inclusion of verapamil (50 μM) in both AP and BL sides abolished the polarized CTS transport across Caco-2 cells. Moreover, CTS was significantly more permeable in the BL to AP than in the AP to BL direction in MDCKII and MDR1-MDCKII cells. The permeability coefficients in the BL to AP direction were significantly higher in MDCKII cells overexpressing PgP. These findings indicate that CTS is a substrate for PgP that can pump CTS into the luminal side.
An MPEG4 Simple Profile Decoder on a Novel Multicore Architecture

Video signal processing algorithms are characterized by high computational complexity and high memory throughput. Since the multicore architectures can provide high computational capacity and high throughput, they suit the video processing applications very well. However, it is very difficult to deal with the increasing design complexity and cost of the multicore system. For video processing application, a generic and flexible video processing multicore platform is essentially required to meet the varying requirements for a wide variety of video standards. In this paper, a novel flexible heterogeneous multicore architecture system is proposed. An MPEG4 simple profile decoder is implemented on the multicore architecture. The decoding performance demonstrates that the proposed architecture is substantially efficient for video processing applications and it is a generic and flexible media-processing design platform.
A Closed Form Approach to the Valuation and Hedging of Basket and Spread Option

The lognormal diffusion model for the returns on the underlying asset is a key assumption of Black-Scholes and many other derivatives models. One advantage of the lognormal is that it is impossible for the price to become negative in the model; another is that asset prices exhibit positive skewness, as is apparent in real world securities. However, when an option is written on a spread or on a portfolio containing both long and short positions in assets that individually follow lognormal diffusions, these properties may not be appropriate. In this paper, Borovkova, Permana, and v.d. Weide propose modeling such portfolios using negative and/or shifted lognormal distributions. This allows a much better fit to the empirical distributions for such cases, while still retaining the closed-form solutions of the Black-Scholes framework for option values and Greek letter risks. The effectiveness and simplicity of the technique are demonstrated by Monte Carlo simulations with a variety of basket options.
The association between vitamin D receptor gene polymorphisms (TaqI and FokI), Type 2 diabetes, and micro-/macrovascular complications in postmenopausal women

Introduction Since there is evidence of the action of vitamin D as a modulator of insulin release and atherosclerosis, it may well be that the vitamin D receptor polymorphisms are associated with diabetes and its chronic complications. Aims To examine the associations between vitamin D receptor polymorphisms (FokI and TaqI) and Type 2 diabetes (T2DM) and its associated chronic complications in postmenopausal women. Methods This cross-sectional study analyzed 100 postmenopausal women with T2DM (mean age 65.7±7.18 years) and 100 postmenopausal women without diabetes in the control group (mean age 65.1±9.18 years; P=0.1608). We evaluated clinical and metabolic parameters and analyzed TaqI and FokI polymorphisms. Results There were no significant differences in genotype and allele frequencies between patients and controls in either of the polymorphisms studied. In the group of patients with diabetes, there were no significant differences in either polymorphism in relation to stroke, retinopathy, nephropathy, or neuropathy. However, in patients with T2DM and coronary artery disease, f genotype (P=0.0361) and the combination of Ff + ff genotypes were observed less frequently (P=0.0462). Conclusion This study suggests the potential protective factor of FokI polymorphism for coronary artery disease in postmenopausal women with T2DM in the recessive model.
Linkages and Economic Development

Specialization is a powerful source of productivity gains, but how production networks at the industry level are related to aggregate productivity in the data is an open question. We construct a database of input-output tables covering a broad spectrum of countries and times, develop a theoretical framework to derive an econometric specification, and document a strong and robust relationship between the strength of industry linkages and aggregate productivity. We then calibrate a multisector neoclassical model and use alternative identification assumptions to extract an industry-level measure of distortions in intermediate input choices. We compute the aggregate losses from these distortions for each country in our sample and find that they are quantitatively consistent with the relationship between industry linkages and aggregate productivity in the data. Our estimates imply that the TFP gains from eliminating these distortions are modest but significant, averaging roughly 10% for middle and low income countries.
Public Audit of Cloud Shared Data by Using Efficient Privacy Preserving Scheme

: Public auditing for cloud storage is of critical importance as the users relies on semi-trusted cloud storage service for data sharing which does not guarantee/assure the integrity of the data being stored. With public auditing of clouds, users resort to a third party auditor (TPA) who verify and assure the internal consistency/lack of corruption of their data in cloud storage services. Despite the good work previously done by researchers in auditing while preserving privacy, still available mechanisms do not efficiently conceal users’ privacy from TPA during sharing of data and yet supporting data and group dynamics. In this paper, we propose privacy preserving auditing scheme that exploits the ring signature to calculate verifications needed to audit data integrity. In this proposed approach, the identities of the user are kept private from public verifier and dynamic groups are supported –that is a new user can be added into the group and an existing group member can be revoked during data sharing.
On Effective Location-Aware Music Recommendation

Rapid advances in mobile devices and cloud-based music service now allow consumers to enjoy music anytime and anywhere. Consequently, there has been an increasing demand in studying intelligent techniques to facilitate context-aware music recommendation. However, one important context that is generally overlooked is user’s venue, which often includes surrounding atmosphere, correlates with activities, and greatly influences the user’s music preferences. In this article, we present a novel venue-aware music recommender system called VenueMusic to effectively identify suitable songs for various types of popular venues in our daily lives. Toward this goal, a Location-aware Topic Model (LTM) is proposed to (i) mine the common features of songs that are suitable for a venue type in a latent semantic space and (ii) represent songs and venue types in the shared latent space, in which songs and venue types can be directly matched. It is worth mentioning that to discover meaningful latent topics with the LTM, a Music Concept Sequence Generation (MCSG) scheme is designed to extract effective semantic representations for songs. An extensive experimental study based on two large music test collections demonstrates the effectiveness of the proposed topic model and MCSG scheme. The comparisons with state-of-the-art music recommender systems demonstrate the superior performance of VenueMusic system on recommendation accuracy by associating venue and music contents using a latent semantic space. This work is a pioneering study on the development of a venue-aware music recommender system. The results show the importance of considering the influence of venue types in the development of context-aware music recommender systems.
The Influence of Ensemble Statistics and Focused Attention on Feature Perception

Ensemble statistics are a means by which our brains can take the average across features such as color (De Gardelle & Summerfield, 2011), size (Chong & Treisman, 2003), and texture (Alvarez & Oliva, 2009) to help us retain the gist of a scene without relying on effortful processing of every object. Previous research has also shown that features such as color appear to be mixed together when attention is split (Golomb et. al, 2014). We wanted to examine how focused attention versus split attention would influence the use of ensemble statistics and feature mixing. To test this, subjects fixated on the center of a computer screen and three squares appeared in their periphery. Either all three of the squares became bold (a split-attention trial) or just one became bold (a focused-attention trial), and subjects were asked to direct their attention to the bold square(s). Each square was then briefly filled with a different color, and subjects were asked to report the color in one of the squares by choosing between two response colors (Experiment 1) or clicking along a color wheel (Experiment 2). Experiment 1 did not show significant effects of the ensemble mean on either attention condition, but this may have been due to a less sensitive experimental design. In Experiment 2 we could fit the distribution of responses with probabolistic models, allowing us to examine differences in guess rate, precision, swapping errors, and shifts toward the ensemble mean. Focused-attention trials showed a decrease in overall noise, with lower standard deviations (precision) and guessing rates. Focused-attention trials also showed a decreased frequency of “swap” errors (reporting one of the distractor colors instead of the target color). We found some evidence that subjects tended to report a color shifted toward the ensemble mean, but there was no significant difference in this measure for focused-attention trials and split-attention trials. These results suggest that ensemble statistics can bias the perception of features by drawing them toward the ensemble mean, and focusing spatial attention does not appear to modulate this effect. Future experiments will test whether this trend persists for larger ensembles containing more objects and different distributions of distractor colors.