Miracle-dz/UniFAR-FTUs huggingface dataset:
Joint CSIT acquisition based on low-rank matrix recovery for FDD massive MIMO systems

Channel state information at the transmitter (CSIT) is essential for frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems, but conventional solutions involve overwhelming overhead both for downlink channel training and uplink channel feedback. In this paper, we propose a joint CSIT acquisition scheme based on low-rank matrix recovery to reduce the overhead. Particularly, unlike conventional schemes where users individually estimate the channel and then feeds back the estimated CSI to the BS to realize CSIT, we propose that all scheduled users feed back their received pilots directly to the BS without individual channel estimation, and then joint MIMO channel estimation can be realized at the BS. We further formulate the joint channel estimation problem at the BS as a low-rank matrix recovery problem by utilizing the low-rank property of the massive MIMO channel matrix, which is caused by the limited number of clusters. Finally, we propose a hybrid low-rank matrix recovery algorithm based on the singular value projection to solve this problem, which can provide accurate CSIT with low overhead as demonstrated by simulations.
Dynamics of k-essence

There are a number of mathematical theorems in the literature on the dynamics of cosmological models with accelerated expansion driven by a positive cosmological constant Λ or a nonlinear scalar field with potential V (quintessence) which do not assume homogeneity and isotropy from the beginning. The aim of this paper is to generalize these results to the case of k-essence models which are defined by a Lagrangian having a nonlinear dependence on the kinetic energy. In particular, Lagrangians are included where late-time acceleration is driven by the kinetic energy, an effect which is qualitatively different from anything seen in quintessence models. A general criterion for isotropization is derived and used to strengthen known results in the case of quintessence.
Pseudo-continuous arterial spin labeling imaging of cerebral blood perfusion asymmetry in drug-naïve patients with first-episode major depression

Many previous studies have reported that regional cerebral blood flow (rCBF) aberrations may be one of the pathological characteristics of depression and rCBF has demonstrated a certain degree of asymmetry. However, studies investigating the cerebral blood perfusion asymmetry changes of drug-naïve patients experiencing their first episode of major depression using pseudo-continuous arterial spin labeling (pCASL) are rare. Ten drug-naïve patients experiencing their first major depression episode and 15 healthy volunteers were enrolled in the current study. A novel pCASL method was applied to whole brain MRI scans of all of the samples. The Statistics Parameter Mapping and Relative Expression Software Tool software packages were used for the pre-processing and statistical analysis of the two sets of images, and the differences in the cerebral blood perfusion at the whole brain level were compared between the two groups. Compared with the healthy control group, the cerebral perfusion of the depression patients showed an asymmetric pattern. Decreased cerebral blood perfusion regions were primarily located in the left hemisphere, specifically in the left temporal lobe, frontal lobe and cingulate cortex [P<0.05 and cluster size ≥30 with false discovery rate (FDR) correction]. Simultaneously, increased perfusion regions were predominantly located in the right hemisphere, specifically in the right cerebellum, thalamus, frontal lobe and anterior cingulate cortex (P<0.05 and cluster size ≥30, with FDR correction). Thus, pCASL may characterize the alterations in cerebral blood perfusion of patients with depression.
Study of MIMO Capacity for Linear Dipole Arrangements using Spherical Mode Expansions

Multiple-input multiple-output (MIMO) antenna systems rank among the emerging key technologies in next generation wireless communication systems. For the analysis of real antenna radiation characteristics and influences by mutual coupling in a multielement antenna arrangement, a spherical eigenmode (SME) evaluation of antenna radiation patterns is presented. In combination with a statistical description of the underlying channel model, the eigenmode expansion provides an efficient alternative to establish an analytical approach in the calculation of antenna envelope correlation and MIMO channel capacity.
Security and Denial of Service Threats in GSM Networks

Mobile networks not only provide great benefits to their users but they also introduce inherent security issues. With respect to security, the emerging risks of denial of service (DoS) attacks will evolve into a critical danger as the availability of mobile networks becomes more and more important for the modern information society. This paper outlines a series of flaws in such networks, particularly DoS attacks and confidentiality threats in GSM networks.
Measuring functional health status in primary care using the COOP-WONCA charts: acceptability, range of scores, construct validity, reliability and sensitivity to change.

BACKGROUND The COOP-WONCA charts comprise six scales designed to measure functional health status in primary care. AIM A study was undertaken to describe the acceptability, distribution of chart scores, construct validity, test-retest reliability and sensitivity to change when these charts were used in the United Kingdom. METHOD For acceptability, distribution of scores and construct validity, data were obtained from 100 consecutive consulting patients aged 16 years and over and 100 non-consulting age-sex matched individuals from one general practice. In order to examine reliability and sensitivity to change, both groups were followed up two weeks later. RESULTS Regarding acceptability, four patients refused to complete the charts during the initial recruitment of the consulters; 74 out of 100 non-consulters returned the first postal questionnaire. The follow-up questionnaire was returned by 68 out of 100 consulters and 57 out of 74 non-consulters. Overall distributions of scores demonstrated reasonable variation. Regarding construct validity, differences between the consulters and non-consulters were all in the anticipated direction and reached statistical significance for three of the six charts. For reliability, the proportion of non-consulters whose scores were unchanged ranged from 56% to 73%. For those whose scores changed, the differences were small and evenly balanced. For sensitivity to change, the proportion of consulters whose scores altered ranged from 45% to 59% with mean changes all indicating improvements in health. There were larger changes for patients consulting about acute problems than for those with chronic problems. CONCLUSION It appears that the charts were acceptable, with reasonable distributions of scores and evidence of construct validity. Moderate levels of reliability and sensitivity to change were demonstrated. This study suggests that the COOP-WONCA charts are suitable for measuring functional health status in primary care in the UK.
Experimental determination of control parameter intervals for repeatable gaits in modular snake robots

Controlling motion in a Modular Snake Robot can be achieved by reducing the high dimensionality of the robot's configuration space Q. This can be done by using cyclic motions programed by functions whose parameters conform to a parameterized space P. In the scope of this research P = ℝ9, wich leads to an infinite set of possible gaits. However, not every combination of parameters leads to feasible and effective gaits. The paper outlines practical limitations of P related to mechanical constraints and theoretical rules that analyze the behavior of the parameterized functions that control the robot's motion. Once these limits were imposed on the parameterized space, an experimental sweep along the feasible parameter intervals was carried out. The aim of this sweep was to verify and analyze the type of locomotion output produced, in order to select a set of gaits according to a criteria that measures their repeatability. The value of select repeatable gaits based on the control parameters relies on the possibility of using them as a basis for determining general locomotion models that are scalable to different numbers of DoF.
Consensus-Based Distributed Cooperative Learning From Closed-Loop Neural Control Systems

In this paper, the neural tracking problem is addressed for a group of uncertain nonlinear systems where the system structures are identical but the reference signals are different. This paper focuses on studying the learning capability of neural networks (NNs) during the control process. First, we propose a novel control scheme called distributed cooperative learning (DCL) control scheme, by establishing the communication topology among adaptive laws of NN weights to share their learned knowledge online. It is further proved that if the communication topology is undirected and connected, all estimated weights of NNs can converge to small neighborhoods around their optimal values over a domain consisting of the union of all state orbits. Second, as a corollary it is shown that the conclusion on the deterministic learning still holds in the decentralized adaptive neural control scheme where, however, the estimated weights of NNs just converge to small neighborhoods of the optimal values along their own state orbits. Thus, the learned controllers obtained by DCL scheme have the better generalization capability than ones obtained by decentralized learning method. A simulation example is provided to verify the effectiveness and advantages of the control schemes proposed in this paper.
Disclosure of Health Databases

Health databases contain a wealth of implicit knowledge on health problems that is difficult to make explicit. This paper investigates the disclosure of the Registration Network Family Practices (RNH) database, a database containing information on health problems of patients in the south of the Netherlands. We achieve a (partial) disclosure of the RNH database using techniques from knowledge discovery in databases (KDD): (1) we build a datawarehouse for efficiently answering queries about incidence and prevalence of diseases, and (2) we mine sequential association rules that represent the co-occurrence of diseases and visualize their time dependencies. The results show that the combination of KDD and straightforward data-mining techniques facilitates the disclosure of knowledge in health databases.
Pumping lemma and Ogden lemma for tree-adjoining grammars

The pumping lemma and Ogden lemma offer a powerful method to prove that a particular language is not context-free. In 2008 Kanazawa proved an analogue of pumping lemma for well-nested multiple-context free languages. However, the statement of lemma is too weak for practical usage. We prove a stronger variant of pumping lemma and an analogue of Ogden lemma for this language family. We also use these statements to prove that some natural context-sensitive languages cannot be generated by tree-adjoining grammars.
Features of effective computerised clinical decision support systems: meta-regression of 162 randomised trials

Objectives To identify factors that differentiate between effective and ineffective computerised clinical decision support systems in terms of improvements in the process of care or in patient outcomes. Design Meta-regression analysis of randomised controlled trials. Data sources A database of features and effects of these support systems derived from 162 randomised controlled trials identified in a recent systematic review. Trialists were contacted to confirm the accuracy of data and to help prioritise features for testing. Main outcome measures “Effective” systems were defined as those systems that improved primary (or 50% of secondary) reported outcomes of process of care or patient health. Simple and multiple logistic regression models were used to test characteristics for association with system effectiveness with several sensitivity analyses. Results Systems that presented advice in electronic charting or order entry system interfaces were less likely to be effective (odds ratio 0.37, 95% confidence interval 0.17 to 0.80). Systems more likely to succeed provided advice for patients in addition to practitioners (2.77, 1.07 to 7.17), required practitioners to supply a reason for over-riding advice (11.23, 1.98 to 63.72), or were evaluated by their developers (4.35, 1.66 to 11.44). These findings were robust across different statistical methods, in internal validation, and after adjustment for other potentially important factors. Conclusions We identified several factors that could partially explain why some systems succeed and others fail. Presenting decision support within electronic charting or order entry systems are associated with failure compared with other ways of delivering advice. Odds of success were greater for systems that required practitioners to provide reasons when over-riding advice than for systems that did not. Odds of success were also better for systems that provided advice concurrently to patients and practitioners. Finally, most systems were evaluated by their own developers and such evaluations were more likely to show benefit than those conducted by a third party.
Determining starting basal rates of insulin infusion for insulin pump users: a comparison between methods

Objective We aimed to assess the accuracy and safety of presently available methods of estimating starting basal insulin rates for patients with type 1 and 2 diabetes, and to compare them against an empirically derived standard basal rate and a newly developed regression formula. Research design and methods Data on 61 patients with type 1 diabetes on continuous subcutaneous insulin infusion (CSII) therapy and 34 patients with type 2 diabetes on CSII were reviewed. Patient data were first analyzed for correlations between initial patient parameters and final basal rates. Starting basal rates were then retrospectively calculated for these patients according to the weight-based method (WB-M), the total daily dose (TDD) of insulin method (TDD-M), a flat empiric value, and a new formula developed by regression analysis of clinical data. These 4 methods were subsequently compared in their accuracy and potential risk of hypoglycemia. Results For type 1 diabetes, patient weight and TDD of long-acting insulin correlated with final basal rates. Both the regression formula and the TDD-M appeared safer than the WB-M and empirical estimates. For type 2 diabetes, only patient TDD of long-acting insulin correlated with final basal rates. The regression formula was significantly more accurate for patients with type 2 diabetes overall, but the TDD-M estimate was marginally safer. Conclusions The pre-existing TDD-M was found to be the safest presently recommended estimate of initial basal rates for pump initiation in both type 1 and 2 diabetes. The best-fit regression was found to have potential use for type 2 CSII initiation.
Parallel Numerical Linear

We survey general techniques and open problems in numerical linear algebra on parallel architectures. We rst discuss basic principles of parallel processing, describing the costs of basic operations on parallel machines, including general principles for constructing eecient algorithms. We illustrate these principles using current architectures and software systems, and by showing how one would implement matrix multiplication. Then, we present direct and iterative algorithms for solving linear systems of equations, linear least squares problems, the symmetric eigenvalue problem, the nonsymmetric eigenvalue problem, the singular value decomposition, and generalizations of these to two matrices. We consider dense, band and sparse matrices.
Distance estimation using two different-aperture images obtained by tilted lens optics camera

In this paper, we propose a distance estimation method using tilted lens optics. Our proposed method uses two input images: one is an all-in-focus image, and the other is a ground-in-focus image. The method estimates a distance value for each pixel by comparing the amount of blur between the ground-in-focus image and multi-focus images that are synthesized by applying a Gaussian filter to the all-in-focus image. As our method needs only two input images and simple calculations, it is suitable for distance estimation applications that require a wide detection range and real-time processing, such as robotics and automotive tasks.
Comparison of reweighted message passing algorithms for LDPC decoding

Low density parity check (LDPC) codes can be decoded with a variety of decoding algorithms, offering a trade-off in terms of complexity, latency, and performance. We describe seven distinct LDPC decoders and provide a performance comparison for a practical regular LDPC code. Our simulations indicate that the best performance/latency trade-off is achieved by one version of the reweighted max-product decoder. When latency is not an issue, the traditional sum-product decoder yields the best performance.
Architecture and assembly of the Gram‐positive cell wall

The bacterial cell wall is a mesh polymer of peptidoglycan – linear glycan strands cross‐linked by flexible peptides – that determines cell shape and provides physical protection. While the glycan strands in thin ‘Gram‐negative’ peptidoglycan are known to run circumferentially around the cell, the architecture of the thicker ‘Gram‐positive’ form remains unclear. Using electron cryotomography, here we show that Bacillus subtilis peptidoglycan is a uniformly dense layer with a textured surface. We further show it rips circumferentially, curls and thickens at free edges, and extends longitudinally when denatured. Molecular dynamics simulations show that only atomic models based on the circumferential topology recapitulate the observed curling and thickening, in support of an ‘inside‐to‐outside’ assembly process. We conclude that instead of being perpendicular to the cell surface or wrapped in coiled cables (two alternative models), the glycan strands in Gram‐positive cell walls run circumferentially around the cell just as they do in Gram‐negative cells. Together with providing insights into the architecture of the ultimate determinant of cell shape, this study is important because Gram‐positive peptidoglycan is an antibiotic target crucial to the viability of several important rod‐shaped pathogens including Bacillus anthracis, Listeria monocytogenes, and Clostridium difficile.
Analysis of shorted V-slot cut dual and wide band triangular microstrip antenna

An extensive analysis to study the dual and wide band response in V-slot cut vertex truncated triangular microstrip antenna shorted on its both ends is proposed. First an analysis of V-slot cut triangular patch shorted on one of its ends is presented. The V-slot reduces the resonance frequencies of shorted TM1/4,0, TM3/4,0 and TM3/4,2 modes of the patch, to yield dual and wide band response. Further when V-slot cut patch is shorted on both its ends, the resonant modes involved in realizing dual and wide band response changes. In this configuration, V-slot reduces the resonance frequencies of dual shorted patch modes like TM10, TM12 and TM20, to yield dual band response. The proposed analysis gives an insight into the functioning of quarter wavelength and half wavelength shorted slot cut patch antennas.
Dynamic Memory Balancing for Virtualization

Allocating memory dynamically for virtual machines (VMs) according to their demands provides significant benefits as well as great challenges. Efficient memory resource management requires knowledge of the memory demands of applications or systems at runtime. A widely proposed approach is to construct a miss ratio curve (MRC) for a VM, which not only summarizes the current working set size (WSS) of the VM but also models the relationship between its performance and the target memory allocation size. Unfortunately, the cost of monitoring and maintaining the MRC structures is nontrivial. This article first introduces a low-cost WSS tracking system with effective optimizations on data structures, as well as an efficient mechanism to decrease the frequency of monitoring. We also propose a Memory Balancer (MEB), which dynamically reallocates guest memory based on the predicted WSS. Our experimental results show that our prediction schemes yield a high accuracy of 95.2% and low overhead of 2%. Furthermore, the overall system throughput can be significantly improved with MEB, which brings a speedup up to 7.4 for two to four VMs and 4.54 for an overcommitted system with 16 VMs.
STATELESS MODEL FOR THE PREVENTION OF MALICIOUS TUNNELS

Abhishek Singh, Ola Nordström, Andre L M dos Santos, Chenguhai Lu Georgia Tech. Information Security Center (GTISC) Center for Experimental Research in Computer Science (CERCS) College of Computing Georgia Institute of Technology Atlanta, GA 30332 {abhi, nola, andre,lulu}@cc.gatech. edu Abstract The use of malicious communication channels is becoming an integral part of the malicious software agents and tools including those employed for remote access tools and distributed denial of service tools. These malicious software agents use the unused fields of ICMP and TCP/IP packets to establish malicious communication channels. Since TCP/IP comprises of 96% of the traffic, the paper identifies the idle fields in TCP/IP and ICMP messages and proposes the use of a stateless model to protect against the misuse of these unused fields. This paper also presents the advantages of using a stateless model over firewalls and IDS. The proposed modifications are recommended highly for the end hosts and it has been shown that the proposed modifications are computationally inexpensive.
Robust adaptive identification of nonlinear system using neural network

It is well-known that disturbances can cause the divergence of neural networks in the identification of nonlinear systems. Sufficient conditions using so-called modified algorithms are available to provide guaranteed convergence for adaptive systems. They are: the dead-zone scheme, adaptive law modification and /spl sigma/-modification. These schemes normally require knowledge of the upper bound of the disturbance. In this paper, a robust weight-tuning algorithm is used to train a multi-layered neural network with an adaptive dead-zone scheme. The proposed robust adaptive algorithm does not require knowledge of either the upper bound of the disturbance or the bound on the norm of the estimate parameter. A complete convergence is provided based on the Lyapunov theorem to deal with the nonlinear system. Simulation results are presented to show the good performance of the algorithm.