Miracle-dz/UniFAR-FTUs huggingface dataset:
Are 4 hands better than 2?: bimanual interaction for quadmanual user interfaces

The design of spatial user interaction for immersive virtual environments (IVEs) is an inherently difficult task. Missing haptic feedback and spatial misperception hinder an efficient direct interaction with virtual objects. Moreover, interaction performance depends on a variety of ergonomics factors, such as the user's endurance, muscular strength, as well as fitness. However, the potential benefits of direct and natural interaction offered by IVEs encourage research to create more efficient interaction methods. We suggest a novel way of 3D interaction by utilizing the fact that for many tasks, bimanual interaction shows benefits over one-handed interaction in a confined interaction space. In this paper we push this idea even further and introduce quadmanual user interfaces (QUIs) with two additional, virtual hands. These magic hands allow the user to keep their arms in a comfortable position yet still interact with multiple virtual interaction spaces. To analyze our approach we conducted a performance experiment inspired by a Fitts' Law selection task, investigating the feasibility of our approach for the natural interaction with 3D objects in virtual space.
Self-Localization Over RFID Tag Grid Excess Channels Using Extended Filtering Techniques

Accuracy of target self-localization in RFID tag information networks and grids critically affects its situation awareness. With an insufficient localization accuracy, information about local 2D or 3D surroundings delivered to a target by request may provoke collisions, even fatal. In RFID networking systems, target state can be observed over a big number of tags. For such a case, the extended Kalman filter (EKF) algorithm is modified and a new extended unbiased finite impulse response (EFIR) filtering algorithm is developed. We show that redundant information captured from the tags allows increasing both the localization accuracy and system stability. The common factor here is that the number of tags required to increase accuracy is limited in the target nonlinear medium, by about six in our case. It is also shown that target state observation over the RFID tag excess channels allows mitigating effect of the imprecisely defined noise statistics on the EKF performance and preventing divergence in EKF.
Speaker verification with the mixture of Gaussian factor analysis based representation

This paper presents a generalized i-vector representation framework using the mixture of Gaussian (MoG) factor analysis for speaker verification. Conventionally, a single standard factor analysis is adopted to generate a low rank total variability subspace where the mean supervector is assumed to be Gaussian distributed. The energy that can't be represented by the low rank space is modeled by a single multivariate Gaussian. However, due to the sparsity of the frame level posterior probability and the short duration characteristics, some dimensions of the first-order statistics may not be Gaussian distributed. Therefore, we replace the single Gaussian with a mixture of Gaussians to better represent the residual energy. Experimental results on the NIST SRE 2010 condition 5 female task and the RSR 2015 part 1 female task show that the MoG i-vector outperforms the i-vector baseline by more than 10% relatively for both text independent and text dependent speaker verification tasks, respectively.
Toxic Cyanobacteria in Water: a Guide to Their Public Health Consequences, Monitoring and Management Chapter 9. Remedial Measures

The management and control of cyanobacteria in water supply storage facilities and of cyanotoxins in drinking water may be approached at a number of points and levels in the hierarchy of the total supply system. A detailed assessment of water supply systems with respect to the potential impact of blooms and cyanotoxins on water quality and public health has been presented in Chapter 6. The first preference for control is the prevention of eutrophication, which is discussed in Chapter 8. The next level of management response is reservoir and water body management which can include some engineering techniques to alter hydrophysical conditions in the water body in order to reduce cyanobacterial growth (section 8.5). The more immediate and short-term control techniques which can be used in the management of raw water abstraction include the avoidance of contamination by positioning of offtakes, selection of intake depth, offtake by bank filtration, and the use of barriers to restrict scum movement. Another intervention technique is chemical treatment with algicides. Algaecides have been, and will continue to be, used as emergency measures for the control of cyanobacteria, and their role in management strategies needs to be assessed from practical and environmental viewpoints. The final option for management of cyanobacterial problems and cyanotoxins in water supplies is within the treatment system. Research on removal of algal and cyanobacterial cells has been widely published (see review by Mouchet and Bonnélye, 1998) and recent work has generated quite detailed knowledge on cyanotoxin removal during drinking water treatment. Much of the work on cyanotoxin removal has focused on single treatment steps, and a few studies have investigated the common combinations of coagulation, clarification and filtration. As a research approach, this is useful because assessments of the performance of individual treatment steps may be generalised more readily than observations gained in complete, but individual, supply systems with their respective site-specific characteristics. However, management approaches aimed at providing safe drinking water from cyanobacteria-infested surface waters require considering the system as a whole, and using different combinations of resource management tailored to the specific locality and different treatment steps. In such an overall approach, steps that individually may be unsatisfactory can have their place in combination with others and thus contribute to a multi-barrier approach. Furthermore, the individual aspects of each drinking water supply necessitate local assessment of performance as well as local optimisation of resource management and treatment strategies.
Constraints on First-Light Ionizing Sources from Optical Depth of the Cosmic Microwave Background

We examine the constraints on high-redshift star formation, ultraviolet and X-ray preionization, and the epoch of reionization at redshift zr, inferred from the recent WMAP-5 measurement, τe = 0.084 ± 0.016, of the electron-scattering optical depth of the cosmic microwave background (CMB). Half of this scattering can be accounted for by the optical depth, τe = 0.04-0.05, of a fully ionized intergalactic medium (IGM) at z ⩽ zGP ≈ 6-7, consistent with Gunn-Peterson absorption in neutral hydrogen. The required additional optical depth, Δ τe = 0.03 ± 0.02 at z > zGP, constrains the ionizing contributions of “first light” sources. WMAP-5 also measured a significant increase in small-scale power, which lowers the required efficiency of star formation and ionization from minihalos. Early massive stars (UV radiation) and black holes (X-rays) can produce a partially ionized IGM, adding to the residual electrons left from incomplete recombination. Inaccuracies in computing the ionization history, xe(z) , and degeneracies in cosmological parameters (Ωm, Ωb, σ8, ns) add systematic uncertainty to the measurement and modeling of τe. From the additional optical depth from sources at z > zGP, we limit the star formation efficiency, the rate of ionizing photon production for Population III and Population II stars, and the photon escape fraction, using standard histories of baryon collapse, minihalo star formation, and black hole X-ray preionization.
A video frame exchange protocol with selfishness detection mechanism under sparse infrastructure-based deployment in VANET

Due to the limited budget and high maintenance cost, it is difficult to deploy a large amount of roadside units (such as 802.11 base stations) to cover the complicated road areas. This paper addresses an important topic on frame sharing since vehicles often need to download large size data such as video clips regarding local news. It is important to fairly use V2V communications at places where an infrastructure is not immediately available or cannot be directly used. We aim to improve local video downloading performance by integrating V2V and V2I communications. The proposed approach, ZFEP/SD, is able to exploit user requests locality and to initiate video frames sharing among neighboring vehicles. We also consider the case of selfish users, e.g., those not willing to share frames with others. Numerical results show that our ZFEP performs better than a pure infrastructure-based download, and that ZFEP/SD ensures that cooperative nodes always get better service than every type of selfish nodes.
Enhancing incretin action for the treatment of type 2 diabetes.

OBJECTIVE To examine the mechanisms of action, therapeutic potential, and challenges inherent in the use of incretin peptides and dipeptidyl peptidase-IV (DPP-IV) inhibitors for the treatment of type 2 diabetes. RESEARCH DESIGN AND METHODS The scientific literature describing the biological importance of incretin peptides and DPP-IV inhibitors in the control of glucose homeostasis has been reviewed, with an emphasis on mechanisms of action, experimental diabetes, human physiological experiments, and short-term clinical studies in normal and diabetic human subjects. RESULTS Glucagon-like peptide 1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP) exert important effects on beta-cells to stimulate glucose-dependent insulin secretion. Both peptides also regulate beta-cell proliferation and cytoprotection. GLP-1, but not GIP, inhibits gastric emptying, glucagon secretion, and food intake. The glucose-lowering actions of GLP-1, but not GIP, are preserved in subjects with type 2 diabetes. However, native GLP-1 is rapidly degraded by DPP-IV after parenteral administration; hence, degradation-resistant, long-acting GLP-1 receptor (GLP-1R) agonists are preferable agents for the chronic treatment of human diabetes. Alternatively, inhibition of DPP-IV-mediated incretin degradation represents a complementary therapeutic approach, as orally available DPP-IV inhibitors have been shown to lower glucose in experimental diabetic models and human subjects with type 2 diabetes. CONCLUSIONS GLP-1R agonists and DPP-IV inhibitors have shown promising results in clinical trials for the treatment of type 2 diabetes. The need for daily injections of potentially immunogenic GLP-1-derived peptides and the potential for unanticipated side effects with chronic use of DPP-IV inhibitors will require ongoing scrutiny of the risk-benefit ratio for these new therapies as they are evaluated in the clinic.
The Parallel Communication and I/O Bandwidth Benchmarks: b eff and b eff io

We describe the design and MPI implementation of two benchmarks created to characterize the balanced system performance of high-performance clusters and supercomputers. We start with a communication-specific benchmark, called b eff that characterizes the message passing performance of a system. Following the same line of development, we extend this work to the design and implementation of the effective I/O bandwidth benchmark (beff io). Both of these benchmarks were developed on a Cray T3E-900 and have two goals: a) to get a detailed insight into the performance strengths and weaknesses of different parallel communication and I/O patterns, and b) to obtain a single bandwidth number that characterizes the average performance of the system namely processor communication for beff, and the I/O subsystem for b eff io. Both benchmarks use a timedriven approach and loop over a variety of communication and access patterns to characterize a system in a fairly automated fashion. Results of the two benchmarks are given for several systems including IBM SPs, Cray T3E, NEC SX5, and Hitachi SR 8000.
A privacy preserving distributed reputation mechanism

Reputation systems allow to estimate the trustworthiness of entities based on their past behavior. Electronic commerce, peer-to-peer routing and collaborative environments, just to cite a few, highly benefit from using reputation systems. To guarantee an accurate estimation, reputation systems typically rely on a central authority, on the identification and authentication of all the participants, or both. In this paper, we go a step further by presenting a distributed reputation mechanism which is robust against malicious behaviors and that preserves the privacy of its clients. Guaranteed error bounds on the estimation are provided.
Acquiring an Environment Map through Image Mosaicking

In this report, we describe methods of acquiring an environment map by image mosaicking. We focus on technique details of the different algorithms involved. These algorithms include image matching, homography estimation, linear image warping and linear self calibration. Many of these details are distributed in various publications and we here bring them together. Furthermore, these algorithms are widely used in other circumstances and we provide all the C++ code for each of the algorithms.
A Two-Way Semi-Linear Model for Normalization and Significant Analysis of cDNA Microarray Data

A basic question in analyzing cDNA microarray data is normalization. The purpose of normalization is to remove systematic bias in the observed expression values by establishing a normalization curve across the whole dynamic range. A proper normalization procedure ensures that the normalized intensity ratios provide meaningful measures of relative expression levels. We propose a two-way semi-linear model (TW-SLM) for normalization and significant analysis of microarray data. This method does not make the usual assumptions underlying some of the existing methods. For example, it does not assume that: (i) the percentage of differentially expressed genes is small; or (ii) there is symmetry in the expression levels of upand down-regulated genes, as required in the lowess normalization method. The TW-SLM also naturally incorporates uncertainty due to normalization into significant analysis of microarrays. We use a semiparametric approach based on polynomial splines in the TW-SLM to estimate the normalization curves and the normalized expression values. We also conduct simulation studies to evaluate the TW-SLM method and illustrate the proposed method using a published microarray data set.
Lung nodule classification based on shape distributions

This paper presents the application of shape distributions to diagnose lung nodules in computerized tomography images. Our study uses the nodule surface and also interior surfaces generated by their voxel's joint attributes and distribution. The surfaces are captured using 3D Alpha Shapes algorithm. All surfaces are characterized using shape distributions D1, D2, D3, D4 and A3 in order to represent shape behavior based on statistical distribution of their points in a 3D contour. We evaluate experiments with these features using Support Vector Machines and the combination of all descriptors proving above of 90% of accuracy. This indicates a promising feature to distinguish malignant from benign nodules for lung cancer diagnosis.
An RFID based indoor tracking method for navigating visually impaired people

This paper tackles the RFID based tracking problem in an obscured indoor environment. The proposed solution is an integral part of a navigation aid for guiding visually impaired people in a store. It uses RF signal strengths and is based on the Bayes Decision Theory. An observation vector is formed by received radio signal strength indication values, transmitted from three transmitters at distinct frequencies in the UHF band. The indoor area is divided into square grids, where each grid is considered as a class. The problem of tracking is expressed as classifying the observed radio signal strengths to the most likely class. A classification rule is formulated by incorporating a priori assumptions appropriate for the studied model. The proposed approach is tested in a laboratory environment. The results prove that the proposed approach is promising in tracking especially when the tracked person is guided by a system.
An application of ontology in collaborative learning

Collaborative learning is a kind of group learning mode. It emphasizes the communication and collaboration among group members. Current collaborative learning systems haven't reached a high intelligent degree, and some problems such as dynamic grouping have not been solved well. Dynamic grouping refers to the problem that how the members who are interested in the same subject conform a learning group dynamically. In order to solve this problem, this paper comes up with a method using ontology-OBDG (Ontology Based Dynamic Grouping) Method. This method can improve the intelligence of collaborative learning system, and experiment results show that it can solve the dynamic grouping problem.
Revisiting the role of Broca's area in sentence processing: Syntactic integration versus syntactic working memory

Most previous neuroimaging studies of sentence processing have associated Broca's area with syntactic processing; however, the exact nature of the processes subserved by this brain region is yet not well understood. Although some authors suggest that Brodmann area (BA) 44 of the left inferior frontal gyrus (i.e., Broca's area) is relevant for syntactic integration processes, others claim that it is associated with working memory mechanisms relevant for language processing. To dissociate these two possible functions, the present study investigated hemodynamic responses elicited while participants processed German indirect wh‐questions. Activation increases were observed in left BA 44 together with superior temporal areas and right hemispheric homologues for sentences with noncanonical word order, in which a verb argument was dislocated from its canonical position over a relatively long distance. In these sentences, syntactic working memory load was assumed to be greatest. In contrast, no activation increase was elicited by object–initial as opposed to subject–initial sentences that did not differ with respect to working memory costs but with respect to syntactic integration costs. These data strongly suggest that Broca's area plays a critical role in syntactic working memory during online sentence comprehension. Hum. Brain Mapping 24:79–91, 2005. © 2004 Wiley‐Liss, Inc.
Toward a Mobile Agent Relay Network Thesis Air Force Institute of Technology toward a Mobile Agent Relay Network

Although wireless communication provides connectivity where hardwired links are difficult or impractical, it is still hindered by the environmental conditions where the communicators reside. Signal loss over large distances or because of intervening obstacles can be mitigated by increasing the user’s transmission power or adding repeater nodes between the users. Unfortunately, increasing the signal strength strains limited power resources and increases the likelihood of eavesdropping. Stationary repeaters are impractical for highly mobile users in dangerous environments. While mobile relay nodes might be a preferred solution, a centralized control scheme saps bandwidth from important traffic and introduces a single point of failure at the control station. An alternative solution is to create a Mobile Agent Relay Network (MARN). Each autonomous node in the MARN decides where to move to maintain the network connectivity using only locally-available information from onboard sensors and communication with in-range neighbor nodes. This is achieved by borrowing concepts from flocking behaviors that motivates our agents to maintain equal distance between its neighboring nodes. In addition, each agent maintains a filtered list of previously visited locations that provided best connection. This thesis takes the first steps toward realizing a MARN by providing mobile relay agents. Each model-based reflex agent is guided by a modified flocking behavior which considers only trustworthy neighbors and uses a Bayesian model to aggregate observations and shared reputation. The relay agents are able to build a network and maintain connectivity for their users. In this work, MARN agent algorithms are evaluated in a simulated unobstructed environment with stationary users. The system behavior is explored under both benign conditions and with varying numbers of misbehaving nodes.
Towards Digital Ecosystems for Skill Based Industrial Clusters: Lessons from the `Digital Mandi' Project

India has a rich foundation of clusters, and initiatives to boost the various functional areas of a cluster by pinpointing the anomalies that cloud them can lead to their dynamism. The digital ecosystem (DE) is one approach through which diffusion and use of ICT can be made self sustaining and self enabling for clusters, specifically clusters that thrive on value addition through embodying their product with skill and craftsmanship. This paper reports initial empirical findings from a collaborative project called the 'Digital Mandi'. The digital ecosystem entails a series of interconnected and intra-dependant digital platforms, created at key institutional levels (international, national and local/Community) augmented by technical (ICT) and social networking processes that help break down barriers to both horizontal and vertical knowledge sharing. The empirical findings show that the 'ecosystem' approach speeds up the process of identification, development and uptake of innovation. We conclude that similar DBEs can be effective for skill based SME clusters facing similar challenges of competitiveness in a rapidly globalizing knowledge driven economy.
Alteplase Therapy for Acute Ischemic Stroke in Pregnancy: Two Case Reports and a Systematic Review of the Literature

Acute ischemic stroke (AIS) during pregnancy is a rare but serious complication. Intravenous alteplase is the only medication approved for hyperacute treatment of AIS; however, it has not been evaluated prospectively in pregnancy. Pregnancy was an exclusion criterion in prospective AIS studies and was only recently removed as a relative contraindication in the 2018 American Heart Association/American Stroke Association Stroke guidelines. Due to the exclusion of pregnant women from randomized controlled trials, the safety of fibrinolytic therapy in pregnant patients is not well established. In this review, we report the use of intravenous alteplase for AIS in two pregnant patients, with temporally associated clinical improvement and without complications to either the mother or fetus. Additionally, we summarize a systematic review of the literature for both intravenous and intra‐arterial alteplase use for AIS in pregnant patients. A total of 31 cases met inclusion criteria for this review of assessment of safety and efficacy of alteplase use in pregnancy. Existing case reports and guidelines support the use of alteplase for AIS in pregnant patients without contraindications.
SWOT analysis in supply chain clustering

The advance of the information technology and e-business strategies made it possible for the (para)pharmaceutical industry in Greece to be organised in clusters in order to deal with the invasion of big international production companies. The paper presents a case study of the Greek (para)pharmaceutical industry and explores the reasons that led the links of this supply chain to align goals and cooperate in an extended supply chain. The main goal of the research is to evaluate through the case study and SWOT analysis the benefits as well as shortcomings of entering in a collaborative cluster of a supply chain.