Miracle-dz/UniFAR-FTUs huggingface dataset:
Beamspace MIMO for high-dimensional multiuser communication at millimeter-wave frequencies

Millimeter-wave (mm-wave) systems operating from 30-300GHz provide a unique opportunity for meeting the exploding capacity demands on wireless networks. In addition to orders-of-magnitude larger bandwidths, the small wavelengths at mm-wave enable high-dimensional multiple-input multiple-output (MIMO) operation. However, fully exploiting the advantages of mm-wave requires prohibitively high transceiver complexity when using conventional MIMO techniques. In this paper we propose and analyze the sum capacity of several linear, reduced-complexity multiuser MIMO (MU-MIMO) precoders that exploit the concept of beamspace MIMO (B-MIMO) communication - multiplexing data onto orthogonal spatial beams that serve as approximate channel eigenfunctions. Due to quasi-optical propagation at mm-wave, MIMO channels are expected to be low-rank and the low channel rank is manifested in the sparsity of the beamspace channel matrix. This enables near-optimal rank and complexity reduction via the concept of multi-beam selection. We present numerical capacity results that demonstrate the reduced-complexity B-MIMO precoders are able to closely approximate the performance of their full-dimensional counterparts with complexity that tracks the number of mobile stations (MSs). In mm-wave systems, where the number of MSs is expected to be much lower than the system dimension, this enables a considerable reduction in the digital signal processing complexity and in systems equipped with analog beamforming front-ends the hardware complexity is also reduced. Thus, the proposed reduced-complexity multiuser precoders provide a near-optimal route for achieving multi-Gigabit/s sum rates in mm-wave MU-MIMO networks with the lowest transceiver complexity.
SAR Image Speckle Removal using Bamberger Pyramids

We present the application of Bambeger pyramids to the removal of speckle noise from SAR images using subband domain shrinking. Bamberger pyramids provide better directional selectivity than the commonly used 2D UDWT allowing better representation of edges and geometrical structures. We show that Bamberger pyramids provide superior speckle removal and edge retention properties when compared to the 2D UDWT, and the commonly used Lee MMSE filter.
The role of data cap in two-part pricing under market competition

Internet services are traditionally priced at flat rates; however, many Internet service providers (ISPs) have recently shifted towards two-part tariffs where a data cap is imposed to restrain data demand from heavy users and usage over the data cap is charged based on a per-unit fee. Although two-part tariffs could generally increase the revenue for ISPs, the role of data cap and its optimal pricing structures are not well understood. In this paper, we study the impact of data cap on the optimal two-part pricing schemes for congestion-prone service markets, e.g., broadband or cloud services. In particular, we characterize users' optimal data demand and derive the equilibrium market share of ISPs under market competition. Based on this equilibrium model, we characterize the optimal structure of the two-part tariffs under market competition. Our results reveal that 1) the data cap provides a mechanism for ISPs to transition between flat-rate and pay-as-you-go type of schemes, 2) with growing data demand and network capacity, the optimal two-part structure will move towards usage-based schemes with diminishing data caps, and 3) under intense market competition, the optimal two-part structure will move in an opposite direction towards flat-rate schemes with higher data caps.
Spacetimes with Semantics (III) - The Structure of Functional Knowledge Representation and Artificial Reasoning

Using the previously developed concepts of semantic spacetime, I explore the interpretation of knowledge representations, and their structure, as a semantic system, within the framework of promise theory. By assigning interpretations to phenomena, from observers to observed, we may approach a simple description of knowledge-based functional systems, with direct practical utility. The focus is especially on the interpretation of concepts, associative knowledge, and context awareness. The inference seems to be that most if not all of these concepts emerge from purely semantic spacetime properties, which opens the possibility for a more generalized understanding of what constitutes a learning, or even `intelligent' system. Some key principles emerge for effective knowledge representation: 1) separation of spacetime scales, 2) the recurrence of four irreducible types of association, by which intent propagates: aggregation, causation, cooperation, and similarity, 3) the need for discrimination of identities (discrete), which is assisted by distinguishing timeline simultaneity from sequential events, and 4) the ability to learn (memory). It is at least plausible that emergent knowledge abstraction capabilities have their origin in basic spacetime structures. These notes present a unified view of mostly well-known results; they allow us to see information models, knowledge representations, machine learning, and semantic networking (transport and information base) in a common framework. The notion of `smart spaces' thus encompasses artificial systems as well as living systems, across many different scales, e.g. smart cities and organizations.
Genomewide scan of ocular refraction in African‐American families shows significant linkage to chromosome 7p15

Refractive development is influenced by environmental and genetic factors. Genetic studies have identified several regions of linkage to ocular refraction, but none have been carried out in African‐derived populations. We performed quantitative trait locus linkage analyses in African‐American (AA) families to identify genomic regions responsible for refraction. We recruited 493 AA individuals in 96 families to participate in the Myopia Family Study. Genotyping of 387 microsatellite markers was performed on 398 participants. The mean refraction among genotyped individuals was −2.87 D (SD=3.58) and myopia of at least 1 D was present in 267 (68%) participants. Multipoint, regression‐based, linkage analyses were carried out on a logarithmic transformation of ocular refraction using the statistical package MERLIN‐REGRESS. Empirical significance levels were determined via 4,898 whole‐genome gene‐dropping simulations. Linkage analyses were repeated after clustering families into two subgroups based on admixture proportions as determined by the software package STRUCTURE. Genomewide significant linkage was seen at 47 cM on chromosome 7 (logarithm of the odds ratio (LOD)=5.87, P=0.00005). In addition, three regions on chromosomes 2p, 3p and 10p showed suggestive evidence of linkage (LOD>2, P<0.005) for ocular refraction. We mapped the first quantitative trait locus for ocular refraction in an AA population to chr.7p15. Two previous studies in European‐derived families reported some evidence of linkage to a nearby region, suggesting that this region may contain polymorphisms that mediate refraction across populations. The genomic region under our linkage peak spans ∼17 Mb and contains ∼170 genes. Further refinement of this region will be pursued in future studies. Genet. Epidemiol. 2008. Published 2008 Wiley‐Liss, Inc.
Modeling active fault systems and seismic events by using a fiber bundle model – example case: the Northridge aftershock sequence

Abstract. Earthquake aftershocks display spatiotemporal correlations arising from their self-organized critical behavior. Dynamic deterministic modeling of aftershock series is challenging to carry out due to both the physical complexity and uncertainties related to the different parameters which govern the system. Nevertheless, numerical simulations with the help of stochastic models such as the fiber bundle model (FBM) allow the use of an analog of the physical model that produces a statistical behavior with many similarities to real series. FBMs are simple discrete element models that can be characterized by using few parameters. In this work, the aim is to present a new model based on FBM that includes geometrical characteristics of fault systems. In our model, the faults are not described with typical geometric measures such as dip, strike, and slip, but they are incorporated as weak regions in the model domain that could increase the likelihood to generate earthquakes. In order to analyze the sensitivity of the model to input parameters, a parametric study is carried out. Our analysis focuses on aftershock statistics in space, time, and magnitude domains. Moreover, we analyzed the synthetic aftershock sequences properties assuming initial load configurations and suitable conditions to propagate the rupture. As an example case, we have modeled a set of real active faults related to the Northridge, California, earthquake sequence. We compare the simulation results to statistical characteristics from the Northridge sequence determining which range of parameters in our FBM version reproduces the main features observed in real aftershock series. From the results obtained, we observe that two parameters related to the initial load configuration are determinant in obtaining realistic seismicity characteristics: (1) parameter P, which represents the initial probability order, and (2) parameter π, which is the percentage of load distributed to the neighboring cells. The results show that in order to reproduce statistical characteristics of the real sequence, larger πfrac values (0.85<πfrac<0.95) and very low values of P (0.0<P≤0.08) are needed. This implies the important corollary that a very small departure from an initial random load configuration (computed by P), and also a large difference between the load transfer from on-fault segments than by off-faults (computed by πfrac), is required to initiate a rupture sequence which conforms to observed statistical properties such as the Gutenberg–Richter law, Omori law, and fractal dimension.
Post-error slowing in preschool children and adolescents with Attention-Deficit/Hyperactivity Disorder

POST-ERROR SLOWING IN PRESCHOOL CHILDREN AND ADOLESCENTS WITH ATTENTION-DEFICIT/HYPERACTIVITY DISORDER by OLGA G. BERWID Advisor: Jeffrey M. Halperin, Ph.D. The objective of this dissertation was to examine whether post-error reaction time slowing, an index of self-regulation, is impaired in individuals with AttentionDeficit/Hyperactivity Disorder (ADHD) at two separate developmental time points: preschool and adolescence. Two studies were conducted with separate cohorts. Study 1 examined post-error slowing in a sample of preschool children rated by parents, teachers, and clinicians as exhibiting high levels of ADHD symptoms. In addition to group comparisons based on symptom status, a cross-sectional examination of age-related changes in post-error slowing in typically developing preschoolers (controls) was also conducted. Study 2 compared post-error slowing in individuals diagnosed with ADHD in childhood, who were diagnostically reassessed in adolescence for persistence versus remission of the disorder, relative to a well-matched comparison group. Post-error slowing was examined as a function of both childhood and adolescent diagnostic status. The results of Study 1 indicated that, although children as young as 3 years of age
Effects of Professional Development and Virtual Teacher Coaching with Videoconferencing on the Increase of Teacher Given Opportunities to Respond and the On-Task Behavior of Students with Emotional/Behavior Disorders

Coaching has been identified as a critical support for persistent use of newly adopted practices and skills (Joyce & Showers, 1982). A systematic review of the literature was conducted to examine the literature base on supervisory coaching, an approach in which an outside expert or supervisor gives specific, positive, and corrective coaching when needed and is offered to the teacher after the completion of the observed lesson in an effort to move the recipient toward a desired level of performance (Joyce & Showers, 1981; 1982; Maeda, 2001; Simonsen, Myers, & DeLuca, 2010). Sixteen quasi-experimental and single-subject studies were identified and reviewed using quality indicators specific to quasi-experimental (Gersten et al., 2005) and single subject (Horner et al., 2005) research. Only six of the sixteen studies met all quality indicators. Mixed results were found across the studies, with six reporting improved teacher results and four reporting improved student behaviors. The subsequent study explored an alternative means to offering supervisory coaching to teachers: professional development and virtual teacher coaching with videoconferencing. A single-case multiple baseline design was used to investigate the effect the intervention had on the frequency with which teachers offer Opportunities to Respond (OTR) and on the on-task behavior of middle school students with emotional/ behavior disorders (E/BD). OTR is a teacher behavior that petitions a student response (Haydon et al., 2010). After baseline data was collected, virtual coaching sessions were implemented to increase OTR after every other observed session. Results indicated there was a functional relation between virtual teacher coaching with videoconferencing and teacher rates of OTR. However, no functional relation was observed between teachers given OTR and student on-task behavior. Implications for virtual teacher coaching, OTR, and future research are discussed. INDEX WORDS: Virtual teacher coaching, Videoconferencing, Professional development, Emotional/behavior disorders, and Opportunities to respond EFFECTS OF PROFESSIONAL DEVELOPMENT AND VIRTUAL TEACHER COACHING WITH VIDEOCONFERENCING ON THE INCREASE OF TEACHER GIVEN OPPORTUNITIES TO RESPONDAND THE ON-TASK BEHAVIOR OF STUDENTS WITH EMOTIONAL BEHAVIOR DISORDERS by
Dynamic feature weighting in nearest neighbor classifiers

One major problem of nearest neighbor (NN) algorithms is inefficiency incurred by irrelevant features. A solution to this problem is to assign weights to features that indicate their salience for classification. Current weighting methods can be divided as global weighting, partial local weighting, and local weighting methods enumerated in increasing order of capability to capture the features' relative salience in classification. However, the existing methods are not sensitive enough to describe the salience of a feature and can be changed given different queries. We suggest that the salience of a feature, in addition to being sensitive to the instance (i.e. varies across instances), should also be sensitive to the variations in the difference of a feature's values between a query and the instances in the instance base. In this paper, we put forward a dynamic feature weighting approach which has more expressive capability, and present a sketch of a classification algorithm based on the notion of dynamic weights.
Regulation of Nucleocytoplasmic Trafficking of Transcription Factor OREBP/TonEBP/NFAT5*

The osmotic response element-binding protein (OREBP), also known as tonicity enhancer-binding protein (TonEBP) or NFAT5, regulates the hypertonicity-induced expression of a battery of genes crucial for the adaptation of mammalian cells to extracellular hypertonic stress. The activity of OREBP/TonEBP is regulated at multiple levels, including nucleocytoplasmic trafficking. OREBP/TonEBP protein can be detected in both the cytoplasm and nucleus under isotonic conditions, although it accumulates exclusively in the nucleus or cytoplasm when subjected to hypertonic or hypotonic challenges, respectively. Using immunocytochemistry and green fluorescent protein fusions, the protein domains that determine its subcellular localization were identified and characterized. We found that OREBP/TonEBP nuclear import is regulated by a nuclear localization signal. However, under isotonic conditions, nuclear export of OREBP/TonEBP is mediated by a CRM1-dependent, leucine-rich canonical nuclear export sequence (NES) located in the N terminus. Disruption of NES by site-directed mutagenesis yielded a mutant OREBP/TonEBP protein that accumulated in the nucleus under isotonic conditions but remained a target for hypotonicity-induced nuclear export. More importantly, a putative auxiliary export domain distal to the NES was identified. Disruption of the auxiliary export domain alone is sufficient to abolish the nuclear export of OREBP/TonEBP induced by hypotonicity. By using bimolecular fluorescence complementation assay, we showed that CRM1 interacts with OREBP/TonEBP, but not with a mutant protein deficient in NES. Our findings provide insight into how nucleocytoplasmic trafficking of OREBP/TonEBP is regulated by changes in extracellular tonicity.
Slotted bow-tie antenna design for RFID readers using hybrid optimization techniques

Recently hybrid optimizations algorithm has attracted a lot of attention as a high-performance optimizer. This paper presents a comparison between different hybrid optimization algorithms. The proposed algorithms are used to design a slotted bow-tie antenna for 2.45 GHz Radio Frequency Identification (RFID) readers. The antenna is optimized using different algorithms integrated with the CST Microwave studio. Four algorithms are compared: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), hybrid approach involving Genetic Algorithm (GA) and Nelder-Mead (NM) algorithm (GA-NM), and a hybrid approach involving PSO and Nelder-Mead optimization algorithm (PSO-NM). It is anticipated that the introduced hybrid approaches are more efficient and can be applied to other types of antennas.
Reasoning ability and ideology: Inaccuracies in hierarchical category relations (but not numerical ability) are associated with right-wing authoritarianism.

Although much is known about the motivational underpinnings of authoritarian ideologies, less is known about the underlying mental abilities. In the present study, the relations between right-wing authoritarianism (RWA), social dominance orientation (SDO), and reasoning abilities were investigated. Participants (n = 198) completed measures of reasoning ability (Necessary Arithmetic Operations task, Diagramming Relationships task), RWA, and SDO. Greater RWA was only associated with lower ability to recognize hierarchical relationships; neither RWA nor SDO were associated with general arithmetic reasoning ability. Implications for understanding ideology are discussed.
SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization

We propose a novel deep neural network that is both lightweight and effectively structured for model parallelization. Our network, which we name as SplitNet, automatically learns to split the network weights into either a set or a hierarchy of multiple groups that use disjoint sets of features, by learning both the class-to-group and feature-to-group assignment matrices along with the network weights. This produces a treestructured network that involves no connection between branched subtrees of semantically disparate class groups. SplitNet thus greatly reduces the number of parameters and required computations, and is also embarrassingly modelparallelizable at test time, since the evaluation for each subnetwork is completely independent except for the shared lower layer weights that can be duplicated over multiple processors, or assigned to a separate processor. We validate our method with two different deep network models (ResNet and AlexNet) on two datasets (CIFAR-100 and ILSVRC 2012) for image classification, on which our method obtains networks with significantly reduced number of parameters while achieving comparable or superior accuracies over original full deep networks, and accelerated test speed with multiple GPUs.
ELECTROPHYSIOLOGICAL CHANGES IN ACUTE GUILLAIN-BARRE SYNDROME

Aim: To study the various electrophysiological changes in the motor conduction, sensory conduction and F wave latencies of acute Guillain-Barre Syndrome patients. Methods: Sixteen patients with acute GBS were included in this study. They were subjected to various nerve conduction studies (NCS) following standardized procedures. The mean values obtained for the various nerve conduction parameters were compared against the corresponding standardized values using Student’s t-test. P value less that 0.05 was considered significant. Results: The results of NCS in GBS patients were as follows: 1.The motor nerve conduction velocity was significantly lower and the motor nerve conduction latency was significantly prolonged. 2. The sensory nerve action potential conduction velocity and amplitude remained normal in most of these individuals. 3. F wave latency was significantly prolonged. Conclusion: Acute Guillain-Barre Syndrome patients manifest with abnormal motor nerve conduction parameters and F wave latency. Electrophysiological studies would help the researchers to diagnose the disease at an early stage.
Real Business Cycles in Emerging Countries?

We use more than a century of Argentine and Mexican data to estimate the structural parameters of a small-open-economy real-business-cycle model driven by nonstationary productivity shocks. We find that the RBC model does a poor job of explaining business cycles in emerging countries. We then estimate an augmented model that incorporates shocks to the country premium and financial frictions. We find that the estimated financial-friction model provides a remarkably good account of business cycles in emerging markets and, importantly, assigns a negligible role to nonstationary productivity shocks. (JEL E13, E32, E44, F43, O11, O16)
KL-HMM based speaker diarization system for meetings

In this paper, the Kullback-Leibler Hidden Markov Model (KL-HMMs) is applied for unsupervised diarization of speech. A general approach to speaker diarization is to split the audio into uniform segments followed by one or more iterations of clustering of the segments and resegmentation of the audio. In the Information Bottlneck (IB) approach to diarization, short uniform segments are clustered using the IB criterion followed by resegmentation with KL-HMM. The KL-HMM approach has been shown to be an effective resegmentation procedure in this respect. Thus, the potential of KL-HMM as an independent diarization system is explored where the uniform segments are clustered and segmented using a sequence of posteriors obtained from the audio with respect to a Gaussian Mixture Model (GMM). The segmentation is performed using KL divergence, while the Jensen Shanon (JS) divergence is used for clustering. The diarization procedure is stopped by applying a Normalized Mutual Information (NMI) based criterion between two consecutive clustering outputs. The proposed method is tested on the NIST RT datasets. A best case relative improvement of 30% is observed in terms of Speaker Error Rate (SER) on the NIST RT 09 dataset when compared with the IB approach.
Expressive Arts Therapy Group Helps Improve Mood State in an Acute Care Psychiatric Setting (Une thérapie de groupe ouverte en studio basée sur les arts de la scène améliore l'humeur des patients en psychiatrie dans un établissement de soins intensifs)

ABSTRACT The objective of this research is to investigate whether an Open Studio-Based Expressive Arts Therapy Group has an impact on the mood of hospital psychiatric inpatients in an acute care setting. Patients participating in a weekly Expressive Arts Therapy Group completed the Profile on Mood States Brief (POMS-B) form to assess mood states before and after group participation. In addition, a true and false questionnaire was given to participants post-group to gather information about their individual experiences. Thirty-six patients participated in the study. Participation in the group was significantly associated with a reduction in the POMS-B Total Mood Disturbance score, consistent with a decrease in negative mood states [POMS-B t(35) = 4.06003, p < . 05].