Miracle-dz/UniFAR-FTUs huggingface dataset:
Reduced Complexity Iterative Channel Estimation with Turbo Equalization for Multiuser Space-Time BICM Signaling

This paper focuses on the problem of detecting multiuser coded space-time signals transmitted over multi-antenna multipath channel, with imprecise channel knowledge in reception. Computationally efficient methods combining soft multiuser interference (MUI) cancellation and minimum mean square error (MMSE) processing are developed for both channel estimation and space-time soft equalization.
“Radio Inside My Head”: A Curious Case of Early Onset “Stuck Song Syndrome” or Obsessive-Compulsive Disorder with Predominant Musical Obsession

Musical obsessions also called “stuck song syndrome” is a topic of limited research. It is among the most poorly understood and rare phenomenology. There are only a few cases reported across the world which describes it. Subjects usually present with complaints of continuous play of a musical tune in the head which the subject is unable to remove. Because of its similarity in presentation with auditory musical hallucination, it presents a diagnostic dilemma to the clinician. Here, we present the case of a 25-year-old man who presented with this particular phenomenon, and the approach we took to manage it.
Structure Counts : Network Theory Applied in the Voluntary Contributions Game

Issues of the prisoners’ dilemma are commonplace observations in public goods games, with real world applications ranging from environmental regulations to information sharing. This paper, by allowing participants to communicate in several different network structures, demonstrates in a voluntary contributions game that communication links affects contributions to public good. We use empirical data collected through Vanderbilt University subjects to test whether different network structures (positive reinforcement) and the ability to punish (negative reinforcement) have different effects on public investment. We find that players in well-connected symmetrical network structures perform much better than alternative network structures and that punishment systems are less effective in enabling cooperation regardless of the network structure.
How to Combine Expert (and Novice) Advice when Actions Impact the Environment?

The so-called "experts algorithms" constitute a methodology for choosing actions repeatedly, when the rewards depend both on the choice of action and on the unknown current state of the environment. An experts algorithm has access to a set of strategies ("experts"), each of which may recommend which action to choose. The algorithm learns how to combine the recommendations of individual experts so that, in the long run, for any fixed sequence of states of the environment, it does as well as the best expert would have done relative to the same sequence. This methodology may not be suitable for situations where the evolution of states of the environment depends on past chosen actions, as is usually the case, for example, in a repeated non-zero-sum game. A new experts algorithm is presented and analyzed in the context of repeated games. It is shown that asymptotically, under certain conditions, it performs as well as the best available expert. This algorithm is quite different from previously proposed experts algorithms. It represents a shift from the paradigms of regret minimization and myopic optimization to consideration of the long-term effect of a player's actions on the opponent's actions or the environment. The importance of this shift is demonstrated by the fact that this algorithm is capable of inducing cooperation in the repeated Prisoner's Dilemma game, whereas previous experts algorithms converge to the suboptimal non-cooperative play.
The Advanced Psychometric Properties of Turkish Strengths And Difficulties Questionnaire (SDQ)

Objective: The aim is of this study is to evaluate the advanced psychometric properties of Turkish Strengths and Difficulties Questionnaire (SDQ). Method: The sample consisted of 565 cases aged between 4 and 17 who applied to Dokuz Eylul University Faculty of Medicine, Child and Adolescent Psychiatry Department between 01.01. 2005 and 31.12. 2005 for the first time and whose SDQs, (scored before clinical assessment) were evaluated to be included in this study. The diagnoses predicted by the SDQ were compared with the diagnoses predicted by clinical assessment and the psychometric properties of SDQ were evaluated. Results: The results indicated that the parent and self-report SDQ had high internal consistency except peer problems subscale. The correlation value between the SDQ forms scored by children and adolescents over age 11, and the same cases’ parent forms’ total difficulties score, impact score and subgroup scores was between 0.402 and 0.573. In the group that contained all cases; the correlation coefficients between psychiatric diagnoses predicted by SDQ and the diagnoses formed by clinical assessment varied between 0.15 and 0.34. SDQ parent and self report forms’ total difficulties score, mean impact score and all the subgroups that belonged to both forms (except SDQ self report form hyperactivity inattention score) were able to distinguish between the group that received a clinical diagnosis that was predicted by SDQ and the group that did not. Discussion: Turkish SDQ is proved to be a valid and reliable scale and it can be used in screening and assessment of clinical psychopathology in Turkish children and adolescent population.
Engineering of Saccharomyces cerevisiae for the synthesis of short chain fatty acids

Carbon feedstocks from fossilized sources are being rapidly depleted due to rising demand for industrial and commercial applications. Many petroleum‐derived chemicals can be directly or functionally substituted with chemicals derived from renewable feedstocks. Several short chain organic acids may fulfill this role using their functional groups as a target for chemical catalysis. Saccharomyces cerevisiae was engineered to produce short chain carboxylic acids (C6 to C10) from glucose using the heterologous Homo sapiens type I fatty acid synthase (hFAS). This synthase was activated by phosphopantetheine transfereases AcpS and Sfp from Escherichia coli and Bacillus subtilis, respectively, both in vitro and in vivo. hFAS was produced in the holo‐form and produced carboxylic acids in vitro, confirmed by NADPH and ADIFAB assays. Overexpression of hFAS in a yeast FAS2 knockout strain, deficient in de novo fatty acid synthesis, demonstrated the full functional replacement of the native fungal FAS by hFAS. Two active heterologous short chain thioesterases (TEs) from Cuphea palustris (CpFatB1) and Rattus norvegicus (TEII) were evaluated for short chain fatty acid (SCFA) synthesis in vitro and in vivo. Three hFAS mutants were constructed: a mutant deficient in the native TE domain, a mutant with a linked CpFatB1 TE and a mutant with a linked TEII TE. Using the native yeast fatty acid synthase for growth, the overexpression of the hFAS mutants and the short‐chain TEs (linked or plasmid‐based) increased in vivo caprylic acid and total SCFA production up to 64‐fold (63 mg/L) and 52‐fold (68 mg/L), respectively, over the native yeast levels. Combined over‐expression of the phosphopantetheine transferase with the hFAS mutant resulted in C8 titers of up to 82 mg/L and total SCFA titers of up to 111 mg/L. Biotechnol. Bioeng. 2014;111: 347–358. © 2013 Wiley Periodicals, Inc.
Discriminative Interlingual Representations

Dissertation title : Discriminative Interlingual Representations Jagadeesh Jagarlamudi, Doctor of Philosophy, 2013 Dissertation advised by: Hal Daumé III Department of Computer Science The language barrier in many multilingual natural language processing (NLP) tasks can be overcome by mapping objects from different languages (“views”) into a common low-dimensional subspace. For example, the name transliteration task involves mapping bilingual names and word translation mining involves mapping bilingual words into a common low-dimensional subspace. Multi-view models learn such a low-dimensional subspace using a training corpus of paired objects, e.g., names written in different languages, represented as feature vectors. The central idea of my dissertation is to learn low-dimensional subspaces (or interlingual representations) that are effective for various multilingual and monolingual NLP tasks. First, I demonstrate the effectiveness of interlingual representations in mining bilingual word translations, and then proceed to developing models for diverse situations that often arise in NLP tasks. In particular, I design models for the following problem settings: 1) when there are more than two views but we only have training data from a single pivot view into each of the remaining views 2) when an object from one view is associated with a ranked list of objects from another view, and finally 3) when the underlying objects have rich structure, such as a tree. These problem settings arise often in real world applications. I choose a canonical task for each of the settings and compare my model with existing state-of-the-art baseline systems. I provide empirical evidence for the first two models on multilingual name transliteration and reranking for the part-of-speech tagging tasks, respectively. For the third problem setting, I experiment with the task of re-scoring target language word translations based on the source word’s context. The model proposed for this problem builds on the ideas proposed in the previous models and, hence, leads to a natural conclusion. Discriminative Interlingual Representations
Partially Purified Human and Rat Atrial Natriuretic Factor

Specific granules of rat atrial myocytes contain a potent fast-acting atrial natriuretic factor (ANF) and have been observed in all mammalian atria thus far examined. In this study, using a rat assay we found ANF in rat, rabbit, dog, baboon, and man. The ANF's from these species induced the characteristic diuresis and natriuresis of rapid onset and decay. The human and rat ANF's were acid-extractable, heat-resistant, and trypsin-sensitive, suggesting that both are peptides. When frac-tionated on Sephadex G-75, ANF eluted at approximately 1.4 to 2.9 elution volume/void volume. The human and rat ANF dose-response relationships showed that changes in urinary sodium excretion (ΔUNaV) were linearly related to log mg protein injected per kg rat assay weight (r2 = 0.9853 and 0.9966, respectively). The minimum and maximum responses to rat ANF on the average were 14 ± 3 and 409 ± 51 μEq Na/kg-10 min ( ± SE) respectively. The ΔUNaV of rats given a second injection of ANF was not altered by a first injection. Furosemide induced a similar but slightly longer diuretic, natriuretic, and kaliuretic response pattern than that of ANF. Nevertheless, a classical four-point log dose-response analysis revealed that under certain conditions furosemide could be a suitable standard against which the potencies of unknown preparations of ANF can be compared. The relative potency of the partially purified rat ANF used in this study was 0.654 mg furosemide/mg protein (95° confidence limits, 0.378 to 1.135). The index of precision (λ) was 0.36. The results of this study suggest that mammalian ANF's, including that in man, share similar physiological and chemical characteris-tics. In addition, furosemide was found to be a suitable standard against which the potencies of unknown preparations of ANF can be compared.
On the Cover‐Hart inequality: What's a sample of size one worth?

Bob predicts a future observation based on a sample of size one. Alice can draw a sample of any size before issuing her prediction. How much better can she do than Bob? Perhaps surprisingly, under a large class of loss functions, which we refer to as the Cover‐Hart family, the best Alice can do is to halve Bob's risk. In this sense, half the information in an infinite sample is contained in a sample of size one. The Cover‐Hart family is a convex cone that includes metrics and negative definite functions, subject to slight regularity conditions. These results may help explain the small relative differences in empirical performance measures in applied classification and forecasting problems, as well as the success of reasoning and learning by analogy in general, and nearest neighbor techniques in particular. Copyright © 2012 John Wiley & Sons, Ltd.
The emotional life of your brain : how its unique patterns affect the way you think, feel, and live--and how you can change them

A leading pioneer in brain science, Richard Davidson in his 30 years of research has produced hundreds of findings, from how the brain triggers empathy to the differences between the autistic brain and the normally developing brain to how the brain’s seat of rationality can plunge us into depths of depression. Davidson’s groundbreaking work has helped all of us to understand what it means to be human.
Online social networking, order and disorder

Whilst online social networking has been used successfully for many years by all strata of the world’s population, its use to ferment and prevent civil disturbances is a relatively new phenomenon. It is clear that the way in which online social networking sites are being used is evolving, and that changing user perceptions of online privacy may impact on the ability of the law enforcement community to adapt to new methods of monitoring and evidence gathering. This paper focuses primarily on the London riots of August 2011, and as such discusses legal issues from a UK perspective. However, the matters discussed are of relevance worldwide, with reference made to similar events outside the UK, to show that what occurred in London was not an isolated incident, or a quirk of the UK social networking scene. This paper explores what occurred, the platforms that were used and how they were used, and the legal framework in which investigations took place. It examines the use of social networking to organise rioters, support community defence, and shape the response of law enforcement agencies such as the police, government and the courts. It concludes that there is significant potential for problems of this type to occur in the future, which will require the evolution of law enforcement methods and procedures, and could change the way in which the law enforcement community utilise e-Government systems.
A Threshold Free Clustering Algorithm for Robust Unsupervised Classification

A new information-theoretic, unsupervised, subtractive clustering algorithm is proposed. The algorithm eliminates threshold constraint to detect possible cluster members. Cluster centers are formed with minimum entropy. Instead of using a fixed- threshold, a decision region is formed with the use of maximum mutual information. Cluster members are chosen with a relative-cost assigned in partitions of data set. The algorithm yields more reliably distributed cluster numbers in statistical sense, hence reducing further computation for validation, which is justified for a set of synthetic data.
Key Concepts in Social Research

Action Research Association and Causation Attitude Scales Auto/Biography and Life Histories Bias Case Study Coding Qualitative Data Community Profiles Community Studies Content Analysis Contingency Tables Documentary Methods Ethical Practice Ethnography Ethnomethodology and Conversational Analysis Evaluation Studies Experiments Feminist Research Fieldwork Grounded Theory Group Discussions/Focus Groups Hawthorne Effect Hypothesis Indicators and Operationalisations Internet and Other Searches Internet Polling Interviewing Key Informants Levels of Measurement Longitudinal and Cross-Sectional Studies Methods and Methodologies Objectivity Observation Official Statistics Participant Observation Positivism and Realism Qualitative Methods Quantitative Methods Questionnaires Reflexivity Reliability Sampling Estimates and Size Sampling Questions of Size Sampling Types Secondary Analysis Social Surveys Telephone and Computer-Assisted Polling Unobstrusive Methods and Triangulation Validity Visual Methods
Characterizing multi-cell cooperation via the outage-probability exponent

Multi-cell cooperation (MCC) is a promising approach for mitigating inter-cell interference in dense cellular networks. To study the MCC performance, existing work typically relies on the over-simplified Wyner-type models that fail to account for mobile spatial statistics, irregular locations of base stations (BSs) and the resultant highly variable path-loss. Unsurprisingly, real-world systems show gains far below those predicted using such idealized models. This paper adopts a stochastic-geometry model for a cellular downlink network with MCC where cells are modeled as a Poisson random tessellation generated by Poisson distributed BSs, these BSs are then clustered using a hexagonal lattice, and BSs in the same cluster mitigate mutual interference by spatial interference avoidance. We analyze the effects of scattering on network coverage as the average number of cooperative BSs, K, increases. For mobiles near the centers of cooperative BS clusters, we show that the outage probability diminishes with increasing K at least sub-exponentially for sparse scattering and following a power law for rich scattering where the exponent is proportional to the signal diversity order. For randomly located mobiles, the outage probability is shown to decrease with increasing K following a power law independent with scattering.
DIVERSITY OF MEDICAL DISCOURSES AND THEIR IMPACT UPON INDIVIDUAL’S NARRATIVES ABOUT ILLNESS IN WEST SUMATERA

Abstract The aim of this article is to give concrete examples of how narratives influence the way person speaks about and interpret his illness. The research was conducted in West Sumatera where people are exposed to a diverse range of health discourses: western medicine, local ethno-medicine or Islamic way of treatment called ruqyah and its discourse changes the interpretation of one`s health condition. This study is part of my research, which focused on the process of creation and negotiation of a diagnosis within a multi-cultural and multi-discursive context of Indonesia. This study concludes that people in West Sumetara withdraws from several different discourses to give meaning to both their health and illness. Abstrak Tujuan artikel ini adalah untuk mengilustrasikan contoh konkrit narasi, dan pengaruhnya bagi cara seseorang berbicara dan memaknai penyakit tertentu yang mereka alami. Penelitian dilakukan di Sumatera Barat, yang memiliki keragaman diskursus kesehatan: obat-obatan barat, cara pengobatan tradisional atau pengobatan secara ruqyah di dalam Islam. Penelitian ini merupakan bagian dari penelitian saya, yang difokuskan pada proses kreasi/negosiasi karena keanekaragaman budaya dan wacana kesehatan di Indonesia. Kajian ini menyimpulkan bahwa individu mengambil dari berbagai wacana kesehatan untuk memahami dan memberi makna tentang sehat dan sakit mereka. © 2013 Universitas Negeri Semarang
Religion and superstition through a cognitive perspective: examining the relationship of religious and superstitious beliefs to cognitive processes

Religion and superstition are complex constructs since they are intertwined with a variety of psychological aspects and are correlated to positive and negative-related effects. For instance, both phenomena have been associated with advantages at behavioural (i.e. performance enhancements) and cognitive levels (i.e. executive function deficits). This thesis represents a systematic attempt to study these constructs under a non-reductionist approach and emphasizes the cognitive processes. Despite underlying and behavioural similarities, both phenomena were treated as peripheral (although independent) constructs with the intention of: a) forwarding the idea that both religion and superstition can have a neuroscience edge and can be integrated thus into novel and/or well-established electrophysiological and cognitive paradigms, b) exploring the links between religious and superstitious factors (namely luck belief) in relation to behavioural performances and cognitive functions, and c) underlying the advantages of a multidimensional non-reductionist view for both constructs. Overall, results further indicated that it is necessary to treat religion and superstition as related (but not equal) multifaceted phenomena. Both negative and positive-related effects were found: physiological evidence showing a correlation between unlucky beliefs and deficits in executive functions (EFs), when comparing event-related potentials (electroencephalogram-derived technique) recorded during a Stroop task of a group associated to these beliefs; a performance enhancement effect related to the use of a religious amulet during an anagram task; finally, a high correlation between negative-oriented beliefs and EFs in a screening that was based on a battery scale containing a myriad of religious, superstitious and EF sub-factors.
Compartmentalization of SHC, GRB2 and mSOS, and hyperphosphorylation of Raf‐1 by EGF but not insulin in liver parenchyma.

Rat liver parenchyma harbors equal numbers of epidermal growth factor (EGF) and insulin receptors. Following administration of a saturating dose of EGF (10 micrograms/100 g body weight), there was a rapid (t1/2 approximately 1.1 min) internalization of receptor coincident with its tyrosine phosphorylation at residue 1173 and receptor recruitment of the adaptor protein SHC, its tyrosine phosphorylation and its association with GRB2 and the Ras guanine nucleotide exchange factor, mSOS, largely in endosomes. This led to a cytosolic pool of a complex of tyrosine‐phosphorylated SHC, GRB2 and mSOS. It was demonstrated that these constituents were linked to Ras activation by the characteristic decrease in Raf‐1 mobility on SDS‐PAGE, which was maintained for 60 min after a single bolus of administered EGF. While insulin administration (15 micrograms/100 g body weight) led to insulin receptor beta‐subunit tyrosine phosphorylation and internalization, there was little detectable tyrosine phosphorylation of SHC, recruitment of GRB2, association of a complex with mSOS or any detectable change in the mobility of Raf‐1. Therefore, in normal physiological target cells in vivo, distinct signaling pathways are realized after EGF or insulin receptor activation, with regulation of this specificity most probably occurring at the locus of the endosome.
Analyzing dynamic information with spy and roassal: an experience report

Dynamic analyses tools are seldom crafted by practitioners. This paper discusses the benefits of supporting the practitioners to build their ad-hoc tool and presents our experience to lower the barrier to gather dynamic information. The experience we present is driven by the combination of the Spy profiling framework and the Roassal visualization engine, two frameworks used in industry and academia. We conclude with two question to discuss at the workshop.
A fully integrated CMOS low noise amplifier for IEEE 802.11a standard applications

In this paper, a fully integrated CMOS low noise amplifier (LNA) with on-chip spiral inductors in 0.18μm CMOS technology for IEEE 802.11a applications is presented. Using cascode topology and modified input impedance network as well as inductor neutralization technique, the LNA power dissipation is lowered to 16mW while having power gain of 17.82dB and reverse isolation factor of −58.37dB at centre frequency of 5.5GHz. S11 and S22 are equal to −16.1dB and −32dB, respectively. Designed LNA has IIP3 of +3dBm and less than 2.9dB noise figure (NF) in working band width, as resulted from transistor level simulation using TSMC RF CMOS 0.18 μm design kit.