Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed inference in wireless sensor networks

Statistical inference is a mature research area, but distributed inference problems that arise in the context of modern wireless sensor networks (WSNs) have new and unique features that have revitalized research in this area in recent years. The goal of this paper is to introduce the readers to these novel features and to summarize recent research developments in this area. In particular, results on distributed detection, parameter estimation and tracking in WSNs will be discussed, with a special emphasis on solutions to these inference problems that take into account the communication network connecting the sensors and the resource constraints at the sensors.
Confessions of a Secular Fundamentalist

Ever since the Babri Masjid dispute in 1986, the debate over secularism and communalism has been revived in all its sound and fury. It now occupies centre stage in our public discourse. In "Confessions of a Secular Fundamentalist", Mani Shankar Aiyar, crusader for a secular credo, calls for an unambiguous and decisive restoration of secularism to the core of our nationhood. In doing so, he revisits every dimension of our secular ethos and exposes the various myths perpetuated by communal elements of all hues. Putting under the scanner contentious issues like conversions, uniform civil code and Article 370, he nails the falsehood underlying terms like 'pseudo-secularism', 'appeasement' and 'soft Hindutva'. And he places the domestic debate over secularism in India in the wider external dimension by discussing the experiences of countries like Pakistan, Sri Lanka, Israel and erstwhile Yugoslavia. Admitting to wearing his secularism on his sleeve, Aiyar reasons that only a determined and inflexible adherence to secularism can counter religious bigotry and fundamentalism.
Cardiovascular Effects of Nicotine, Chlorisondamine, and Mecamylamine in the Pigeon

Chlorisondamine and mecamylamine are nicotinic antagonists that produce both ganglionic and central blockade. Chlorisondamine, when administered as a large systemic dose, produces a persistent central block, despite being charged. The present study evaluated the cardiovascular effects of chlorisondamine. Shortly after administration, chlorisondamine (0.10, 1, and 10 mg/kg i.m.) lowered blood pressure significantly and decreased heart rate at the low dose (0.1 mg/kg i.m.) and increased heart rate at the high dose (10 mg/kg i.m.). Mecamylamine (1 and 10 mg/kg i.m.) also lowered blood pressure and heart rate. After both antagonists, heart rate returned to baseline values within 90 min and blood pressure within 24 h. Low doses of nicotine (0.01-0.03 mg/kg i.m.) lowered blood pressure but did not affect heart rate. Higher doses (0.10-3.2 mg/kg i.m.) transiently increased blood pressure and heart rate. Subsequent to antagonist administration, nicotine was administered to determine whether either drug blocked the cardiovascular effects of nicotine. Chlorisondamine (0.1, 1, and 10 mg/kg i.m.) administered 30 min before nicotine blocked the increases in blood pressure and heart rate. Only the high dose (10 mg/kg i.m.) of chlorisondamine administered 24 h before nicotine produced a blockade of nicotine's pressor effect. This block diminished within 3 days. Mecamylamine (1 mg/kg i.m.) antagonized only nicotine's tachycardic effect. Longer pretreatment with mecamylamine (10 mg/kg, 24 h before nicotine challenge) did not antagonize the cardiovascular effects of nicotine. Thus, chlorisondamine produces a longer lasting blockade of nicotine's cardiovascular effects than mecamylamine.
Therapy of the Substance Abuse Syndromes

This book provides the reader with a systematic and comprehensive approach to substance abuse treatment. It explores new integrations of familiar approaches, introduces innovative theoretical constructs, and describes new practical applications. The models and methods presented have been developed specifically to address treatment planning for patients who have been recurrent treatment failures in both psychotherapy and addiction treatment programs. These approaches are also applicable to less refractory cases of substance abuse, and to nonsubstance addictions, such as compulsive sexual behavior. Dr. Richards describes the process of addiction as a movement through a cycle of three primitive states of self-experience. These are: (1) a position typified by egotism, assertiveness, and super-confidence (the Inflated/Grandiose position); (2) a position typified by depression and helplessness (the Depleted/Depressed position); and (3) a position typified by isolation, fantasy, and self-absorption (the Detached/Schizoid position). Movement through this cycle is driven by failures in self-regulation, and by the time-limited, self-undermining, and only partially effective substitute solution to these failures that drugs provide. In addition, the substance abusing patient's reliance on paranoid processes (splitting, projection, and introjection) are shown to be the cornerstone to continued drug dependence as a substitute for poor self-regulation. In addition to advancing theory, this volume describes in detail a comprehensive system for assessment and treatment planning based on the dual diagnosis paradigm. The system consists of three interrelated concept sets and an understanding of theirrelationships: drug categories, symptom complexes, and biopsychosocial functions of addiction. Following this formulation a description of recovery processes for addiction/mental illness and corresponding treatment needs provides the basis for intervention. Using abundant clinical ex
Color Image Segmentation with Different Image Segmentation Techniques

This paper deals with different image segmentation techniques to enhance the quality of color images. The technique follows the principle of clustering and region merging algorithm. The system is combination various stages like histogram with hill climbing techniques; auto clustering includes k means clustering, the consistency test of regions, and automatic image segmentation using dynamic region merging algorithms. The different techniques of image segmentation include thresolding, clustering, region merging, region growing, color segmentation, motion segmentation and automatic image segmentation. This paper mention different methods for efficient segmentation which is combination of different algorithms. Here the given image gets converted into histogram. The histogram is graphical representation of input image. The peaks from histogram diagram are detected using hill climbing algorithm; this gives the rough number of clusters for the further steps. The clusters are form usingefficient K means clusteringalgorithm. The regions having homogenous or similar characteristics can be combining with the nearest neighbor algorithm and dynamic region merging algorithm . This segmentation technique is useful in field of image processing as well as advance medical use.
Partial Awareness Creates the “Illusion” of Subliminal Semantic Priming

We argue that the lack of consensus regarding the existence of subliminal semantic processing arises from not taking into account the fact that linguistic stimuli are represented across several processing levels (features, letters, word form) that can independently reach or not reach awareness. Using masked words, we constructed conditions in which participants were aware of some letters or fragments of a word, while remaining unaware of the whole word. Three experiments using the Stroop priming paradigm show that when the stimulus set is reduced and participants are encouraged to guess the identity of the prime, such partially perceived stimuli can nonetheless give rise to “semantic” processing. We provide evidence that this effect is due to illusory reconstruction of the incompletely perceived stimulus, followed by usual semantic processing of the result. We conclude that previously reported unconscious Stroop priming is in fact a conscious effect, but applied to a perceptual illusion.
Volume and Outcome in Hospital Care: Evidence, Explanations and Implications

The relationship between the volume of work undertaken in a hospital and the outcome of care has assumed increasing importance in recent years. A review of the literature reveals that most studies have been carried out in the USA and have largely been confined to six specific areas of health care. There is evidence that better outcomes are obtained at higher volumes for several surgical operations, cardiac catheterisation and care of the severely injured. As yet there is no clear association for coronary, neo-natal and burn care. There are two competing hypotheses to explain any association — ‘practice-makes-perfect’ and ‘selective referral’. These are discussed and implications for the future provision of hospital services considered.
The Distribution of Security Price Changes: A Test of a Volume-Mixture Model with Cauchy Disturbances

This paper considers a time-series model for changes in security prices from one transaction to the next, in which they are viewed as depending on previous price changes, on transaction volume, and on a random disturbance. The dependence on transaction volume implies that the marginal distribution of price changes is a mixture of distributions, the form of which is determined by the behaviors of volume and the disturbance. Even when the disturbance follows a finite-variance distribution, such as the normal, the volume-mixture model implies a marginal distribution for price changes with the characteristic thick tails that are observed in practice. An alternative hypothesis, however, is that volume plays no role and that the disturbance itself is appropriately described by an infinite-variance probability law. Parametric tests of these two hypotheses are conducted by estimating the volume parameter in the mixture model under the alternative assumptions that the disturbance follows Gaussian and Cauchy laws.
Monoaminergic and Neurotrophic Gene Variation Associated with Fronto-Limbic Circuitry affect Mood and Cognitive Recovery Post-TBI

Following traumatic brain injury (TBI), ~80% of individuals will experience cognitive deficits, and ~50% will experience post-TBI depression (PTD). Identifying individual risk patterns for these complications is important for preventive treatment and early intervention. In uninjured populations, individuals with depression have distinct accompanying cognitive deficits. Importantly, dysregulation of fronto-limbic regions may, in part, explain the co-occurrence of both depressive and cognitive symptoms. The work presented investigates biological factors that influence survival after severe TBI, and among survivors, the presence and severity of PTD and/or cognitive deficits. The scientific framework under which this work was completed proposes targeted interactions between monoaminergic and neurotrophic gene variation that may lead to cognitive deficits and depressive symptoms. In addition to cognition, serotonergic (5-HT) and dopaminergic (DA) signaling both contribute to depressed mood and anhedonia, suggesting genetic variation in their signaling pathways may modulate PTD risk. Brain-derived neurotrophic factor (BDNF), a ubiquitous neurotrophin involved in neuronal survival and synaptic plasticity, is implicated in depression and cognitive dysfunction, and BDNF interacts with 5-HT/DA signaling in mood and cognitive processes. The work presented examines monoaminergic-neurotrophic biomarkers for predicting PTD risk and cognitive deficits. Serum and cerebrospinal fluid (CSF) BDNF levels, and fronto-limbic atrophy, were examined as possible biomarkers of PTD and cognitive deficits. A battery of targeted genes were examined for their proposed roles in survival, depression, cognition, and/or modulation of fronto-limbic connectivity. The data show variation within monoaminergic genes was associated with PTD incidence (serotonin transporter, 5-HTTLPR) and cognitive deficits post-TBI (dopamine D2 receptor, DRD2 and COMT). When investigating BDNF associations with PTD, we discovered that variation in BDNF interacts with MONOAMINERGIC AND NEUROTROPHIC GENE VARIATION ASSOCIATED WITH FRONTO-LIMBIC CIRCUITRY AFFECT MOOD AND COGNITIVE RECOVERY POST-TBI Michelle D. Failla, PhD University of Pittsburgh, 2014 v age to influence TBI survival, and acute BDNF levels were consistent biomarkers for TBI survival. Among TBI survivors, acute BDNF levels were associated with chronic cognitive performance and depressive symptoms severity, suggesting early neurotrophic support may facilitate chronic recovery. Investigating fronto-limbic regional brain volumes identified significant relationships to PTD and suggested non-uniform fronto-limbic atrophy patterns that may explain PTD susceptibility. Overall, this work supports that monoaminergic-neurotrophin genetic variability affects individual risk for PTD and related cognitive deficits, possibly through relationships with fronto-limbic circuitry.
Cluster-Based Collaborative Spectrum Sensing for Energy Harvesting Cognitive Wireless Communication Network

We consider a cluster-based collaborative spectrum sensing (CSS) scheme in energy harvesting cognitive wireless communication network (EH-CWCN), where cognitive nodes (CNs) are clustered based on their received power levels for enhancing sensing performance. In CSS scheme, time resource is limited and shared by energy harvesting, spectrum sensing, and data transmission. The purpose of this paper is to maximize the average throughput of EH-CWCN by identifying the optimal parameter set, including the durations of energy harvesting and spectrum sensing, local detection threshold, and the number of CNs. Moreover, it is hard to confirm the optimal local detection threshold at CNs with different received power levels. By constructing a fictitious cognitive node (FCN), which is assumed to have the same sensing performance as the sink node, the process for finding the optimal local detection threshold can be converted into the process for searching the optimal received signal-to-noise ratio of the FCN. Then, we formulate the general optimization problem under the collision constraint and energy constraint. Then, the existence and uniqueness of time fractions for energy harvesting and spectrum sensing are proved in this paper. The optimal parameter set is achieved by using the bisection method and a simplified linear search method. Finally, the theoretical analysis and the impact of the optimized parameters on the system performance are verified and shown through numerical simulations.
Burkholderia oxyphila sp. nov., a bacterium isolated from acidic forest soil that catabolizes (+)-catechin and its putative aromatic derivatives.

A novel bacterium, designated strain OX-01(T), was isolated from acidic soil, taxonomically investigated and identified as an agent that catabolizes (+)-catechin into taxifolin. Strain OX-01(T) is a Gram-reaction-negative, aerobic, non-sporulating, non-motile and rod-shaped bacterium. 16S rRNA gene sequence analysis identified this strain as a member of the genus Burkholderia and occupying a phylogenetic position closest to, but clearly distinct from, Burkholderia sacchari. Strain OX-01(T) does not have any nif genes, which are required for N(2)-fixation, in its genome, a feature that is similar to B. sacchari, which lacks nifH, but is distinct from the N(2)-fixing features of many other phylogenetically related taxa, such as Burkholderia ferrariae, B. heleia, B. mimosarum, B. nodosa, B. silvatlantica, B. tropica and B. unamae. Strain OX-01(T) has the following chemotaxonomic characteristics: the major ubiquinone is Q-8, the DNA G+C content is 64 mol% and the major fatty acids are C(16 : 0), C(17 : 0) cyclo and C(18 : 1)ω7c. It also has a unique profile of carbohydrate utilization among other species of the genus Burkholderia. The strain cannot assimilate many pentoses, hexoses and oligosaccharides, whereas it can catabolize (+)-catechin and its putative aromatic derivatives, such as 4-hydroxy-3-methoxycinnamic acid, protocatechuic acid, p-hydroxybenzoic acid, trans-p-coumaric acid and vanillic acid. Based on its morphological, physiological and chemotaxonomic characteristics, together with DNA-DNA relatedness values and 16S rRNA gene sequence comparison data, we show that strain OX-O1(T) represents a novel species of the genus Burkholderia, for which the name Burkholderia oxyphila sp. nov. is proposed. The type strain is OX-01(T) (=NBRC 105797(T) =DSM 22550(T)).
Fuzzy estimation system of dementia severity using biological information during sleep

Recently, the increase of care burden due to the increase of number of the elderly dementia patients is a matter of concern in Japan. However, dementia of the elderly tends to be wrongly recognized as the effect of aging, and there are many cases in which early detection are difficult. In this paper, we focus on the cognitive impairment as one of the core symptoms of dementia, and propose the fuzzy estimation system to detect the level of dementia through monitoring the participants' sleep using air pressure and ultrasonic sensor systems which were developed by our laboratory. As a result of applying this method to twenty-three women in a nursing home, we could confirm the high correlation between the degree of dementia and the truth value, the score of Revised Hasegawa's dementia scale.
Automated selection of check variables for area-efficient soft-error tolerant datapath synthesis

As the size of semiconductor devices has decreased, reliability degradation caused by soft-errors has become one of the greatest issues in VLSI circuit design. In this paper, we propose a method to synthesize soft-error tolerant application-specific datapaths via high-level synthesis. Our method is based on a concurrent error detection and a retry mechanism for error detection and error correction. The proposed model makes two novel contributions: (1) speculative resource sharing between retry parts and secondary parts for hardware/time overhead mitigation; (2) selective insertion of comparison-operations which detects soft-errors in order to increase the opportunity for speculative resource sharing. Datapath synthesis experiments found that the combination of speculative resource sharing and the selective insertion of comparison-operations achieves a maximum 32.3% improvement in latency.
Bmc Plant Biology Molecular Characterisation of the Strubbelig-receptor Family of Genes Encoding Putative Leucine-rich Repeat Receptor-like Kinases in Arabidopsis Thaliana

Background: Receptor-like kinases are a prominent class of surface receptors that regulate many aspects of the plant life cycle. Despite recent advances the function of most receptor-like kinases remains elusive. Therefore, it is paramount to investigate these receptors. The task is complicated by the fact that receptor-like kinases belong to a large monophyletic family with many sub-clades. In general, functional analysis of gene family members by reverse genetics is often obscured by several issues, such as redundancy, subtle or difficult to detect phenotypes in mutants, or by decision problems regarding suitable biological and biochemical assays. Therefore, in many cases additional strategies have to be employed to allow inference of hypotheses regarding gene function.
Unconventional Anthroponyms: Formation Patterns and Discursive Function

Unconventional Anthroponyms: Formation Patterns and Discursive Function continues a series of collective volumes comprising studies on onomastics, edited by Oliviu Felecan with Cambridge Scholars Publishing. Previous titles in this series include Name and Naming: Synchronic and Diachronic Perspectives (2012) and Onomastics in Contemporary Public Space (2013, co-edited with Alina Bughesiu). In contemporary naming practice, one can distinguish two verbal (linguistic) means of nominal referential identification: a "natural" one, which occurs in the process of conventional, official, canonical, standard naming and results in conventional/official/canonical/standard anthroponyms; a "motivated" one, which occurs in the process of unconventional, unofficial, uncanonical, non-standard naming and results in unconventional/unofficial/uncanonical/non-standard anthroponyms. The significance of an official name is arbitrary, conventional, unmotivated, occasional and circumstantial, as names are not likely to carry any intrinsic meaning; names are given by third parties (parents, godparents, other relatives and so on) with the intention to individualise (to differentiate from other individuals). Any meaning with which a name might be endowed should be credited to the name giver: s/he assigns several potential interpretations to the phonetic form of choice, based on his/her aesthetic and cultural options and other kinds of tastes, which are manifested at a certain time. Unconventional anthroponyms (nicknames, bynames, user names, pseudonyms, hypocoristics, individual and group appellatives that undergo anthroponymisation) are nominal "derivatives" that result from a name giver's wish to attach a specifying/defining verbal (linguistic) tag to a certain individual. An unconventional anthroponym is a person's singular signum, which may convey a practical necessity (to avoid anthroponymic homonymy: the existence of several bearers for a particular name) or the intention to qualify a certain human type (to underline specific difference - in this case, the unconventional anthroponym has an over-individualising role - or, on the contrary, to mark an individual's belonging to a class, his/her association with other individuals with whom s/he is typologically related - see the case of generic unconventional anthroponyms).
A Covert Timing Channel via Algorithmic Complexity Attacks: Design and Analysis

A covert channel is a communication channel that bypasses the access controls of the system, and it is a threat to the system's security. In this paper, we propose a new covert timing channel which exploits the algorithmic complexity vulnerabilities in the name lookup algorithm of the kernel. This covert channel has a high capacity and it is practically exploitable. In our experiments, the data rate reaches 2256 bps under a very low error rate. This data rate is high enough for practical use. So our covert channel is dangerous. To our knowledge, no previous works propose this covert channel nor implement it. We describe our design and implementation of the covert channel on a SELinux system, discuss the subtle issues that arose in the design, present performance data of the covert channel and analyse its capacity.
Design of Binary Quantizers for Distributed Detection Under Secrecy Constraints

In this paper, we investigate the design of distributed detection networks in the presence of an eavesdropper (Eve). We consider the problem of designing binary sensor quantizers that maximize the Kullback-Leibler (KL) divergence at the fusion center (FC), when subject to a tolerable constraint on the KL divergence at Eve. We assume that the channels between the sensors and the FC (likewise the channels between the sensors and the Eve) are modeled as binary symmetric channels (BSCs). In the case of i.i. d. received symbols at both the FC and Eve, we prove that the structure of the optimal binary quantizers is a likelihood ratio test (LRT). We also present an algorithm to find the threshold of the optimal LRT, and illustrate it for the case of Additive white Gaussian noise (AWGN) observation models at the sensors. In the case of non-i.i. d. received symbols at both FC and Eve, we propose a dynamic-programming based algorithm to find efficient quantizers at the sensors. Numerical results are presented to illustrate the performance of the proposed network.