Miracle-dz/UniFAR-FTUs huggingface dataset:
A Truly Low-Cost High-Efficiency ASK Demodulator Based on Self-Sampling Scheme for Bioimplantable Applications

In the fields of wireless bioelectronics implants and sensor network systems, amplitude shift keying (ASK) is one of the most commonly used schemes employed to modulate the baseband signal with reference to the intermediate or even the carrier frequency. In this study, a demodulator architecture capable of dealing with most of the previous limitations in an ASK-utilized medical implant, especially in want of being powered through wireless delivering, is proposed. It features the abilities of working on a very small modulation index and being provided without any R/C component(s) inside by means of a self-sampling scheme. The design has been implemented in an 18-mum CMOS process. The demodulator circuit occupies a die size of merely 32.3 times 14.5 mu m2. Analytic results from both simulated gradation and fabricated chips show that the proposed circuit can operate at a carrier of 2 MHz and achieve a modulation rate of up to 50%. The results also demonstrate that the presented work can still perform a proper demodulation even with a modulation index beneath 5.5%. An average power of approximately 336 muW was confirmed in return for the remarkable advantages. All aspects regarding the design, including a review of the prior arts, system consideration, circuit description, and analyses from simulation phase to actual measurement, are presented in detail.
A System Identification Approach to Estimating Complex Impedance spectra from Electrochemical noise Data

A system identification approach for the analysis of electrochemical noise data is proposed. The most common techniques, used by many investigators, are based on: (i) the ratio of sample standard deviations, which gives no information about the frequency dependence of the electrode impedance, or (ii) Power Spectral Density estimates, which deliver the modulus of the spectrum with large variations at the lowest frequencies. Phase is, almost invariably, not included. In this work, the electrochemical cell is modeled by an input-output model. With the application of system identification techniques, it is possible to identify values of the parameters of the system model. It is shown that this approach delivers a description of the system under study with: smooth electrode impedance curves, and magnitude and phase information. Some results obtained with the most common electrochemical noise analysis techniques are presented for comparison with the proposed approach. A theoretical limitation of the proposed approach appears if a perfect symmetry between both electrodes is considered.
A Principled Framework for General Adaptive Social Robotics

A principled framework for general adaptive intelligent systems is described and applied to the domain of social robotics. Under the principled framework, the author develops computational methods to address an important aspect of a social robot, which is the ability to rapidly adapt to changes in the environment such as the introduction of novel objects and installations that serve novel purposes. Methods are also developed to address another important aspect of a social robot, which is the ability to understand the needs of humans that it interacts with by having a deep model of their needs, which enables the robot to assist humans in various tasks in a socially realistic manner. The author describes the methods of causal learning and script learning through computational visual observation that allow a robot to acquire the scripts and plans that enable it to understand the intentions of humans as well as solve problems to provide assistance to humans. The robot thus adapts rapidly to changing environmental factors as new observation provides new knowledge to guide its behavior. The assistance provided to humans is formulated as a script interaction problem and the optimal points at which assistance is provided are computed using a motivational strength model derived from psychological research and formulated computationally for robotic purposes. Also, a method is proposed to handle competition of needs which arises frequently in the course of robot-human interactions to generate socially realistic and appropriate behavior on the part of the robot. This paper uses primarily a home environment to demonstrate the methodology involved, but a robot that incorporates the methodology described could rapidly adapt to any environments such as the office and factory.
Effect of Drought on Herbivore-Induced Plant Gene Expression: Population Comparison for Range Limit Inferences

Low elevation “trailing edge” range margin populations typically face increases in both abiotic and biotic stressors that may contribute to range limit development. We hypothesize that selection may act on ABA and JA signaling pathways for more stable expression needed for range expansion, but that antagonistic crosstalk prevents their simultaneous co-option. To test this hypothesis, we compared high and low elevation populations of Boechera stricta that have diverged with respect to constitutive levels of glucosinolate defenses and root:shoot ratios; neither population has high levels of both traits. If constraints imposed by antagonistic signaling underlie this divergence, one would predict that high constitutive levels of traits would coincide with lower plasticity. To test this prediction, we compared the genetically diverged populations in a double challenge drought-herbivory growth chamber experiment. Although a glucosinolate defense response to the generalist insect herbivore Spodoptera exigua was attenuated under drought conditions, the plastic defense response did not differ significantly between populations. Similarly, although several potential drought tolerance traits were measured, only stomatal aperture behavior, as measured by carbon isotope ratios, was less plastic as predicted in the high elevation population. However, RNAseq results on a small subset of plants indicated differential expression of relevant genes between populations as predicted. We suggest that the ambiguity in our results stems from a weaker link between the pathways and the functional traits compared to transcripts.
Exploring a New World of Identity with Identity 2.0 based Solutions

On the Internet today, account registration is nearly always a requirement to interact with any website in a meaningful way. Each digital identity a user creates is a new and completely disjoint identity from all other existing digital identities of the user. These traditional identities, Identity 1.0 identities, are site-centric and centralized. Alternatively, Identity 2.0 identity solutions are completely decentralized and user-centric. This paper presents four different examples of user interaction using Identity 2.0 based solutions that weren’t possible within a traditional identity framework: greylisting, identity multiplexing, user-centric privacy, and site preregistration. To understand the examples further, two applications using aspects of the examples provided were developed and deployed on the Internet for public use. Moreover, a third prototype was developed to further understand how users interact within an Identity 2.0 based Internet. Through the study of server logs and informal user studies, two key observations were observed regarding general user patterns of users authenticating themselves within a new identity framework.
Defining the mechanistic role of high mobility group box-1 and its utility as a biomarker in the inflammatory pathogenesis of epilepsy

Epilepsy, which affects 50 million people worldwide, is a chronic neurological condition characterized by a predisposition to generate spontaneous seizures. Antiepileptic drug resistance is a significant problem, the causes of which are poorly understood. Inflammation is purported to play a pathological role in the development of epilepsy following brain insult. High mobility group box-1 (HMGB1) has been implicated in the development of seizures and epilepsy in preclinical models and human studies. HMGB1 undergoes post-translational modifications, including acetylation and redox changes, which dictate its inflammatory extracellular function. Novel inflammatory blood biomarkers such as HMGB1 that are intricately involved in the epilepsy disease process per se may act as stratification markers to identify patients who may benefit from immunomodulatory interventions. This thesis aimed to characterise the role of HMGB1 in seizures and epilepsy and its utility as a clinical biomarker. Analysis of 24 healthy volunteers undergoing a 24-hour blood-sampling study did not demonstrate any significant circadian fluctuations in serum HMGB1. No intra or inter-subject variability was also observed in the biomarker. A further study involving patients with idiopathic intracranial hypertension (IIH, n=18), neuroinfection (n=15) and Rasmussen’s encephalitis (n=10) showed that there was no correlation between serum and cerebrospinal (CSF) fluid levels of HMGB1, regardless of blood brain barrier integrity. Subgroup analysis of bacterial meningitis showed that both CSF and serum HMGB1 was significantly elevated (as compared to IIH). Furthermore, CSF HMGB1 was more than 10-fold higher in those with bacterial (n=6) rather than viral meningitis (n=8). The expression pattern of HMGB1 acetylation and redox isoforms in brain and blood was examined in three distinct preclinical models of seizures and epilepsy including recurrent seizures and status epilepticus in the kainate-model, single seizure in the maximal electroshock test (MES) and chronic spontaneous seizures in the pilocarpine epilepsy model. In response to kainate-induced seizures, in both brain and blood, an early rise in non-acetylated and reduced HMGB1 isoforms was demonstrated consistent with functional chemotaxis. This was followed by a delayed 6-fold rise at 24 hours in brain of the acetylated, disulphide inflammatory form of HMGB1. In serum, significant expression of the inflammatory isoforms was seen after 14 days, possibly coinciding with the onset of spontaneous seizures. Inflammatory isoforms of HMGB1 were not identified within the first 24 hours following isolated MES-seizure in mice. Serum, but not brain, total HMGB1 was significantly elevated (by 311%) in chronic epileptic mice experiencing regular spontaneous seizures; however the contribution of the different isoforms remains to be elucidated. In humans with epilepsy, compared to both healthy controls (1.11±0.07ng/ml, p
IL-27 Directly Restrains Lung Tumorigenicity by Suppressing Cyclooxygenase-2-Mediated Activities1

Gene transfer of IL-27 to tumor cells has been proven to inhibit tumor growth in vivo by antiproliferation, antiangiogenesis, and stimulation of immunoprotection. To investigate the nonimmune mechanism of IL-27 that suppresses lung cancer growth, we have established a single-chain IL-27-transduced murine Lewis lung carcinoma (LLC-1) cell line (LLC-1/scIL-27) to evaluate its tumorigenic potential in vivo. Mice inoculated with LLC/scIL-27 displayed retardation of tumor growth. Production of IL-12, IFN-γ, and cytotoxic T cell activity against LLC-1 was manifest in LLC/scIL-27-injected mice. Of note, LLC-1/scIL-27 exhibited decreased expression of cyclooxygenase-2 (COX-2) and PGE2. On the cellular level, the LLC/scIL-27 transfectants had reduced malignancy, including down-regulation of vimentin expression and reduction of cellular migration and invasion. The suppression of tumorigenesis by IL-27 on lung cancer cells was further confirmed by the treatment with rIL-27 on the murine LLC-1 and human non-small cell lung carcinoma (NSCLC) cell lines. PGE2-induced vimentin expression, movement, and invasiveness were also suppressed by the treatment with rIL-27. Our data show that IL-27 not only suppresses expression of COX-2 and PGE2 but also decreases the levels of vimentin and the abilities of cellular migration and invasion. Furthermore, inoculation of LLC/scIL-27 into immunodeficient NOD/SCID mice also exhibited reduced tumor growth. Our data indicate that IL-27-induced nonimmune responses can contribute to significant antitumor effects. Taken together, the results suggest that IL-27 may serve as an effective agent for lung cancer therapy in the future.
Boa

In today's software-centric world, ultra-large-scale software repositories, such as SourceForge, GitHub, and Google Code, are the new library of Alexandria. They contain an enormous corpus of software and related information. Scientists and engineers alike are interested in analyzing this wealth of information. However, systematic extraction and analysis of relevant data from these repositories for testing hypotheses is hard, and best left for mining software repository (MSR) experts! Specifically, mining source code yields significant insights into software development artifacts and processes. Unfortunately, mining source code at a large scale remains a difficult task. Previous approaches had to either limit the scope of the projects studied, limit the scope of the mining task to be more coarse grained, or sacrifice studying the history of the code. In this article we address mining source code: (a) at a very large scale; (b) at a fine-grained level of detail; and (c) with full history information. To address these challenges, we present domain-specific language features for source-code mining in our language and infrastructure called Boa. The goal of Boa is to ease testing MSR-related hypotheses. Our evaluation demonstrates that Boa substantially reduces programming efforts, thus lowering the barrier to entry. We also show drastic improvements in scalability.
Growth Models in the New Zealand Wine Industry: Some Case Study Evidence

Abstract One of the most dominant models for explaining organisational growth is that of organisational lifecycles. Drawing parallels with biology, life cycle theorists argue firms are born, grow, mature and decline. Despite a proliferation of models of organisational lifecycle, there is little empirical support for their general validity. The present study builds a four-stage model of organisational life cycle based on case study research in the New Zealand wine industry. Far from being driven by internal pressures, these cycles seem to be related to the demands of the global wine market, as well as the strategy chosen by each firm.
Melatonin combined with exercise cannot alleviate cerebral injury in a rat model of focal cerebral ischemia/reperfusion injury

Previous studies have demonstrated that melatonin combined with exercise can alleviate secondary damage after spinal cord injury in rats. Therefore, it is hypothesized that melatonin combined with exercise can also alleviate ischemic brain damage. In this study, adult rats were subjected to right middle cerebral artery occlusion after receiving 10 mg/kg melatonin or vehicle subcutaneously twice daily for 14 days. Forced exercise using an animal treadmill was performed at 20 m/min for 30 minutes per day for 6 days prior to middle cerebral artery occlusion. After middle cerebral artery occlusion, each rat received melatonin combined with exercise, melatonin or exercise alone equally for 7 days until sacrifice. Interestingly, rats receiving melatonin combined with exercise exhibited more severe neurological deficits than those receiving melatonin or exercise alone. Hypoxia-inducible factor 1α mRNA in the brain tissue was upregulated in rats receiving melatonin combined with exercise. Similarly, microtubule associated protein-2 mRNA expression was significantly upregulated in rats receiving melatonin alone. Chondroitin sulfate proteoglycan 4 (NG2) mRNA expression was significantly decreased in rats receiving melatonin combined with exercise as well as in rats receiving exercise alone. Furthermore, neural cell loss in the primary motor cortex was significantly reduced in rats receiving melatonin or exercise alone, but the change was not observed in rats receiving melatonin combined with exercise. These findings suggest that excessive intervention with melatonin, exercise or their combination may lead to negative effects on ischemia/reperfusion-induced brain damage.
Identifying determinants to predict intention to complete a health risk assessment

Purpose – The purpose of this paper is to determine which constructs (factors) will significantly predict and influence the intention to complete a health risk assessment (HRA) in a hospital employee population. Design/methodology/approach – The authors used a cross-sectional design using the theory of planned behavior to design a questionnaire to determine the variables associated with intention to complete an HRA. From a sample of those who completed (n=17) and those who did not complete (n=16) the HRA, the authors used elicitation inquiry to determine the leading factors associated with the intention to complete an HRA. The authors used the responses from this inquiry to develop a questionnaire for a hospital population (n=1,550). A total of 503 hospital employees completed and returned this questionnaire. Using the returned questionnaire data, the authors used logistic regression analysis to determine the best fit model for predicting intention to complete an HRA. Findings – The predictive model was s.
ZHU , SHAO AND TANG : BOOSTED CROSS-DOMAIN CATEGORIZATION 1 Boosted Cross-Domain Categorization

A boosted cross-domain categorization framework that utilizes labeled data from other visual domains as the auxiliary knowledge for enhancing the original learning system is presented. The source domain data under a different data distribution are adapted to the target domain through both feature representation level and classification level adaptation. The proposed framework is working in conjunction with a learned domainadaptive dictionary pair, so that both the source domain data representations and their distribution are optimized in order to match the target domain. By iteratively updating the weak classifiers, the categorization system allocates more credits to “similar” source domain samples, while abandoning “dissimilar” source domain samples. Using a set of Web images and selected categories from the HMDB51 dataset as the source domain data, the proposed framework is evaluated with both image classification and human action recognition tasks on the Caltech-101 and the UCF YouTube datasets, respectively, achieving promising results.
Spatial competition on the master-saliency map

The saliency map model (Itti and Koch, 2000) is a hierarchically structured computational model, simulating visual saliency processing. Iso-feature processing on feature maps and conspicuity maps precedes cross-dimensional signal processing on the master map, where the most salient location of the visual field is selected. This texture segmentation study focuses on a possible spatial structure on the master map. In four experiments the spatial distance between a texture irregularity in the stimulus (“target”) and a cross-dimensional task irrelevant texture irregularity in the backward mask (“patch”) was varied. The results show that the target-patch distance modulates target detection, and that this modulation is limited to critical distances around the target. We conclude that the signals from different feature dimensions compete on a spatial master map. There is first evidence that the critical distances increase with target eccentricity.
Savoirs sur l'eau : les techniques à l'appui des relations de pouvoir ?

Le contexte actuel, surtout dans les pays du Sud, est celui d’une concurrence accrue pour l’accès à l’eau. L’intensification des usages agricoles, domestiques et industriels, ainsi que l’utilisation de nouvelles techniques permettant d’atteindre l’eau à des profondeurs considérables ne font que l’accentuer. S’y ajoutent des modèles climatiques qui prévoient des modifications profondes de disponibilité en eau et donc des situations davantage critiques. Quant aux réformes sur l’eau, elles se caractérisent par une généralisation des politiques de gestion participative et de gestion intégrée à travers le monde. La question des savoirs sur l’eau devient dès lors cruciale. Ces savoirs sous-tendent en effet les choix techniques d’appropriation et de distribution de l’eau, le processus de qualification de la ressource et de quantification de sa disponibilité, l’organisation de la gestion et du partage.
Distributed Source Coding with One Distortion Criterion and Correlated Messages

In this paper, distributed (or multiterminal) source coding with one distortion criterion and correlated messages is considered. This problem can be also called ``Berger-Yeung problem with correlated messages''. It corresponds to the source coding part of the graph-based framework for transmission of a pair of correlated sources over the multiple-access channel (MAC) where one is lossless and the other is lossy. As a result, the achievable rate-distortion region for this problem is provided. It is an information-theoretic characterization of the rate of exponential growth (as a function of the number of source samples) of the size of the bipartite graphs which can represent a pair of correlated sources with satisfying one distortion criterion. A rigorous proof of the achievability and the converse part is given. It is also shown that there exists functional duality between Berger-Yeung problem with correlated messages and semi-deterministic broadcast channel with correlated messages. This means that the optimal encoder-decoder mappings for one problem become the optimal decoder-encoder mappings for the dual problem. In the duality setup, the correlation structure of the messages in the two dual problems, source distortion measure and channel cost measure are also specified.
The Chemistry Development Kit (CDK): An Open-Source Java Library for Chemo-and Bioinformatics

The Chemistry Development Kit (CDK) is a freely available open-source Java library for Structural Chemo-and Bioinformatics. Its architecture and capabilities as well as the development as an open-source project by a team of international collaborators from academic and industrial institutions is described. The CDK provides methods for many common tasks in molecular informatics, including 2D and 3D rendering of chemical structures, I/O routines, SMILES parsing and generation, ring searches, isomorphism checking, structure diagram generation, etc. Application scenarios as well as access information for interested users and potential contributors are given.