Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Reionization on the Stellar Populations of Nearby Dwarf Galaxies

Cold dark matter models for galaxy formation predict that low-mass systems will be the first sites of star formation. As these objects have shallow gravitational potential wells, the subsequent growth of their stellar populations may be halted by heating and gas loss due to reionization. This effect has been suggested to have profoundly influenced properties of present-day dwarf galaxies, including their stellar populations and even survival as visible galaxies. In this Letter we draw on results from quantitative studies of Local Group dwarf galaxy star formation histories, especially for Milky Way satellites, to show that no clear signature exists for a widespread evolutionary impact from reionization. All nearby dwarf galaxies studied in sufficient detail contain ancient populations indistinguishable in age from the oldest Galactic globular clusters. Ancient star formation activity proceeded over several Gyr, and some dwarf spheroidal galaxies even experienced fairly continuous star formation until just a few Gyr ago. Despite their uniformly low masses, their star formation histories differ considerably. The evolutionary histories of nearby dwarf galaxies appear to reflect influences from a variety of local processes rather than a dominant effect from reionization.
Is left-handedness associated with a more pronounced age-related cognitive decline?

The effect of handedness on cognitive functioning has been the subject of much controversy. The influential “pathological left-handedness theory” posited by Coren and Halpern (1991) claims that left-handedness is probabilistically related to deviations from the neurological and cognitive norm. Many studies have failed to find negative effects of left-handedness on cognitive functioning, but most of these studies related handedness to cognition at one moment in time. Such studies do not exclude the possibility that sinistrality may be related to a more pronounced age-related longitudinal decline in cognitive functions. This hypothesis was tested in the present study. In a longitudinal study involving a large population sample of cognitively intact people aged at least 50 years at baseline, we evaluated the effect of handedness on age-related decline in four major cognitive domains: speed of information processing, verbal learning, long-term verbal memory, and executive functioning. The results failed to provide support for the hypothesis that sinistrality is associated with a more pronounced age-related cognitive decline. Recommendations for future studies are provided.
Flier Meet: Crowdsensing Enabled Urban Public Information Reposting and Sharing

Bulletin boards serve an important function for public information sharing. In this video we present Flier Meet, a system that enables cross-space reposting, intelligent tagging, and pervasive sharing of distributed fliers in urban surfaces. We use a story to present the usage and implementation of Flier Meet and illustrate how it facilitates information sharing and public activity recommendation, and how it provides support to enhance social connections.
Novel Approach to Circuit Board Testing

This paper describes research and development efforts in the application of nanoscale sensors to implement an original method for bed-of-needles testing for printed circuit boards testing. This approach performs functional testing that eliminates the need to have a pre-existing model of a circuit board while automating much of the development process. The general concept involves creating arrays of nanoscale sensor probes , using molecular electronics for incorporating test instruments and computing logic for test interpretation directly into a pod consisting of multiple nails, and distributing these pods across the face and back of a circuit card using a contact fixture. The resulting test approach exhibits massive parallelism combined with extremely compact size that facilitates novel testing approaches not possible with current generation or planned test equipment. In consequence, many existing limitations are expected to be overcome with test speed and accuracy significantly improved.
A FINE STRUCTURAL INVESTIGATION OF SURFACE SPECIALIZATIONS AND THE CORTICAL REACTION IN EGGS OF THE CNIDARIAN BUNODOSOMA CAVERNATA

Developing oocytes of the cnidarian Bunodosoma cavernata are located within the mesoglea of the mesenteries of the gastrovascular cavity. The cortex of the more mature vitellogenic oocytes contains numerous, electron-dense, membrane-bound, cortical granules. The surface of these oocytes possesses prominent radially projecting structures termed cytospines. Each cytospine has a core of microfilaments, 50–70 Å in diameter, that extends basally as a rootlet through the cortical layer. During spawning, ova lacking any extraneous investments are released from the enclosing gastrodermis. As a consequence of fertilization or events associated with the earliest stages of development the ova undergo a massive cortical reaction. This reaction, which occurs during or just after release of the ova, involves extensive reorganization of the cortical layer. The cortical granule membranes and egg surface membrane fuse and vesiculate resulting in the massive discharge of granule contents. This event is accompanied by the loss of vesicular remnants of cortical ooplasm and the disruption of cytospine organization. Light and electron microscope comparisons of unreacted and reacted eggs show that the reaction results in a significant decrease in egg diameter with the oolemma of the reacted egg reorganizing in a position centripetal to its original location.
XSDF: A system for XML semantic disambiguation

This paper briefly describes and evaluates XSDF, a new XML Semantic Disambiguation Framework, taking as input: an XML document and a general purpose semantic network, and then producing as output a semantically augmented XML tree made of unambiguous semantic concepts. Experiments demonstrate the effectiveness of XSDF in comparison with alternative methods.
Scheduling a multi class queue with many exponential servers: asymptotic optimality in heavy traffic

We consider the problem of scheduling a queueing system in which many statistically identical servers cater to several classes of impatient customers. Service times and impatience clocks are exponential while arrival processes are renewal. Our cost is an expected cumulative discounted function, linear or nonlinear, of appropriately normalized performance measures. As a special case, the cost per unit time can be a function of the number of customers waiting to be served in each class, the number actually being served, the abandonment rate, the delay experienced by customers, the number of idling servers, as well as certain combinations thereof. We study the system in an asymptotic heavy-traffic regime where the number of servers n and the offered load r are simultaneously scaled up and carefully balanced: n\approx r+\beta \sqrtr for some scalar \beta. This yields an operation that enjoys the benefits of both heavy traffic (high server utilization) and light traffic (high service levels.)
ALua: An Event-Driven Communication Mechanism for Parallel and Distributed Programming

This paper presents ALua, an event-driven communication mechanism based on the interpreted language Lua. This mechanism takes advantage of the interpreted nature of Lua to deene messages as chunks of code which are executed by the receiver. The event-driven distributed programming model is discussed and demonstrated with a set of examples. Applicability of ALua in real-sized parallel applications is studied by comparing the implementation of two parallel applications written in ALua with their compiled counterparts.
Behavioral screening for neuroactive drugs in zebrafish

The larval zebrafish has emerged as a vertebrate model system amenable to small molecule screens for probing diverse biological pathways. Two large‐scale small molecule screens examined the effects of thousands of drugs on larval zebrafish sleep/wake and photomotor response behaviors. Both screens identified hundreds of molecules that altered zebrafish behavior in distinct ways. The behavioral profiles induced by these small molecules enabled the clustering of compounds according to shared phenotypes. This approach identified regulators of sleep/wake behavior and revealed the biological targets for poorly characterized compounds. Behavioral screening for neuroactive small molecules in zebrafish is an attractive complement to in vitro screening efforts, because the complex interactions in the vertebrate brain can only be revealed in vivo. © 2011 Wiley Periodicals, Inc. Develop Neurobiol 72: 373–385, 2012
A 2.0 GHz CMOS triple cascode push-pull power amplifier with second harmonic injection for linearity enhancement

A novel linearization technique to a CMOS push-pull power amplifier (PA) by second harmonic injection has been proposed. In order to inject second harmonics to the PAs, a new balun with a branching filter has been proposed and fabricated by using multi-layered organic substrates. The PA was fabricated in 0.18-μm CMOS process and was implemented on the balun by flip-chip connection. Because of the low breakdown voltage of CMOS power transistors, triple cascode configuration was adapted. The proposed push-pull PA has delivered an output power of 28.6 dBm with a power-added efficiency (PAE) of 42.2 % at 2.0 GHz and 5.4 V supply voltage. It has been also demonstrated that using second harmonic injection from input port of the PA, PAE and output power with a wideband code division multiple access (WCDMA) modulated signal are improved by 5 % and 2.0 dB respectively at adjacent channel leakage power ratio (ACLR) of -39 dBc.
Identifikation kognitiver Effekte in Online-Bewertungen

Wie und ob die Meinungsbildung das Verhalten der Verbraucher und Dienstleistungsnehmer beeinflusst und wie Wissensverarbeitung bei Menschen abläuft, sind die Fragen, mit denen sich Sozialund Kognitionspsychologen beschäftigen (Stürmer, 2009; Wolff, 1993). Fehlerhafte Urteile bei der Meinungsbildung, auch kognitive Effekte genannt, werden in bestimmten Situationen wie der Bewertung von Produkten oder in Anspruch genommenen Leistungen besonders deutlich. Sie lassen sich in der Wissensorganisation und Gedächtnisstruktur des menschlichen Gehirns begründen. Mögliche Gründe für verzerrte Meinungen sind falsche Wahrnehmungen, die auf Basis kognitiver Informationsorganisation und -verarbeitung, aber auch aufgrund emotionaler Betroffenheit und/oder persönlicher Voreingenommenheit entstehen können.
Use of Only Oral Rehydration Salt Solution for Successful Management of a Young Infant with Serum Sodium of 201 mmol/L in an Urban Diarrhoeal Diseases Hospital, Bangladesh

A boy aged 4 months 7 days was admitted to the Intensive Care Unit (ICU) of the Dhaka Hospital of icddr,b, Dhaka, Bangladesh, with the problems of acute watery diarrhoea with some dehydration, pneumonia, lethargy, and hypernatraemia (serum sodium of 201 mmol/L). Correction for hypernatraemia was tried by using only oral rehydration salt (ORS) solution. Seizures occurred during correction of the hypernatraemia. These were difficult to control and required three doses of injection lorazepam, a loading dose of injection phenobarbitone, followed by injection phenytoin and finally two doses of injection mannitol (even though there was no clinical or imaging evidence by ultrasonography or computed tomography of cerebral oedema). The correction was continued with ORS, and all the anticonvulsants were successfully weaned without any further seizures, and the patient recovered without any overt neurological sequelae. We present a case report of extreme hypernatraemia, which was successfully managed using only ORS.
An EEG Coherence Based Method Used for Mental Tasks Classification

In this paper a new coherence based method to extract the appropriate EEG features for a five mental tasks classification problem is proposed. The new introduced method has the advantage of using an adaptive new technique that models the EEG signal using the frequency information obtained by employing the coherence function to each EEG recording channel. The adaptive attribute of the technique is due to both, to the amplitude and, respective, to the phase adaptive processes used to model the EEG signal. Another specificity of the new modeling technique is given by the fact of exploiting the nonlinear dynamics of the brain system; this is reflected in the particular spectral mixing of the fundamental spectral components obtained first, by using the coherence function. Finally, to conclude the obtained results in comparison with the results reported in the literature, by using this new approach the classification rate was noticeably improved.
Category verbal fl uency performance may be impaired in amnestic mild cognitive impairment

To study category verbal fl uency (VF) for animals in patients with amnestic mild cognitive impairment (aMCI), mild Alzheimer disease (AD) and normal controls. Method: Fifteen mild AD, 15 aMCI, and 15 normal control subjects were included. Diagnosis of AD was based on DSM-IV and NINCDS-ADRDA criteria, while aMCI was based on the criteria of the International Working Group on Mild Cognitive Impairment, using CDR 0.5 for aMCI and CDR 1 for mild AD. All subjects underwent testing of category VF for animals, lexical semantic function (Boston Naming-BNT, CAMCOG Similarities item), WAIS-R forward and backward digit span, Rey Auditory Verbal Learning (RAVLT), Mini-Mental Status Examination (MMSE), and other task relevant functions such as visual perception, attention, and mood state (with Cornell Scale for Depression in Dementia). Data analysis used ANOVA and a post-hoc Tukey test for intergroup comparisons, and Pearson’s coeffi cient for correlations of memory and FV tests with other task relevant functions (statistical signifi cance level was p<0.05). Results: aMCI patients had lower performance than controls on category VF for animals and on the backward digit span subtest of WAIS-R but higher scores compared with mild AD patients. Mild AD patients scored signifi cantly worse than aMCI and controls across all tests. Conclusion: aMCI patients may have poor performance in some non-memory tests, specifi cally category VF for animals in our study, where this could be attributable to the infl uence of working memory.
Constant Time EXPected Similarity Estimation using Stochastic Optimization

A new algorithm named EXPected Similarity Estimation (EXPoSE) was recently proposed to solve the problem of large-scale anomaly detection. It is a non-parametric and distribution free kernel method based on the Hilbert space embedding of probability measures. Given a dataset of $n$ samples, EXPoSE needs only $\mathcal{O}(n)$ (linear time) to build a model and $\mathcal{O}(1)$ (constant time) to make a prediction. In this work we improve the linear computational complexity and show that an $\epsilon$-accurate model can be estimated in constant time, which has significant implications for large-scale learning problems. To achieve this goal, we cast the original EXPoSE formulation into a stochastic optimization problem. It is crucial that this approach allows us to determine the number of iteration based on a desired accuracy $\epsilon$, independent of the dataset size $n$. We will show that the proposed stochastic gradient descent algorithm works in general (possible infinite-dimensional) Hilbert spaces, is easy to implement and requires no additional step-size parameters.
Constrained Least Squares Algorithm for TOA-Based Mobile Location under NLOS Environments

This paper presents a mobile station (MS) location method using constrained least-squares (CLS) estimation in the non-line-sight (NLOS) conditions. Three or more time-of-arrival (TOA) measurements of a signal traveling between a MS and base stations (BSs) are necessary for its localization. However, when some of the measurements are from NLOS paths, the location errors can be very large. We propose a method that mitigates possible large TOA error measurements caused by NLOS. This method does not depend on a particular distribution of the NLOS error. Simulation results show that the location accuracy is significantly improved over traditional algorithms, even under highly NLOS conditions. geometrical approach, the geometric relationship between the mobile device and its reference is exploited to establish the Euclidean distance between them and to identify the physical location of the device. In this paper, we propose a novel least-square (LS) approach combining with geometrical relationship. It firstly adjusts the NLOS-corrupted range measurements to approach their LOS values, and then minimizes a constrained least- squares function incorporating the known relation between the intermediate variable and the position coordinate, based on the technique of Lagrange multipliers. This algorithm does not require the distinction between NLOS and LOS BSs (6), and the knowledge of the statistics of measurement noise and NLOS errors. Our approach also has the advantage of requiring no modifications to the subscriber equipment. The location estimation can be performed at either the MS if it has the functionality or at special location units in the network. The remainder of this paper is organized as follows. The proposed algorithm is outlined in Section II and the simulation results and performance analysis are discussed in Section III. Finally, conclusions are drawn in Section IV.
A Femtocell-based Testbed for Evaluating Future Cellular Networks

This paper argues that the network community needs research testbeds for cellular wireless networks, and introduces a femtocell-based testbed, dubbed Cell-Lab, which is currently being developed for evaluating next-generation wireless network protocols. The Cell-Lab is being designed to support virtualization to enable multiple experiments simultaneously on top of femtocell base stations. In addition, open and remote access to the testbed, and integration with wired testbeds will be considered as basic features. To this end, our novel implementation strategy for achieving these goals and Cell-Lab’s usage scenarios are described.
Privacy-Preserving Layer over MapReduce on Cloud

Cloud computing provides powerful and economical infrastructural resources for cloud users to handle ever-increasing Big Data with data-processing frameworks such as MapReduce. Based on cloud computing, the MapReduce framework has been widely adopted to process huge-volume data sets by various companies and organizations due to its salient features. Nevertheless, privacy concerns in MapReduce are aggravated because the privacy-sensitive information scattered among various data sets can be recovered with more ease when data and computational power are considerably abundant. Existing approaches employ techniques like access control or encryption to protect privacy in data processed by MapReduce. However, such techniques fail to preserve data privacy cost-effectively in some common scenarios where data are processed for data analytics, mining and sharing on cloud. As such, we propose a flexible, scalable, dynamical and costeffective privacy-preserving layer over the MapReduce framework in this paper. The layer ensures data privacy preservation and data utility under the given privacy requirements before data are further processed by subsequent MapReduce tasks. A corresponding prototype system is developed for the privacy-preserving layer as well.
Comparative analysis of routing protocols in MANETS

Mobile networks have become one of the most popular forms of modern world communication. These are different from conventional networks because they lack a fixed infrastructure. Since the nodes are mobile, therefore routes have to be constantly updated. The data transmission on these constantly changing routes has to be maintained efficiently with respect to successful delivery of data packets between source and destination, and delay in this transaction. Along with these two, several other parameters have also to be taken care of. There are several protocols available for data transfer on mobile ad hoc networks (MANETs). No single algorithm could be termed best for all applications. Optimal results for any algorithm depend on the conditions in which it is used, and the parameters which are given high priority. In this paper, some popular routing protocols for MANETs including both proactive protocols such as DSDV, OLSR, FSR and reactive protocols such as AODV, DSR, TORA have been compared and found that on-demand protocols are more befitting than table driven protocols, especially with increased number of nodes and mobility. At low mobility, table driven protocols perform better than on-demand protocols.
Process variation aware data management for STT-RAM cache design

The spin-transfer torque random access memory (STT-RAM) has gained increasing attentions for its high density, fast read access, zero standby power, and good scalability. The recently proposed retention-relax design further improves STT-RAM write access performance and makes it even more promising as an on-chip memory technology. Nevertheless, the process variations could affect the writability of STT-RAM cells. The situation for retention-relax design is even more severe. In this paper, we comprehensively study the impact of process variations, including those from both CMOS and magnetic technologies, on key STT-RAM design parameters. Furthermore, we propose process variation aware nonuniform cache access (PVA-NUCA) technique for large STT-RAM cache design. Besides the varying interconnect latencies determined by memory locations, PVA-NUCA compensates write time variations of STT-RAM cells resulted by process variations. Two algorithms, namely, conservative promotion and aggressive prediction, have been introduced and evaluated. A conflict-reduction mechanism is utilized to degrade the data access miss rate caused by conflicts of access-intensive data blocks. Compared to the traditional STT-RAM dynamic nonuniform cache access (DNUCA), our proposed dynamic PVA-NUCA can improve 25.29% of IPC performance and reduce 26.4% of STT-RAM cache energy consumption, with < 1% of area overhead.
Modeling High-Performance Wormhole NoCs for Critical Real-Time Embedded Systems

Manycore chips are a promising computing platform to cope with the increasing performance needs of critical real-time embedded systems (CRTES). However, manycores adoption by CRTES industry requires understanding task's timing behavior when their requests use manycore's network-on-chip (NoC) to access hardware shared resources. This paper analyzes the contention in wormhole-based NoC (wNoC) designs - widely implemented in the high-performance domain - for which we introduce a new metric: worst-contention delay (WCD) that captures wNoC impact on worst-case execution time (WCET) in a tighter manner than the existing metric, worst-case traversal time (WCTT). Moreover, we provide an analytical model of the WCD that requests can suffer in a wNoC and we validate it against wNoC designs resembling those in the Tilera-Gx36 and the Intel-SCC 48-core processors. Building on top of our WCD analytical model, we analyze the impact on WCD that different design parameters such as the number of virtual channels, and we make a set of recommendations on what wNoC setups to use in the context of CRTES.