Miracle-dz/UniFAR-FTUs huggingface dataset:
Point source confusion in SZ cluster surveys

We examine the effect of point source confusion on cluster detection in Sunyaev-Zel'dovich (SZ) surveys. A filter matched to the spatial and spectral characteristics of the SZ signal optimally extracts clusters from the astrophysical backgrounds. We calculate the expected confusion (point source and primary cosmic microwave background [CMB]) noise through this filter and quantify its effect on the detection threshold for both single and multiple frequency surveys. Extrapolating current radio counts, we estimate that confusion from sources below ~$100~\mu$Jy limits single-frequency surveys to $1\sigma$ detection thresholds of $Y\sim 3$ $\times$ 10 -6 arcmin 2 at 30 GHz and $Y\sim 10^{-5}$ arcmin 2 at 15 GHz (for unresolved clusters in a 2 arcmin beam); these numbers are highly uncertain, and an extrapolation with flatter counts leads to much lower confusion limits. Bolometer surveys must contend with an important population of infrared point sources. We find that a three-band matched filter with 1 arcmin resolution (in each band) efficiently reduces confusion, but does not eliminate it: residual point source and CMB fluctuations contribute significantly to the total filter noise. In this light, we find that a 3-band filter with a low-frequency channel (e.g, 90+150+220 GHz) extracts clusters more effectively than one with a high frequency channel (e.g, 150+220+300 GHz).
Targeting β-arrestin2 in the treatment of l-DOPA–induced dyskinesia in Parkinson’s disease

Significance β-Arrestins are unique proteins that have multiple cellular functions such as G protein-coupled receptor signal desensitization, protein trafficking and signaling molecule scaffolding. Treatment of Parkinson’s disease (PD) motor symptoms by l-3,4-dihydroxyphenylalanine (l-DOPA) has been hampered by abnormal involuntary movements or dyskinetic side effects. The cause of these dyskinesias has been attributed to receptor supersensitivity and uncontrolled neuronal excitability. Here we demonstrate in multiple preclinical models of l-DOPA–induced dyskinesias and PD that expression levels of β-arrestin2 can alter manifestation of these dyskinesias by reducing receptor supersensitivity while maintaining the therapeutic effect of l-DOPA. Thus novel drugs that increase β-arrestin–dependent function at dopamine receptors may be useful in ameliorating PD motor symptoms without inducing dyskinesias. Parkinson’s disease (PD) is characterized by severe locomotor deficits and is commonly treated with the dopamine (DA) precursor l-3,4-dihydroxyphenylalanine (l-DOPA), but its prolonged use causes dyskinesias referred to as l-DOPA–induced dyskinesias (LIDs). Recent studies in animal models of PD have suggested that dyskinesias are associated with the overactivation of G protein-mediated signaling through DA receptors. β-Arrestins desensitize G protein signaling at DA receptors (D1R and D2R) in addition to activating their own G protein-independent signaling events, which have been shown to mediate locomotion. Therefore, targeting β-arrestins in PD l-DOPA therapy might prove to be a desirable approach. Here we show in a bilateral DA-depletion mouse model of Parkinson’s symptoms that genetic deletion of β-arrestin2 significantly limits the beneficial locomotor effects while markedly enhancing the dyskinesia-like effects of acute or chronic l-DOPA treatment. Viral rescue or overexpression of β-arrestin2 in knockout or control mice either reverses or protects against LIDs and its key biochemical markers. In other more conventional animal models of DA neuron loss and PD, such as 6-hydroxydopamine–treated mice or rats and 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine–treated nonhuman primates, β-arrestin2 overexpression significantly reduced dyskinesias while maintaining the therapeutic effect of l-DOPA. Considerable efforts are being spent in the pharmaceutical industry to identify therapeutic approaches to block LIDs in patients with PD. Our results point to a potential therapeutic approach, whereby development of either a genetic or pharmacological intervention to enhance β-arrestin2- or limit G protein-dependent D1/D2R signaling could represent a more mechanistically informed strategy.
Integrated Optimization of Network Topology and DG Outputs for MVDC Distribution Systems

Medium-voltage DC (MVDC) distribution systems are receiving more and more attractions. For a MVDC distribution system, less network power losses can be obtained if the network topology and the outputs of distributed generations are optimized together. However, this is a tough optimization problem due to the mixed integer non-convex programming property. To efficiently address this problem, a convex mixed-integer quadratic programming (MIQP) based integrated optimization approach is proposed in this letter, which is validated via three MVDC systems.
Grand Challenge : Scalable Stateful Stream Processing for Smart Grids

We describe a solution to the ACM DEBS Grand Challenge 2014, which evaluates event-based systems for smart grid analytics. Our solution follows the paradigm of stateful data stream processing and is implemented on top of the SEEP stream processing platform. It achieves high scalability by massive data-parallel processing and the option of performing semantic load-shedding. In addition, our solution is fault-tolerant—the large processing state of stream operators is not lost after failure. Our experimental results show that our solution processes 1 month worth of data for 40 houses in 4 hours. When we scale out the system, the time reduces linearly to 30 minutes before the system bottlenecks at the data source. We then apply semantic load-shedding, maintaining a low median prediction error and reducing the time further to 17 minutes. The system achieves these results with median latencies below 30 ms and a 90th percentile below 50 ms.
Alignment of U3 region sequences of mammalian type C viruses: identification of highly conserved motifs and implications for enhancer design

We aligned published sequences for the U3 region of 35 type C mammalian retroviruses. The alignment reveals that certain sequence motifs within the U3 region are strikingly conserved. A number of these motifs correspond to previously identified sites. In particular, we found that the enhancer region of most of the viruses examined contains a binding site for leukemia virus factor b, a viral corelike element, the consensus motif for nuclear factor 1, and the glucocorticoid response element. Most viruses containing more than one copy of enhancer sequences include these binding sites in both copies of the repeat. We consider this set of binding sites to constitute a framework for the enhancers of this set of viruses. Other highly conserved motifs in the U3 region include the retrovirus inverted repeat sequence, a negative regulatory element, and the CCAAT and TATA boxes. In addition, we identified two novel motifs in the promoter region that were exceptionally highly conserved but have not been previously described.
Lanes Detection Based on Unsupervised and Adaptive Classifier

This paper describes an algorithm to detect the road lanes based on an unsupervised and adaptive classifier. We have selected this classifier because in the road we do not know the parameters of lanes, although we know that lanes are there, only they need to be classified. First of all, we tested and measured the brightness of the lanes of the road in many videos. Generally, the lines on the road are white. We used the HSV image and we improved the region of study. Then, we used a Hough transform which yields a set of possible lines. These lines have to be classified. The classifier starts with initial parameters because we suppose that the vehicle is on road and in the center of the lane. There are two classes, the first one is the left road line and the second one is the right road line. Each line has two parameters that are: middle point of line and the line slope. These parameters will be changing in order to adjust to the real lanes. A tensor holds the two lines, so these lines will not separate more than the tensor allows. A Kalman filter estimates the new class's parameters and improves the tracking of the lanes. Finally, we use a mask in order to highlight the lane and show to the user a better image.
Managing Google's data lake: an overview of the Goods system

For most large enterprises today, data constitutes their core asset, along with code and infrastructure. For most enterprises, the amount of data that they produce internally has exploded in recent years. At the same time, in many cases, engineers and data scientists do not use centralized data-management systems and end up creating what became known as a data lake —a collection of datasets that often are not well organized or not organized at all and where one needs to “ﬁsh” for useful datasets. In this paper, we describe our experience building and deploying G OODS , a system to manage Google’s internal data lake. G OODS crawls Google’s infrastructure and builds a catalog of discovered datasets, including structured ﬁles, databases, spreadsheets, and even services that provide access to the data. G OODS extracts meta-data about datasets in a post-hoc way: engineers continue to generate and organize datasets in the same way that they have before, and G OODS provides value without disrupting teams’ practices. The technical challenges that we had to address resulted both from the scale and heterogeneity of Google’s data lake and from our decision to extract metadata in a post-hoc manner. We believe that many of the lessons that we learned are applicable to building large-scale enterprise-level data-management systems in general.
Tele-impedance: Teleoperation with impedance regulation using a body–machine interface

This work presents the concept of tele-impedance as a method for remotely controlling a robotic arm in interaction with uncertain environments. As an alternative to bilateral force-reflecting teleoperation control, in tele-impedance a compound reference command is sent to the slave robot including both the desired motion trajectory and impedance profile, which are then realized by the remote controller without explicit feedback to the operator. We derive the reference command from a novel body–machine interface (BMI) applied to the master operator’s arm, using only non-intrusive position and electromyography (EMG) measurements, and excluding any feedback from the remote site except for looking at the task. The proposed BMI exploits a novel algorithm to decouple the estimates of force and stiffness of the human arm while performing the task. The endpoint (wrist) position of the human arm is monitored by an optical tracking system and used for the closed-loop position control of the robot’s end-effector. The concept is demonstrated in two experiments, namely a peg-in-the-hole and a ball-catching task, which illustrate complementary aspects of the method. The performance of tele-impedance control is assessed by comparing the results obtained with the slave arm under either constantly low or high stiffness.
Aggregation of group A streptococci by human saliva and effect of saliva on streptococcal adherence to host cells

The aggregation of group A streptococci by whole, stimulated human saliva (WHS) and the effect of saliva on streptococcal adherence to host cells was investigated. WHS samples from 11 individuals were found to aggregate both M+ and M- group A streptococci to various degrees. The aggregating activity was sensitive to heat, EDTA, EGTA [ethylene glycol-bis(beta-aminoethyl ether)-N,N,N',N'-tetraacetic acid], sodium dodecyl sulfate, and lipoteichoic acid. None of the simple sugars tested, mercaptoethanol, albumin, or nonionic detergents had any effect on aggregation. The aggregating activity of EDTA-treated saliva was restored by 0.1 mM Ca2+ and 1.0 mM Mn2+ but not by up to 5 mM Mg2+. Only streptococci from the stationary phase were aggregated. Hyaluronidase treatment of streptococci from the exponential phase of growth restored their ability to be aggregated, suggesting that the hyaluronic acid capsule interferes with agglutination. Adsorption of WHS by one strain of Streptococcus pyogenes removed aggregating activity for other strains of S. pyogenes and Streptococcus sanguis but not agglutinins for Escherichia coli, suggesting that the agglutinin is specific for certain gram-positive bacteria. Molecular sieve chromatography of WHS and identification of streptococcus-binding components of saliva suggest that either a glycoprotein of approximately 360 kDa or a mucin of saliva of greater than 1,000 kDa mediates aggregation of streptococci. WHS also inhibited adherence of S. pyogenes to buccal epithelial cells.
Neuropsychological function as a result of chronic exposure to methadone and other opioids

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Analysis of natural and synthetic speech using Fujisaki model

Text-to-speech (TTS) synthesis systems are being advanced to achieve naturalness and intelligibility in synthetic speech. Unit selection-based synthesis (USS) and Hidden Markov Model-based text-to-speech synthesis systems (HTS) are recent techniques in this area. USS-based synthetic speech is known to be natural (due to concatenation of natural speech sound units). On the other hand, HTS-based speech is not as natural in perception as USS-based synthetic speech. Due to speech synthesis technologies, voice biometrics systems may face threats due to impostor attacks. Thus, it is important to study the differences that exist between natural and synthetic speech. In this context, we investigate the effectiveness of parameters of Fujisaki model for capturing Fundamental frequency (F0) contour variations in natural and synthetic speech. F0 contour of speech contains linguistic and non-linguistic information. Experimental results on several utterances from Gujarati (a low resourced language) demonstrate the effectiveness of phrase and accent components to analyze the difference between these two speeches. Variability in phrase and accent components suggests that synthetic speech differs in terms of prosodic information in excitation source as compared to natural speech. These findings may assist to distinguish these two speeches and provide an aid to alleviate impostor attacks.
Beyond Sensorimotor Intelligence: Assessment of Symbolic Maturity Through Analysis of Pretend Play.

This paper demonstrates methodology for assessing symbolic maturity or mental representation as evidenced in symbolic play. The system was developed from stage-specific behavior described by Piaget (1962). The behavior described develops between approxi mately nine and twenty-four months of age. The levels of play de scribed by Piaget are derived from the child's actions with respect to objects and people in the environment. Development proceeds from initial realistic treatment of objects through pretended activities which are increasingly abstract and complex, to the beginning of pretend activities that are planned, and thus mentally represented in advance of performance. The following describes the place of symbolic play stages in de velopmental theory, makes reference to current research on cognitive aspects of pretend play, and refers to research undertaken with the symbolic assessment instrument. However, the major focus of this presentation is description of procedures for assessing symbolic maturity through analysis of pretend play. Symbolic development was treated by Piaget (1962) but the proposed stages have not been fully replicated. A system for assessing symbolic development in the second year of life should prove important on theoretical grounds because it opens the path to evaluating empirically the assumption of Piaget (1962) and Werner and Kaplan (1963) that language is a manifestation of a general symbolizing function, evolving from earlier cognitive developments. Several authors have suggested that cognitive development is expressed in play (Bruner, Olver, & Greenfield, 1966; Piaget, 1962; Sinclair, 1970; Fein, 1974; and Lowe, 1975). In studying play be havior of children between 12 and 26 months of age, Sinclair (1970) reported a developmental sequence in the children's actions with a standard group of play objects which was consistent with the levels
Central suboptimal mean-square H ∞ controller design for linear stochastic time-varying systems

This article designs the central finite-dimensional H ∞ controller for linear stochastic time-varying systems with integral-quadratically bounded deterministic disturbances, that is suboptimal for a given threshold γ with respect to a modified Bolza–Meyer quadratic criterion including the attenuation control term with the opposite sign. In contrast to the previously obtained results, this article reduces the original H ∞ controller problem to the corresponding optimal H 2 controller problem, using the technique proposed in Doyle et al. (Doyle, J.C., Glover, K., Khargonekar, P.P., and Francis, B.A. (1989), ‘State-space Solutions to Standard H 2 and H ∞ Control Problems’, IEEE Transactions on Automatic Control, 34, 831–847). Numerical simulations are conducted to verify the performance of the designed controller for a linear stochastic system against the central suboptimal H ∞ controller available for the corresponding deterministic system.
Piezo-Electric Energy Harvesting for Wireless Sensor Networks

Numerous industrial and military applications require remote sensing of various machine and equipment operating parameters in locations where traditional power sources may not be available and long periods of unattended operation are required. Quite often, however, some source of vibrating energy may be present in operation of the machine in question. Herein, a piezoelectric source is efficiently utilized to generate power for the operation of a microcontroller and radio transmitter to acquire sampled machine data. Various techniques for the efficient conversion, use, and storage of piezoelectric power are detailed and used in a general energy harvesting data transmitter design.
Generational differences in leader values and leadership behaviors.

As a new generation of workers enters the workforce and the realms of leadership and management, headlines in the business and popular press are encouraging managers to deal with generational differences that appear to be affecting employees, particularly those in the leadership ranks. This article describes generational cohort theory and summarizes research on the impact of generational differences on work processes. It then explores what differences are occurring among managers in different cohorts in terms of attributes they value in leaders and their actual behaviors as leaders (as perceived by self, boss, and subordinates) using data obtained from 2 large databases, including managers across the country spanning 4 generations. Results of the 1st study demonstrate that managers and professionals in different generational cohorts do value different attributes in leaders. Results of the 2nd study find that managers in different generational cohorts also report behaving differently. Although the differen.
Exploiting pathogens' tricks of the trade for engineering of plant disease resistance: challenges and opportunities

With expansion of our understanding of pathogen effector strategies and the multiplicity of their host targets, it is becoming evident that novel approaches to engineering broad‐spectrum resistance need to be deployed. The increasing availability of high temporal gene expression data of a range of plant–microbe interactions enables the judicious choices of promoters to fine‐tune timing and magnitude of expression under specified stress conditions. We can therefore contemplate engineering a range of transgenic lines designed to interfere with pathogen virulence strategies that target plant hormone signalling or deploy specific disease resistance genes. An advantage of such an approach is that hormonal signalling is generic so if this strategy is effective, it can be easily implemented in a range of crop species. Additionally, multiple re‐wired lines can be crossed to develop more effective responses to pathogens.
Major role of the extracellular matrix in airway smooth muscle phenotype plasticity: Implications for chronic asthma

Airway smooth muscle (ASM) plays a key role in the development of airway hyperresponsiveness and remodeling in asthma, which may involve maturation of ASM cells to a hypercontractile phenotype. In vitro studies have indicated that long-term exposure of bovine tracheal smooth muscle (BTSM) to insulin induces a functional hypercontractile, hypoproliferative phenotype. Similarly, the extracellular matrix protein laminin has been found to be involved in both the induction and maintenance of a contractile ASM phenotype. Using BTSM, we now investigated the role of laminins in the insulin-induced hypercontractile, hypoproliferative ASM phenotype. The results demonstrate that insulin-induced hypercontractility after 8 days of tissue culture was fully prevented by combined treatment of BTSM-strips with the laminin competing peptides Tyr-Ile-Gly-Ser-Arg (YIGSR) and Arg-Gly-Asp-Ser (RGDS). YIGSR also prevented insulin-induced increases in sm -myosin expression and abrogated the suppressive effects of prolonged insulin treatment on PDGF-induced DNA-synthesis in cultured cells. In addition, insulin time-dependently increased laminin (cid:3)2, (cid:2)1 and (cid:4)1 chain protein, but not mRNA abundance in BTSM strips. Moreover, as previously found for contractile protein accumulation, signaling through PI3-kinase and Rho kinase dependent pathways was required for the insulin-induced increase in laminin abundance and contractility. Collectively, our results indicate a critical role for (cid:2)1-containing laminins, likely laminin-211, in the induction of a hypercontractile, hypoproliferative ASM phenotype by prolonged insulin exposure. Increased laminin production by ASM could be involved in the increased ASM contractility and contractile protein expression in asthma. Moreover, the results may be of interest for the use of inhaled insulin administrations by diabetics.
A review of automated debugging systems: knowledge, strategies and techniques

The authors propose a classification of debugging knowledge, and a description of the corresponding knowledge representation in the systems. Then they propose a classification of global debugging strategies used in the systems, and a description of the corresponding techniques. They assess the identified strategies from a real-world program development point of view. The knowledge types identified are: (1) knowledge of the intended program; (2) knowledge of the actual program; (3) understanding of the programming language; (4) general programming expertise; (5) knowledge of the application domain; (6) knowledge of bugs; and (7) knowledge of debugging methods. The strategies identified are: (1) filtering; (2) checking computational equivalence of intended program and actual one; (3) checking the well-formedness of actual program; and (4) recognizing stereotyped errors. <<ETX>>
Experiences of deculturation among United States Peace Corps volunteers

Abstract This research tests the theoretical concept of unlearning in the experiences of Peace Corps volunteers. An open-ended interview method was used to identify two types of cultural experiences: 1) unlearning or deculturation; and 2) long-term cultural mindsets. The findings indicate that the subjects as a whole did not experience deculturation. They also identified a long-term cultural perspective. The results of this research argue for a re-examination of intercultural theories using the concept of deculturation.