Miracle-dz/UniFAR-FTUs huggingface dataset:
RECEPTORS AND USES THEREOF

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A Generalized Estimating Equation Approach to Analysis of Maintenance of Wakefulness Testing in a Study of Lisdexamfetamine Dimesylate, Armodafinil, and Placebo in Sleep-Deprived Adults

Abstract In a study of acute sleep deprivation in healthy male volunteers randomized to double-blind treatment with lisdexamfetamine dimesylate (20, 50, or 70 mg), placebo control, or an active control (armodafinil 250 mg), Maintenance of Wakefulness Test data were compared using a generalized estimating equation analysis to eliminate the need for unequivocal sleep latency imputation. Compared with placebo across all Maintenance of Wakefulness Tests, all active treatments were associated with lower risk of falling asleep (risk ratio [95% confidence interval]): 0.45 (0.27–0.76; P = 0.0026), 0.10 (0.05–0.20; P < 0.0001), and 0.05 (0.02–0.14; P < 0.0001) for 20, 50, and 70 mg lisdexamfetamine dimesylate, respectively, and 0.11 (0.06–0.21; P < 0.0001) for the active control. Sleep-risk ratios were similar for lisdexamfetamine dimesylate 50 or 70 mg and for the active control, but lisdexamfetamine 20 mg was associated with a greater risk of falling asleep compared with the active control (4.13 [1.97–8.67]; P = 0.0002). Generalized estimating equation analysis detected wake-promoting effects of active treatments and eliminating data imputation, suggesting model utility in future studies.
Effort versus Reward: Preparing Samples for Fungal Community Characterization in High-Throughput Sequencing Surveys of Soils

Next generation fungal amplicon sequencing is being used with increasing frequency to study fungal diversity in various ecosystems; however, the influence of sample preparation on the characterization of fungal community is poorly understood. We investigated the effects of four procedural modifications to library preparation for high-throughput sequencing (HTS). The following treatments were considered: 1) the amount of soil used in DNA extraction, 2) the inclusion of additional steps (freeze/thaw cycles, sonication, or hot water bath incubation) in the extraction procedure, 3) the amount of DNA template used in PCR, and 4) the effect of sample pooling, either physically or computationally. Soils from two different ecosystems in Minnesota, USA, one prairie and one forest site, were used to assess the generality of our results. The first three treatments did not significantly influence observed fungal OTU richness or community structure at either site. Physical pooling captured more OTU richness compared to individual samples, but total OTU richness at each site was highest when individual samples were computationally combined. We conclude that standard extraction kit protocols are well optimized for fungal HTS surveys, but because sample pooling can significantly influence OTU richness estimates, it is important to carefully consider the study aims when planning sampling procedures.
Role of Reuniens Nucleus Projections to the Medial Prefrontal Cortex and to the Hippocampal Pyramidal CA1 Area in Associative Learning

We studied the interactions between short- and long-term plastic changes taking place during the acquisition of a classical eyeblink conditioning and following high-frequency stimulation (HFS) of the reuniens nucleus in behaving mice. Synaptic changes in strength were studied at the reuniens-medial prefrontal cortex (mPFC) and the reuniens-CA1 synapses. Input/output curves and a paired-pulse study enabled determining the functional capabilities of the two synapses and the optimal intensities to be applied at the reuniens nucleus during classical eyeblink conditioning and for HFS applied to the reuniens nucleus. Animals were conditioned using a trace paradigm, with a tone as conditioned stimulus (CS) and an electric shock to the trigeminal nerve as unconditioned stimulus (US). A single pulse was presented to the reuniens nucleus to evoke field EPSPs (fEPSPs) in mPFC and CA1 areas during the CS-US interval. No significant changes in synaptic strength were observed at the reuniens-mPFC and reuniens-CA1 synapses during the acquisition of eyelid conditioned responses (CRs). Two successive HFS sessions carried out during the first two conditioning days decreased the percentage of CRs, without evoking any long-term potentiation (LTP) at the recording sites. HFS of the reuniens nucleus also prevented the proper acquisition of an object discrimination task. A subsequent study revealed that HFS of the reuniens nucleus evoked a significant decrease of paired-pulse facilitation. In conclusion, reuniens nucleus projections to prefrontal and hippocampal circuits seem to participate in the acquisition of associative learning through a mechanism that does not required the development of LTP.
A Truthful Budget Feasible Multi-Armed Bandit Mechanism for Crowdsourcing Time Critical Tasks

Motivated by allocation and pricing problems faced by service requesters on modern crowdsourcing platforms, we study a multi-armed bandit (MAB) problem with several real-world features: (a) the requester wishes to crowdsource a number of tasks but has a fixed budget which leads to a trade-off between cost and quality while allocating tasks to workers; (b) each task has a fixed deadline and a worker who is allocated a task is not available until this deadline; (c) the qualities (probability of completing a task successfully within deadline) of crowd workers are not known; and (d) the crowd workers are strategic about their costs. We propose a mechanism that maximizes the expected number of successfully completed tasks, assuring budget feasibility, incentive compatibility, and individual rationality. We establish an upper bound of O(B2/3(K ln(KB))1/3) on the expected regret of the proposed mechanism with respect to an appropriate benchmark algorithm, where B is the total budget and K is the number of workers. Next, we provide a characterization of any deterministic truthful mechanism that solves the above class of problems and use this characterization to establish a lower bound of Ω(B2=3K1=3) on the expected regret for any budgeted MAB mechanism satisfying the above properties.
Physical Custody Reconsidered: Examining Measurement Equivalence Across Dimensions of Post-Divorce Co-Parenting

For parents of minor children, the co-parenting relationship is often a highly salient yet volatile aspect of post-divorce life. The nature of this relationship is also dependent upon the greater social context, particularly those aspects that facilitate or constrain interactions between parents. This study evaluates four dimensions of co-parenting behaviors among a sample of recently divorced and divorcing parents (N = 396) and tests for measurement equivalence across physical custody arrangements. Item functioning was determined to be empirically similar for nonresident parents and parents with shared physical custody, so post-hoc tests were conducted comparing a combined group of these parents with a group of resident parents. Results indicated that covert conflictual behaviors falling within the exclusive control of the individual functioned similar across physical custody arrangements. Co parental support, overt forms of conflict, and covert conflict that fell outside the control of the individual differed at a mean-level. As such, there is discussion of co-parenting under particular contextual conditions and the potential impact of those conditions on child well-being.
Analyzing and comparing Montgomery multiplication algorithms

Montgomery multiplication methods constitute the core of modular exponentiation, the most popular operation for encrypting and signing digital data in public-key cryptography. In this article, we study the operations involved in computing the Montgomery product, describe several high-speed, space-efficient algorithms for computing MonPro(a, b), and analyze their time and space requirements. Our focus is to collect several alternatives for Montgomery multiplication, three of which are new. However, we do not compare the Montgomery techniques to other modular multiplication approaches.
Towards Meta-Adaptation Support with Reusable and Composable Adaptation Components

Software systems today are increasingly used in changing environments and expected to adapt with variable adaptation concerns. This requirement demands a systematic approach to efficiently construct system global adaptation behaviour according to the dynamic adaptation requirements. This paper presents Transformer a framework for adaptation behaviour composition support based on reusable and compos able adaptation components. Rather than using one adaptation module for all possible contexts, Transformer constructs system global adaptation behaviour by contextually fusing adaptation plans from multiple adaptation components. Explicit conflict resolution is provided to handle possible conflicts raised in the fusion process. In addition to the description of the Transformer framework, this paper also presents its implementation and its application to a video conferencing system. Qualitative analysis and simulation results show that our framework exhibits significant advantage over traditional approaches in light of flexibility and reusability of the adaptation components with little performance overhead.
Soft-Core Processors for Embedded Systems

A soft-core processor is a hardware description language (HDL) model of a specific processor (CPU) that can be customized for a given application and synthesized for an ASIC or FPGA target. In many applications, soft-core processors provide several advantages over custom designed processors such as reduced cost, flexibility, platform independence and greater immunity to obsolescence. Embedded systems are hardware and software components working together to perform a specific function. Usually they contain embedded processors that are often in the form of soft-core processors that execute software code. This paper presents a survey of soft-core processors that are used in embedded systems. Several soft-core processors available from commercial vendors and open-source communities are reviewed and compared based on major architectural features. In addition, several real world examples of embedded systems that employ soft-core processors are summarized. As the complexity of embedded systems continues to increase, it is expected that the usage of customizable soft-core processors will become more widespread.
Does a Brief Motivational Intervention Reduce Frequency of Pregaming in Mandated Students?

ABSTRACT Background: Pregaming, also known as frontloading or predrinking, is a common but risky drinking behavior among college students. However, little is known about the way in which a brief motivational intervention (BMI) addressing general alcohol use and consequences may impact pregaming frequency. Objectives: This study examined whether mandated students reduced frequency of pregaming following a BMI when pregaming was spontaneously discussed and whether gender moderated these effects. Methods: Participants (n = 269, 32% female) were mandated college students who had received a campus-based alcohol citation and continued to exhibit risky alcohol use six weeks after receiving a brief advice session. Participants were randomized to a brief motivational intervention (BMI, n = 145) or assessment only (AO, n = 124) and completed follow-up assessments at 3, 6, and 9 months postintervention. Hierarchical Linear Modeling (HLM) was used to examine both between-person (Level 2) effects (i.e., condition) and within-person (Level 1) effects (i.e., time) on pregaming frequency. Analyses examining discussions of pregaming within the BMI were conducted using a subsample of the BMI sessions which had been transcribed (n = 121). Results: Participants in the BMI group did not significantly reduce the frequency of pregaming compared to those in the AO group, even when pregaming was explicitly discussed during the BMI. Moreover, the BMI was equally ineffective at reducing pregaming frequency for both males and females. Conclusion/Importance: Pregaming frequency appears to be resistant to conventional intervention efforts, but recent research suggests several innovative strategies for addressing pregaming in the college student population.
Efficient identification and approximation of k-nearest moving neighbors

Nowadays, massive amounts of tracking data for various types of moving objects, including vehicles, humans and animals, are becoming available. Analyzing this type of spatio-temporal data is crucial for discovering movement patterns, understanding and forecasting behaviors, and developing novel applications and services. One problem of particular interest is finding objects that move close together with a certain object during some periods of time. In this paper, we focus on finding the k-nearest moving neighbors for a given query object and time interval. We formulate the problem, using a similarity function that takes into consideration both the proximity and the direction of the trajectories, and we firstly present an exact algorithm. Then, we focus on approximate algorithms in order to reduce the execution time, investigating two directions. The first employs line simplification to approximate the compared trajectories, thus reducing the calculations needed to identify the nearest neighbors. The second relies on estimates of prior probabilities derived from trajectory distributions and attempts to achieve a faster approximation of the k-nearest neighbors. A detailed experimental evaluation of the aforementioned algorithms on three real-world datasets is finally presented in order to verify their efficiency and accuracy.
An efficient approximate algorithm for delay-cost-constrained QoS routing

The problem of finding a path with two additive constraints is called a multi-constrained path (MCP) problem in the literature. In this paper, we explore the MCP problem based on the idea of single mixed weight. Given two infeasible paths, it can be theoretically proved that a better path can possibly be found if we choose an appropriate parameter to construct the mixed weight. An approximate algorithm is thus proposed to solve the MCP problem. A large number of experiments on networks of different sizes demonstrate that this algorithm can make a correct judgment whether there is a feasible path or not with a very high probability. On the other hand, the time complexity of this algorithm is very small since it only needs to execute Dijkstra's algorithm a limited number of times even for a network of relatively large size.
Interpersonal effects of strategic and spontaneous guilt communication in trust games

ABSTRACT A social partner’s emotions communicate important information about their motives and intentions. However, people may discount emotional information that they believe their partner has regulated with the strategic intention of exerting social influence. Across two studies, we investigated interpersonal effects of communicated guilt and perceived strategic regulation in trust games. Results showed that communicated guilt (but not interest) mitigated negative effects of trust violations on interpersonal judgements and behaviour. Further, perceived strategic regulation reduced guilt’s positive effects. These findings suggest that people take emotion-regulation motives into account when responding to emotion communication.
Neural-network-based gender classification using genetic search for eigen-feature selection

We consider the problem of gender classification from frontal facial images using feature selection and neural networks. We argue that feature selection is an important issue in gender classification and we demonstrate that by removing features that do not encode important gender information from the image representation of faces, the error rate can be reduced significantly. Automatic feature subset selection is used. First, principal component analysis (PCA) is used to represent each image as a feature vector (i.e., eigen-features) in a low-dimensional space, spanned by the eigenvectors of the covariance matrix of the training images (i.e., coefficients of the linear expansion). A genetic algorithm (GA) is then used to select a subset of features from the low-dimensional representation by removing certain eigenvectors. Finally, a neural network is trained to perform gender classification using the selected eigen-feature subset. Experimental results demonstrate a significant improvement in error rate reduction. Using a subset of eigen-features containing only 18% of the features in the complete set, the average NN classification error goes down to 11.3% from an average error rate of 17.7%.
FAM222B Is Not a Likely Novel Candidate Gene for Cerebral Cavernous Malformations

Cerebral cavernous malformations (CCMs) are prevalent slow-flow vascular lesions which harbour the risk to develop intracranial haemorrhages, focal neurological deficits, and epileptic seizures. Autosomal dominantly inherited CCMs were found to be associated with heterozygous inactivating mutations in 3 genes, CCM1(KRIT1), CCM2(MGC4607), and CCM3(PDCD10) in 1999, 2003 and 2005, respectively. Despite the availability of high-throughput sequencing techniques, no further CCM gene has been published since. Here, we report on the identification of an autosomal dominantly inherited frameshift mutation in a gene of thus far unknown function, FAM222B(C17orf63), through exome sequencing of CCM patients mutation-negative for CCM1-3. A yeast 2-hybrid screen revealed interactions of FAM222B with the tubulin cytoskeleton and STAMBP which is known to be associated with microcephaly-capillary malformation syndrome. However, a phenotype similar to existing models was not found, neither in fam222bb/fam222ba double mutant zebrafish generated by transcription activator-like effector nucleases nor in an in vitro sprouting assay using human umbilical vein endothelial cells transfected with siRNA against FAM222B. These observations led to the assumption that aberrant FAM222B is not involved in the formation of CCMs.
Influence of oil contamination on in vitro bond strength of bonding agents to dental substrates.

PURPOSE To evaluate the influence of cleaning procedures (pumice, anionic detergent and both procedures together) on the tensile bond strength of etch-and-rinse and self-etch adhesive systems to bovine enamel and dentin in vitro. METHODS Eighty non-carious, bovine incisors were extracted, embedded in acrylic resin to obtain enamel/dentin specimens. Flat bonding surfaces were obtained by grinding. Groups were divided according to substrate (enamel or dentin), adhesive system [etch-and-rinse, Adper Single Bond 2 (SB) or self-etch, Clearfil Protect Bond (PB)]; and cleaning substances (pumice, anionic detergent and their combination). The teeth were randomly divided into 20 groups (n=8): G1--Enamel (E) + SB; G2--E + oil (O) + SB; G3--E + O + Pumice (P) + SB; G4--E + O + Tergentol (T) + SB; G5--E + O + P + T + SB; G6--E + PB; G7--E + O + PB; G8--E + O + P + PB; G9--E + O + T + PB; G10--E + O + P + T + PB; G11--Dentin (D) + SB; G12 D + SB + O; G13--D + SB + O + P; G14--D + SB + O + T;G15--D + SB + O + P + T; G16--D + PB; G17--D + O + PB +; G18--D + O + P + PB; G19--D + O + T + PB; G20--D + O + P + T + PB. Specimens were contaminated with handpiece oil for 5 seconds before bonding. Adhesive systems and resin composite were applied according to manufacturers' instructions. Specimens were tested in tension after 24 hours of immersion using a universal testing machine at a crosshead speed of 0.5 mm/minute. Bond strengths were analyzed with ANOVA. Failure sites were observed and recorded. RESULTS Tensile bond strength in MPa were: G1 (23.6 +/- 0.9); G2 (17.3 +/- 2.2); G3 (20.9 +/- 0.9); G4 (20.6 +/- 0.5); G5 (18.7 +/- 2.3); G6 (23.0 +/- 1.0); G7 (21.5 +/- 2.4); G8 (19.9 +/- 1.3); G9 (22.1 +/- 1.2); G10 (19.1 +/- 1.2); G11 (18.8 +/- 1.3); G12 (15.7 +/- 2.1); G13 (17.8 +/- 3.3); G14 (15.3 +/- 2.9); G15 (15.6 +/- 1.9); G16 (14.7 +/- 2.3); G17 (5.5 +/- 0.9); G18 (19.3 +/- 1.8); G19 (15.6 +/- 1.6); G20 (20.3 +/- 3.9). Statistical analysis showed that the main factors substrate and cleaning were statistically significant, as well as the triple interaction between factors of variance. However, the factor adhesive system did not show statistical difference. Oil contamination reduced bond strengths, being less detrimental to enamel than to dentin. Etch-and-rinse (SB) and two-step self-etch (PB) systems had similar bond strengths in the presence of oil contamination. For etch-and-rinse (SB), the cleaning procedures were able to clean enamel, but dentin was better cleaned by pumice. When self-etch (PB) system was used on enamel, anionic detergent was the best cleaning substance, while on dentin the tested procedures were similarly efficient.
Observation vs statistics: Near optimal online channel access in cognitive radio networks

We investigate efficient channel learning and opportunity utilization problem in cognitive radio networks (CRN). We find that the sensing order of multiple channels and channel accessing policy play a critical role in designing effective and efficient scheme to maximize the throughput. Leveraging this important finding, we propose a near optimal online channel access policy. We prove that, our policy can converge to an optimal point in a guaranteed probability. Further, we design a computational efficient channel access policy, integrating optimal stopping theory and multi-armed bandit policy effectively. The computational complexity is reduced from O(K NK) to O(K), where N is the number of channels, and K is the maximum number of sensing/probing times in each procedure. Our simulation results validate our policy, showing at least 40% performance improvement over statistically optimal but fixed policy.