Miracle-dz/UniFAR-FTUs huggingface dataset:
Substructural analysis using evolutionary computing techniques

Substructural analysis (SSA) was one of the very first machine learning techniques to be applied to chemoinformatics in the area of virtual screening. For this method, given a set of compounds typically defined by their fragment occurrence data (such as 2D fingerprints). The SSA computes weights for each of the fragments which outlines its contribution to the activity (or inactivity) of compounds containing that fragment. The overall probability of activity for a compound is then computed by summing up or combining the weights for the fragments present in the compound. A variety of weighting schemes based on specific relationship-bound equations are available for this purpose. This thesis identifies uplift to the effectiveness of SSA, using two evolutionary computation methods based on genetic traits, particularly the genetic algorithm (GA) and genetic programming (GP). Building on previous studies, it was possible to analyse and compare ten published SSA weighting schemes based on a simulated virtual screening experiment. The analysis showed the most effective weighting scheme to be the R4 equation which was a part of document-based weighting schemes. A second experiment was carried out to investigate the application of GA-based weighting scheme for the SSA in comparison to an experiment using the R4 weighting scheme. The GA algorithm is simple in concept focusing purely on suitable weight generation and effective in operation. The findings show that the GA-based SSA is superior to the R4-based SSA, both in terms of active compound retrieval rate and predictive performance. A third experiment investigated the genetic application via a GP-based SSA. Rigorous experiment results showed that the GP was found to be superior to the existing SSA weighting schemes. In general, however, the GP-based SSA was found to be less effective than the GA-based SSA. A final experimented is described in this thesis which sought to explore the feasibility of data fusion on both the GA and GP. It is a method producing a final ranking list from multiple sets of ranking lists, based on several fusion rules. The results indicate that data fusion is a good method to boost GA-and GP-based SSA searching. The RKP rule was considered the most effective fusion rule.
Coding of navigational affordances in the human visual system

Significance As we move about the world, we use vision to determine where we can go in our local environment and where our path is blocked. Despite the ubiquity of this problem, little is known about how it is solved by the brain. Here we show that a specific region in the human visual system, known as the occipital place area, automatically encodes the structure of navigable space in visual scenes, thus providing evidence for a bottom-up visual mechanism for perceiving potential paths for movement in one’s immediate surroundings. These findings are consistent with classic theoretical work predicting that sensory systems are optimized for processing environmental features that afford ecologically relevant behaviors, including the fundamental behavior of navigation. A central component of spatial navigation is determining where one can and cannot go in the immediate environment. We used fMRI to test the hypothesis that the human visual system solves this problem by automatically identifying the navigational affordances of the local scene. Multivoxel pattern analyses showed that a scene-selective region of dorsal occipitoparietal cortex, known as the occipital place area, represents pathways for movement in scenes in a manner that is tolerant to variability in other visual features. These effects were found in two experiments: One using tightly controlled artificial environments as stimuli, the other using a diverse set of complex, natural scenes. A reconstruction analysis demonstrated that the population codes of the occipital place area could be used to predict the affordances of novel scenes. Taken together, these results reveal a previously unknown mechanism for perceiving the affordance structure of navigable space.
Fast and Accurate Vanishing Point Detection and Its Application in Inverse Perspective Mapping of Structured Road

Fast and accurate visual scene understanding in autonomous vehicles is necessary but still very challenging. An autonomous vehicle must be taught to read the road like a human driver for better controlling the vehicle, so it is important to efficiently detect the road area and road markings. In this paper, we mainly focus on the vanishing point detection and its application in inverse perspective mapping (IPM) for road marking understanding. We first propose a fast and accurate vanishing point detection method for various types of roads, by adopting and improving Weber local descriptor to obtain salient representative texture and orientation information of the road area, and then voting for the dominant vanishing point with a simple line-voting scheme. Experimental results demonstrate that the proposed vanishing point detection approach gains a better performance than some state-of-the-art methods in terms of accuracy and computation time. Furthermore, we introduce the detected vanishing point into the IPM algorithm in the structured road environment, since some important calibration parameters can be automatically calculated by the vanishing point, especially on the rough road. Experiments also show that our proposed vanishing point-based IPM method is adaptive and accurate, which is conducive to the subsequent road marking detection and recognition.
Why Wait? Early Determinants of School Dropout in Preventive Pediatric Primary Care

Background To answer the question of what bio-psychosocial determinants in infancy, early and middle childhood, and adolescence predict school drop-out in young adulthood, we approached the complex process towards school dropout as a multidimensional, life-course phenomenon. The aim is to find signs of heightened risks of school dropout as early as possible which will eventually help public health workers in reducing these risks. Methods In a case-control design, we used data from both the Preventive Pediatric Primary Care (PPPC) files (that contain information from birth onwards) and additional questionnaires filled out by 529 youngsters, aged 18–23 years, and living in the South-east of the Netherlands. We first conducted univariate logistic regression analyses with school-dropout as the dependent variable. Backward and forward stepwise analyses with the significant variables were done with variables pertaining to the 0 to 4 year period. Remaining significant variables were forced into the next model and subsequently variables pertaining to respectively the 4 to 8, 8 to 12 and 12 to 16 year period were introduced in a stepwise analysis. All analyses were cross-validated in an exploratory and confirmatory random half of the sample. Results One parent families and families with a non-Western background less often attended the health examinations of the PPPC and such less attendance was related to school dropout. The birth of a sibling (OR 0.63, 95% CI 0.43–0.93) in infancy and self-efficacy (OR 0.53, 95% CI 0.38–0.74) in adolescence decreased the odds of school dropout; externalizing behavior (OR 2.81, 95% CI 1.53–5.14) in middle childhood and (sickness) absence (OR 5.62, 95% CI 2.18–14.52) in adolescence increased the risks. Conclusion To prevent school dropout, PPPC professionals should not wait until imminent dropout, but should identify and tackle risk factors as early as possible and actively approach youngsters who withdraw from public health care.
A Fresh Perspective on a Familiar Problem

Background: Disparities in the presentation of knee osteoarthritis (OA) and in the utilization of treatment across sex, racial, and ethnic groups in the United States are well documented. Objectives: We used a Markov model to calculate lifetime costs of knee OA treatment. We then used the model results to compute costs of disparities in treatment by race, ethnicity, sex, and socioeconomic status. Research Design: We used the literature to construct a Markov Model of knee OA and publicly available data to create the model parameters and patient populations of interest. An expert panel of physicians, who treated a large number of patients with knee OA, constructed treatment pathways. Direct costs were based on the literature and indirect costs were derived from the Medical Expenditure Panel Survey. Results: We found that failing to obtain effective treatment increased costs and limited benefits for all groups. Delaying treatment imposed a greater cost across all groups and decreased benefits. Lost income because of lower labor market productivity comprised a substantial proportion of the lifetime costs of knee OA. Population simulations demonstrated that as the diversity of the US population increases, the societal costs of racial and ethnic disparities in treatment utilization for knee OA will increase. Conclusions: Our results show that disparities in treatment of knee OA are costly. All stakeholders involved in treatment decisions for knee OA patients should consider costs associated with delaying and forgoing treatment, especially for disadvantaged populations. Such decisions may lead to higher costs and worse health outcomes.
Effect of Uveal Melanocytes on Choroidal Morphology in Rhesus Macaques and Humans on Enhanced-Depth Imaging Optical Coherence Tomography

Purpose To compare cross-sectional choroidal morphology in rhesus macaque and human eyes using enhanced-depth imaging optical coherence tomography (EDI-OCT) and histologic analysis. Methods Enhanced-depth imaging–OCT images from 25 rhesus macaque and 30 human eyes were evaluated for choriocapillaris and choroidal–scleral junction (CSJ) visibility in the central macula based on OCT reflectivity profiles, and compared with age-matched histologic sections. Semiautomated segmentation of the choriocapillaris and CSJ was used to measure choriocapillary and choroidal thickness, respectively. Multivariate regression was performed to determine the association of age, refractive error, and race with choriocapillaris and CSJ visibility. Results Rhesus macaques exhibit a distinct hyporeflective choriocapillaris layer on EDI-OCT, while the CSJ cannot be visualized. In contrast, humans show variable reflectivities of the choriocapillaris, with a distinct CSJ seen in many subjects. Histologic sections demonstrate large, darkly pigmented melanocytes that are densely distributed in the macaque choroid, while melanocytes in humans are smaller, less pigmented, and variably distributed. Optical coherence tomography reflectivity patterns of the choroid appear to correspond to the density, size, and pigmentation of choroidal melanocytes. Mean choriocapillary thickness was similar between the two species (19.3 ± 3.4 vs. 19.8 ± 3.4 μm, P = 0.615), but choroidal thickness may be lower in macaques than in humans (191.2 ± 43.0 vs. 266.8 ± 78.0 μm, P < 0.001). Racial differences in uveal pigmentation also appear to affect the visibility of the choriocapillaris and CSJ on EDI-OCT. Conclusions Pigmented uveal melanocytes affect choroidal morphology on EDI-OCT in rhesus macaque and human eyes. Racial differences in pigmentation may affect choriocapillaris and CSJ visibility, and may influence the accuracy of choroidal thickness measurements.
Sleep Continuity, Architecture and Quality Among Treatment-Seeking Cannabis Users: An In-Home, Unattended Polysomnographic Study

The objective of the study was to describe self-report and objectively measured sleep characteristics of adult treatment-seeking cannabis users. Study participants (n = 87) were adults who were screened for a 12-week outpatient cannabis treatment research program in Baltimore, MD. Participants completed objective and self-report measures of sleep quality. Data were analyzed for the sample overall and after stratifying by sex (54 men, 33 women). Participants were primarily urban, socioeconomically disadvantaged African Americans. Participants were frequent, heavy cannabis users; among a subset of participants assessed, 76.7% used cannabis on the day/night of the assessment. Participants had low rates of other substance abuse and of psychiatric comorbidities. Polysomnography indicated 19.5% of participants received the recommended 7 to 9 hr of sleep, with women averaging more sleep than men. One third (31.0%) had sleep latencies >30 min, one half spent >30 min awake after sleep onset, and more than one half of the sample (55.2%) had sleep efficiency scores of <85%. Most participants met criteria for subthreshold (36.8%) or clinical insomnia (25.3%) on the Insomnia Severity Index, 77.0% had scores of >5 on the Pittsburgh Sleep Quality Index. Most had average scores on the Dysfunctional Beliefs and Attitudes About Sleep (DBAS) questionnaire (M = 51.1, SD = 18.8) that were higher than average among clinical insomnia patients. Women had higher DBAS scores than men. Most participants exhibited characteristics of disordered sleep, and sex differences were observed on polysomnography and self-report measures. Findings extend prior research concerning the association between cannabis use and disordered sleep. Data presented in this article come from Clinical Trial NCT01685073.
Convergence Through a Weak Consistency Model: Timed Causal Consistency

Given a distributed system with several shared objects and many processes concurrently updating and reading them, it is convenient that the system achieves convergence on the value of these objects. Such property can be guaranteed depending on the consistency model being employed. Causal Consistency is a weak consistency model that is easy and cheap to implement. However, due to the lack of real-time considerations, this model cannot offer convergence. A solution for overcoming that problem is to include time aspects within the framework of the model. This is the aim of Timed Causal Consistency.
Automatic Detection and Query of Wireless Spectrum Events from Streaming Data

Several alternatives for more efficient spectrum management have been proposed over the last decade, resulting in new techniques for automatic wideband spectrum sensing. However, while spectrum sensing technology is important, understanding, using and taking actions on this data for better spectrum and network resource management is at least equally important. In this paper, we propose a system that is able to automatically detect wireless spectrum events from streaming spectrum sensing data, and enables the consumption of the events as they are produced, as a statistical report or on a per-query basis. The proposed system is referred to as spectrum streamer and is wireless technology agnostic, scalable, able to deliver actionable information to humans and machines and also enables application development by custom querying of the detected events.
SAP HANA - The Evolution of an In-Memory DBMS from Pure OLAP Processing Towards Mixed Workloads

The journey of SAP HANA started as an in-memory appliance for complex, analytical applications. The success of the system quickly motivated SAP to broaden the scope from the OLAP workloads the system was initially architected for to also handle transactional workloads, in particular to support its Business Suite flagship product. In this paper, we highlight some of the core design changes to evolve an in-memory column store system towards handling OLTP workloads. We also discuss the challenges of running mixed workloads with low-latency OLTP queries and complex analytical queries in the context of the same database management system and give an outlook on the future database interaction patterns of modern business applications we see emerging currently.
Dendritic spikes in hippocampal granule cells are necessary for long-term potentiation at the perforant path synapse

Long-term potentiation (LTP) of synaptic responses is essential for hippocampal memory function. Perforant-path (PP) synapses on hippocampal granule cells (GCs) contribute to the formation of associative memories, which are considered the cellular correlates of memory engrams. However, the mechanisms of LTP at these synapses are not well understood. Due to sparse firing activity and the voltage attenuation in their dendrites, it remains unclear how associative LTP at distal synapses occurs. Here we show that NMDA receptor-dependent LTP can be induced at PP-GC synapses without backpropagating action potentials (bAPs) in acute rat brain slices. Dendritic recordings reveal substantial attenuation of bAPs as well as local dendritic Na + ‐spike generation during PP-GC input. Inhibition of Na+ ‐spikes impairs LTP suggesting that LTP at PP-GC synapse requires local Na + ‐spikes. Thus, dendritic spikes are essential for LTP induction at PP-GC synapse and may constitute a key cellular mechanism for memory formation in the dentate gyrus.
CFD-CAA Coupled Calculations of a Tandem Cylinder Configuration to Assess Facility Installation Effects

This paper presents a numerical assessment of acoustic installation effects in the tandem cylinder (TC) experiments conducted in the NASA Langley Quiet Flow Facility (QFF), an open-jet, anechoic wind tunnel. Calculations that couple the Computational Fluid Dynamics (CFD) and Computational Aeroacoustics (CAA) of the TC configuration within the QFF are conducted using the CFD simulation results previously obtained at NASA LaRC. The coupled simulations enable the assessment of installation effects associated with several specific features in the QFF facility that may have impacted the measured acoustic signature during the experiment. The CFD-CAA coupling is based on CFD data along a suitably chosen surface, and employs a technique that was recently improved to account for installed configurations involving acoustic backscatter into the CFD domain. First, a CFD-CAA calculation is conducted for an isolated TC configuration to assess the coupling approach, as well as to generate a reference solution for subsequent assessments of QFF installation effects. Direct comparisons between the CFD-CAA calculations associated with the various installed configurations allow the assessment of the effects of each component (nozzle, collector, etc.) or feature (confined vs. free jet flow, etc.) characterizing the NASA LaRC QFF facility.
Development of a subject-oriented reference process model for the telecommunications industry

Generally the usage of reference models can be structured top-down or bottom-up. The practical need of agile change and flexible organizational implementation requires a consistent mapping to an operational level. In this context, well-established reference process models are typically structured top-down. The subject-oriented Business Process Management (sBPM) offers a modeling concept that is structured bottom-up and concentrates on the process actors on an operational level. This paper applies sBPM to the enhanced Telecom Operations Map (eTOM), a well-accepted reference process model in the telecommunications industry. The resulting design artifact is a concrete example for a combination of a bottom-up and top-down developed reference model. The results are evaluated and confirmed in practical context through the involvement of the industry body TM Forum.
Inhibition of Zika Virus Replication by Silvestrol

The Zika virus (ZIKV) outbreak in 2016 in South America with specific pathogenic outcomes highlighted the need for new antiviral substances with broad-spectrum activities to react quickly to unexpected outbreaks of emerging viral pathogens. Very recently, the natural compound silvestrol isolated from the plant Aglaia foveolata was found to have very potent antiviral effects against the (−)-strand RNA-virus Ebola virus as well as against Corona- and Picornaviruses with a (+)-strand RNA-genome. This antiviral activity is based on the impaired translation of viral RNA by the inhibition of the DEAD-box RNA helicase eukaryotic initiation factor-4A (eIF4A) which is required to unwind structured 5´-untranslated regions (5′-UTRs) of several proto-oncogenes and thereby facilitate their translation. Zika virus is a flavivirus with a positive-stranded RNA-genome harboring a 5′-capped UTR with distinct secondary structure elements. Therefore, we investigated the effects of silvestrol on ZIKV replication in A549 cells and primary human hepatocytes. Two different ZIKV strains were used. In both infected A549 cells and primary human hepatocytes, silvestrol has the potential to exert a significant inhibition of ZIKV replication for both analyzed strains, even though the ancestor strain from Uganda is less sensitive to silvestrol. Our data might contribute to identify host factors involved in the control of ZIKV infection and help to develop antiviral concepts that can be used to treat a variety of viral infections without the risk of resistances because a host protein is targeted.
A Parametric Study on Friction Instabilities in Mechanical Face Seals

ABSTRACT The present article aims to analyze and evaluate how dynamic parameter design influences the behavior of mechanical face seals and improves their performance by detecting undesirable phenomena like stick–slip and ringing. Those phenomena occur in situations of boundary lubrication. A new lumped parameter model is proposed to study mechanical face seals used in automotive cooling water pumps in order to examine how dynamic parameters such as mass, moment of inertia, and stiffness are involved in stick–slip phenomena. The aim of this work is to provide a practical design tool to predict stick–slip conditions and to choose the optimal mechanical specifications. Numerical simulations demonstrate how the critical service conditions vary with design parameters and permit tabulation of the results.
A Negotiation-Based TDMA Scheduling with Consecutive Slots Assignment for Wireless Sensor Networks

TDMA protocols are recognized to save energy consumption by avoiding unnecessary idle listening and communication collision. As sensor nodes are usually equipped with limited resource supply, they are thus desirable to improve network capacity and energy efficiency by adopting TDMA scheduling for wireless sensor networks (WSNs). This paper proposes a TDMA scheduling approach, which reuses time slots among sensor nodes, for WSNs. Specifically, with the idea of consecutive slots assignment, our approach can reduce both the time and energy cost of establishing nodes' schedule. Furthermore, the energy of node's switching is also reduced. To avoid the transmission of a node's result interference to all irrelevant receivers within its interference range, we develop a slot negotiation mechanism for slot assignment. We perform extensive simulations in NS-2 to evaluate our proposed approach. The results show that our approach outperforms existing TDMA scheduling in terms of time and energy overhead.