Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Emission Effects Related to Drivers’ Compliance Rates for Cooperative Vehicle-Infrastructure System at Signalized Intersections

Unknown remaining time of signal phase at a signalized intersection generally results in extra accelerations and decelerations that increase variations of operating conditions and thus emissions. A cooperative vehicle-infrastructure system can reduce unnecessary speed changes by establishing communications between vehicles and the signal infrastructure. However, the environmental benefits largely depend on drivers’ compliance behaviors. To quantify the effects of drivers’ compliance rates on emissions, this study applied VISSIM 5.20 (Planung Transport Verkehr AG, Karlsruhe, Germany) to develop a simulation model for a signalized intersection, in which light duty vehicles were equipped with a cooperative vehicle-infrastructure system. A vehicle-specific power (VSP)-based model was used to estimate emissions. Based on simulation data, the effects of different compliance rates on VSP distributions, emission factors, and total emissions were analyzed. The results show the higher compliance rate decreases the proportion of VSP bin = 0, which means that the frequencies of braking and idling were lower and light duty vehicles ran more smoothly at the intersection if more light duty vehicles complied with the cooperative vehicle-infrastructure system, and emission factors for light duty vehicles decreased significantly as the compliance rate increased. The case study shows higher total emission reductions were observed with higher compliance rate for all of CO2, NOx, HC, and CO emissions. CO2 was reduced most significantly, decreased by 16% and 22% with compliance rates of 0.3 and 0.7, respectively.
An Exploration of Some Pitfalls of Thematic Map Assessment Using the New Map Tools Resource

A variety of metrics are commonly employed by map producers and users to assess and compare thematic maps’ quality, but their use and interpretation is inconsistent. This problem is exacerbated by a shortage of tools to allow easy calculation and comparison of metrics from different maps or as a map’s legend is changed. In this paper, we introduce a new website and a collection of R functions to facilitate map assessment. We apply these tools to illustrate some pitfalls of error metrics and point out existing and newly developed solutions to them. Some of these problems have been previously noted, but all of them are under-appreciated and persist in published literature. We show that binary and categorical metrics, including information about true-negative classifications, are inflated for rare categories, and more robust alternatives should be chosen. Most metrics are useful to compare maps only if their legends are identical. We also demonstrate that combining land-cover classes has the often-neglected consequence of apparent improvement, particularly if the combined classes are easily confused (e.g., different forest types). However, we show that the average mutual information (AMI) of a map is relatively robust to combining classes, and reflects the information that is lost in this process; we also introduce a modified AMI metric that credits only correct classifications. Finally, we introduce a method of evaluating statistical differences in the information content of competing maps, and show that this method is an improvement over other methods in more common use. We end with a series of recommendations for the meaningful use of accuracy metrics by map users and producers.
Event-Based Vision Meets Deep Learning on Steering Prediction for Self-Driving Cars

Event cameras are bio-inspired vision sensors that naturally capture the dynamics of a scene, filtering out redundant information. This paper presents a deep neural network approach that unlocks the potential of event cameras on a challenging motion-estimation task: prediction of a vehicle's steering angle. To make the best out of this sensor-algorithm combination, we adapt state-of-the-art convolutional architectures to the output of event sensors and extensively evaluate the performance of our approach on a publicly available large scale event-camera dataset (~1000 km). We present qualitative and quantitative explanations of why event cameras allow robust steering prediction even in cases where traditional cameras fail, e.g. challenging illumination conditions and fast motion. Finally, we demonstrate the advantages of leveraging transfer learning from traditional to event-based vision, and show that our approach outperforms state-of-the-art algorithms based on standard cameras.
NanoSIMS imaging: an approach for visualizing and quantifying lipids in cells and tissues

Over the past few decades, several approaches have been used to image lipids in cells and tissues, but most have limited spatial resolution and sensitivity. Here, we discuss a relatively new approach, nanoscale secondary ion mass spectrometry imaging, that makes it possible to visualize lipids in cells and tissues in a quantitative fashion and with high spatial resolution and high sensitivity.
Mitotic Recombination and Genetic Changes inSaccharomyces cerevisiae during Wine Fermentation

ABSTRACT Natural strains of Saccharomyces cerevisiae are prototrophic homothallic yeasts that sporulate poorly, are often heterozygous, and may be aneuploid. This genomic constitution may confer selective advantages in some environments. Different mechanisms of recombination, such as meiosis or mitotic rearrangement of chromosomes, have been proposed for wine strains. We studied the stability of the URA3 locus of a URA3/ura3 wine yeast in consecutive grape must fermentations. ura3/ura3homozygotes were detected at a rate of 1 × 10−5 to 3 × 10−5 per generation, and mitotic rearrangements for chromosomes VIII and XII appeared after 30 mitotic divisions. We used the karyotype as a meiotic marker and determined that sporulation was not involved in this process. Thus, we propose a hypothesis for the genome changes in wine yeasts during vinification. This putative mechanism involves mitotic recombination between homologous sequences and does not necessarily imply meiosis.
Comparison of effects of amphotericin B deoxycholate infused over 4 or 24 hours: randomised controlled trial

Abstract Objective: To test the hypothesis that amphotericin B deoxycholate is less toxic when given by continuous infusion than by conventional rapid infusion. Design: Randomised, controlled, non-blinded, single centre study. Setting: University hospital providing tertiary clinical care. Patients: 80 mostly neutropenic patients with refractory fever and suspected or proved invasive fungal infections. Intervention: Patients were randomised to receive 0.97 mg/kg amphotericin B by continuous infusion over 24 hours or 0.95 mg/kg by rapid infusion over four hours. Main outcome measures: Patients were evaluated for side effects related to infusion, nephrotoxicity, and mortality up to three months after treatment. Analysis was on an intention to treat basis. Results: Patients in the continuous infusion group had fewer side effects and significantly reduced nephrotoxicity than those in the rapid infusion group. Overall mortality was higher during treatment and after three months' follow up in the rapid infusion than in the continuous infusion group. Conclusion: Continuous infusions of amphotericin B reduce nephrotoxicity and side effects related to infusion without increasing mortality
A Pleliminary Study on Human Chewing Action Counter

This paper deals with a novel method which can estimate the occurrence number of human chewing actions by the help of image processing technique. At first, the user's mouth is recognized by the help of Haar cascade classifiers for human face and mouth. And then, this mouth image is processed with our proposed algorithm which can counter the occurrence number of human chewing action and can also reset the counter by confirming the mouth openness for new meal consumption. The experimental results show that it can be applied to improve chewing habits for kids.
Visualizing information on a sphere

We describe a method for the visualization of information units on spherical domains which is employed in the banking industry for risk analysis, stock prediction and other tasks. The system is based on a quantification of the similarity of related objects that governs the parameters of a mass-spring system. Unlike existing approaches we initialize all information units onto the inner surface of two concentric spheres and attach them with springs to the outer sphere. Since the spring stiffnesses correspond to the computed similarity measures, the system converges into an energy minimum which reveals multidimensional relations and adjacencies in terms of spatial neighborhoods. Depending on the application scenario our approach supports different topological arrangements of related objects. In order to cope with large data sets we propose a blobby clustering mechanism that enables encapsulation of similar objects by implicit shapes. In addition, we implemented various interaction techniques allowing semantic analysis of the underlying data sets. Our prototype system IVORY is written in Java, and its versatility is illustrated by an example from financial service providers.
The relationship of gross upper and lower limb motor competence to measures of health and fitness in adolescents aged 13–14 years

Introduction Motor competence (MC) is an important factor in the development of health and fitness in adolescence. Aims This cross-sectional study aims to explore the distribution of MC across school students aged 13–14 years old and the extent of the relationship of MC to measures of health and fitness across genders. Methods A total of 718 participants were tested from three different schools in the UK, 311 girls and 407 boys (aged 13–14 years), pairwise deletion for correlation variables reduced this to 555 (245 girls, 310 boys). Assessments consisted of body mass index, aerobic capacity, anaerobic power, and upper limb and lower limb MC. The distribution of MC and the strength of the relationships between MC and health/fitness measures were explored. Results Girls performed lower for MC and health/fitness measures compared with boys. Both measures of MC showed a normal distribution and a significant linear relationship of MC to all health and fitness measures for boys, girls and combined genders. A stronger relationship was reported for upper limb MC and aerobic capacity when compared with lower limb MC and aerobic capacity in boys (t=−2.21, degrees of freedom=307, P=0.03, 95% CI −0.253 to –0.011). Conclusion Normally distributed measures of upper and lower limb MC are linearly related to health and fitness measures in adolescents in a UK sample. Trial registration number NCT02517333.
PSK/QAM modulation recognition by convolutional neural network

In this paper, we propose an algorithm to extract a one-dimensional (1D) non-intuitive feature of the received signal for automatic modulation classification (AMC). This designed phase-related feature which can reflect the inherent information about modulation patterns has not been utilized before. In order to learn the intrinsic message of these extracted features and recognize their corresponding modulation types, we adopt convolutional neural network (CNN) as classifier. Furthermore, we apply CNN to some conventional features as classifier for performance comparison. Empirically, the proposed 1D feature may contains more information of the original signal compared with some conventional features. Simulation results also verify the superiority of the proposed system whose classification accuracy is beyond 99% at 0 dB.
Overnight T-wave alternans in sleep apnea patients

Sleep apnea (SA) is linked to cardiovascular complications and to an increased risk of sudden cardiac death. Microvolt T-wave alternans (TWA) is a noninvasive electrocardiographic (ECG) index of cardiovascular risk; its rate of occurrence in SA patients remains unknown. Thus, this study investigated the occurrence of TWA in SA patients during night. To this aim, overnight ECG recordings of 16 SA patients were analyzed for TWA identification by means of our heart rate adaptive match filter. Results indicate that overnight TWA was characterized by a low mean amplitude (mean TWA: 6±3 μV). However, higher-amplitude transient TWA episodes (max TWA: 29±21 μV) occurred overnight, sometimes when patients were awake (max TWA: 33±18 μV; 56% of cases) and sometimes when patients were sleeping (max TWA: 24±23 μV; 44% of cases with 13%, 19%, 6% and 6% during sleep stage 1, 2, 3 and 4, respectively). In only 3 subjects (19%) TWA peaks occurred during an SA episode: during obstructive apnea with arousal in two cases (max TWA of 7 μV and 17 μV, during stages 1 and 2, respectively) and during hypoapnea with arousal in one case (max TWA of 6 μV while awake). Thus, SA patients show significant transient overnight TWA episodes, not necessarily occurring during a SA episode.
Personalized location recommendation for location-based social networks

With the development of social networks and wireless communication technology, location-based social networks (LBSNs) are developing rapidly. Personalized location service in location-based social networks can provide users with a new point-of-interest (POI). Compared to traditional recommendation, point-of-interest recommendation integrates the social network with the location that connects online users and physical places. In current studies, user preference, social influence and geographical influence are mostly taken into consideration to recommend satisfying point-of-interests to users. Although geographical context is significant, most articles only consider spatial properties of geographical influence. In addition to spatial properties of geographical influence, we put a special emphasis on sequence properties of that to exploit implicit dependencies between POIs. We model spatial properties using a kernel density estimation approach to generate a unique distribution for each user. Furthermore, user preference, social influence, and sequence properties of geographical influence are integrated into a random walk model on graph. Finally, we conduct a comprehensive performance evaluation over two real-world datasets collected from Brightkite and Gowalla. Experimental results show that the proposed recommendation approach performs better than other methods.
Autophagy inhibition enhances radiosensitivity of Eca-109 cells via the mitochondrial apoptosis pathway

Autophagy inhibition is crucial for the improvement of the efficacy of radiotherapy in cancer. The aim of the present study was to determine the potential therapeutic value of autophagy and its correlation with mitochondria in human esophageal carcinoma cells following treatment with ionizing radiation (IR). Autophagy in Eca-109 cells was induced under poor nutrient conditions. The formation of autophagic vacuoles was monitored using electron microscopy. In addition, cell apoptosis after IR and mitochondrial membrane potential (MMP) were analyzed by flow cytometry. LC3, beclin-1, cytochrome c and apoptosis-related proteins were assayed by western blotting. A nude mouse xenograft model was also employed to verify the biological effects and mechanisms underlying autophagy in vivo. The formed autophagic vesicles and increased LC3 II/LC3 I ratio indicated marked induction of autophagy by Earle's balanced salt solution (EBSS) in Eca-109 cells. 3-Methyladenine or LY294002 significantly antagonized EBSS-induced autophagy and increased apoptosis of irradiated cells, suggesting that autophagy inhibition conferred radiosensitivity in vitro. Notably, IR induced prominent release of cytochrome c and Bax activation, and decreased Bcl-2 and MMP expression in Eca-109 cells under poor nutrient conditions. Of note, these changes were more prominent following pretreatment with autophagy inhibitors. In vivo, IR treatment mildly delayed tumor growth, but the radiotherapeutic effect was improved significantly by abolishing autophagy. Furthermore, mitochondrial signaling was investigated in the Eca-109 xenograft nude mice model, and the results were consistent with the in vitro study. Therefore, the mitochondrial pathway may be associated with improvement of radiosensitivity in Eca-109 cells.
Optimal Scheduling of VMs in Queueing Cloud Computing Systems With a Heterogeneous Workload

This paper studies the delay-optimal virtual machine (VM) scheduling problem in cloud computing systems, which have a constant amount of infrastructure resources, such as CPU, memory, and storage in the resource pool. The cloud computing system provides VMs as services to users. Cloud users request various types of VMs randomly over time, and the requested VM-hosting durations vary vastly. We first adopt a queuing model for the heterogeneous and dynamic workloads. Then, we formulate the VM scheduling in such a queuing cloud computing system as a decision-making process, where the decision variable is the vector of VM configurations and the optimization objective is the delay performance in terms of average job completion time. A low-complexity online scheme that combines the shortest-job-first (SJF) buffering and min–min best fit (MMBF) scheduling algorithms, i.e., SJF-MMBF, is proposed to determine the solutions. Another scheme that combines the SJF buffering and reinforcement learning (RL)-based scheduling algorithms, i.e., SJF-RL, is further proposed to avoid the potential of job starvation in SJF-MMBF. The simulation results show that SJF-RL achieves its goal of delay-optimal scheduling of VMs by provisioning a low delay at various job arrival rates for various shapes of job length distributions. The simulation results also illustrate that although SJF-MMBF is sub-delay-optimal in a heavy-loaded and highly dynamic environment, it is efficient in throughput performance in terms of the average job hosting rate provisioning.
Brain size of the lion ( Panthera leo ) and the tiger ( P. tigris ): Implications for intrageneric phylogeny, intraspecific differences, and the effects of captivity

Intraspecific encephalization of the lion and the tiger is investigated for the first time using a very large sample. Using cranial volume as a measure of brain size, the tiger has a larger brain relative to greatest length of skull than the lion, the leopard and the jaguar. The Asian lion has a relatively much smaller brain compared with those of sub-Saharan lions, between which there are few differences. The Balinese and Javan tigers had relatively larger brains compared with those of Malayan and Sumatran tigers, even although these four putative subspecies occupy adjacent ranges in south-eastern Asia. Differences in brain size do not appear to correlate with any known differences in behaviour and ecology and, therefore, may reflect only chance differences in intrageneric and intraspecific phylogeny. However, captive-bred big cats generally have a reduced brain size compared with that of wild animals, so that an animal's life history and living conditions may affect brain size and, hence, functional or environmental explanations should be considered when linking brain size differences to intraspecific phylogenies. (C) 2009 The Linnean Society of London, Biological Journal of the Linnean Society, 2009, 98, 85-93.
AGRICULTURE, METEOROLOGY AND WATER QUALITY IN IRELAND: A REGIONAL EVALUATION OF PRESSURES AND PATHWAYS OF NUTRIENT LOSS TO WATER

Abstract:The main environmental impact of Irish agriculture on surface and ground water quality is the potential transfer of nutrients to water. Soil water dynamics mediate the transport of nutrients to water, and these dynamics in turn depend on agro-meteorological conditions, which show large variations between regions, seasons and years. In this paper we quantify and map the spatio-temporal variability of agro-meteorological factors that control nutrient pressures and pathways of nutrient loss. Subsequently, we evaluate their impact on the water quality of Irish rivers. For nitrogen, pressure and pathways factors coincide in eastern and southern areas, which is reflected in higher nitrate levels of the rivers in these regions. For phosphorus, pathway factors are most pronounced in north-western parts of the country. In south-eastern parts, high pressure factors result in reduced biological water quality. These regional differences require that farm practices be customised to reflect the local risk of nutrient loss to water. Where pathways for phosphorus loss are present almost year-round—as is the case in most of the north-western part of the country—build-up of pressures should be prevented, or ameliorated where already high. In south-eastern areas, spatio-temporal coincidence of nutrient pressures and pathways should be prevented, which poses challenges to grassland management.
Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses

Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE) but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1), down-regulation in NOE but rescue in RSE (pattern 2), up-regulation in both restraint stress followed by a saline injection (RSS) and NOE, and further amplification in RSE (pattern 3), and up-regulation in RSS but reduction in both NOE and RSE (pattern 4). We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs) to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA) signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses.