Miracle-dz/UniFAR-FTUs huggingface dataset:
Routing Service Quality -- Local Driver Behavior Versus Routing Services

Mobile location-based services is a very successful class of services that are being used frequently by users with GPS-enabled mobile devices such as smartphones. This paper presents a study of how to exploit GPS trajectory data, which is available in increasing volumes, for the assessment of the quality of one kind of location-based service, namely routing services. Specifically, the paper presents a framework that enables the comparison of the routes provided by routing services with the actual driving behaviors of local drivers. Comparisons include route length, travel time, and also route popularity, which are enabled by common driving behaviors found in available trajectory data. The ability to evaluate the quality of routing services enables service providers to improve the quality of their services and enables users to identify the services that best serve their needs. The paper covers experiments with real vehicle trajectory data and an existing online navigation service. It is found that the availability of information about previous trips enables better prediction of route travel time and makes it possible to provide the users with more popular routes than does a conventional navigation service.
Combining Local and Global KNN With Cotraining

Semi-supervised learning is a machine learning paradigm in which the induced hypothesis is improved by taking advantage of unlabeled data. It is particularly useful when labeled data is scarce. Cotraining is a widely adopted semi-supervised approach that assumes availability of two views of the training data a restrictive assumption for most real world tasks. In this paper, we propose a one-view Cotraining approach that combines two different k-Nearest Neighbors (KNN) strategies referred to as global and local k-NN. In global KNN, the nearest neighbors selected to classify a new instance are given by the training examples which include this instance as one of their own k-nearest neighbors. In local KNN, on the other hand, the neighborhood considered when classifying a new instance is computed with the traditional KNN approach. We carried out experiments showing that a combination of these strategies significantly improves the classification accuracy in Cotraining, particularly when one single view of training data is available. We also introduce an optimized algorithm to cope with time complexity of computing the global KNN, which enables tackling real classification problems.
How Semantic Knowledge can Enhance the Access to PA Online Services

Current e-government initiatives are offering a huge amount of information about available services, which tends to overload citizens, who are often "lost". Intelligent Web-based portals represent a possible solution to this problem, by providing an effective and user-friendly access to online information and service descriptions. In particular, this paper proposes an approach based on formal ontologies and shows how they can provide a great enhancement in this direction. Formal semantic knowledge, in fact, enables the exploitation of reasoning mechanisms to understand users goals and provide them with information and services satisfying their needs. The proposed approach has been tested on a set of services provided by a local Italian Public Administration and results are encouraging.
08 / 6302 QUANTIFYING THE LANDING REACTION OF COCKROACHES

Planetary exploration missions include an entry-descent-landing phase, where the spacecraft descends on a relatively steep trajectory to the surface. In order to minimize the loads during landing, a deceleration system is employed, consisting essentially of some or a combination of parachutes, retrorockets and airbags. Due to the communication round-trip delay time between spacecraft and ground control, external supervision of the descent is limited. As a consequence, a landing device is desired that can autonomously stabilize the descent and guide the spacecraft to a safe landing place. In the research field of unmanned autonomous vehicles, animal models have become intensively studied models for potential technological transfer. Inspiration is drawn from various aspects such as neuronal control, aerodynamics, material properties, and actuators. Studying the neuronal control (biocybernetics) of insect flight is appealing for a number of reasons. First, in insects neurons can be addressed individually and hence, their function can be well determined. Secondly, flight control is realized in a fly-by-wire manner: Sensory data is acquired and processed in a way that only one individual steering signal for each flight situation is generated and sent downstream to the motor control. From this single signal, the appropriate motor reactions are generated. The present study aims at a 'technological transfer' of the neuronal architecture involved in triggering the landing reaction of steeply descending cockroaches. Cockroaches obtain flying capacities of robustly designed wings but are rarely observed to fly. From observations of scientists we know that cockroaches use their wings mostly in emergency situations, i.e. when forced to jump off elevated spots. Once air born, the cockroaches quickly deploy their wings and use them to glide to the ground, controlling their trajectory and choosing a landing site. This task requires fast reactions and quick decisional strategies. The cockroaches' flight system is therefore assumed to be tuned specifically towards fast landing and not to e.g. flying or takeoff. In consequence, it is assumed that the cockroach model – compared to other potentially flying insects – is simpler in its neuronal architecture and hence faster in its reaction and hence displays a potential model for a biomimetic transfer to an engineered landing system. Proposing universities and research centres are encouraged to include in their proposals relevant additional scientific information or a critical analysis of these assumptions. Cockroach behaviour Cockroaches are a popular model animal in the study field of dynamic legged locomotion, mostly because of their self-stabilizing …
A 57.9-to-68.3GHz 24.6mW frequency synthesizer with in-phase injection-coupled QVCO in 65nm CMOS

Under the influence of increasing demand for high-data-rate communication systems such as 60GHz band applications, the requirements of PLLs keep getting higher. In a mm-Wave direct-conversion transceiver, the quadrature LO signal generation is challenging. The conventional techniques to generate quadrature LO signals suffer from many problems. The method of using a divide-by-2 divider after a VCO with double LO frequency is popular in multi-GHz designs, but it is difficult to be realized at mm-Wave frequencies. Employing passive RC complex filters is another way to generate quadrature signals, but high power is required to compensate its loss. The conventional parallel-coupled QVCO seems to be a good choice for mm-Wave application. However, the approach suffers from poor phase noise. This work presents a fully integrated 57.9-to-68.3GHz frequency synthesizer, which employs an in-phase injection-coupled QVCO (IPIC-QVCO) to produce low-phase-noise quadrature signals with low power.
Conditioning and hyperalgesia in newborns exposed to repeated heel lances.

CONTEXT Hospitalized infants undergo repeated invasive procedures. It is unknown whether cumulative experiences with pain lead to anticipatory pain behaviors and hyperalgesia. OBJECTIVES To determine whether newborns who are born to mothers with diabetes and undergo repeated pain learn to anticipate pain and exhibit more pain during a painful procedure than normal infants. DESIGN, SETTING, AND PARTICIPANTS Prospective cohort study of 21 full-term newborns born to mothers with diabetes and 21 born to mothers with uneventful pregnancies, at a university teaching hospital between August 1999 and October 2000. Infants of diabetic mothers underwent repeated heel lances in the first 24 to 36 hours of life for monitoring of blood glucose concentrations. Pain responses of all infants undergoing a venipuncture on the dorsum of the hand to obtain blood for the newborn screening test after the first day of life were compared. In addition, from September through November 2001, 12 infants of diabetic mothers and 12 normal infants were compared for pain reactions to intramuscular vitamin K injection after birth. MAIN OUTCOME MEASURES Percentages of time observed grimacing and crying and visual analog scale (VAS) scores. RESULTS Raters were blinded to exposure group. Median baseline scores for grimacing, crying time, and VAS did not differ significantly between groups (P =.27, P =.32, and P =.32, respectively). Median scores (interquartile range) for grimacing during skin cleansing were higher in infants of diabetic mothers (22.2% [77.5%] vs 0% [15%]; P =.03). The VAS scores for both groups were zero, but the distribution of the scores was significantly different (86% of normal infants vs 52% of infants of diabetic mothers had scores of zero) (P =.04). During venipuncture, infants of diabetic mothers had higher median scores for grimacing (81.7% [32.5%] vs 40% [73.4%]; P =.01), VAS (69% [27.5%] vs 5% [60.5%]; P =.002), and crying (40.2% [77%] vs 0% [54.8%]; P =.03) compared with normal infants. There were no differences between groups on any pain measure in response to intramuscular injection. CONCLUSIONS Newborns who had diabetic mothers and were exposed to repeated heel lances in the first 24 to 36 hours of life learned to anticipate pain and exhibited more intense pain responses during venipuncture than normal infants.
The feature and neural mechanism of attentional bias among individuals with insecure attachment

: The attentional bias of individuals with insecure attachment refers to the fact that individuals with certain traits generate the attention of preference, attached or avoidant, responding to the attachment information, which allows individuals to form a specific cognitive mechanism dealing with the relationships with attachment figures: The avoidant individuals prefer defensive mechanisms and tend to shy away from the attachment information; the anxious individuals are in favor of exaggerated mechanisms, incline to exaggerate the threatening information, pay more attention to the threatening information and thus seek closeness to attachment figures actively. In the study of behaviors, the attentional bias of individuals with insecure attachment mainly reflects on emotional information, spacial allocation, pain sensation and working memory; about the EEG index, it mainly involves P1, N1 and LPP waves, which respectively represent automatic attention processing and controlled attention processing; on the part of brain network, it mainly includes limbic system which is responsible for the assessment of emotion and neural networks which are in charge of emotion management and represented by prefrontal cortex. Future studies should focus on ecological validity of stimuli, inspection on whether attachment system is activated or not, the relationship between automatic processing and controlled processing stages to attentional bias, the molecular genetic mechanism which results in the attentional bias of individuals with insecure attachment and the cross-culture study of attentional bias.
- 1-Implementation of B 2 B Electronic Commerce Systems with using the UML and XML

This paper presents a case study highlightring the best practices in designing and developing a B2B e-commerce system, We developed a remote order and delivery web-based system for an auto-parts manufacturing company. An initial scenario of the system was prototyped and then refined till the users and developers were satisfied. A formalized specification of the requirements employing Use-Case Diagrams and based on event flow was developed, and coded using XML to keep documentation simple and clear. Testing was performed at the component level allowing for feedback to previous steps when errors appeared. Digital signatures were employed for implementing security. The implementation approach preserved and promoted harmonious communication among the users and the developers. The end product enabled a reduction in the processing time of transactions, reduced processing cost, improved accuracy, effciency, reliability, and security of transmitted data; and at the same time our strategy shortened the System Development Life Cycle.
Comparative metagenomics reveals impact of contaminants on groundwater microbiomes

To understand patterns of geochemical cycling in pristine versus contaminated groundwater ecosystems, pristine shallow groundwater (FW301) and contaminated groundwater (FW106) samples from the Oak Ridge Integrated Field Research Center (OR-IFRC) were sequenced and compared to each other to determine phylogenetic and metabolic difference between the communities. Proteobacteria (e.g., Burkholderia, Pseudomonas) are the most abundant lineages in the pristine community, though a significant proportion ( >55%) of the community is composed of poorly characterized low abundance (individually <1%) lineages. The phylogenetic diversity of the pristine community contributed to a broader diversity of metabolic networks than the contaminated community. In addition, the pristine community encodes redundant and mostly complete geochemical cycles distributed over multiple lineages and appears capable of a wide range of metabolic activities. In contrast, many geochemical cycles in the contaminated community appear truncated or minimized due to decreased biodiversity and dominance by Rhodanobacter populations capable of surviving the combination of stresses at the site. These results indicate that the pristine site contains more robust and encodes more functional redundancy than the stressed community, which contributes to more efficient nutrient cycling and adaptability than the stressed community.
Refining cellular automata with routing constraints

A cellular automaton (CA) is an infinite array of cells, each containing the same automaton. The dynamics of a CA is distributed over the cells where each computes its next state as a function of the previous states of its neighborhood. Thus, the transmission of such states between neighbors is considered as feasible directly, in no time. When considering the implementation of a cellular automaton on a many-cores System-on-Chip (SoC), this state transmission is no longer abstract and instantaneous, but has to follow the interconnection medium of the SoC. It is usually a grid or a mesh matching the underlying topology of the CA but finite. In order to consider such constraints at a higher level, we propose a refinement of the classical model of CA where the topology is considered as the communication medium. If the state of a cell depends on its neighbors up to a certain distance, then a given state must be broadcasted to all its neighbors at the same distance, as they all require it to compute their next state. It means routing and duplicating the state in the topology. We study the routing patterns needed to efficiently implement such state broadcasting algorithm. We provide a solution by which each router can locally predict where to redirect the states to correctly and efficiently implement this broadcasting algorithm.
Attention-driven eye gaze and blinking for virtual humans

Gaze and blinking have recently been considered for application to social interactions among computer characters based on emotional states. In this sketch, we present improvements to a gaze controller in terms of both the contributions by the joints involved in the motion and also by a closer analysis of the role of blinking and blink synchronisation in the realism of the final animation. Unlike previous approaches, our controllers are driven by internal character states derived from, among other factors, a model of visual attention and short-term memory. Given a position to look at and taking into account internal state information such as an agent’s interests, motivation and memory, the gaze and blink controllers are charged with the responsibility of executing an appropriate gaze motion in an expressive manner.
Genetic analysis of structural brain connectivity using DICCCOL models of diffusion MRI in 522 twins

Genetic and environmental factors affect white matter connectivity in the normal brain, and they also influence diseases in which brain connectivity is altered. Little is known about genetic influences on brain connectivity, despite wide variations in the brain's neural pathways. Here we applied the “DICCCOL” framework to analyze structural connectivity, in 261 twin pairs (522 participants, mean age: 21.8 y ± 2.7SD). We encoded connectivity patterns by projecting the white matter (WM) bundles of all “DICCCOLs” as a tracemap (TM). Next we fitted an A/C/E structural equation model to estimate additive genetic (A), common environmental (C), and unique environmental/error (E) components of the observed variations in brain connectivity. We found 44 “heritable DICCCOLs” whose connectivity was genetically influenced (α2>1%); half of them showed significant heritability (α2>20%). Our analysis of genetic influences on WM structural connectivity suggests high heritability for some WM projection patterns, yielding new targets for genome-wide association studies.
Nitrous oxide exposure does not seem to be associated with increased mortality, stroke, and myocardial infarction: a non-randomized subgroup analysis of the General Anaesthesia compared with Local Anaesthesia for carotid surgery (GALA) trial.

BACKGROUND Nitrous oxide has been associated with increased vascular risk in the perioperative period. Here, we conducted a secondary analysis of the GALA trial to ascertain the impact of nitrous oxide on outcomes after carotid surgery under general anaesthesia (GA). METHODS One thousand seven hundred and seventy-three patients underwent GA, but 158 patients were excluded from this analysis as nitrous oxide use was unknown. The decision to use nitrous oxide was at the discretion of the anaesthetist and was not randomized. Six hundred and seventy-one patients received nitrous oxide and 944 patients did not. Logistic regression was used to analyse the same primary outcome as the original trial (risk of death, stroke, or myocardial infarction within 30 days of the operation). RESULTS Patients who received nitrous oxide were more likely to have had coronary artery disease, peripheral vascular disease, and atrial fibrillation (all P<0.05). Overall, there were 35 (5.2%) primary outcome events in patients receiving nitrous oxide compared with 44 (4.7%) in those who did not [relative risk 1.12, 95% confidence interval (CI: 0.73, 1.73); P=0.63]. The adjustment for the imbalanced baseline variables using logistic regression reduced the point estimate of harm for nitrous oxide [adjusted odds ratio 1.09, 95% CI (0.68, 1.74); P=0.73]. CONCLUSIONS Given the greater prevalence of vascular risk factors in the nitrous oxide group and the lack of any definite effect on the primary outcome measure, these data do not support a clinically meaningful adverse effect of nitrous oxide on our composite outcome in patients undergoing carotid surgery.
A NOVEL CONTROLLER BASED ON MULTI-RESOLUTION DECOMPOSITION USING WAVELET TRANSFORMS

In this paper, a Wavelet Controller analogous to a Propo rti nal-IntegralDerivative controller is proposed. The control stra tegy is based on the multi-resolution decomposition of error signal using Wavelet Transforms . The output from a system represents the cumulative effect of many underlying phenom a such as process dynamics, measurement noise, effects of external dis turbances etc., which manifest on different scales. The wavelet decomposition, which repr esents the error signal at different scales, enables us to compensate for these u ncertainties in the control design. The work presented here is a first step in this direction . Simulation results are shown to validate the control strategy.
Mechanotransduction in intervertebral discs

Mechanotransduction plays a critical role in intracellular functioning—it allows cells to translate external physical forces into internal biochemical activities, thereby affecting processes ranging from proliferation and apoptosis to gene expression and protein synthesis in a complex web of interactions and reactions. Accordingly, aberrant mechanotransduction can either lead to, or be a result of, a variety of diseases or degenerative states. In this review, we provide an overview of mechanotransduction in the context of intervertebral discs, with a focus on the latest methods of investigating mechanotransduction and the most recent findings regarding the means and effects of mechanotransduction in healthy and degenerative discs. We also provide some discussion of potential directions for future research and treatments.
Toward millions of laser pulses using pyrromethene and perylene doped xerogels

Signiﬁcant improvements have been obtained for solid-state dye lasers with doped xerogels. By using longitudinal pumping with a frequency-doubled Q -switched Nd: YAG laser, we obtained as much as 86% slope efﬁciency and 5 (cid:51) 10 5 pulses lifetime. Furthermore, newly prepared deoxygenated samples exhibited even greater lifetimes.
No-leak authentication by the Sherlock Holmes method

Abstract. We propose a class of authentication schemes that are literally zero-knowledge, as compared to what is formally defined as “zero-knowledge” in cryptographic literature. We call this “no-leak” authentication to distinguish from an established “zero-knowledge” concept. The “no-leak” condition implies “zero-knowledge” (even “perfect zero-knowledge”), but it is actually stronger, as we illustrate by examples. The principal idea behind our schemes is: the verifier challenges the prover with questions that he (the verifier) already knows answers to; therefore, even a computationally unbounded verifier who follows the protocol cannot possibly learn anything new during any number of authentication sessions. This is therefore also true for a computationally unbounded passive adversary.
Refined phylogenetic profiles method for predicting protein-protein interactions

MOTIVATION The increasing availability of complete genome sequences provides excellent opportunity for the further development of tools for functional studies in proteomics. Several experimental approaches and in silico algorithms have been developed to cluster proteins into networks of biological significance that may provide new biological insights, especially into understanding the functions of many uncharacterized proteins. Among these methods, the phylogenetic profiles method has been widely used to predict protein-protein interactions. It involves the selection of reference organisms and identification of homologous proteins. Up to now, no published report has systematically studied the effects of the reference genome selection and the identification of homologous proteins upon the accuracy of this method. RESULTS In this study, we optimized the phylogenetic profiles method by integrating phylogenetic relationships among reference organisms and sequence homology information to improve prediction accuracy. Our results revealed that the selection of the reference organisms set and the criteria for homology identification significantly are two critical factors for the prediction accuracy of this method. Our refined phylogenetic profiles method shows greater performance and potentially provides more reliable functional linkages compared with previous methods.