Miracle-dz/UniFAR-FTUs huggingface dataset:
A combined vision-inertial fusion approach for 6-DoF object pose estimation

The estimation of the 3D position and orientation of moving objects (‘pose’ estimation) is a critical process for many applications in robotics, computer vision or mobile services. Although major research efforts have been carried out to design accurate, fast and robust indoor pose estimation systems, it remains as an open challenge to provide a low-cost, easy to deploy and reliable solution. Addressing this issue, this paper describes a hybrid approach for 6 degrees of freedom (6-DoF) pose estimation that fuses acceleration data and stereo vision to overcome the respective weaknesses of single technology approaches. The system relies on COTS technologies (standard webcams, accelerometers) and printable colored markers. It uses a set of infrastructure cameras, located to have the object to be tracked visible most of the operation time; the target object has to include an embedded accelerometer and be tagged with a fiducial marker. This simple marker has been designed for easy detection and segmentation and it may be adapted to different service scenarios (in shape and colors). Experimental results show that the proposed system provides high accuracy, while satisfactorily dealing with the real-time constraints.
Riskalyzer

An individual's risk-taking propensity is "the stable tendency to choose options with a lower probability of success, but greater rewards". This risk propensity plays a central role in decision making by customers as well as managers, and is a mediator in behavior associated with security, privacy, health, finance, and well-being. Most common approach to understanding an individual's risk propensity remain lab-based games and surveys. Administering such surveys and games is a manual, time, and money intensive process that is also fraught with multiple biases. Recently, smartphones are increasingly seen as large-scale sensors of human activity, recording data related to physical and social aspects of people's lives. Building on this trend we investigate the potential of passive phone-based data for automatically inferring an individual's risk propensity. Specifically, we describe a novel approach to model an individual's risk propensity based on her mobile phone usage. Based on a 10-week field + lab study involving 50 participants, we report that: (1) multiple phone-based features (e.g., average gyradius) are intricately associated with participants' risk propensity; and (2) a phone-based model outperforms demography-based models by 39% in terms of accuracy of predicting risk propensity. In organizational terms, a better understanding of risk behavior could contribute significantly to risk management programs. At the same time, such results could open doors for more nuanced understanding of the underlying human risk phenomena and their interconnections with social and mobility behavior.
Towards hierarchical cooperative analytics architecture in law enforcement agencies

The vast growth in populations and the widespread of metropolitan areas hinder the efforts of crime investigation and inhibit tracking the risk of threats to safety and national security. Information technology has been helping in tracing criminals and terrorists, but with the outspread of social networks and the emergence of the Internet of Things, new challenges have arisen. The Internet is becoming a major part of everyone's daily life. Data representing trustful and suspicious activities is continuously generated and stored everywhere at an unprecedented scale. This extremely large data, which is known as Big Data, may contain critical and helpful information that can be used in detecting, and in many cases, preventing illegal activities, crimes and more importantly terror attacks. Unfortunately, the limitations on the communication between administrative zones, the huge amount of data and the intrinsically unstructured nature of such data makes leveraging its usefulness impractical. In this paper, we propose a hierarchical cooperative analytics architecture that utilizes Big Data Analytics, Ontologies, and Metamodels to facilitate the analysis of data collected from different sources to aid law enforcement agencies' efforts in establishing law and maintaining security.
Tunable Morphology of Monodisperse Polymer Particles With Microfluidics

In this work, we propose a novel method to fabricate polymer particles with controlled morphology in microchannel by solidification of polymer solutions and study the transition in the shape of these particles from spheres, to cups, and to donuts. The non-spherical geometries are achieved through nonuniform diffusion of the solvent, leading to non-uniform solidification. By adjusting the flow rates of both continuous and dispersed phases, the spatial heterogeneity in the solvent diffusion rate and thus the morphology of the final polymer particles can be tuned. This approach offers a one-step continuous process for the fabrication of non-spherical polymer particles. The technique is applicable to different polymers under appropriate polymer-solvent combinations. The ability to tune the shapes of polymer particles easily will create new opportunities for applications that require anisotropic functional particles, such as in biomedical engineering.Copyright © 2011 by ASME
Map-based curvilinear coordinates for autonomous vehicles

Localization within high definition maps is a key problem for autonomous navigation as vehicles need to extract information from them. In addition, many navigation tasks are defined with respect to map features. For instance, estimating the cross-track and along-track gaps of a vehicle with respect to a given path is critical for lane keeping or intersection management. Map-based localization is also important for cooperative tasks like platooning in curved roads or lane changing. This work studies different methods to compute map-based coordinates defined as curvilinear abscissa, lateral distance and heading with respect to paths in high definition maps. Four approaches using polylines, lanelets and splines are compared. Thanks to real experiments, the discontinuity issues of polylines used in current high definition maps are evaluated and we discuss advantages and drawbacks of splines-based and lanelet methods. We also report experimental results corresponding to a platoon of two vehicles in curved roads and evaluate the effects of the use of low cost GNSS receivers.
A high performance NIDS using FPGA-based regular expression matching

A Network Intrusion Detection System (NIDS) monitors all incoming packets in the network and detects packets that are malicious to the internal system. The NIDS should also have ability to update the detection rules because new attack patterns are unpredictable. Incorporating FPGAs into the NIDS is one of the best solutions that can provide both high performance and high flexibility comparing to the other approaches such as software solutions. In this paper we propose a novel approach to design the parallel comparator of NIDS that can not only minimize additional resources but also maximize the processing performance. The performance and resource tradeoff due to the implementation of the parallel comparator in the prefix sharing is also analyzed.
Leisure-time Physical Activity and Sedentary Behaviour in Older People: The Influence of Sport Involvement on Behaviour Patterns in Later Life

Given the dramatic demographic change underway in most industrialized nations, the health of older adults is a major concern, particularly given the prevalence of sedentary behaviours and physical inactivity among ageing populations. Researchers have suggested sport participation in later life promotes other health-related behaviours, however, these relationships are poorly understood. It is possible for individuals to be classified as sufficiently active and still spend most of their day involved in sedentary pursuits. Moreover, there is little information on older sport participants' use of time compared to leisurely active or inactive peers and whether type of physical activity involvement is associated with differences in older adults' behaviour patterns. With this in mind, data from 1,723 respondents (65 years and older) who completed the sport module of the 2010 Canadian General Social Survey–Time Use were used to investigate the influence of physical activity involvement (competitive sport vs. non-competitive sport vs. physically active leisure vs. inactivity) on time spent in leisure-time physical activity and sedentary behaviours. Results indicated that competitive sport participants spent less time engaging in sedentary behaviours compared to the physically active leisure or inactive respondents; however, sport participants (both competitive and non-competitive) also spent less time engaging in leisure-time physical activities than the physically active leisure group. Implications of these findings to assumptions related to the activity levels of older sport participants, suggestions for future research, and considerations for sport-related interventions aimed at enhancing health in older adulthood are discussed.
Spontaneously Emerging Object Part Segmentation

Object part is a fine-grained understanding of objects. It is also a generic model of objects in the same category. People recognize object subparts naturally, and meaningful object part segmentation exists for almost all natural objects. However, not many research works are conducted on the subpart level of generic object types, probably due to the lack of available data sources. In this project, we explore the possibility of forming object part segmentation without direct supervision. We apply deep learning with specifically designed loss on the ShapeNet dataset, and demonstrate a plausible system that can discover consistent and understandable object part segmentation spontaneously.
Evaluation and validation of an ion mobility quadrupole time-of-flight mass spectrometry pesticide screening approach.

An ion mobility quadrupole time-of-flight mass spectrometry-based pesticide suspect screening methodology was developed and validated covering 20 plant-derived food matrices deriving from six commodity groups of different complexity according to the actual European Commission document SANTE/11813/2017 applying a QuEChERS sample preparation protocol. The method combines ultra-performance liquid chromatography, traveling wave ion mobility, and quadrupole time-of-flight mass spectrometry. Besides the determination of the physicochemical property collision cross-section and the establishment of a corresponding scientific suspect screening database comprising 280 pesticides for several pesticides, different protomers, sodium adducts, as well as dimers were identified in ion mobility spectrometry traces. Additionally, collision cross-section values were included in the validation requirements regarding chromatography and mass spectrometry for the detection of pesticides. A collision cross-section value window was analyzed within a tolerable error of ±2%. For this cross-matrix validation, screening detection limits were determined at concentration levels of 0.100 mg/kg (84% of the original pesticide scope), 0.010 mg/kg (56%), and 0.001 mg/kg (21%). By application of ion mobility spectrometry, the compound identification was improved due to independence of commodity of concern and concentration levels of analyte molecules, as false assignments are reduced by application of a collision cross-section range.
Predictors of Reversion from Mild Cognitive Impairment to Normal Cognition

Background/Aims: Few studies have examined predictors of reversion from mild cognitive impairment (MCI) to normal cognition. We sought to identify baseline predictors of reversion, using the National Alzheimer's Coordinating Center Uniform Data Set, by comparing MCI individuals who reverted to normal cognition to those who progressed to dementia. Methods: Participants (n = 1,208) meeting MCI criteria were evaluated at the baseline visit and 3 subsequent annual visits. Clusters of baseline predictors of MCI reversion included demographic/genetic data, global functioning, neuropsychological functioning, medical health/dementia risk score, and neuropsychiatric symptoms. Stepwise logistic regression models identified predictors of MCI reversion per cluster, which were then entered into a final comprehensive model to find overall predictor(s). Results: At 2 years, 175 (14%) reverted to normal cognition, 612 (51%) remained MCI, and 421 (35%) progressed to dementia, with sustained diagnoses at 3 years. Significant variables associated with MCI reversion were younger age, being unmarried, absence of APOE ε4 allele, lower CDR-SOB score, and higher memory/language test scores. Conclusion: A relatively sizable proportion of MCI individuals reverted to normal cognition, which is associated with multiple factors previously noted. Findings may enhance MCI prognostic accuracy and increase precision of early intervention studies of dementia.
Open snake model based on global guidance field for embryo vessel location

The development of vessels can provide important information about the growth status of animal embryos. It is, therefore, important to automatically locate the deformed vessel branches from the embryo images. However, very few vessel detectors can accurately locate all vessel branches when the captured images are low quality and the implied vessel shapes are complex. In this study, a new framework consisting of vessel region extraction and snake shape optimisation is proposed. The main contribution in this detector is a novel open snake model based on the global guidance field and deformation template initialisation. Experimental results on a specific application of an embryo vessel database [Database and source codes: https://github.com/wcxie/Egg-embryro-vessel-location/. ] demonstrate that the proposed algorithm not only locates the vessel shape properly but also obtains the orientations of embryo vessel branches accurately. Comparison to traditional guidance fields and the active appearance model illustrates the effectiveness and competitiveness of the proposed model.
The relationship between different dimensions of alcohol use and the burden of disease—an update

Abstract Background and aims Alcohol use is a major contributor to injuries, mortality and the burden of disease. This review updates knowledge on risk relations between dimensions of alcohol use and health outcomes to be used in global and national Comparative Risk Assessments (CRAs). Methods Systematic review of reviews and meta‐analyses on alcohol consumption and health outcomes attributable to alcohol use. For dimensions of exposure: volume of alcohol use, blood alcohol concentration and patterns of drinking, in particular heavy drinking occasions were studied. For liver cirrhosis, quality of alcohol was additionally considered. For all outcomes (mortality and/or morbidity): cause of death and disease/injury categories based on International Classification of Diseases (ICD) codes used in global CRAs; harm to others. Results In total, 255 reviews and meta‐analyses were identified. Alcohol use was found to be linked causally to many disease and injury categories, with more than 40 ICD‐10 three‐digit categories being fully attributable to alcohol. Most partially attributable disease categories showed monotonic relationships with volume of alcohol use: the more alcohol consumed, the higher the risk of disease or death. Exceptions were ischaemic diseases and diabetes, with curvilinear relationships, and with beneficial effects of light to moderate drinking in people without heavy irregular drinking occasions. Biological pathways suggest an impact of heavy drinking occasions on additional diseases; however, the lack of medical epidemiological studies measuring this dimension of alcohol use precluded an in‐depth analysis. For injuries, except suicide, blood alcohol concentration was the most important dimension of alcohol use. Alcohol use caused marked harm to others, which has not yet been researched sufficiently. Conclusions Research since 2010 confirms the importance of alcohol use as a risk factor for disease and injuries; for some health outcomes, more than one dimension of use needs to be considered. Epidemiological studies should include measurement of heavy drinking occasions in line with biological knowledge.
E3 ubiquitin ligase SP1 regulates peroxisome biogenesis in Arabidopsis

Significance Peroxisomes are eukaryotic organelles crucial for development. Peroxisomal matrix proteins are imported by the peroxisome import machinery composed of peroxins (PEX proteins), but how the function of these PEX proteins is regulated is largely unknown. We discovered in Arabidopsis that the ubiquitin–proteasome system regulates peroxisome protein import via an E3 ubiquitin ligase, SP1 (suppressor of ppi1 locus1), which targets PEX13 and possibly several other components of the peroxisome matrix protein import machinery for degradation. Our data demonstrate that the same E3 ubiquitin ligase can be shared by metabolically linked peroxisomes and chloroplasts to promote the destabilization of distinct components of the two import machineries, suggesting that the ubiquitin–proteasome system may represent an important regulatory mechanism coordinating the biogenesis of functionally associated organelles. Peroxisomes are ubiquitous eukaryotic organelles that play pivotal roles in a suite of metabolic processes and often act coordinately with other organelles, such as chloroplasts and mitochondria. Peroxisomes import proteins to the peroxisome matrix by peroxins (PEX proteins), but how the function of the PEX proteins is regulated is poorly understood. In this study, we identified the Arabidopsis RING (really interesting new gene) type E3 ubiquitin ligase SP1 [suppressor of plastid protein import locus 1 (ppi1) 1] as a peroxisome membrane protein with a regulatory role in peroxisome protein import. SP1 interacts physically with the two components of the peroxisome protein docking complex PEX13–PEX14 and the (RING)-finger peroxin PEX2. Loss of SP1 function suppresses defects of the pex14-2 and pex13-1 mutants, and SP1 is involved in the degradation of PEX13 and possibly PEX14 and all three RING peroxins. An in vivo ubiquitination assay showed that SP1 has the ability to promote PEX13 ubiquitination. Our study has revealed that, in addition to its previously reported function in chloroplast biogenesis, SP1 plays a role in peroxisome biogenesis. The same E3 ubiquitin ligase promotes the destabilization of components of two distinct protein-import machineries, indicating that degradation of organelle biogenesis factors by the ubiquitin–proteasome system may constitute an important regulatory mechanism in coordinating the biogenesis of metabolically linked organelles in eukaryotes.
The effect of coils axial misalignments on yhe efficiency of an inductive powering unit with class E power amplifier

Advancement in inductive powering technology appears to be a promising direction for development of implantable medical devices. A class E power amplifier is often used together with an inductive link to achieve high efficiency of inductive powering unit (IPU). The class E amplifier is sensitive to the changes in its loading network. Therefore, coils misalignment in the link leads to the decreased system efficiency. This paper presents simulation results of the IPU with the class E amplifier for different coil pairs. The results of the simulation show a decrease in efficiency for both cases: when the coils get closer and farther away. The coils with lower inductance (3.4 μH) lead to smaller losses than the coils with higher inductance (9–12 μH) in the case of axial distance reduction. In the case of axial distance increase the coils with lower inductance lead to higher losses than the coils with higher inductance.
Home Oxygen in Chronic Obstructive Pulmonary Disease.

Two landmark trials conducted more than 35 years ago provided scientific evidence that, under very specific circumstances, long-term oxygen therapy (LTOT) may prolong life. These two trials enrolled 290 patients with chronic obstructive pulmonary disease and severe daytime hypoxemia documented by direct arterial blood gas measurement. From that time, LTOT became a standard of care, and the indications for oxygen therapy expanded to include nocturnal oxygen therapy for isolated nocturnal oxygen desaturation, ambulatory oxygen to correct exercise-induced desaturation, and short-burst oxygen to relieve dyspnea. In most cases, the rationale for broadening the indications for oxygen therapy is that, if hypoxemia exists, correcting it by increasing the FiO2 should help. However, with the exception of LTOT in severely hypoxemic patients with chronic obstructive pulmonary disease, randomized controlled trials of oxygen therapy have failed to demonstrate clinically significant benefits. Also, adherence to LTOT is usually suboptimal. Important areas for future research include improving understanding of the mechanisms of action of supplemental oxygen, the clinical and biochemical predictors of responsiveness to LTOT, the methods for measuring and enhancing adherence to LTOT, and the cost-effectiveness of oxygen therapy. A standardization of terminology to describe the use of supplemental oxygen at home is provided.
THE PNF (PROPRIOCEPTIVE NEUROMUSCULAR FACILITATION) STRETCHING TECHNIQUE - A BRIEF REVIEW

The aim of this paper is to realize a brief review on the PNF stretching technique. PNF stretching (or proprioceptive muscular facilitation) is one of the most effective forms of flexibility training for increasing range of motion. PNF stretching is a method of flexibility training that can reduce hypertonus, allowing muscles to relax and lengthen and can be applied to patients of all ages. PNF can be used to supplement daily stretching and these techniques help develop muscular strength and endurance, joint stability, mobility, neuromuscular control and coordination. PNF techniques are as follows: Contract Relax, Hold Relax, Rhythmic Initiation, Rhythmic Stabilisation, Slow reversals, Alternating isometrics and Alternating rhythmic stabilization. Conclusion. Whether promoting flexibility, developing muscular strength and endurance, improving joint stability or increasing neuromuscular control and coordination, PNF is a valuable part of every rehabilitation program.
A test for stability robustness of linear time‐varying systems utilizing the linear time‐invariant ν‐gap metric

A stability robustness test is developed for internally stable, nominal, linear time‐invariant (LTI) feedback systems subject to structured, linear time‐varying uncertainty. There exists (in the literature) a necessary and sufficient structured small gain condition that determines robust stability in such cases. In this paper, the structured small gain theorem is utilized to formulate a (sufficient) stability robustness condition in a scaled LTI ν‐gap metric framework. The scaled LTI ν‐gap metric stability condition is shown to be computable via linear matrix inequality techniques, similar to the structured small gain condition. Apart from a comparison with a generalized robust stability margin as the final part of the stability test, however, the solution algorithm implemented to test the scaled LTI ν‐gap metric stability robustness condition is shown to be independent of knowledge about the controller transfer function (as opposed to the LMI feasibility problem associated with the scaled small gain condition which is dependent on knowledge about the controller). Thus, given a nominal plant and a structured uncertainty set, the stability robustness condition presented in this paper provides a single constraint on a controller (in terms of a large enough generalized robust stability margin) that (sufficiently) guarantees to stabilize all plants in the uncertainty set. Copyright © 2008 John Wiley & Sons, Ltd.