Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust multiview range image registration

We present a new method for precise registration of multiple range images with low overlap based on enhanced genetic algorithms (GAs). The proposed method minimizes the alignment error within the common overlap area among a set of views, which is computed by a novel robust evaluation metric, called the surface interpenetration measure. Because they search in a space of transformations, GAs are capable of registering surfaces without need for prealignment, as opposed to methods based on the iterative closest point (ICP) algorithm, the most popular to date. The experimental results confirm that the new method ensures more precise alignments than combined sequential pairwise alignments for multiview registration, providing accurate global alignment among overlapping views.
Inactivation of the Streptococcus mutans wall-associated protein A gene (wapA) results in a decrease in sucrose-dependent adherence and aggregation

A 0.8-kb HindIII-BamHI internal fragment of the Streptococcus mutans wall-associated protein A gene (wapA) was ligated to the 5.1-kb HindIII-BamHI fragment of the chimeric Streptococcus-Escherichia coli plasmid pVA891 (Emr Cmr). The resulting construct was used to transform S. mutans GS-5, and erythromycin-resistant mutants were isolated and analyzed. Directed mutagenesis of the wapA gene by plasmid insertion through homologous recombination was demonstrated by Southern blot hybridization with the wapA and pVA891 probes. Stable mutants were obtained, and the alteration of the wapA gene by insertional inactivation was associated with a significant decrease in S. mutans sucrose-dependent aggregation and binding to smooth surfaces. Thus, WapA may play an important role in the colonization of the tooth surface by S. mutans and in the buildup of dental plaque. These findings provided an explanation for previous studies which indicated that WapA was effective in the prevention of dental caries in animal models. Thus, the use of recombinant WapA in the preparation of a safe and effective human dental vaccine should be investigated further.
Association between WHO cut-offs for childhood overweight and obesity and cardiometabolic risk

Abstract Objective To examine the association between cardiovascular risk and childhood overweight and obesity using the BMI cut-offs recommended by the WHO. Design Children were classified as normal weight, overweight and obese according to the WHO BMI-for-age reference. Blood pressure, lipids, glucose, insulin, homeostasis model assessment–insulin resistance (HOMA-IR) and uric acid levels were compared across BMI groups. ANOVA and tests of linearity were used to assess overall mean differences across groups. Crude and adjusted odds ratios were calculated for adverse plasma levels of biochemical variables. Setting Paediatric care centres. Subjects Children (n 149) aged 8–18 years. Results About 37 %, 22 % and 41 % of children were classified respectively as normal weight, overweight and obese. There were significant linear mean differences between BMI groups in systolic blood pressure, HDL-cholesterol, TAG, insulin, HOMA-IR and uric acid. Obese children were 10·6 times more likely than normal-weight children to have hypertension; OR for other associations were 60·2 (high insulin), 39·5 (HOMA-IR), 27·9 (TAG), 16·0 (HDL-cholesterol), 4·3 (LDL-cholesterol) and 3·6 (uric acid). Overweight children were more likely than normal-weight children to have hypertension (OR = 3·5), high insulin (OR = 28·2), high HOMA-IR (OR = 23·3) and high TAG (OR = 16·1). Nearly 92 % and 57 % of the obese and overweight children, respectively, had one or more risk factor. Conclusions Obesity and overweight defined using the WHO BMI-for-age cut-offs identified children with higher metabolic and vascular risk. These results emphasize the importance of prevention of overweight and obesity in childhood to reduce cardiovascular risk.
Machine-Checked Proofs of Privacy for Electronic Voting Protocols

We provide the first machine-checked proof of privacy-related properties (including ballot privacy) for an electronic voting protocol in the computational model. We target the popular Helios family of voting protocols, for which we identify appropriate levels of abstractions to allow the simplification and convenient reuse of proof steps across many variations of the voting scheme. The resulting framework enables machine-checked security proofs for several hundred variants of Helios and should serve as a stepping stone for the analysis of further variations of the scheme. In addition, we highlight some of the lessons learned regarding the gap between pen-and-paper and machine-checked proofs, and report on the experience with formalizing the security of protocols at this scale.
Anticipating performance of work stations in MMPs at sensor breakdowns

Multi-Station Manufacturing Processes (MMPs) occasionally encounters the problem of deviation in the attributes of the products as compared to the design specifications. Sensors are installed in the work stations to detect the sources of errors in the product dimensions. This paper identifies the problem concerned with breakdown of the sensors and proposes an approach that identifies the interdependence relations among the various sensors using Bayesian Networks. Particle Swarm Optimization technique has been used to search the Optimal Bayesian Network. This proposed strategy will aid the manufacturers to check the delay in production time and to control the quality of production at times of sensor breakdown.
Recurrent, severe wheezing is associated with morbidity and mortality in adults with sickle cell disease

Prior studies of asthma in children with sickle cell disease (SCD) were based on reports of a doctor‐diagnosis of asthma with limited description of asthma features. Doctor‐diagnoses of asthma may represent asthma or wheezing unrelated to asthma. Objectives of this study were to determine if asthma characteristics are present in adults with a doctor‐diagnosis of asthma and/or wheezing, and to examine the relationship between doctor‐diagnosis of asthma, wheezing and SCD morbidity. This was an observational cohort study of 114 adults with SCD who completed respiratory symptom questionnaires and had serum IgE measurements. A subset of 79 participants completed pulmonary function testing. Survival analysis was based on a mean prospective follow‐up of 28 months and data were censored at the time of death or loss to follow‐up. Adults reporting a doctor‐diagnosis of asthma (N = 34) were more likely to have features of asthma including wheeze, eczema, family history of asthma, and an elevated IgE level (all P < 0.05). However, there was no difference in pain or ACS rate, lung function, or risk of death between adults with and without a doctor‐diagnosis of asthma. In contrast, adults who reported recurrent, severe episodes of wheezing (N = 34), regardless of asthma, had twice the rates of pain and ACS, decreased lung function and increased risk of death compared with adults without recurrent, severe wheezing. Asthma features were not associated with recurrent, severe wheezing. Our data suggest that wheezing in SCD may occur independently of asthma and is a marker of disease severity. Am. J. Hematol. 2011. © 2011 Wiley‐Liss, Inc.
Contagion and Interdependence in Financial Markets : A New Approach

The concepts of contagionandinterdependence are two ways to characterize the transmission mechanisms of shocks from one market to the others. In the case of contagion, the implicit assumption is one of dominance of a market on the others and the transmission takes the form of the diffusion of the events with a temporal lag, while in the presence of interdependence this behavior is in two directions, in the sense that each market can transmit or receive the shock. In this paper we exploit a new approach to capture these aspects, applying it to the Asian case.
THE SHAPE AND PROFILE OF THE MILKY WAY HALO AS SEEN BY THE CANADA–FRANCE–HAWAII TELESCOPE LEGACY SURVEY

We use Canada–France–Hawaii Telescope Legacy Survey data for 170 deg2, recalibrated and transformed to the Sloan Digital Sky Survey ugri photometric system, to study the distribution of near-turnoff main-sequence stars in the Galactic halo along four lines of sight to heliocentric distances of ∼35 kpc. We find that the halo stellar number density profile becomes steeper at Galactocentric distances greater than Rgal ∼ 28 kpc, with the power-law index changing from ninner = −2.62 ± 0.04 to nouter = −3.8 ± 0.1. In particular, we test a series of single power-law models and find them to be strongly disfavored by the data. The parameters for the best-fit Einasto profile are n = 2.2 ± 0.2 and Re = 22.2 ± 0.4 kpc. We measure the oblateness of the halo to be q ≡ c/a = 0.70 ± 0.01 and detect no evidence of it changing across the range of probed distances. The Sagittarius stream is detected in the l = 173° and b = −62° direction as an overdensity of [Fe/H] ∼ -1.5 dex stars at Rgal ∼ 32 kpc, providing a new constraint for the Sagittarius stream and dark matter halo models. We also detect the Monoceros stream as an overdensity of [Fe/H] > -1.5 dex stars in the l = 232° and b = 26° direction at Rgal ≲ 25 kpc. In the two sight lines where we do not detect significant substructure, the median metallicity is found to be independent of distance within systematic uncertainties ([Fe/H] ∼ -1.5 ± 0.1 dex).
Three Types of Naturally Occurring Modified Lipoproteins Induce Intracellular Lipid Accumulation in Human Aortic Intimal Cells — The Role of Lipoprotein Aggregation

Blood monocytes or intimal smooth muscle cells from normal aorta were incubated with low density lipoprotein (LDL) from patients with coronary atherosclerosis, or with LDL from diabetic patients, or with lipoprotein(a) (Lp(a)). In each case there was a 2- to 4-fold rise in the intracellular cholesteryl ester content. LDL from healthy subjects failed to induce intracellular lipid accumulation in these cells. LDL from patients with coronary atherosclerosis, LDL from diabetic patients, and Lp(a) form aggregates under cell culture conditions. The ability of these lipoproteins to increase the cholesteryl ester content of cultured cells is directly correlated to the degree of lipoprotein aggregation. When aggregates were removed from the lipoprotein preparations by filtration, the latter became less effective in promoting intracellular lipid accumulation. Incubation of cells with lipoprotein aggregates, isolated by gel filtration, induced a 3- to 5-fold elevation of the cellular cholesteryl ester content. These results suggest that LDL from atherosclerotic patients, or LDL from diabetic patients, or Lp(a) have a tendency to form aggregates and that these aggregates are avidly taken up by intimal smooth muscle cells followed by lipid accumulation. This aggregation tendency may play a role in atherogenesis.
Triaxial Accelerometer Error Coefficients Identification with a Novel Artificial Fish Swarm Algorithm

Artificial fish swarm algorithm (AFSA) is one of the state-of-the-art swarm intelligence techniques, which is widely utilized for optimization purposes. Triaxial accelerometer error coefficients are relatively unstable with the environmental disturbances and aging of the instrument. Therefore, identifying triaxial accelerometer error coefficients accurately and being with lower costs are of great importance to improve the overall performance of triaxial accelerometer-based strapdown inertial navigation system (SINS). In this study, a novel artificial fish swarm algorithm (NAFSA) that eliminated the demerits (lack of using artificial fishes’ previous experiences, lack of existing balance between exploration and exploitation, and high computational cost) of AFSA is introduced at first. In NAFSA, functional behaviors and overall procedure of AFSA have been improved with some parameters variations. Second, a hybrid accelerometer error coefficients identification algorithm has been proposed based on NAFSA and Monte Carlo simulation (MCS) approaches. This combination leads to maximum utilization of the involved approaches for triaxial accelerometer error coefficients identification. Furthermore, the NAFSA-identified coefficients are testified with 24-position verification experiment and triaxial accelerometer-based SINS navigation experiment. The priorities of MCS-NAFSA are compared with that of conventional calibration method and optimal AFSA. Finally, both experiments results demonstrate high efficiency of MCS-NAFSA on triaxial accelerometer error coefficients identification.
Flow calorimeter for equipment test

The efficiency of power supplies and power electronic converters is increasing. The loss measurement is often the difference between much lager numbers. The output frequency can be high or the output may require a high number of wires, which make the power measurement difficult. The presented flow calorimeter is intended for equipment test but it is also suited for passive component test in the range of 4-80 W losses. A compact design is obtained having an inner room (in mm) of 220times260times180 high and outer dimensions of 280times320times290 high. It is simple in realization and transportable
A Lightweight Intrusion Detection Model Based on Feature Selection and Maximum Entropy Model

Intrusion detection is a critical component of secure information systems. Current intrusion detection systems (IDS) especially NIDS (network intrusion detection system) examine all data features to detect intrusions. However, some of the features may be redundant or contribute little to the detection process and therefore they have great impact on the system performance. This paper proposes a lightweight intrusion detection model that is computationally efficient and effective based on feature selection and maximum entropy (ME) model. Firstly, the issue of identifying important input features is addressed. Since elimination of the insignificant and/or useless inputs leads to a simplification of the problem, therefore results to faster and more accurate detection. Secondly, classic ME model is used to learn and detect intrusions using the selected important features. Experimental results on the well-known KDD 1999 dataset show the proposed model is effective and can be applied to real-time intrusion detection environments.
Factors Regulating Microbial Biofilm Development in a System with Slowly Flowing Seawater

Microbial biofilm development was followed under growth conditions similar to those of a projected salinity power plant. Microscope glass cover slips were piled in biofilm reactors to imitate the membrane stacks in such a plant. A staining technique closely correlating absorbance values with biofilm dry weight was used for the study. Generally, the biofilms consisted of solitary and filamentous bacteria which were evenly distributed with considerable amounts of various protozoa and entrapped debris of organic origin. Protozoa predation was shown to decrease the amount of biofilm produced. The biofilm development lag phase was longer at lower temperatures. The subsequent growth phase was approximately arithmetic until stationary phase appeared. Adaptation of a hyperbolic saturation function gave curves that agreed well with the logarithm of the amount of biofilm as a function of time. Increased flow velocity, temperature, and nutrient concentration increased the biofilm production rate. An exponential relationship was shown between biofilm production rate and flow velocity within the range of 0 to 15 cm s−1. Intervals in which the biofilms were exposed to fresh water decreased the biofilm production rate more than four times. If the cover slips were inoculated with untreated seawater for 24 h, subsequent UV treatment had an insignificant effect on the biofilm formation.
A Neuromorphic Person Re-Identification Framework for Video Surveillance

This paper presents a neuromorphic person re-identification (NPReId) framework to establish the correspondence among individuals observed across two disjoint camera views. The proposed framework comprises three modules (observation, cognition, and contemplation), inspired by the form-and-color-and-depth (FACADE) theory model of object recognition system. In the observation module, a semantic partitioning scheme is introduced to segment a pedestrian into several logical parts, and an exhaustive set of experiments have been carried out to select the best possible complementary feature cues. In the cognition module, an unsupervised procedure is suggested to partition the gallery candidates into multiple consensus clusters with high intra-cluster and low inter-cluster similarity. A supervised classifier is then deployed to learn the relationship between each gallery candidate and its associated cluster, which is subsequently used to identify a set of inlier consensus clusters. This module also includes weighing of contribution of each feature channel toward defining a consensus cluster. Finally, in the contemplation module, the contributory weights are employed in a correlation-based similarity measure to find the corresponding match within the inlier set. The proposed framework is compared with several state-of-the-art methods on three challenging data sets: VIPeR, iLIDS-VID, and CUHK01. The experimental results, with respect to recognition rates, demonstrate that the proposed framework can obtain superior performance as compared with the counterparts. The proposed framework, along with its low-rank bound property, further establishes its suitability in practical scenarios through yielding high cluster hit rate with low database penetration.
The Poisson Inverse Gaussian Regression Model in the Analysis of Clustered Counts Data

We explore the possibility of modeling clustered count data using the Poisson Inverse Gaussian distribution. We develop a regression model, which relates the number of mastitis cases in a sample of dairy farms in Ontario, Canada, to various farm level covariates, to illustrate the methodology. Residual plots are constructed to explore the quality of the fit. We compare the results with a negative binomial regression model using maximum likelihood estimation, and to the generalized linear mixed regression model fitted in SAS.
Automated 3-D echocardiography analysis compared with manual delineations and SPECT MUGA

A major barrier for using 3-D echocardiography for quantitative analysis of heart function in routine clinical practice is the absence of accurate and robust segmentation and tracking methods necessary to make the analysis automatic. In this paper, we present an automated three-dimensional (3-D) echocardiographic acquisition and image-processing methodology for assessment of left ventricular (LV) function. We combine global image information provided by a novel multiscale fuzzy-clustering segmentation algorithm, with local boundaries obtained with phase-based acoustic feature detection. We then use the segmentation results to fit and track the LV endocardial surface using a 3-D continuous transformation. To our knowledge, this is the first report of a completely automated method. The protocol is evaluated in a small clinical case study (nine patients). We compare ejection fractions (EFs) computed with the new approach to those obtained using the standard clinical technique, single-photon emission computed tomography multigated acquisition. Errors on six datasets were found to be within six percentage points. A further two, with poor image quality, improved upon EFs from manually delineated contours, and the last failed due to artifacts in the data. Volume-time curves were derived and the results compared to those from manual segmentation. Improvement over an earlier published version of the method is noted.
Tremor in neuropathies of different origin.

BACKGROUND AND PURPOSE Tremor accompanies some poly-neuropathies, but its prevalence and its clinical and electrophysiological manifestations are not well known. The aim of the study was to assess the occurrence and characteristics of hand tremor in patients with polyneuropathy of different origins, as well as relations between the occurrence of tremors and clinical and neurographic findings of polyneuropathy. MATERIAL AND METHODS Eighty-nine patients diagnosed with polyneuropathy of known aetiology, and 50 age- and sex-matched healthy volunteers were included in the study. All subjects were interviewed regarding the occurrence of tremor. Tremor was assessed clinically and objectively using a triaxial accelerometer and electromyographic (EMG) recordings. A load test with a weight of 500 γ was performed in order to differentiate between enhanced physiological tremor (EPT) and essential tremor-like (ET-L) tremor. RESULTS Tremor was found in 59.5% of patients in clinical assessment and in 74% of patients in objective evaluation, significantly more often than in controls (12%). Tremor was detected in all types of polyneuropathy apart from paraproteinaemic IgM polyneuropathy. Tremor was postural (70%), but resting (51%) or kinetic (32%) tremor was also present. In the majority of cases, the severity of the tremor was mild. Essential tremor-like tremor prevailed in the study group. The occurrence of hand tremor was not related to the axonal or demyelinating type of polyneuropathy, nor to the conduction velocity or other electrophysiological findings of the investigated upper limb nerves. CONCLUSION Tremor accompanies 60-70% of patients with polyneuropathy; it is mostly postural, ET-L type with mild severity, and unrelated to other typical clinical and electrophysiological findings of neuropathy.
Wait and Transplant for Stage 2 Hepatocellular Carcinoma With Deceased-Donor Liver Grafts

Background As a new scheme at our center, a Model for End-stage Liver Disease score of 18 points is assigned to candidates of deceased-donor liver transplantation (DDLT) who have hepatocellular carcinoma (HCC) remaining at stage 2 six months after their disease has been confirmed stage 2 HCC. Two points are added every 3 months if their disease remains at stage 2 or below. This study evaluated patient and tumor characteristics as well as surgical and short-term outcomes of DDLT in these patients. Methods Comparison of survival was made among three groups of patients who underwent liver transplantation (LT) in the same period. Group 1 consisted of 22 HCC patients who received DDLT under the new scheme. Group 2 consisted of 18 HCC patients who underwent living-donor LT. Group 3 consisted of 52 patients who underwent DDLT because of liver failure, among whom 6 had HCC but were not included in the new scheme. Results Group 1 had a median follow-up period of 17.9 months, and the 1-, 3-, and 5-year overall survival rates were 100%, 100%, and 80%, respectively. Group 2 had the corresponding rates at 100%, 100%, and 100% with a median follow-up of 19.6 months. Group 3 had the corresponding rates at 96.1%, 96.1%, and 96.1% with a median follow-up of 19.4 months. Conclusions The policy of a 6-month wait has benefited the HCC patients who practically had no chance of undergoing living-donor LT. Their survival outcomes will be excellent as long as they can stand the test of time.
Shrinking Horizon Model Predictive Control with chance-constrained signal temporal logic specifications

We present Shrinking Horizon Model Predictive Control (SHMPC) for linear dynamical systems, under stochastic disturbances, with probabilistic constraints encoded as Signal Temporal Logic (STL) specifications. The control objective is to minimize a cost function under the restriction that the given STL specification be satisfied with some minimum probability. The presented approach utilizes the knowledge of the disturbance distribution to synthesize the controller in SHMPC. We show that this synthesis problem can be (conservatively) transformed into sequential optimizations involving linear constraints. We experimentally demonstrate the effectiveness of our proposed approach by evaluating its performance on room temperature control of a building.