Miracle-dz/UniFAR-FTUs huggingface dataset:
A new physical model with multilayer architecture for facial expression animation using dynamic adaptive mesh

This paper presents a new physically-based 3D facial model based on anatomical knowledge which provides high fidelity for facial expression animation while optimizing the computation. Our facial model has a multilayer biomechanical structure, incorporating a physically-based approximation to facial skin tissue, a set of anatomically-motivated facial muscle actuators, and underlying skull structure. In contrast to existing mass-spring-damper (MSD) facial models, our dynamic skin model uses the nonlinear springs to directly simulate the nonlinear visco-elastic behavior of soft tissue and a new kind of edge repulsion spring is developed to prevent collapse of the skin model. Different types of muscle models have been developed to simulate distribution of the muscle force applied on the skin due to muscle contraction. The presence of the skull advantageously constrain the skin movements, resulting in more accurate facial deformation and also guides the interactive placement of facial muscles. The governing dynamics are computed using a local semiimplicit ODE solver. In the dynamic simulation, an adaptive refinement automatically adapts the local resolution at which potential inaccuracies are detected depending on local deformation. The method, in effect, ensures the required speedup by concentrating computational time only where needed while ensuring realistic behavior within a predefined error threshold. This mechanism allows more pleasing animation results to be produced at a reduced computational cost.
An Integrated Passive Phase-Shift Keying Modulator for Biomedical Implants With Power Telemetry Over a Single Inductive Link

This paper presents a passive phase-shift keying (PPSK) modulator for uplink data transmission for biomedical implants with simultaneous power and data transmission over a single 13.56 MHz inductive link. The PPSK modulator provides a data rate up to 1.35 Mbps with a modulation index between 3% and 38% for a variation of the coupling coefficient between 0.05 and 0.26. This modulation scheme is particularly suited for biomedical implants that have high power demand and low coupling coefficients. The PPSK modulator operates in conjunction with on-off-keying downlink communication. The same inductive link is used to provide up to 100 mW of power to a multi-channel stimulator. The majority of the system on the implant side was implemented as an application specific integrated circuit (ASIC), fabricated in 0.6- <inline-formula> <tex-math notation="LaTeX">$\mu\text{m}$</tex-math></inline-formula> high voltage CMOS technology. The theory of PPSK modulation, simulated and measured performance evaluation, and comparison with other state-of-the-art impedance modulation techniques is presented. The measured bit error rate around critical coupling at 1.35 Mbps is below <inline-formula> <tex-math notation="LaTeX">$6 \times 10^{-8}$</tex-math></inline-formula>.
The Cognitive Impact of the ANK3 Risk Variant for Bipolar Disorder: Initial Evidence of Selectivity to Signal Detection during Sustained Attention

Background Abnormalities in cognition have been reported in patients with Bipolar Disorder (BD) and their first degree relatives, suggesting that susceptibility genes for BD may impact on cognitive processes. Recent genome-wide genetic studies have reported a strong association with BD in a single nucleotide polymorphism (SNP) (rs10994336) within ANK3, which codes for Ankyrin 3. This protein is involved in facilitating the propagation of action potentials by regulating the assembly of sodium gated ion channels. Since ANK3 influences the efficiency of transmission of neuronal impulses, allelic variation in this gene may have widespread cognitive effects. Preclinical data suggest that this may principally apply to sequential signal detection, a core process of sustained attention. Methodology/Principal Findings One hundred and eighty-nine individuals of white British descent were genotyped for the ANK3 rs10994336 polymorphism and received diagnostic interviews and comprehensive neurocognitive assessment of their general intellectual ability, memory, decision making, response inhibition and sustained attention. Participants comprised euthymic BD patients (n = 47), their unaffected first-degree relatives (n = 75) and healthy controls (n = 67). The risk allele T was associated with reduced sensitivity in target detection (p = 0.0004) and increased errors of commission (p = 0.0018) during sustained attention regardless of diagnosis. We found no effect of the ANK3 genotype on general intellectual ability, memory, decision making and response inhibition. Conclusions/Significance Our results suggest that allelic variation in ANK3 impacts cognitive processes associated with signal detection and this mechanism may relate to risk for BD. However, our results require independent replication and confirmation that ANK3 (rs10994336) is a direct functional variant.
Intensive physical training in geriatric patients after severe falls and hip surgery.

BACKGROUND Intensive exercise training can lead to improvement in strength and functional performance in older people living at home and nursing home residents. There is little information whether intensive physical exercise may be applicable and effective in elderly patients suffering from the acute sequelae of injurious falls or hip surgery. OBJECTIVE To assess the feasibility, safety and efficacy of intensive, progressive physical training in rehabilitation after hip surgery. DESIGN Prospective, randomised, placebo-controlled intervention study of a 3-months training intervention and a 3-months' follow-up. SETTING Physical training 6-8 weeks after hip surgery. SUBJECTS Twenty-eight (15 intervention, 13 control) elderly patients with a history of injurious falls admitted to acute care or inpatient rehabilitation because of acute fall-related hip fracture or elective hip replacement. METHODS Progressive resistance and functional training to improve strength and functional performance. RESULTS No training-related medical problems occurred in the study group. Twenty-four patients (86%) completed all assessments during the intervention and follow-up period. Adherence was excellent in both groups (intervention: 93, 0+/-13, 5% versus control: 96, 7+/-6, 2%). Training significantly increased strength, functional motor performance and balance and reduced fall-related behavioural and emotional problems. Some improvements in strength persisted during 3-months follow-up while other strength variables and functional performances were lost after cessation of training. Patients in the control group showed no change in strength, functional performance and emotional state during intervention and follow-up. CONCLUSIONS Progressive resistance training and progressive functional training are safe and effective methods to increase strength and functional performance during rehabilitation in patients after hip surgery and a history of injurious falls. Because part of the training improvements were lost after stopping the training, a continuing training regime should be established.
Multiple Scan Trees Synthesis for Test Time/Data and Routing Length Reduction under Output Constraint

A synthesis methodology for multiple scan trees that considers output pin limitation, scan chain routing length, test application time and test data compression rate simultaneously is proposed in this paper. Multiple scan trees, also known as a scan forest, greatly reduce test data volume and test application time in SOC testing. However, previous research on scan tree synthesis rarely considered issues such as routing length and output port limitation, and hence created scan trees with a large number of scan output ports and excessively long routing paths. The proposed algorithm provides a mechanism that effectively reduces test time and test data volume, and routing length under output port constraint. As a result, no output compressors are required, which significantly reduce the hardware overhead.
Quantitative evaluation of bone density using the Hounsfield index.

PURPOSE The primary aims of this retrospective study were to: (1) evaluate bone quality in different segments of the edentulous jaw and correlate it with demographic data and (2) establish a quantitative and objective assessment of bone quality based on the Hounsfield scale. MATERIALS AND METHODS One hundred one randomly selected computerized tomographic (CT) scans were used for the analysis. Edentulous segments ranging from 10 to 30 mm were selected for evaluation, and the findings were analyzed and correlated to demographics. Implant recipient sites were evaluated visually for bone classification by 2 independent examiners. The same sites were subsequently evaluated digitally using the Hounsfield scale, and the results were correlated with the visual classification. RESULTS The 4 quadrants of the mouth displayed Hounsfield unit (HU) values ranging from -240 HU to 1,159 HU. The highest unit/mean density value (559 +/- 208 HU) was found in the anterior mandible, followed by 517 +/- 177 HU for the anterior maxilla, 333 +/- 199 HU for the posterior maxilla, and 321 +/- 132 HU for the posterior mandible. There was no association between the Hounsfield value and density and age or gender. When subjective bone quality was correlated to Hounsfield index findings, only the relationship between HU and type 4 bone was found to be significant. CONCLUSIONS Knowledge of the Hounsfield value as a quantitative measurement of bone density can be helpful as a diagnostic tool. It can provide the implant surgeon with an objective assessment of bone density, which could result in modification of surgical techniques or extended healing time, especially in situations where poor bone quality is suspected.
Brief report pregnancy outcome in women assigned an ICD-9/ICD-9-CM 655.0 code "central nervous system malformation in fetus affecting management of pregnancy": can these codes aid in surveillance for central nervous system defects?

BACKGROUND The difficulty many birth defects registries have in identifying early pregnancy terminations can lead to significant underreporting of certain types of malformations. This study was designed to determine the potential benefit of using maternal ICD-9 codes relating to management of pregnancy due to fetal anomaly in surveillance of central nervous system (CNS) defects (655.0). METHODS Women assigned the ICD-9/ICD-9-CM (henceforth termed ICD-9) code 655.0 between 1990 and 2000 were ascertained from two administrative health databases in Manitoba, Canada, one relating to maternal serum screening and one based on hospital discharges. Information was collected on the type of CNS defect identified and whether it was isolated or associated with other anomalies. The relationship of these variables to pregnancy outcome and its potential impact on surveillance for these types of defects was explored. RESULTS Neural tube defects were the most common finding (67%) identified in the fetuses/infants of women assigned code 655.0, followed by hydrocephaly (20%) and Dandy-Walker anomaly (6%), but the proportion of neural tube defect cases declined after food fortification with folic acid. Termination of pregnancy occurred in ∼50% of neural tube defect cases, 18% before 20 weeks of gestation, but was rare for other CNS defects. CONCLUSION The maternal ICD-9 code 655.0 had a very high (97%) positive predictive value for identifying fetuses with a CNS defect; 655.00 was particularly effective in identifying neural tube defects pregnancies terminated before 20 weeks gestation that would be difficult to ascertain, especially by passive surveillance systems using infant related data alone.
Metastatic behavior of an adriamycin-resistant murine tumor.

The metastatic behavior of a murine fibrosarcoma (UV-2237M-ADMR) resistant to Adriamycin (ADM) (doxorubicin) was investigated. Subclones isolated from the UV-2237M-ADMR line, which originated from a single colony, generally displayed a similar degree of resistance to ADM (eight out of nine clones did not differ from this UV-2237M-ADMR line). In contrast, they differed significantly in their capacity to form lung colonies after i.v. injection (six of nine clones differed significantly from the UV-2237M-ADMR line, p less than or equal to 0.005, Mann-Whitney U test). The UV-2237M-ADMR cell line maintained resistance to ADM even after 17 weeks of growth in syngeneic mice, although a gradual decrease in resistance was observed over this time. Spontaneous metastases from the UV-2237M-ADMR tumor commonly retained resistance to ADM. Of 18 cell lines, each established from an individual lung nodule, 16 showed plating efficiencies in the presence of ADM comparable to that of the primary UV-2237M-ADMR tumor. The remaining two lines had partially reverted to the sensitive state. The i.v. administration of ADM significantly reduced the lung tumor burden of mice with ADM-sensitive UV-2237M tumors but failed to affect the lung tumor burden of mice with UV-2237M-ADMR tumors. The UV-2237M-ADMR tumor line, exhibiting as it does both drug-resistant and metastatic behavior, provides a useful model system with which to investigate the metastatic process and the development of drug resistance.
The approximate inverse in action: IV. Semi-discrete equations in a Banach space setting

This article concerns the method of approximate inverse to solve semi-discrete, linear operator equations in Banach spaces. Semi-discrete means that we search for a solution in an infinite-dimensional Banach space having only a finite number of data available. In this sense the situation is applicable to a large variety of applications where a measurement process delivers a discretization of an infinite-dimensional data space. The method of approximate inverse computes scalar products of the data with pre-computed reconstruction kernels which are associated with mollifiers and the dual of the model operator. The convergence, approximation power and regularization property of this method when applied to semi-discrete operator equations in Hilbert spaces has been investigated in three prequels to this paper. Here we extend these results to a Banach space setting. We prove convergence and stability for general Banach spaces and reproduce the results specifically for the integration operator acting on the space of continuous functions.
Main Functions and Taxonomic Distribution of Virulence Genes in Brucella melitensis 16 M

Many virulence genes have been detected in attenuated mutants of Brucella melitensis 16 M; nevertheless, a complete report of these genes, including the main Cluster of Orthologous Groups (COG) represented as well as the taxonomical distribution among all complete bacterial and archaeal genomes, has not been analyzed. In this work a total of 160 virulence genes that have been reported in attenuated mutants in B. melitensis were included and analyzed. Additionally, we obtained 250 B. melitensis randomly selected genes as a reference group for the taxonomical comparisons. The COGs and the taxonomical distribution profile for 789 nonredundant bacterial and archaeal genomes were obtained and compared with the whole-genome COG distribution and with the 250 randomly selected genes, respectively. The main COGs associated with virulence genes corresponded to the following: intracellular trafficking, secretion and vesicular transport (U); cell motility (N); nucleotide transport and metabolism (F); transcription (K); and cell wall/membrane/envelope biogenesis (M). In addition, we found that virulence genes presented a higher proportion of orthologs in the Euryarchaeota and Proteobacteria phyla, with a significant decrease in Chlamydiae, Bacteroidetes, Tenericutes, Firmicutes and Thermotogae. In conclusion, we found that genes related to specific functions are more relevant to B. melitensis virulence, with the COG U the most significant. Additionally, the taxonomical distribution of virulence genes highlights the importance of these genes in the related Proteobacteria, being less relevant in distant groups of organisms with the exception of Euryarchaeota.
Infection with Human Immunodeficiency Virus Type 1 Upregulates DNA Methyltransferase, Resulting in De Novo Methylation of the Gamma Interferon (IFN-γ) Promoter and Subsequent Downregulation of IFN-γ Production

ABSTRACT The immune response to pathogens is regulated by a delicate balance of cytokines. The dysregulation of cytokine gene expression, including interleukin-12, tumor necrosis factor alpha, and gamma interferon (IFN-γ), following human retrovirus infection is well documented. One process by which such gene expression may be modulated is altered DNA methylation. In subsets of T-helper cells, the expression of IFN-γ, a cytokine important to the immune response to viral infection, is regulated in part by DNA methylation such that mRNA expression inversely correlates with the methylation status of the promoter. Of the many possible genes whose methylation status could be affected by viral infection, we examined the IFN-γ gene as a candidate. We show here that acute infection of cells with human immunodeficiency virus type 1 (HIV-1) results in (i) increased DNA methyltransferase expression and activity, (ii) an overall increase in methylation of DNA in infected cells, and (iii) the de novo methylation of a CpG dinucleotide in the IFN-γ gene promoter, resulting in the subsequent downregulation of expression of this cytokine. The introduction of an antisense methyltransferase construct into lymphoid cells resulted in markedly decreased methyltransferase expression, hypomethylation throughout the IFN-γ gene, and increased IFN-γ production, demonstrating a direct link between methyltransferase and IFN-γ gene expression. The ability of increased DNA methyltransferase activity to downregulate the expression of genes like the IFN-γ gene may be one of the mechanisms for dysfunction of T cells in HIV-1-infected individuals.
Improving the Usefulness of Alerts Generated by Automated Static Analysis Tools

Static analysis tools are programs that analyze software without executing it. They can be simple style checkers or follow intricate rules to efficiently find problems often overlooked by developers. Unfortunately, the alerts generated by those tools are not always correct. The high number of false positives has been found to be one of the major reasons why such tools have not been widely adopted. One approach to improve these tools is to post-process the generated alerts and only report actionable ones, i.e. true positives which will be acted upon by the developers. In this work, we evaluate several machine-learning classifiers that use historic alert data to classify new alerts as actionable or not. We build a framework called Autobugs to collect the necessary information. It runs a static analysis tool on past revisions of a software project, saves the generated alerts and computes the lifetime-based actionability label. This is then used to train a linear support vector machine (SVM), a nonlinear SVM and a decision tree on three similar open-source forum-software projects written in PHP. We evaluate each classifiers for each project individually as well as the application of a trained model on a different project. Based on the results, we constructed an additional classifier, which only takes into account the lifetime of an alert, classifying younger ones as actionable. It outperforms the other algorithms for our sample software-projects.
Encapsulated cells producing retroviral vectors for in vivo gene transfer

Because gene therapy of the future will primarily take an in vivo approach, a number of problems associated with its current implementation exist. Currently, repeated delivery of a vector in vivo is necessary to ensure adequate transfer of the therapeutic gene. This may lead to the development of an immune response against the vector, thus interfering with gene delivery. To circumvent this problem, retroviral vector packaging cells that permanently produce recombinant retroviral vector particles have been encapsulated.
Spatial Heterogeneity in Glacier Mass-Balance Sensitivity across High Mountain Asia

Mass balance of glaciers in High Mountain Asia (HMA) varies substantially across the region. While the spatial variability is attributed to differences in climatic setting and sensitivity of these glaciers to climate change, an assessment of these factors to date has only been performed on a small sample of glaciers and a small set of climate perturbation scenarios. To advance the assessment to larger datasets, we first reconstruct the time series of reference-surface mass balance for 1952–2014 periods using an empirical model calibrated with observed mass balance from 45 glaciers across the HMA. Forcing the model with a set of independent stepwise changes of temperature (±0.5 K to ±6 K) and precipitation (±5% to ±30%), we assess the reference-surface mass balance sensitivity of each glacier in the sample. While the relationship between the change in mass balance and the change in precipitation is linear, the relationship with the change in temperature is non-linear. Spatial heterogeneity in the simulated mass balance sensitivities is attributed to differences in climatic setting, elevation, and the sensitivity of mass-balance profile (gradient) to changes in temperature and precipitation. While maritime and low-lying continental glaciers show high sensitivity to temperature changes and display a uniform mass-balance sensitivity with elevation, the high-lying continental glaciers show high sensitivity to precipitation changes and display a non-uniform mass-balance sensitivity with elevation. Our analysis reveals the dominant drivers of spatial variability in the mass balance sensitivity across the region: temperature as a single driver for maritime glaciers, and a superposition of temperature, precipitation seasonality, and snow/rain differentiation for continental glaciers. Finally, a set of sensitivity tests with perturbed model parameters confirms the robustness of our results. The model’s ability and robustness to resolve spatial patterns in the sensitivities and their drivers implies that simple modeling approaches remain a powerful tool for analyzing glacier response to climate change in HMA.
Model-Based Hydraulic Impedance Control for Dynamic Robots

Increasingly, robots are designed to interact with the environment, including humans and tools. Legged robots, in particular, have to deal with environmental contacts every time they take a step. To handle these interactions properly, it is desirable to be able to set the robot's dynamic behavior, i.e., its impedance. In this contribution, we investigate the most relevant theoretical and practical aspects in impedance control using hydraulic actuators, ranging from the force dynamics analysis and model-based controller design to the overall stability and performance assessment. We present results with one leg of the quadruped robot HyQ and also highlight the influence of hardware parameters, such as valve bandwidth and inertia, in the impedance and force tracking. In addition, we demonstrate the capabilities of HyQ's actively compliant leg by experimentally comparing it with a passively compliant version of the same leg. With such a broad spectrum of analyses and discussions, this paper aims to serve as a practical and comprehensive guide for implementing high-performance impedance control on highly dynamic hydraulic robots.