Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial Patterning of the Viscoelastic Core Layer of a Hybrid Sandwich Composite Material to Trigger Its Vibro-Acoustic Performances

With the aim of decreasing CO2 emissions, car producers’ efforts are focused, among others, on reducing the weight of vehicles yet preserving the overall vibrational comfort. To do so, new lightweight materials combining high stiffness and high (passive) damping are sought. For panels essentially loaded in bending, sandwich composites made of two external metallic stiff layers (skins) and an inner polymeric (i.e. absorbing) core are broadly used. Now aiming at creating materials by design with a better control of the final performance of the part, the tuning of the local material properties is pursued. To this end, the present work focuses on controlling the spatial in-plane viscoelastic properties of the polymeric core of such sandwich structures. The spatial patterning is achieved using a recently developed UV irradiation selective technique of Room Temperature Vulcanization (RTV) silicone elastomeric membrane, in which the ultraviolet (UV) irradiation dose, curing time and temperature are the process parameters controlling the viscoelastic properties of the polymeric membrane. Finally, a protocol for the realization of architected aluminum - silicone - aluminum composite sandwich panels is proposed. The influence of UV irradiation selective technique is demonstrated by Dynamic Mechanical Analysis (DMA) measurements on the silicone core itself and by the Corrected Force Analysis Technique (CFAT) to measure the equivalent Young’s modulus and damping of the sandwich structure over a large frequency band. As a first demonstration application, sandwich beams with different core patterns (homogeneous and heterogeneous) are designed and tested. Furthermore, the analytical formalism developed by Guyader et al. is used to model the vibro-acoustic performances of the homogenous sandwich beams and fair model-experiments comparisons are obtained. The spatial patterning of the polymer layer is found to successfully affect the local properties of the composite heterogeneous beam as evidenced by the CFAT method. Finally, this work permits the enunciation of guidelines for designing complex architectured systems with further control of the vibro-acoustics performances.
Accounting for Genotype-by-Environment Interactions and Residual Genetic Variation in Genomic Selection for Water-Soluble Carbohydrate Concentration in Wheat

Abiotic stress tolerance traits are often complex and recalcitrant targets for conventional breeding improvement in many crop species. This study evaluated the potential of genomic selection to predict water-soluble carbohydrate concentration (WSCC), an important drought tolerance trait, in wheat under field conditions. A panel of 358 varieties and breeding lines constrained for maturity was evaluated under rainfed and irrigated treatments across two locations and two years. Whole-genome marker profiles and factor analytic mixed models were used to generate genomic estimated breeding values (GEBVs) for specific environments and environment groups. Additive genetic variance was smaller than residual genetic variance for WSCC, such that genotypic values were dominated by residual genetic effects rather than additive breeding values. As a result, GEBVs were not accurate predictors of genotypic values of the extant lines, but GEBVs should be reliable selection criteria to choose parents for intermating to produce new populations. The accuracy of GEBVs for untested lines was sufficient to increase predicted genetic gain from genomic selection per unit time compared to phenotypic selection if the breeding cycle is reduced by half by the use of GEBVs in off-season generations. Further, genomic prediction accuracy depended on having phenotypic data from environments with strong correlations with target production environments to build prediction models. By combining high-density marker genotypes, stress-managed field evaluations, and mixed models that model simultaneously covariances among genotypes and covariances of complex trait performance between pairs of environments, we were able to train models with good accuracy to facilitate genetic gain from genomic selection.
Evidence-based cancer prevention recommendations for Japanese

A comprehensive evidence-based cancer prevention recommendation for Japanese was developed. We evaluated the magnitude of the associations of lifestyle factors and infection with cancer through a systematic review of the literature, meta-analysis of published data, and pooled analysis of cohort studies in Japan. Then, we judged the strength of evidence based on the consistency of the associations between exposure and cancer and biological plausibility. Important factors were extracted and summarized as an evidence-based, current cancer prevention recommendation: 'Cancer Prevention Recommendation for Japanese'. The recommendation addresses six important domains related to exposure and cancer, including smoking, alcohol drinking, diet, physical activity, body weight and infection. The next step should focus on the development of effective behavior modification programs and their implementation and dissemination.
The adenosine monophosphate–activated protein kinase—vacuolar adenosine triphosphatase–pH axis: A key regulator of the profibrogenic phenotype of human hepatic stellate cells

Liver fibrosis and cirrhosis are characterized by activation of hepatic stellate cells (HSCs), which is associated with higher intracellular pH (pHi). The vacuolar H+ adenosine‐triphosphatase (v‐ATPase) multisubunit complex is a key regulator of pHi homeostasis. The present work investigated the functional role of v‐ATPase in primary human HSC (hHSC) activation and its modulation by specific adenosine monophosphate–activated protein kinase (AMPK) subunits. We demonstrate that the expression of different v‐ATPase subunits was increased in in vivo and in vitro activated hHSCs compared to nonactivated hHSCs. Specific inhibition of v‐ATPase with bafilomycin and KM91104 induced a down‐regulation of the HSC fibrogenic gene profile, which coincided with increased lysosomal pH, decreased pHi, activation of AMPK, reduced proliferation, and lower metabolic activity. Similarly, pharmacological activation of AMPK by treatment with diflunisal, A769662, and ZLN024 reduced the expression of v‐ATPase subunits and profibrogenic markers. v‐ATPase expression was differently regulated by the AMPK α1 subunit (AMPKα1) and AMPKα2, as demonstrated in mouse embryo fibroblasts specifically deficient for AMPK α subunits. In addition, activation of v‐ATPase in hHSCs was shown to be AMPKα1‐dependent. Accordingly, pharmacological activation of AMPK in AMPKα1‐depleted hHSCs prevented v‐ATPase down‐regulation. Finally, we showed that v‐ATPase expression was increased in fibrotic livers from bile duct–ligated mice and in human cirrhotic livers. Conclusion: The down‐regulation of v‐ATPase might represent a promising target for the development of antifibrotic strategies. (Hepatology 2018).
A New Decidable Class of Tuple Generating Dependencies: The Triangularly-Guarded Class

In this paper we introduce a new class of tuple-generating dependencies (TGDs) called triangularly-guarded TGDs, which are TGDs with certain restrictions on the atomic derivation track embedded in the underlying rule set. We show that conjunctive query answering under this new class of TGDs is decidable. We further show that this new class strictly contains some other decidable classes such as weak-acyclic, guarded, sticky and shy, which, to the best of our knowledge, provides a unified representation of all these aforementioned classes.
On the application of higher‐order elements in the hierarchical interface‐enriched finite element method

This article introduces a new algorithm for evaluating enrichment functions in the higher‐order hierarchical interface‐enriched finite element method (HIFEM), which enables the fully mesh‐independent simulation of multiphase problems with intricate morphologies. The proposed hierarchical enrichment technique can accurately capture gradient discontinuities along materials interfaces that are in close proximity, in contact, and even intersecting with one another using nonconforming finite element meshes for discretizing the problem. We study different approaches for creating higher‐order HIFEM enrichments corresponding to six‐node triangular elements and analyze the advantages and shortcomings of each approach. The preferred method, which yields the lowest computational cost and highest accuracy, relies on a special mapping between the local and global coordinate systems for evaluating enrichment functions. A comprehensive convergence study is presented to show that this method yields similar convergence rate and precision as those of the standard FEM with conforming meshes. Finally, we demonstrate the application of the higher‐order HIFEM for simulating the thermal and deformation responses of several materials systems and engineering problems with complex geometries. Copyright © 2015 John Wiley & Sons, Ltd.
A Joint Convolutional Bidirectional LSTM Framework for Facial Expression Recognition

SUMMARY Facial expressions are generated by the actions of the facial muscles located at di ﬀ erent facial regions. The spatial dependencies of di ﬀ erent spatial facial regions are worth exploring and can improve the performance of facial expression recognition. In this letter we propose a joint convolutional bidirectional long short-term memory (JCBLSTM) framework to model the discriminative facial textures and spatial relations between di ﬀ erent regions jointly. We treat each row or column of feature maps output from CNN as individual ordered sequence and employ LSTM to model the spatial dependencies within it. Moreover, a shortcut connection for convolutional feature maps is introduced for joint feature representation. We conduct experiments on two databases to evaluate the proposed JCBLSTM method. The experimental results demonstrate that the JCBLSTM method achieves state-of-the-art performance on Multi-PIE and very competitive result on FER-2013.
Laplacian Damping for Projective Dynamics

Damping is an important ingredient in physics-based simulation of deformable objects. Recent work introduced new fast simulation methods such as Position Based Dynamics and Projective Dynamics. Explicit velocity damping methods currently used in conjunction with Position Based Dynamics or Projective Dynamics are simple and fast, but have some limitations. They may damp global motion or non-physically transport velocities throughout the simulated object. More advanced damping models do not have these limitations, but are slow to evaluate, defeating the benefits of fast solvers such as Projective Dynamics. We present a new type of damping model specifically designed for Projective Dynamics, which provides the quality of advanced damping models while adding only minimal computing overhead. The key idea is to define damping forces using Projective Dynamics’ Laplacian matrix. In a number of simulation examples we show that this damping model works very well in practice. When used with a modified Projective Dynamics solver that uses a non-dissipative implicit midpoint integrator, our damping method provides fully user-controllable damping, allowing the user to quickly produce visually pleasing and vivid animations. CCS Concepts • Computing methodologies → Physical simulation;
PhaseNet: A Deep-Neural-Network-Based Seismic Arrival Time Picking Method

As the number of seismic sensors grows, it is becoming increasingly difficult for analysts to pick seismic phases manually and comprehensively, yet such efforts are fundamental to earthquake monitoring. Despite years of improvements in automatic phase picking, it is difficult to match the performance of experienced analysts. A more subtle issue is that different seismic analysts may pick phases differently, which can introduce bias into earthquake locations. We present a deep-neural-network-based arrival-time picking method called "PhaseNet" that picks the arrival times of both P and S waves. Deep neural networks have recently made rapid progress in feature learning, and with sufficient training, have achieved super-human performance in many applications. PhaseNet uses three-component seismic waveforms as input and generates probability distributions of P arrivals, S arrivals, and noise as output. We engineer PhaseNet such that peaks in probability provide accurate arrival times for both P and S waves, and have the potential to increase the number of S-wave observations dramatically over what is currently available. This will enable both improved locations and improved shear wave velocity models. PhaseNet is trained on the prodigious available data set provided by analyst-labeled P and S arrival times from the Northern California Earthquake Data Center. The dataset we use contains more than seven million waveform samples extracted from over thirty years of earthquake recordings. We demonstrate that PhaseNet achieves much higher picking accuracy and recall rate than existing methods.
National survey on internal quality control for tumour markers in clinical laboratories in China

Introduction This survey was initiated to obtain knowledge on the current situation of internal quality control (IQC) practice for tumour markers (TMs) in China. Additionally, we tried to acquire the most appropriate quality specifications. Materials and methods This survey was a current status survey. The IQC information had been collected via online questionnaires. All of 1821 clinical laboratories which participated in the 2016 TMs external quality assessment (EQA) programme had been enrolled. The imprecision evaluation criteria were the minimal, desirable, and optimal allowable imprecisions based on biological variations, and 1/3 total allowable error (TEa) and 1/4 TEa. Results A total of 1628 laboratories answered the questionnaires (89%). The coefficients of variation (CVs) of the IQC of participant laboratories varied greatly from 1% (5th percentile) to 13% (95th percentile). More than 82% (82 - 91%) of participant laboratories two types of CVs met 1/3 TEa except for CA 19-9. The percentiles of current CVs were smaller than cumulative CVs. A number of 1240 laboratories (76%) reported their principles and systems used. The electrochemiluminescence was the most used principle (45%) and had the smallest CVs. Conclusions The performance of laboratories for TMs IQC has yet to be improved. On the basis of the obtained results, 1/3 TEa would be realistic and attainable quality specification for TMs IQC for clinical laboratories in China.
Monitoring and detecting abnormal behavior in mobile cloud infrastructure

Recently, several mobile services are changing to cloud-based mobile services with richer communications and higher flexibility. We present a new mobile cloud infrastructure that combines mobile devices and cloud services. This new infrastructure provides virtual mobile instances through cloud computing. To commercialize new services with this infrastructure, service providers should be aware of security issues. In this paper, we first define new mobile cloud services through mobile cloud infrastructure and discuss possible security threats through the use of several service scenarios. Then, we propose a methodology and architecture for detecting abnormal behavior through the monitoring of both host and network data. To validate our methodology, we injected malicious programs into our mobile cloud test bed and used a machine learning algorithm to detect the abnormal behavior that arose from these programs.
Behavioral Advertising: The Offer You Cannot Refuse

At UC Berkeley, we are informing political debates surrounding online privacy through empirical study of website behaviors. In 2009 and 2011, we surveyed top websites to determine how they were tracking consumers. We found that advertisers were using persistent tracking technologies that were relatively unknown to consumers. Two years later, we found that the num­ ber of tracking cookies expanded dramatically and that advertisers had de­ veloped new, previously unobserved tracking mechanisms that users cannot avoid even with the strongest privacy settings. These empirical observations are valuable for the political debate sur­ rounding online privacy because they inform the framing and assumptions surrounding the merits of privacy law. Our work demonstrates that advertisers use new, relatively unknown technologies to track people, specifically because consumers have not heard of these techniques. Furthermore, these technologies obviate choice mecha­ nisms that consumers exercise. In the political debate, “paternalism” is a frequently invoked objection to privacy rules. Our work inverts the assumption that privacy interventions are paternalistic while market approaches promote freedom. We empirically demonstrate that advertisers are making it impossible to avoid online track­ ing. Advertisers are so invested in the idea of a personalized web that they do not think consumers are competent to decide to reject it. We argue that policymakers should fully appreciate the idea that consumer privacy inter­
Increased vessel perfusion predicts the efficacy of immune checkpoint blockade

Immune checkpoint blockade (ICB) has demonstrated curative potential in several types of cancer, but only for a small number of patients. Thus, the identification of reliable and noninvasive biomarkers for predicting ICB responsiveness is an urgent unmet need. Here, we show that ICB increased tumor vessel perfusion in treatment-sensitive EO771 and MMTV-PyVT breast tumor as well as CT26 and MCA38 colon tumor models, but not in treatment-resistant MCaP0008 and 4T1 breast tumor models. In the sensitive tumor models, the ability of anti–cytotoxic T lymphocyte–associated protein 4 or anti–programmed cell death 1 therapy to increase vessel perfusion strongly correlated with its antitumor efficacy. Moreover, globally enhanced tumor vessel perfusion could be detected by Doppler ultrasonography before changes in tumor size, which predicted final therapeutic efficacy with more than 90% sensitivity and specificity. Mechanistically, CD8+ T cell depletion, IFN-&ggr; neutralization, or implantation of tumors in IFN-&ggr; receptor knockout mice abrogated the vessel perfusion enhancement and antitumor effects of ICB. These results demonstrated that ICB increased vessel perfusion by promoting CD8+ T cell accumulation and IFN-&ggr; production, indicating that increased vessel perfusion reflects the successful activation of antitumor T cell immunity by ICB. Our findings suggest that vessel perfusion can be used as a novel noninvasive indicator for predicting ICB responsiveness.
Efficient ternary organic solar cells with energy cascade and Foerster resonance energy transfer by doping phosphorescent small molecule

In this work, we fabricated the ternary bulk hetero junction (BHJ) polymer solar cells (PSCs) by doping a phosphorescent small molecule bis[2-(4-tertbutylphenyl)benzothiazolato-N,C2′] iridium(acetylacetonate)[(tbt)2Ir(acac)] into the conventional active layer of poly(3-hexylthiophene) (P3HT) and [6,6]-phenyl-C71-butyric acid methyl ester (PC71BM). After doping (tbt)2Ir(acac), the short circuit current and fill factor are simultaneously enhanced compared with binary device and the power conversion efficiency (PCE) of P3HT:PC71BM based ternary devices is improved from 2.99% to 4.14%. More excellent photovoltaic performance of ternary PSCs is mainly attributed to enhanced charge transportation by appropriate energy cascade alignment and enhanced exciton harvesting by Foerster resonance energy transfer from (tbt)2Ir(acac) to P3HT.
Classifying real and imaginary finger press tasks on a P300-based brain-computer interface

Brain computer interfaces based on P300 and sensory-motor rhythms are widely studied and recent advances show some interest in the combination of the two. In this paper, typical P300 paradigm is modified by adding animation guide of the finger press as a stimulus and by using different response strategies (silent counting and actual/imaginary left or right index finger press following the animation). Both P300 potentials and sensory-motor rhythms are directly exploited and discussed. Classification results showed that even under very demanding conditions, which was, 200ms inter-stimulus interval of the P300 stimuli and actual/imaginary finger press once per 1.6s, the paradigm can evoke both P300 potentials and sensory-motor rhythms simultaneously. Actual finger press increased single trial P300 selection accuracy of different subjects by 5–29.5% compared with silent counting; imaginary finger press did not increase the P300 selection accuracy apparently for most subjects except the two who were very poor at counting task. This showed by using different interface design and adopting certain mental response strategies, the ‘BCI illiteracy’ may be cured. Also imaginary task had good performance of left versus right classification (with the best subject reached 81.1% of accuracy), which is an additional information that can be used to improve system performance.
Development of the boston retinal prosthesis

A small, hermetic, wirelessly-controlled retinal prosthesis was developed for pre-clinical studies in Yucatan mini-pigs. The device was implanted on the outside of the eye in the orbit, and it received both power and data wirelessly from external sources. The prosthesis drove a sub-retinal thin-film array of sputtered iridium oxide stimulating electrodes. The implanted device included a hermetic titanium case containing the 16-channel stimulator chip and discrete circuit components. Feedthroughs in the hermetic case connected the chip to secondary power- and data-receiving coils, which coupled to corresponding external power and data coils driven by a power amplifier. Power was delivered by a 500 KHz carrier, and data were delivered by frequency shift keying. Stimulation pulse strength, duration and frequency were programmed wirelessly from an external computer system. Through an ‘outbound’ telemetry channel, electrode impedances were monitored by an on-board analog to digital converter that sampled the output voltage waveforms. The final assembly was tested in vitro in physiological saline and in vivo in two mini-pigs for up to three months by measuring stimulus artifacts generated by the implant's current drivers.
Incremental scene understanding on dense SLAM

We present an architecture for online, incremental scene modeling which combines a SLAM-based scene understanding framework with semantic segmentation and object pose estimation. The core of this approach comprises a probabilistic inference scheme that predicts semantic labels for object hypotheses at each new frame. From these hypotheses, recognized scene structures are incrementally constructed and tracked. Semantic labels are inferred using a multi-domain convolutional architecture which operates on the image time series and which enables efficient propagation of features as well as robust model registration. To evaluate this architecture, we introduce a large-scale RGB-D dataset JHUSEQ-25 as a new benchmark for the sequence-based scene understanding in complex and densely cluttered scenes. This dataset contains 25 RGB-D video sequences with 100,000 labeled frames in total. We validate our method on this dataset and demonstrate improved performance of semantic segmentation and 6-DoF object pose estimation compared with methods based on the single view.