Miracle-dz/UniFAR-FTUs huggingface dataset:
The Design of Acoustic Logging Ring Array Based on Genetic Algorithm

Conventional single acoustic sensor launch has no directivity, leading to too much energy loss. This paper use genetic algorithm to design the suitable array weighting coefficient, it can control the circle array acoustic radiation of the azimuth and the sidelobe level, The use of emission array facilitate in excited effectively and reduce the energy loss of p-wave. The circle array model is simulated by the finite element software comsol under the weighted coefficient of radiation sound wave, and we analyze the circle array radiation directivity of acoustic logging in various modes of wave receiving the influence of amplitude and time of arrival. The results show that the width and direction of the main acoustic beam can be designed according to different actual conditions, so long as the appropriate magnitude of the excitation signal is applied to the array of rings. The use of ring array can obviously improve the measurement quality of acoustic logging. This paper provides a theoretical basis for the application of acoustic radiators in petroleum exploration.
Selection and Characterization of a DNA Aptamer Specifically Targeting Human HECT Ubiquitin Ligase WWP1

Nucleic acid aptamers hold promise as therapeutic tools for specific, tailored inhibition of protein targets with several advantages when compared to small molecules or antibodies. Nuclear WW domain containing E3 ubiquitin ligase 1 (WWP1) ubiquitin ligase poly-ubiquitinates Runt-related transcription factor 2 (Runx2), a key transcription factor associated with osteoblast differentiation. Since WWP1 and an adapter known as Schnurri-3 are negative regulators of osteoblast function, the disruption of this complex has the potential to increase bone deposition for osteoporosis therapy. Here, we develop new DNA aptamers that bind and inhibit WWP1 then investigate efficacy in an osteoblastic cell culture. DNA aptamers were selected against three different truncations of the HECT domain of WWP1. Aptamers which bind specifically to a C-lobe HECT domain truncation were observed to enrich during the selection procedure. One particular DNA aptamer termed C3A was further evaluated for its ability to bind WWP1 and inhibit its ubiquitination activity. C3A showed a low µM binding affinity to WWP1 and was observed to be a non-competitive inhibitor of WWP1 HECT ubiquitin ligase activity. When SaOS-2 osteoblastic cells were treated with C3A, partial localization to the nucleus was observed. The C3A aptamer was also demonstrated to specifically promote extracellular mineralization in cell culture experiments. The C3A aptamer has potential for further development as a novel osteoporosis therapeutic strategy. Our results demonstrate that aptamer-mediated inhibition of protein ubiquitination can be a novel therapeutic strategy.
Prelaunch Demand Estimation

Demand estimation is important for new-product strategies, but is challenging in the absence of actual sales data. We develop a cost-effective method to estimate the demand of new products based on incentive-aligned choice experiments. Our premise is that there exists a structural relationship between manifested demand and the probability of consumer choice being realized. We illustrate the mechanism using a theory model, in which consumers learn their product valuation through costly effort and their effort incentive depends on the realization probability. We run a large-scale field experiment on a mobile game platform, where we randomize the price and realization probability when selling a new product. The data support our theoretical prediction and the decision effort mechanism. We then estimate a structural model of consumer choice. The structural estimates allow us to infer actual demand with reasonable accuracy using inexpensive choice experiments with small to moderate realization probabilities.
Human's Capability to Discriminate Spatial Forces at the Big Toe

A key factor for reliable object manipulation is the tactile information provided by the skin of our hands. As this sensory information is so essential in our daily life it should also be provided during teleoperation of robotic devices or in the control of myoelectric prostheses. It is well-known that feeding back the tactile information to the user can lead to a more natural and intuitive control of robotic devices. However, in some applications it is difficult to use the hands as natural feedback channels since they may already be overloaded with other tasks or, e.g., in case of hand prostheses not accessible at all. Many alternatives for tactile feedback to the human hand have already been investigated. In particular, one approach shows that humans can integrate uni-directional (normal) force feedback at the toe into their sensorimotor-control loop. Extending this work, we investigate the human's capability to discriminate spatial forces at the bare front side of their toe. A state-of-the-art haptic feedback device was used to apply forces with three different amplitudes—2 N, 5 N, and 8 N—to subjects' right big toes. During the experiments, different force stimuli were presented, i.e., direction of the applied force was changed, such that tangential components occured. In total the four directions up (distal), down (proximal), left (medial), and right (lateral) were tested. The proportion of the tangential force was varied corresponding to a directional change of 5° to 25° with respect to the normal force. Given these force stimuli, the subjects' task was to identify the direction of the force change. We found the amplitude of the force as well as the proportion of tangential forces to have a significant influence on the success rate. Furthermore, the direction right showed a significantly different successrate from all other directions. The stimuli with a force amplitude of 8 N achieved success rates over 89% in all directions. The results of the user study provide evidence that the subjects were able to discriminate spatial forces at their toe within defined force amplitudes and tangential proportion.
Hybrid finite element for analysis of functionally graded beams

ABSTRACT A hybrid finite element model is presented, where stiffness and mass distributions over a beam with functionally graded material (FGM) are accurately modeled for both elastic and inelastic material responses. Von Mises and Drucker-Prager plasticity models are implemented for metallic and ceramic parts of FGM, respectively. Three-dimensional stress-strain relations are solved by a general closest point projection algorithm, and then condensed to the dimensions of the beam element. Numerical examples and verification studies on a proposed element demonstrate accuracy and robustness under inelastic material response as well as capturing fundamental, higher, and mix modes of vibration frequencies and shapes.
Accelerating Prototype-Based Drug Discovery using Conditional Diversity Networks

Designing a new drug is a lengthy and expensive process. As the space of potential molecules is very large (10 23 - 10 60 ), a common technique during drug discovery is to start from a molecule which already has some of the desired properties. An interdisciplinary team of scientists generates hypothesis about the required changes to the prototype. In this work, we develop an algorithmic unsupervised-approach that automatically generates potential drug molecules given a prototype drug. We show that the molecules generated by the system are valid molecules and significantly different from the prototype drug. Out of the compounds generated by the system, we identified 35 FDA-approved drugs. As an example, our system generated Isoniazid - one of the main drugs for Tuberculosis. The system is currently being deployed for use in collaboration with pharmaceutical companies to further analyze the additional generated molecules.
Research of Classification Impact Factors Mining Based on the Contrast Pattern Equivalence Classes

In the domain of multi-label data and big data, it is hard for most classification methods to generate explainable classify rules, which makes it harder to get impact factors for classification. In this paper, contrast pattern equivalence class was discussed and mined to determine main impact factors for different classes, considering combination of frequent pattern mining and data classification. The rationality and feasibility to determine classification impact factors through contrast pattern equivalence classes mining was theoretically analyzed. Also the mine process and result analysis was shown through an experiment on the real dataset. Experimental results show the validity of the method proposed.
PlaceComm: A framework for context-aware applications in place-based virtual communities

There is increasing interest in context-aware applications, ranging from traffic routing, location-based services, friend finding, context-aware messaging, virtual tour guides, to physical world search. We make three observations: (i) many context-aware applications use knowledge about the individuals (and groups of people), places and objects within a particular place, that is, they are place-based, (ii) such knowledge about a place can be shared by different applications and reused, without each application having the same knowledge reengineered (there is at least overlap among such knowledge across different applications), and (iii) applications can not only be consumers of knowledge but also be contributors of knowledge about the place. We propose the PlaceComm framework for building such context-aware applications with “place” as a key abstraction, where place knowledge can be collected and shared. The knowledge is structured using an ontology called the Place-Based Virtual Community ontology. Our framework utilizes a multiagent architecture for modularity, separation of concerns and extensibility. We also describe three applications built using our approach: PlaceGuide, PlaceAware and PlaceSense.
Multi-Views Fusion CNN for Left Ventricular Volumes Estimation on Cardiac MR Images

<italic>Objective</italic>: Left ventricular (LV) volume estimation is a critical procedure for cardiac disease diagnosis. The objective of this paper is to address a direct LV volume prediction task. <italic>Methods</italic>: In this paper, we propose a direct volume prediction method based on the end-to-end deep convolutional neural networks. We study the end-to-end LV volume prediction method in items of the data preprocessing, network structure, and multiview fusion strategy. The main contributions of this paper are the following aspects. First, we propose a new data preprocessing method on cardiac magnetic resonance (CMR). Second, we propose a new network structure for end-to-end LV volume estimation. Third, we explore the representational capacity of different slices and propose a fusion strategy to improve the prediction accuracy. <italic>Results</italic>: The evaluation results show that the proposed method outperforms other state-of-the-art LV volume estimation methods on the open accessible benchmark datasets. The clinical indexes derived from the predicted volumes agree well with the ground truth (<inline-formula> <tex-math notation="LaTeX">${\rm{EDV:R}}^{{\rm 2}}={\text{0.974}}$</tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">${\rm{RMSE\,}}= {\text{9.6}}{\rm{\,ml}}$</tex-math></inline-formula>; <inline-formula> <tex-math notation="LaTeX">${\rm{ESV:R}}^{{\rm 2}}={\text{0.976}}$</tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">${\rm{RMSE}}= {\text{7.1}}\,{\text{ml}}$</tex-math></inline-formula>; <inline-formula> <tex-math notation="LaTeX">${\rm{EF:R}}^{{\rm 2}} ={\text{0.828}}$</tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">${\rm{RMSE}}= {\text{4.71}}\% $</tex-math></inline-formula>). <italic>Conclusion</italic>: Experimental results prove that the proposed method may be useful for the LV volume prediction task. <italic> Significance</italic>: The proposed method not only has application potential for cardiac diseases screening for large-scale CMR data, but also can be extended to other medical image research fields.
Weak localization in electric-double-layer gated few-layer graphene

We induce surface carrier densities up to ∼7⋅1014 cm−2 in few-layer graphene devices by electric double layer gating with a polymeric electrolyte. In 3-, 4- and 5-layer graphene below 20–30 K we observe a logarithmic upturn of resistance that we attribute to weak localization in the diffusive regime. By studying this effect as a function of carrier density and with ab initio calculations we derive the dependence of transport, intervalley and phase coherence scattering lifetimes on total carrier density. We find that electron–electron scattering in the Nyquist regime is the main source of dephasing at temperatures lower than 30 K in the ∼1013 cm−2 to ∼7⋅1014 cm−2 range of carrier densities. With the increase of gate voltage, transport elastic scattering is dominated by the competing effects due to the increase in both carrier density and charged scattering centers at the surface. We also tune our devices into a crossover regime between weak and strong localization, indicating that simultaneous tunability of both carrier and defect density at the surface of electric double layer gated materials is possible.
Antimicrobial Effect of Probiotics against Common Pathogens

The antimicrobial or antagonistic activity of probiotics is an important property that includes the production of antimicrobial compounds, competitive exclusion of pathogens, enhancement of the intestinal barrier function and others. There are many methods to ascertain probiotic properties, including various in vitro and in vivo methods. The in vivo methods include various modifications of the spot‐on lawn assay, agar well diffusion assay (AWDA), co‐culturing methods, usage of cell lines and others. In many cases in vitro antagonist activity is observed, but in real settings it is not observed. The in vivo methods mainly used are animal models; however, their use is being restricted according to the European legislation OJ L136. The justification of animal models is also questionable as the results of studies on animals do not predict the same results for humans. The use of replacement alternative methods, for example incorporating human cells and tissues, avoids such confounding variables. Most important studies are double‐ blinded randomized clinical trials; however, these studies are difficult to perform as it is not easy to achieve uniform conditions. There is a clear need for more elaborate assays that would better represent the complex interactions between the probiotics and the final host. This complex situation is a challenge for scientists.
Prior Independent Equilibria and Linear Multi-dimensional Bayesian Games

We show that a Bayesian strategy map profile is a Bayesian Nash Equilibrium independent of any prior if and only if the Bayesian strategy map profile, evaluated at any type profile, is the Nash equilibrium of the so-called local deterministic game corresponding to that type profile. We call such a Bayesian game type-regular. We then show that an m-dimensional n-agent Bayesian game whose utilities are linearly dependent on the types of the agents is equivalent, following a normalisation of the type space of each agent into the (m-1)-simplex, to a simultaneous competition in nm so-called basic n-agent games. If the game is own-type-linear, i.e., the utility of each player only depends linearly on its own type, then the Bayesian game is equivalent to a simultaneous competition in m basic n-agent games, called a multi-game. We then prove that an own-type-linear Bayesian game is type-regular if it is type-regular on the vertices of the (m-1)-simplex, a result which provides a large class of type-regular Bayesian maps. The class of m-dimensional own-type-linear Bayesian games can model, via their equivalence with multi-games, simultaneous decision-making in m different environments. We show that a two dimensional own-type-linear Bayesian game can be used to give a new model of the Prisoner's Dilemma (PD) in which the prosocial tendencies of the agents are considered as their types and the two agents play simultaneously in the PD as well as in a prosocial game. This Bayesian game addresses the materialistic and the prosocial tendencies of the agents. Similarly, we present a new two dimensional Bayesian model of the Trust game in which the type of the two agents reflect their prosocial tendency or trustfulness, which leads to more reasonable Nash equilibria. We finally consider an example of such multi-environment decision making in production by several companies in multi-markets.
RE: Reliable Email

The explosive growth in unwanted email has prompted the development of techniques for the rejection of email, intended to shield recipients from the onerous task of identifying the legitimate email in their inboxes amid a sea of spam. Unfortunately, widely used content-based filtering systems have converted the spam problem into a false positive one: email has become unreliable. Email acceptance techniques complement rejection ones; they can help prevent false positives by filing email into a user's inbox before it is considered for rejection. Whitelisting, whereby recipients accept email from some set of authorized senders, is one such acceptance technique. We present Reliable Email (RE:), a new whitelisting system that incurs zero false positives among socially connected users. Unlike previous whitelisting systems, which require that whitelists be populated manually, RE: exploits friend-of-friend relationships among email correspondents to populate whitelists automatically. To do so, RE: permits an email's recipient to discover whether other email users have whitelisted the email's sender, while preserving the privacy of users' email contacts with cryptographic private matching techniques. Using real email traces from two sites, we demonstrate that RE: renders a significant fraction of received email reliable. Our evaluation also shows that RE: can prevent up to 88% of the false positives incurred by a widely deployed email rejection system, at modest computational cost.
BIAS AND VARIABILITY IN IMAGE-BASED VOLUMETRIC YTTRIUM-90 DOSIMETRY

vi List of Figures . xvi List of Tables . xxi Chapter 1: Introduction . 1 1.1. Background . 1 1.2. Purpose statement . 3 1.3. Hypothesis and aims . 5 1.3. 1. Central hypothesis . 5 1.3. 2. Specific aim 1. 5 1.3. 3. Specific aim 2. 6 1.3. 4. Specific aim 3. 8 1.3. 5. Specific aim 4. 9
Association of follow-up infarct volume with functional outcome in acute ischemic stroke: a pooled analysis of seven randomized trials

Background Follow-up infarct volume (FIV) has been recommended as an early indicator of treatment efficacy in patients with acute ischemic stroke. Questions remain about the optimal imaging approach for FIV measurement. Objective To examine the association of FIV with 90-day modified Rankin Scale (mRS) score and investigate its dependency on acquisition time and modality. Methods Data of seven trials were pooled. FIV was assessed on follow-up (12 hours to 2 weeks) CT or MRI. Infarct location was defined as laterality and involvement of the Alberta Stroke Program Early CT Score regions. Relative quality and strength of multivariable regression models of the association between FIV and functional outcome were assessed. Dependency of imaging modality and acquisition time (≤48 hours vs >48 hours) was evaluated. Results Of 1665 included patients, 83% were imaged with CT. Median FIV was 41 mL (IQR 14–120). A large FIV was associated with worse functional outcome (OR=0.88(95% CI 0.87 to 0.89) per 10 mL) in adjusted analysis. A model including FIV, location, and hemorrhage type best predicted mRS score. FIV of ≥133 mL was highly specific for unfavorable outcome. FIV was equally strongly associated with mRS score for assessment on CT and MRI, even though large differences in volume were present (48 mL (IQR 15–131) vs 22 mL (IQR 8–71), respectively). Associations of both early and late FIV assessments with outcome were similar in strength (ρ=0.60(95% CI 0.56 to 0.64) and ρ=0.55(95% CI 0.50 to 0.60), respectively). Conclusions In patients with an acute ischemic stroke due to a proximal intracranial occlusion of the anterior circulation, FIV is a strong independent predictor of functional outcome and can be assessed before 48 hours, oneither CT or MRI.
SmoothOperator: Reducing Power Fragmentation and Improving Power Utilization in Large-scale Datacenters

With the ever growing popularity of cloud computing and web services, Internet companies are in need of increased computing capacity to serve the demand. However, power has become a major limiting factor prohibiting the growth in industry: it is often the case that no more servers can be added to datacenters without surpassing the capacity of the existing power infrastructure. In this work, we first investigate the power utilization in Facebook datacenters. We observe that the combination of provisioning for peak power usage, highly fluctuating traffic, and multi-level power delivery infrastructure leads to significant power budget fragmentation problem and inefficiently low power utilization. To address this issue, our insight is that heterogeneity of power consumption patterns among different services provides opportunities to re-shape the power profile of each power node by re-distributing services. By grouping services with asynchronous peak times under the same power node, we can reduce the peak power of each node and thus creating more power head-rooms to allow more servers hosted, achieving higher throughput. Based on this insight, we develop a workload-aware service placement framework to systematically spread the service instances with synchronous power patterns evenly under the power supply tree, greatly reducing the peak power draw at power nodes. We then leverage dynamic power profile reshaping to maximally utilize the headroom unlocked by our placement framework. Our experiments based on real production workload and power traces show that we are able to host up to 13% more machines in production, without changing the underlying power infrastructure. Utilizing the unleashed power headroom with dynamic reshaping, we achieve up to an estimated total of 15% and 11% throughput improvement for latency-critical service and batch service respectively at the same time, with up to 44% of energy slack reduction.
Evaluating Heavy Metal Stress Levels in Rice Based on Remote Sensing Phenology

Heavy metal pollution of croplands is a major environmental problem worldwide. Methods for accurately and quickly monitoring heavy metal stress have important practical significance. Many studies have explored heavy metal stress in rice in relation to physiological function or physiological factors, but few studies have considered phenology, which can be sensitive to heavy metal stress. In this study, we used an integrated Normalized Difference Vegetation Index (NDVI) time-series image set to extract remote sensing phenology. A phenological indicator relatively sensitive to heavy metal stress was chosen from the obtained phenological periods and phenological parameters. The Dry Weight of Roots (WRT), which directly affected by heavy metal stress, was simulated by the World Food Study (WOFOST) model; then, a feature space based on the phenological indicator and WRT was established for monitoring heavy metal stress. The results indicated that the feature space can distinguish the heavy metal stress levels in rice, with accuracy greater than 95% for distinguishing the severe stress level. This finding provides scientific evidence for combining rice phenology and physiological characteristics in time and space, and the method is useful to monitor heavy metal stress in rice.