Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional analysis of tanshinone IIA that blocks the redox function of human apurinic/apyrimidinic endonuclease 1/redox factor-1

Apurinic/apyrimidinic endonuclease 1/redox factor-1 (APE1/Ref-1) is a multifunctional protein possessing both DNA repair and redox regulatory activities. It has been shown that blocking redox function leads to genotoxic, antiangiogenic, cytostatic, and proapoptotic effects in cells. Therefore, the selective inhibitors against APE1’s redox function can be served as potential pharmaceutical candidates in cancer therapeutics. In the present study, we identified the biological specificity of the Chinese herbal compound tanshinone IIA (T2A) in blocking the redox function of APE1. Using dual polarization interferometry, the direct interaction between APE1 and T2A was observed with a KD value at subnanomolar level. In addition, we showed that T2A significantly compromised the growth of human cervical cancer and colon cancer cells. Furthermore, the growth-inhibitory or proapoptotic effect of T2A was diminished in APE1 knockdown or redox-deficient cells, suggesting that the cytostatic effect of T2A might be specifically through inhibiting the redox function of APE1. Finally, T2A pretreatment enhanced the cytotoxicity of ionizing radiation or other chemotherapeutic agents in human cervical cancer and colon cancer cell lines. The data presented herein suggest T2A as a promising bioactive inhibitor of APE1 redox activity.
Bridge Defect Diagnosis with Physical Information

Circuit behavior in the presence of bridge defects is affected by three factors: bridge resistance, drive strength of bridged signals and the threshold voltages of downstream gates. Current bridge defect diagnosis methods either ignore all of these factors or consider drive strengths and/or threshold voltages only. Specifically, existing diagnosis methods have not considered the effect caused by bridge resistance. So the diagnosis results from current procedures may not be as accurate as possible. In this paper, we present a bridge defect diagnosis method taking all three factors into account. Experiments conducted on benchmark circuits and one industrial design demonstrate that the proposed method can achieve a very high diagnosis accuracy and resolution.
Statistical language model based on a hierarchical approach: MCnv

In this paper, we propose a new language model based on dependent word sequences organized in a multi-level hierarchy. We call this model MC$_{n}^{\nu}$, where $n$ is the maximum number of words in a sequence and $\nu$ is the maximum number of levels. The originality of this model is its capacity to take into account dependent variable-length sequences for very large vocabularies. In order to discover the variable-length sequences and to build the hierarchy, we use a set of $233$ syntactic classes extracted from the $8$ French elementary grammatical classes. The MC$_{n}^{\nu}$ model learns hierarchical word patterns and uses them to reevaluate and filter the n-best utterance hypotheses outputted by our speech recognizer MAUD. The model has been trained on a corpus of $43$ million words extracted from a French newspaper and uses a vocabulary of $20000$ words. Tests have been conducted on $300$ sentences. Results achieved $17\%$ decrease in perplexity compared to an interpolated class trigram model. Rescoring the original n-best hypotheses resulted in an improvement of $5\%$ in accuracy.
A multi-project decision process simulation of defense contractor behavior (II)

This paper describes the design and initial validation of a computerized decision process model simulating the operating environment, behavior and performance of defense contractors. The conceptual foundations of this research are presented in Cohen, Lewin and Morey (1979). The model employs feedback adaption and search mechanisms to simulate the internal decision making structure of defense contractors at the project, corporate and DOD levels. The objective of this research is to develop a capability to model the impact of various contract incentive schemes on the performance of DOD contractors.
PERMANENT GENETIC RESOURCES: Eighteen new polymorphic microsatellite markers for the endangered Florida manatee, Trichechus manatus latirostris

Here we describe 18 polymorphic microsatellite loci for Trichechus manatus latirostris (Florida manatee), isolated using a polymerase chain reaction‐based technique. The number of alleles at each locus ranged from two to four (mean = 2.5) in specimens from southwest (n = 58) and northeast (n = 58) Florida. Expected and observed heterozygosities ranged from 0.11 to 0.67 (mean = 0.35) and from 0.02 to 0.78 (mean = 0.34), respectively. Departures from Hardy–Weinberg equilibrium occurred at two loci. There was no evidence of genotypic disequilibrium for any pair of loci. For individual identification, mean random‐mating and θ‐corrected match probabilities were 9.36 × 10−7 and 1.95 × 10−6, respectively.
Control of Position and Bending-Torsion-Coupled Vibration of Rotating Elastic Plate Using Double Tendon Mechanisms

For a control method of position and bending-torsion-coupled vibration of a rotating plate, a control method using double trapezoid tendon mechanisms is presented in this study. The proposed trapezoid tendon mechanisms consist of two control sticks, two pairs of wires and two driving sticks individually driven by motors. First, the modeling of the proposed mechanism is carried out by applying the Lagrange's equation method and the modal expansion technique. Secondly, by formulating the crite rion function to take into account the square sum of the rotation angle, the bending, stress and the torsion angle of a thin plate, the optimal control law is derived. Finally, in order to investigate the usefulness of the mechanism, computer simulations and experiments were carried out. To summarize the results, it was demonstrated that the proposed control mechanism is useful for the controls of both the positioning and the vibrations.
Geography of plant mating system 1 2 No association between plant mating system and geographic 3 range overlap 1 4 5

5 Dena Grossenbacher, Ryan Briscoe Runquist, Emma E. Goldberg, and Yaniv 6 Brandvain 7 8 Department of Plant Biology, University of Minnesota, St. Paul, MN, 55108, USA; Department 9 of Ecology, Evolution and Behavior, University of Minnesota, St. Paul, MN, 55108, USA 10 11 Corresponding author: Dena Grossenbacher, Department of Plant Biology, University 12 of Minnesota, St. Paul, MN, 55108, USA; 530-204-7824; dgrossen@umn.edu 13 14 rbriscoe@umn.edu, eeg@umn.edu, ybrandva@umn.edu 15 16 17 18 19 20 21
Knockdown of ttc26 disrupts ciliogenesis of the photoreceptor cells and the pronephros in zebrafish

The article describes characterization of the cilia protein Ttc26. The data show that Ttc26 is localized in the transition zone of primary cilia and photoreceptor cells. Knockdown of Ttc26 produced defective cilia in murine inner medullary collecting duct 3 cells and ciliogenesis defects in retinal photoreceptor and motile cilia in the pronephros in zebrafish.
What you are is when you are: the temporal dimension of feature types in location-based social networks

Feature types play a crucial role in understanding and analyzing geographic information. Usually, these types are defined, standardized, and controlled by domain experts and cover geographic features on the mesoscale level, e.g., populated places, forests, or lakes. While feature types also underlie most Location-Based Services (LBS), assigning a consistent typing schema for Points Of Interest (POI) across different data sets is challenging. In case of Volunteered Geographic Information (VGI), types are assigned as tags by a heterogeneous community with different backgrounds and applications in mind. Consequently, VGI research is shifting away from data completeness and positional accuracy as quality measures towards attribute accuracy. As tags can be assigned by everybody and have no formal or stable definition, we propose to study category tags via indirect observations. We extract user check-ins from massive real-world data crawled from Location-based Social Networks to understand the temporal dimension of Points Of Interest. While users may assign different category tags to places, we argue that their temporal characteristics, e.g., opening times, will show distinguishable patterns.
Analyzing Training Dependencies and Posterior Fusion in Discriminant Classification of Apnea Patients Based on Sustained and Connected Speech

We present a novel approach using both sustained vowels and connected speech, to detect obstructive sleep apnea (OSA) cases within a homogeneous group of speakers. The proposed scheme is based on state-of-the-art GMM-based classifiers, and acknowledges specifically the way in which acoustic models are trained on standard databases, as well as the complexity of the resulting models and their adaptation to specific data. Our experimental database contains a suitable number of utterances and sustained speech from healthy (i.e control) and OSA Spanish speakers. Finally, a 25.1% relative reduction in classification error is achieved when fusing continuous and sustained speech classifiers. Index Terms: obstructive sleep apnea (OSA), gaussian mixture models (GMMs), background model (BM), classifier fusion.
On countering online dictionary attacks with login histories and humans-in-the-loop

Automated Turing Tests (ATTs), also known as human-in-the-loop techniques, were recently employed in a login protocol by Pinkas and Sander (2002) to protect against online password-guessing attacks. We present modifications providing a new history-based login protocol with ATTs, which uses failed-login counts. Analysis indicates that the new protocol offers opportunities for improved security and user friendliness (fewer ATTs to legitimate users) and greater flexibility (e.g., allowing protocol parameter customization for particular situations and users). We also note that the Pinkas--Sander and other protocols involving ATTs are susceptible to minor variations of well-known middle-person attacks. We discuss complementary techniques to address such attacks, and to augment the security of the original protocol.
Theano: A CPU and GPU Math Compiler in Python

Theano is a compiler for mathematical expressions in Python that combines the convenience of NumPy's syntax with the speed of optimized native machine language. The user composes mathematical expressions in a high-level description that mimics NumPy's syntax and semantics, while being statically typed and functional (as opposed to imperative). These expressions allow Theano to provide symbolic differentiation. Before performing computation, Theano optimizes the choice of expressions, translates them into C++ (or CUDA for GPU), compiles them into dynamically loaded Python modules, all automatically. Common machine learn- ing algorithms implemented with Theano are from 1:6 to 7:5 faster than competitive alternatives (including those implemented with C/C++, NumPy/SciPy and MATLAB) when compiled for the CPU and between 6:5 and 44 faster when compiled for the GPU. This paper illustrates how to use Theano, outlines the scope of the compiler, provides benchmarks on both CPU and GPU processors, and explains its overall design.
An efficient online Adaptive Sampling strategy for Matrix Completion

Matrix Completion (MC) i.e., estimating the missing values of an unknown matrix based on limited information, has been a prominent topic of study in the last decades. In this paper, we focus more precisely on a little-known aspect of MC, namely how the recommendation of new entries can help improve the accuracy of the reconstruction. We present an efficient online algorithm to solve the MC task, and propose an Adaptive Sampling under Smoothness Assumption (AdSSA) strategy, which is suitable for operation on smooth low-rank matrices. This technique is able to predict iteratively which entries are the most informative. Our numerical examples illustrate that AdSSA performs significantly better than the Uniform Random Sampling (URS) and the Query by Committee (QbC). In addition, AdSSA algorithm can be straightforwardly implemented in an online and efficient manner, which constitutes another advantage.
Optimal Resource Allocation and Policy Formulation in Loosely-Coupled Markov Decision Processes

The problem of optimal policy formulation for teams of resource-limited agents in stochastic environments is composed of two strongly-coupled subproblems: a resource allocation problem and a policy optimization problem. We show how to combine the two problems into a single constrained optimization problem that yields optimal resource allocations and policies that are optimal under these allocations. We model the system as a multiagent Markov decision process (MDP), with social welfare of the group as the optimization criterion. The straightforward approach of modeling both the resource allocation and the actual operation of the agents as a multiagent MDP on the joint state and action spaces of all agents is not feasible, because of the exponential increase in the size of the state space. As an alternative, we describe a technique that exploits problem structure by recognizing that agents are only loosely-coupled via the shared resource constraints. This allows us to formulate a constrained policy optimization problem that yields optimal policies among the class of realizable ones given the shared resource limitations. Although our complexity analysis shows the constrained optimization problem to be NP-complete, our results demonstrate that, by exploiting problem structure and via a reduction to a mixed integer program, we are able to solve problems orders of magnitude larger than what is possible using a traditional multiagent MDP formulation.
Risky Human Capital and Deferred Capital Income Taxation

We study the structure of optimal wedges and capital taxes in a dynamic Mirrlees economy with endogenous distribution of skills. Human capital is a private, stochastic state variable that drives the skill process of each individual. Building on the findings of the labor literature, we construct a tractable life-cycle model of human capital evolution with risky investment and stochastic depreciation. In this setting, we demonstrate the optimality of (a) a human capital premium, i.e., an excess return on human capital relative to physical capital, (b) a large intertemporal wedge early in the life-cycle, and (c) a non-zero intratemporal wedge even at the top of the skill distribution at all dates except the last date in the life-cycle. The main implication for the structure of optimal linear capital taxes is the necessity of deferred taxation of physical capital. The average marginal tax rate on physical capital held in every period is zero in present value. However, expected capital tax payments do not equal zero in every period. Necessarily, agents face negative expected capital tax payments early in the life-cycle and positive expected capital tax payments late in the life-cycle.
Exploiting Silhouette Descriptors and Synthetic Data for Hand Gesture Recognition

This paper proposes a novel real-time hand gesture recognition scheme explicitly targeted to depth data. The hand silhouette is ﬁrstly extracted from the acquired data and then two ad-hoc feature sets are computed from this representation. The ﬁrst is based on the local curvature of the hand contour, while the second represents the thickness of the hand region close to each contour point using a distance transform. The two feature sets are rearranged in a three dimensional data structure representing the values of the two features at each contour location and then this representation is fed into a multi-class Support Vector Machine. The classiﬁer is trained on a synthetic dataset generated with an ad-hoc rendering system developed for the purposes of this work. This approach allows a fast construction of the training set without the need of manually acquiring large training datasets. Experimental results on real data show how the approach is able to achieve a 90% accuracy on a typical hand gesture recognition dataset with very limited computational resources.
Electrical and Optical Enhancement Properties of Metal / Semimetal Nanostructures for Metal Oxide UV Photodetectors 36

UV photodetectors have been investigated for various commercial and military applications, such as secure space-to-space communications, pollution monitoring, water sterilization, flame sensing, and early missile plume detection [1]. To date, epitaxially grown or bulk wide bandgap semiconductors such as GaN, AlN, AlGaN, C (diamond), and SiC have been used for ultraviolet detection [2–12]. Fabrication of devices from these materials is often expensive with intricate processes. Also organic semiconductor materials are an attractive alternative [13, 14], though they lack the carrier mobility of inorganic semiconductors. Metal oxide semiconductor nanomaterials have the advantages of low processing cost, ease of fabrication, a large surface-to-volume ratio with carrier and photon confinement, and amenability to surface functionalization for hybrid inorganic–organic configurations. Furthermore, the unique combination of the carrier transport mechanism and oxygen adsorption/desorption processes on the nanostructures surface leads to a high internal gain. However, they also lead to slow transient response with response time on the order of seconds. Significant enhancement of photodetector performance can be enabled by layers of metal/semimetal nanostructures. The trade-off between sensitivity and time response may be significantly reduced with careful design of metallic nanostructures relative to metal oxide active regions. The primary mechanisms for enhancement include surface plasmon resonance and carrier transfer to highly conductive materials. Details of the fundamental concepts, parameters of influence, and comparisons of enhanced devices are presented.
Flow velocity profile measurement of scattering liquid using Doppler optical coherence tomography

The aim of this study was to measure the velocity and velocity profile of 0.3% Intralipid mixture in a 1.5-mm thick glass capillary using Doppler Optical Coherence Tomography (DOCT). First, while still empty, the dimensions of the capillary were measured. The outer diameter was 1.50 mm ± 0.01 mm while the lumen diameter was 1.01 ± 0.01 mm. Then, having filled the capillary with 0.3% solution, the lumen diameter was measured again. The mean refractive index of the solution was calculated and turned out to be 1.36 ± 0.01 mm. During the next stage, flow measurements were performed at an angle of 88° between the illuminating beam and the velocity vector of the fluid. The velocity profile, based on a set of 10 measurements, was calculated from the DOCT signal using a discrete Fourier transform in 32 sections of the capillary. The maximum velocity, located in the middle part of the capillary, was 0.256 ± 0.035 m/s. The results show that the flow velocity profile of 0.3% Intralipid solution can be obtained from a glass capillary.
Greedy Gossip With Eavesdropping

This paper presents greedy gossip with eavesdropping (GGE), a novel randomized gossip algorithm for distributed computation of the average consensus problem. In gossip algorithms, nodes in the network randomly communicate with their neighbors and exchange information iteratively. The algorithms are simple and decentralized, making them attractive for wireless network applications. In general, gossip algorithms are robust to unreliable wireless conditions and time varying network topologies. In this paper, we introduce GGE and demonstrate that greedy updates lead to rapid convergence. We do not require nodes to have any location information. Instead, greedy updates are made possible by exploiting the broadcast nature of wireless communications. During the operation of GGE, when a node decides to gossip, instead of choosing one of its neighbors at random, it makes a greedy selection, choosing the node which has the value most different from its own. In order to make this selection, nodes need to know their neighbors' values. Therefore, we assume that all transmissions are wireless broadcasts and nodes keep track of their neighbors' values by eavesdropping on their communications. We show that the convergence of GGE is guaranteed for connected network topologies. We also study the rates of convergence and illustrate, through theoretical bounds and numerical simulations, that GGE consistently outperforms randomized gossip and performs comparably to geographic gossip on moderate-sized random geometric graph topologies.
Tracking articulated objects in real-time range image sequences

A simple algorithm for tracking the pose of articulated objects in real-time range image sequences is proposed. This method models each target segment as a planar patch bounded by the convex hull of two circles, and utilizes both edge-like and region-like information in matching the model to the target. It uses hard constraints for joint attachment and is designed to be robust to occlusions and missing data. Experimental results are presented in which a human arm is successfully tracked over 26 frames of real, video-rate range imagery.
Thermal stability of electrodeposited nanocrystalline nickel and iron–nickel alloys

Abstract The thermal stability of electrodeposited nanocrystalline nickel and iron–nickel alloys has been studied using TEM, X-ray diffraction, and atom probe analysis. All of the as deposited materials were purely fcc and had grain sizes of 10–20 nm. Heat treatment of nanocrystalline nickel in the range 190–320°C resulted in abnormal grain growth with an activation energy of 122±15 kJ mol-1. Abnormal grain growth in Fe–50 at. -%Ni was only observed at 400°C but not at 220 or 300°C, where grain growth was very slow. In Fe–33 at. -%Ni, room temperature aging resulted in the formation of large grained areas (∼1 µm), some of which transformed to bcc. In heat treated nickel specimens, some evidence of sulphur and carbon enrichment was found at grain boundaries.
Applications and Challenges of Mobile P2P Systems in Ad Hoc Network

Mobile peer to peer system in Ad hoc network is a brand novel application system. In this paper backgrounds and basic concepts of mobile peer to peer (p2p) systems are introduced firstly. Then possible applications of mobile p2p systems are expounded. Afterwards, technical challenges which mobile p2p system must face are analyzed in detail. In the end, the developments and implementation of mobile p2p system are explored and some conclusions are given.