Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential Contributions of mSWI/SNF Chromatin Remodeler Sub-Families to Myoblast Differentiation

Mammalian SWI/SNF (mSWI/SNF) complexes are ATP-dependent chromatin remodeling enzymes that are critical for normal cellular functions. mSWI/SNF enzymes are classified into three sub-families based on the presence of specific subunit proteins. The sub-families are Brm- or Brg1-associated factor (BAF), ncBAF (non-canonical BAF), and polybromo-associated BAF (PBAF). The biological roles for the different enzyme sub-families are poorly described. We knocked down the expression of genes encoding unique subunit proteins for each sub-family, Baf250A, Brd9, and Baf180, which mark the BAF, ncBAF, and PBAF sub-families, respectively, and examined the requirement for each in myoblast differentiation. We found that Baf250A and the BAF complex were required to drive lineage-specific gene expression. KD of Brd9 delayed differentiation. However, while the Baf250A-dependent gene expression profile included myogenic genes, the Brd9-dependent gene expression profile did not, suggesting Brd9 and the ncBAF complex indirectly contributed to differentiation. Baf180 was dispensable for myoblast differentiation. The results distinguish between the roles of the mSWI/SNF enzyme sub-families during myoblast differentiation.
Mining Regional Co-Occurrence Patterns for Image Classification

In the context of image classification, bag-of-visual-words mode is widely used for image representation. In recent years several works have aimed at exploiting color or spatial information to improve the representation. In this paper two kinds of representation vectors, namely, Global Color Co-occurrence Vector (GCCV) and Local Color Co-occurrence Vector (LCCV), are proposed. Both of them make use of the color and co-occurrence information of the superpixels in an image. GCCV describes the global statistical distribution of the colorful superpixels with embedding the spatial information between them. By this way, it is capable of capturing the color and structure information in large scale. Unlike the GCCV, LCCV, which is embedded in the Riemannian manifold space, reflects the color information within the superpixels in detail. It records the higher-order distribution of the color between the superpixels within a neighborhood by aggregating the co-occurrence information in the second-order pooling way. In the experiment, we incorporate the two proposed representation vectors with feature vector like LLC or CNN by Multiple Kernel Learning (MKL) technology. Several challenging datasets for visual classification are tested on the novel framework, and experimental results demonstrate the effectiveness of the proposed method.
Analysis and Optimization of Switched-Capacitor Piezoelectric Energy Harvesting Interface Circuits

Closed-form expressions for the output dc voltage and load power of commonly used switched-capacitor (SC) piezoelectric interface circuits are derived. The proposed analysis approach computes the equivalent impedance introduced by an interface circuit to a piezoelectric transducer (PT). The input impedance of an interface is estimated by evaluating the equivalent linear time-invariant (LTI) network of the periodically switched ac side in the interface circuit. The advantage of the proposed model is that it quantifies the improvement that a given interface circuit provides to the transducer source impedance independent of its load-controlled internal current. In addition, the optimal load value that maximizes the output power of an interface circuit can be readily found from the interface equivalent input impedance. Unlike prior approaches, the proposed analysis takes the transducer’s internal resistance into account, which allows for determining the maximum achievable harvesting efficiency of an interface. Interestingly, it is found that the maximum power that a bias-flip rectifier can extract from a PT is limited to only 81% of the theoretical maximum power available under conjugate impedance matching. The developed analysis has been verified through circuit simulations.
Modeling, Analysis, and Design of 5G Networks using Stochastic Geometry

Modeling, Analysis, and Design of 5G Networks using Stochastic Geometry Konpal Shaukat Ali Improving spectral-utilization is a core focus to cater the ever-increasing demand in data rate and system capacity required for the development of 5G. This dissertation focuses on three spectrum-reuse technologies that are envisioned to play an important role in 5G networks: device-to-device (D2D), full-duplex (FD), and nonorthogonal multiple access (NOMA). D2D allows proximal user-equipments (UEs) to bypass the cellular base-station and communicate with their intended receiver directly. In underlay D2D, the D2D UEs utilize the same spectral resources as the cellular UEs. FD communication allows a transmit-receive pair to transmit simultaneously on the same frequency channel. Due to the overwhelming self-interference encountered, FD was not possible until very recently courtesy of advances in transceiver design. NOMA allows multiple receivers (transmitters) to communicate with one transmitter (receiver) in one time-frequency resource-block by multiplexing in the power domain. Successive-interference cancellation is used for NOMA decoding. Each of these techniques significantly improves spectral efficiency and consequently data rate and throughput; however, the price paid is increased interference. Since each of these technologies allow multiple transmissions within a cell on a time-frequency resource-block, they result in interference within the cell (i.e., intracell interference). Additionally, due to the increased communication, they increase network interference from outside the cell under consideration as well (i.e., increased intercell interference). Real networks are becoming very dense; as a result, the impact of intercell interference coming from the entire network is significant. As such, using models that 5 consider a single-cell/few-cell scenarios result in misleading conclusions. Hence, accurate modeling requires considering a large network. In this context, stochastic geometry is a powerful tool for analyzing random patterns of points such as those found in wireless networks. In this dissertation, stochastic geometry is used to model and analyze the different technologies that are to be deployed in 5G networks. This gives us insight into the network performance, showing us the impacts of deploying a certain technology into real 5G networks. Additionally, it allows us to propose schemes for integrating such technologies, mode-selection, parameter-selection, and resource-allocation that enhance the parameters of interest in the network such as data rate, coverage, and secure communication.
Ultra-Wideband and High-Gain Vivaldi Antenna with Artificial Electromagnetic Materials

An ultra-wideband and high-gain Vivaldi antenna with artificial electromagnetic material, suitable for ground-penetrating radar (GPR) systems, is proposed. Directors loaded inside the antenna gradient slot direct electromagnetic waves by inducing current to improve gain. The artificial electromagnetic material, also called metamaterial, is composed of multiple “H”-shaped units arranged in a certain regular pattern, loaded at the antenna aperture. The artificial electromagnetic units affect the antenna radiation waves by changing the refractive index to improve radiation directivity. The four Vivaldi units are arranged into a horn-shaped array, and each two units are orthogonally fed to realize dual polarization. Experimental results demonstrate that the antenna has good impedance matching of S11≤−10 dB in 0.9–4 GHz, and the maximum realized gain can reach 15.2 dBi.
Mixed Convection Flow Along a Horizontal Circular Cylinder with Small Amplitude Oscillation in Surface Temperature and Free Stream

The problem is considered on mixed convection flow due to the effect of small amplitude oscillations of a viscous incompressible fluid along a horizontal circular cylinder. Direct implicit finite-difference scheme is employed to solve the dimensionless system of partial differential equations. In case of steady flow, the solutions are presented as functions of the curvature parameter X on the entire surface of the cylinder and there is a visual comparison with the existing result. For fluctuating flow, considering Prandtl number, Pr=1.0, the results are shown graphically in terms of amplitude and phase of the Nusselt number for different values of buoyancy parameter Lambda. Due to the effect of Lambda and frequency parameter omega, streamlines and isotherms as well as transient shear stress and heat transfer are illustrated in the interplay of study.
The Inhibition and Clearup of the Mobile Worm in Wireless Sensor Networks

The network performance of WSNs (Wireless Sensor Networks) can be improved significantly by injecting mobile elements. However, the infection process of worm will be greatly accelerated once the mobile element has been captured and become the new infection source. To cope with this new threat, this paper first proposes the infection model for the networks with the mobile worm and designs a heuristic algorithm to identify the boundary of infected area. High risk nodes near the boundary can be found and switched to sleeping states to block the further spreading of the worm. Second, an algorithm with directed-diffusion based anti-worm is designed to repair those infected sensors. Theoretical analysis and experimental results show that the proposed methods can achieve better worm cleaning effect with low cost, which can be applied to energy-limited wireless sensor networks.
Put it in the bag: Order fulfillment with a pocket sorter system

Due to high real estate costs in urban areas, shop floor space is scarce in most brick‐and‐mortar stores. Maneuvering newly arrived merchandise through narrow aisles during shelf replenishment is time‐consuming for the sales staff and impedes customers. Therefore, many retail chains nowadays aim for store‐friendly shipments (SFS). By mirroring the layout of a store in the buildup of its dedicated shipments, the need for a zigzag movement through the store when replenishing shelves can be avoided. On the negative side, however, additional effort arises in the distribution centers. A suitable warehousing system to assemble SFS without excessive effort is a pocket (or pouch or bag) sorter, where each item is put into its separate bag. These bags, filled with items, are automatically transported while hanging from an overhead conveyor and can be sorted into any sequence before being delivered to the workstations that build SFS. This article investigates the assembly of SFS with a pocket sorter and presents scheduling procedures to enhance the efficiency of this process for a given set of store orders. We demonstrate that, despite its notorious complexity, the problem can be solved by simple decision rules with good performance. In a case study, we show that this approach can dramatically reduce the completion times of store orders, resulting in savings of more than 60% of the total working hours compared to a simple real‐world policy. Another 30% of reduction can be obtained by standardized store layouts.
Synthesis of phase pure vanadium dioxide (VO2) thin film by reactive pulsed laser deposition

Thin films of phase pure VO 2 (M1 phase) are deposited on thermally grown oxide (Si/SiO 2) substrate by reactive pulsed laser deposition of vanadium metal target. The influence of deposition parameters is studied by varying oxygen partial pressure while keeping other parameters constant. A thin film obtained at 50 mTorr is found to be phase pure by XRD and Raman spectral studies. SEM and AFM studies show smooth morphology with a surface roughness of 3–5 nm. The quality of the thin film was further established by characterizing the 68 °C (T S M T) transition by 2–3 orders of jump in resistance and a 60% change in reflectivity with minimum hysteresis. This single step process of deposition would be a suitable method for fabricating devices for smart window and metamaterial applications.
Morphological and Phylogenetic Characterization of Five Novel Nematode-Trapping Fungi (Orbiliomycetes) from Yunnan, China

Nematode-trapping fungi are widely studied due to their unique morphological structure, survival strategy, and potential value in the biological control of harmful nematodes. During the identification of carnivorous fungi preserved in our laboratory, five novel nematode-trapping fungi were established and placed in the genera Arthrobotrys and Drehslerella based on morphological and multigene (ITS, TEF, and RPB2) phylogenetic analyses. A. hengjiangensis sp. nov. and A. weixiensis sp. nov. are characterized by producing adhesive networks to catch nematodes. Dr. pengdangensis sp. nov., Dr. tianchiensis sp. nov., and Dr. yunlongensis sp. nov. are characterized by producing constricting rings. Morphological descriptions, illustrations, taxonomic notes, and phylogenetic analysis are provided for all new taxa; a key for Drechslerella species is listed; and some deficiencies in the taxonomy and evolution study of nematode-trapping fungi are also discussed herein.
ON CONSTRUCTION OF A RELIABLE GROUND TRUTH FOR EVALUATION OF VISUAL SLAM ALGORITHMS

In this work we are concerning the problem of localization accuracy evaluation of visual-based Simultaneous Localization and Mapping (SLAM) techniques. Quantitative evaluation of the SLAM algorithm performance is usually done using the established metrics of Relative pose error and Absolute trajectory error which require a precise and reliable ground truth. Such a ground truth is usually hard to obtain, while it requires an expensive external localization system. In this work we are proposing to use the SLAM algorithm itself to construct a reliable ground-truth by offline frame-by-frame processing. The generated ground-truth is suitable for evaluation of different SLAM systems, as well as for tuning the parametrization of the on-line SLAM. The presented practical experimental results indicate the feasibility of the proposed approach.
Standard error estimation by an automated blocking method

The sample mean X is probably the most popular estimator of the expected value in all sciences and var(X) measures the error (standardand mean-square-errors). Here, an alternative approach to estimation of var(X) for time series data is presented. The method has an accuracy similar to dependent bootstrapping, but scales in O(n) time, and applies to stationary time series, including stationary Markov chains. The computational complexity is bounded by 12n floating point operations, but this can be reduced to n + O(1) in large computations. Convergence in relative error squared is faster than n−1/2 and the method is insensitive to the probability distribution of the observations. It is proven that a small part of the correlation structure is relevant to the convergence rate of the method. From this, proof of the Blocking method [Flyvbjerg and Petersen, J. Chem. Phys. 91, 461 (1989)] follows as a corollary. The result is also used to propose a hypothesis test surveying the relevant part of the correlation structure. It yields a fully automatic method which is sufficiently robust to operate without supervision. An algorithm and sample code showing the implementation is available for PYTHON, C++, and R [www.github. com/computative/block]. Method validation using autoregressive AR(1) and AR(2) processes and physics applications is included. Method self-evaluation is provided by bias and mean-square-error statistics. The method is easily adapted to multithread applications and data larger than computing cluster memory, such as ultralong time series or data streams. This way, the paper provides a stringent and modern treatment of the Blocking method using rigorous linear algebra, multivariate probability theory, real analysis, and Fisherian statistical inference.
Looking for blazars among the Fermi/LAT unidentified sources in the 3FGL catalogue

After 4 years of observations, the LAT telescope on board the Fermi satellite has detected the gamma-ray emission from 3034 sources (3FGL catalogue). About one third of these sources have no assigned counterparts at other wavelengths and are of unidentified nature. We present the search of blazar candidates among these unidentified sources. Considering a set of carefully choosen discriminant blazar/non-blazar parameters, we have built two multivariate classifiers (boosted decision trees and multilayer perceptron neural networks) and combined their decisions in order to obtain a high level of blazar indentification efficiency along with a well controlled level of non-blazar contamination. The low latitude and high latitude cases have been treated separately. Applying these classifiers to the sample of 1009 unidentified sources, we have determined a list of 538 blazar candidates, respectively 420 and 118 located at high (|b|> 10◦) and low (|b| ≤ 10◦) latitude. The corresponding level of mis-classification is estimated to be ∼7 sources for the high latitude case (less than 2%) and ∼28 sources for the low latitude case (∼24%).
Efficacy and Safety of Stylage XL Lidocaine for the Restoration and/or Augmentation of Facial Volume: The Beauty Volume Study

Abstract Background Hyaluronic acid (HA)-based gel fillers help correct facial volume deficits through their volumizing effect. Objectives This postmarket clinical follow-up study was a single-center prospective cohort study designed to evaluate the efficacy and safety of Stylage XL Lidocaine (Laboratoires VIVACY, Paris, France) for the augmentation and/or restoration of facial volume. Methods Healthy patients aged between 30 and 65 years with a facial volume grade of 3 to 5 according to the facial volume loss scale (FVLS) were considered eligible. Participants were injected subcutaneously in the area of the cheekbones (essential area). If necessary, patients were also injected in the chin, the temples, and the facial oval (optional areas). Outcomes were assessed at 1, 3, 6, 12, and 18 months following the initial treatment. A touch-up was possible at 1 month following the initial injection. The primary endpoint was the variation in the mean FVLS scores at M6 compared to baseline as evaluated by an independent assessor. Results A total of 40 female patients (mean age of 52.5 years) were recruited between November 2019 and July 2021. There was a significant improvement in the mean FVLS score at 6 months compared to baseline (2.3 [0.6] vs 3.1 [0.6]; P < .0001). Patients were satisfied with the achieved aesthetic improvements and results were still observed at 12 and 18 months. Stylage XL Lidocaine also had a good safety profile and was well tolerated by the study cohort. Conclusions The results of the 18-month Beauty Volume study confirmed the efficacy and safety of the Stylage XL Lidocaine HA-based gel filler in the augmentation and/or restoration of facial volumes. Level of Evidence: 3
Magnon transport in noncollinear spin textures: Anisotropies and topological magnon Hall effects

We analyze signatures of noncollinear spin textures in the magnon transport of both spin and heat by means of atomistic spin dynamics. The influence of the spin texture is demonstrated for a spin spiral and for a skyrmion lattice on a frustrated antiferromagnet. Spin spirals show an anisotropy in the longitudinal transport, whereas skyrmion lattices exhibit transverse transport, which is interpreted in terms of topology and establishes skyrmion-induced versions of magnon Hall effects. The conductivities depend sensitively on the spiral pitch and on the skyrmion size; we predict magnon Hall angles as large as 60%.
New Approaches to Protein Structure Prediction

Protein structure prediction is concerned with the prediction of a protein’s three dimensional structure from its amino acid sequence. Such predictions are commonly performed by searching the possible structures and evaluating each structure by using some scoring function. If it is assumed that the target protein structure resembles the structure of a known protein, the search space can be significantly reduced. Such an approach is referred to as comparative structure prediction. When such an assumption is not made, the approach is known as ab initio structure prediction. There are several difficulties in devising efficient searches or in computing the scoring function. Many of these problems have ready solutions from known mathematical methods. However, the problems that are yet unsolved have hindered structure prediction methods from more ideal predictions. The objective of this study is to present a complete framework for ab initio protein structure prediction. To achieve this, a new search strategy is proposed, and better techniques are devised for computing the known scoring functions. Some of the remaining problems in protein structure prediction are revisited. Several of them are shown to be intractable. In many of these cases, approximation methods are suggested as alternative solutions. The primary issues addressed in this thesis are concerned with local structures prediction, structure assembly or sampling, side chain packing, model comparison, and structural alignment. For brevity, we do not elaborate on these problems here; a concise introduction is given in the first section of this thesis. Results from these studies prompted the development of several programs, forming a utility suite for ab initio protein structure prediction. Due to the general usefulness of these programs, some of them are released with open source licenses to benefit the community.
Boundary element methods for particles and microswimmers in a linear viscoelastic fluid

The consideration of viscoelasticity within fluid dynamical boundary element methods has traditionally required meshing over the whole flow domain. In turn, a major advantage of the boundary element method is lost, namely the need to consider only surface boundary integrals. Here, using a generalised reciprocal relation and viscoelastic force singularities, a boundary element method is developed for linear viscoelastic flows. We proceed to explore finite-deformation microswimming in a linear Maxwell fluid. We firstly deduce a finite-amplitude generalisation of a previously reported result that the flow field is unchanged between a Newtonian and linear Maxwell fluid for prescribed small-amplitude deformations. Hence Purcell’s theorem holds for a linear Maxwell fluid. We proceed to consider deformation swimming in a linear Maxwell fluid given an external forcing. Boundary scattering trajectories for an exemplar squirmer approaching a surface are observed to exhibit a weak dependence on the Deborah number, while the trajectories of a sperm and monotrichous bacterium near a surface are predicted to be essentially unaffected at moderate Deborah number. In turn, the latter supports the common simplification of using Newtonian Stokes flows for studying flagellate swimming in linear Maxwell media. In addition, the motion of a magnetic helix under the influence of an external magnetic field is considered, and highlights that linear viscoelasticity can significantly impact the propagation of the helix, in turn demonstrating that even linear rheology is important to consider for forced swimmers. Finally, the presented framework requires minimalistic adjustments to Newtonian boundary element codes, enabling rapid implementation, and is more generally applicable, for instance to studies of particle interactions in active linear rheology on the microscale.