bluuebunny/crossref_metadata_2025 huggingface dataset:
The AdS𝜃2/CFT1 correspondence and noncommutative geometry II: Noncommutative quantum black holes
Authors: Ydri Badis
Published: April 2022

In this paper, we present the construction of noncommutative [Formula: see text] black hole and its four-dimensional Yang–Mills IKKT-type matrix model which includes two competing Myers term one responsible for the condensation of pure [Formula: see text] and the other one responsible for the condensation of the dilaton field. It is argued that the phase diagram of this matrix model features three phases: (1) a gravitational phase ([Formula: see text] black hole), (2) a geometric phase ([Formula: see text] background) and (3) a Yang–Mills phase. The Hawking process is therefore seen as an exotic line of discontinuous transitions between the gravitational and geometrical phases. Alternatively, a noncommutative nonlinear sigma model describing the transition of the dilaton field between the gravitational and geometrical phases is also constructed.
The AdS𝜃2/CFT1 correspondence and noncommutative geometry III: Phase structure of the noncommutative AdS𝜃2 × 𝕊N2
Authors: Bouraiou Loubna , Ydri Badis
Published: April 2022

The near-horizon noncommutative geometry of black holes, given by [Formula: see text], is discussed and the phase structure of the corresponding Yang–Mills matrix models is presented. The dominant phase transition as the system cools down, i.e. as the gauge coupling constant is decreased is an emergent geometry transition between a geometric noncommutative [Formula: see text] phase (discrete spectrum) and a Yang–Mills matrix phase (continuous spectrum) with no background geometrical structure. We also find a possibility for topology change transitions in which space or time directions grow or decay as the temperature is varied. Indeed, the noncommutative near-horizon geometry [Formula: see text] can evaporate only partially to a fuzzy sphere [Formula: see text] (emergence of time) or to a noncommutative anti-de Sitter space–time [Formula: see text] (topology change).
Analysis of generalized ghost dark energy and new holographic dark energy in Chameleon Brans–Dicke theory
Authors: Biswas Mahasweta , Debnath Ujjal
Published: April 2022

In this work, we discuss the stability analysis of generalized ghost dark energy (GGDE) and new holographic dark energy (NHDE) in the framework of Chameleon Brans–Dicke (CBD) gravity. The adiabatic squared sound speed [Formula: see text] plays a crucial role to analyze the stability of the models. We know that the models are stable if [Formula: see text] and unstable if [Formula: see text]. We study the interacting and noninteracting versions of GGDE and NHDE with dark matter in CBD model in a nonflat FLRW universe. We also try to show that in all cases of investigation, the models are classically stable with suitable choices of parameters. Finally, we analyze the perturbative analysis for both GGDE and NHDE models in the background of CBD gravity.
R-GEFS: Condorcet Rank Aggregation with Graph Theoretic Ensemble Feature Selection Algorithm for Classification
Authors: Bania Rubul Kumar
Published: April 2022

In the last few years, ensemble learning has received more interest primarily for the task of classification. It is based on the postulation that combining the output of multiple experts is better than the output of any individual expert. Ensemble feature selection may improve the performance of the learning algorithms and has the ability to obtain more stable and robust results. However, during the process of feature aggregation and selection, selected feature subset may contain high levels of inter-feature redundancy. To address this issue, a novel algorithm based on feature rank aggregation and graph theoretic technique for ensemble feature selection (R-GEFS) with the fusion of Pearson and Spearman correlation metrics is proposed. The method works by aggregation of the profile of preferences of five feature rankers as the base feature selectors. Then similar features are grouped into clusters using graph theoretic approach. The most representative feature strongly co-related to target decision classes is drawn from each cluster. The efficiency and effectiveness of the R-GEFS algorithm are evaluated through an empirical study. Extensive experiments on 15 diverse benchmark datasets are carried out to compare R-GEFS with seven state-of-the-art feature selection models with respect to four popular classifiers, namely decision tree, k nearest neighbor, random forest, and support vector machine. The proposed method turns out to be effective by selecting smaller feature subsets with lesser computational complexities and it assists in increasing the classification accuracy.
New Deep Spatio-Structural Features of Handwritten Text Lines for Document Age Classification
Authors: Shivakumara Palaiahnakote , Das Alloy , Raghunandan K. S. , Pal Umapada , Blumenstein Michael
Published: April 2022

Document age estimation using handwritten text line images is useful for several pattern recognition and artificial intelligence applications such as forged signature verification, writer identification, gender identification, personality traits identification, and fraudulent document identification. This paper presents a novel method for document age classification at the text line level. For segmenting text lines from handwritten document images, the wavelet decomposition is used in a novel way. We explore multiple levels of wavelet decomposition, which introduce blur as the number of levels increases for detecting word components. The detected components are then used for a direction guided-driven growing approach with linearity, and nonlinearity criteria for segmenting text lines. For classification of text line images of different ages, inspired by the observation that, as the age of a document increases, the quality of its image degrades, the proposed method extracts the structural, contrast, and spatial features to study degradations at different wavelet decomposition levels. The specific advantages of DenseNet, namely, strong feature propagation, mitigation of the vanishing gradient problem, reuse of features, and the reduction of the number of parameters motivated us to use DenseNet121 along with a Multi-layer Perceptron (MLP) for the classification of text lines of different ages by feeding features and the original image as input. To demonstrate the efficacy of the proposed model, experiments were conducted on our own as well as standard datasets for both text line segmentation and document age classification. The results show that the proposed method outperforms the existing methods for text line segmentation in terms of precision, recall, F-measure, and document age classification in terms of average classification rate.
Local Resultant Gradient Vector Difference and Inpainting for 3D Text Detection in the Wild
Authors: Zhong Dajian , Shivakumara Palaiahnakote , Nandanwar Lokesh , Pal Umapada , Blumenstein Michael , Lu Yue
Published: April 2022

Three-dimensional (3D) text appearing in natural scene images is common due to 3D cameras and the capture of text from different angles, which presents new problems for text detection. This is because of the presence of depth information, shadows, and decorative characters in the images. In this work, we consider those images where 3D text appears with depth, as well as shadow information for text detection. We propose a novel method based on local resultant gradient vector difference (LRGVD), inpainting and a deep learning model for detecting 3D as well as two-dimensional (2D) texts in natural scene images. The boundary of components that are invariant to the above challenges is detected by exploring LRGVD. The LRGVD uses gradient magnitude and direction in a novel way for detecting the boundary of the components. Further, we propose an inpainting method in a new way for restoring the character background information using boundaries. For a given region and the input image, the inpainting method divides the whole image into planes and then propagates the values in the planes into the missing region based on posterior probabilities and neighboring information. This results in text regions with false positives. Then, the differential binarization network (DB-Net) is proposed for detecting text irrespective of orientation, background, 3D or 2D, etc. Experiments conducted on our 3D text images and standard datasets of natural scene text images, namely ICDAR 2019 MLT, ICDAR 2019 ArT, DAST1500, Total-Text and SCUT-CTW1500, show that the proposed method is effective in detecting 3D and 2D texts in the images.
Stratified spaces, directed algebraic topology, and state-sum TQFTs
Authors: Lee I. J. , Yetter D. N.
Published: April 2022

We apply the theory of directed topology developed by Grandis [Directed homotopy theory, I. The fundamental category, Cah. Topol. Géom. Différ. Catég. 44 (2003) 281–316; Directed Algebraic Topology: Models of Non-Reversible Worlds, New Mathematical Monographs, Vol. 13 (Cambridge University Press, Cambridge, 2009)] to the study of stratified spaces by describing several ways in which a stratification or a stratification with orientations on the strata can be used to produce a related directed space structure. This description provides a setting for the constructions of state-sum TQFTs with defects of [A. L. Dougherty, H. Park and D. N. Yetter, On 2-dimensional Dikjgraaf-Witten theory with defects, J. Knot Theory Ramifications 25(5) (2016) 1650021, doi:10.1142/S0218216516500218 ; I. J. Lee and D. N. Yetter, Dijkgraaf–Witten type invariants of Seifert surfaces in 3-manifolds, J. Knot Theory Ramifications 26(5) (2017) 1750026, doi:10.1142/S0218216517500262 ], which we extend to a similar construction of a Dijkgraaf–Witten type TQFT in the case where the defects (lower-dimensional strata) are not sources or targets, but sources on one side and targets on the other, according to an orientation convention.
MODELING AND GENETIC ALGORITHM INTER-RELATIONSHIP-OPTIMIZED PLASMA-SPRAYED IN718 THERMAL BARRIER COATING STRUCTURE
Authors: DWIVEDI VIJAY KUMAR , SHARMA PRIYANKA , KUMAR DIPAK
Published: April 2022

Current paper comprises the inter-relationship between second-order regression modeling and genetic algorithm (GA)-based optimization of air plasma deposited with improved thermal barrier coating (TBC) systems structures. For developing the regression model, experiments were performed as per [Formula: see text] orthogonal array, and models were established by MINITAB software. The regression models have been found satisfactory for predicting the responses at 99% confidence level. GA optimization showed a 14.86% improvement in hardness and a 15.99% reduction in roughness. The optimal level of air plasma spraying (APS) parameters was obtained as 8 number of spraying layers, 70[Formula: see text]V of accelerating voltage, 600[Formula: see text]A of Arc current, 30[Formula: see text]mm/s of travel speed, 100[Formula: see text]mm of spray distance, 25[Formula: see text]g/min of powder feed rate, 4[Formula: see text]J/min of carrier gas flow rate, and 55[Formula: see text]L/min of primary gas flow rate for maximum hardness and minimum roughness.
RESEARCH ON THE APPLICATION OF SPORTS BIOMECHANICS IN IMPROVING ATHLETES’ PHYSICAL FITNESS IN TRACK AND FIELD PHYSICAL EDUCATION COURSES
Authors: WANG BO
Published: April 2022

Object: In this paper, eight male basketball players were tested for physical fitness using the method of sports biology. The content of the physical examination is the isokinetic muscle strength of the shoulder joint. This paper aims to investigate the effect of shoulder isokinetic muscle strength on athletic performance. Methods: This paper uses the principles of sports biology and the isokinetic muscle strength test system to measure the shoulder torque and fatigue index of eight basketball players. At the same time, this paper analyzes the obtained data using the method of mathematical statistics. Results: There were significant differences in the test data of eight male basketball players (P < 0.05). The fatigue of basketball players is mainly in the middle and late stages of sports. At average speed, the fatigue index of the shoulder is the lowest at 180°/s. Conclusion: Basketball players have stronger shoulder extensors than flexors. The balance of strength in the shoulder flexors is greater than the balance in the extensors.
Localization in quantum walks with periodically arranged coin matrices
Authors: Kiumi Chusei
Published: April 2022

There is a property called localization, which is essential for applications of quantum walks. From a mathematical point of view, the occurrence of localization is known to be equivalent to the existence of eigenvalues of the time evolution operators, which are defined by coin matrices. A previous study proposed an approach to the eigenvalue problem for space-inhomogeneous models using transfer matrices. However, the approach was restricted to models whose coin matrices are the same in positions sufficiently far to the left and right, respectively. This study shows that the method can be applied to extended models with periodically arranged coin matrices. Moreover, we investigate localization by performing the eigenvalue analysis and deriving their time-averaged limit distribution.
Impact of the COVID-19 Outbreak on Engineers’ Mobility: Evidence From Patent Data in the Semiconductor Industry
Authors: Fujiwara Ayano
Published: April 2022

This study examines how the mobility of engineers in the semiconductor industry changed after COVID-19. Through the analysis of patent data, differences in the impact on the probability of engineers moving across borders before and after the outbreak were compared. The analysis reveals that before the outbreak, the probability of engineers moving internationally was higher for top-ranked engineers, who accounted for 1% of all engineers, than that for second-, third-, and lowest-ranked engineers. However, after the outbreak, behavioral changes were observed only in top-ranked engineers, so they had a lower probability of mobility than any other rank of engineers.
A Framework to Manage University–Industry Technology Transfer
Authors: Sharma Priyanka
Published: April 2022

This paper focuses on university–industry relationships, and the value in such linkages that motivates firms to choose a particular mode to acquire university-generated research output. We combined insights from literature review and 15 exploratory interviews of multiple stakeholders, and developed a framework to examine university–industry linkages. We grounded our framework on the social exchange theory (SET) and quadruple helix concept. It proposes university climate readiness (e.g. incentive system), firm climate readiness (e.g. managers’ attitude toward academic research), and exchange readiness (e.g. a firm’s absorptive capacity) as antecedents to science-business collaboration, coupled with environmental readiness factors (e.g. unique socio-cultural setting in developing economies) as moderating variables. The framework highlights (1) functional value (i.e. technology pricing, quality, and applicability) and (2) relational value (i.e. trust between academia and industry) in the said relationship. The framework further provides a basis for practitioners to arrive at a suitable university-developed technology transfer mode (e.g. patent licensing, research services, and research partnerships).
Photosensitizer-hyaluronic acid complexes for antimicrobial photodynamic therapy (aPDT)
Authors: Khurana Bhavya , Ouk Tan-Sothea , Lucas Romain , Senge Mathias O. , Sol Vincent
Published: April 2022

The number of drug-resistant bacteria is increasing significantly. To combat such issues, antimicrobial PDT (aPDT) provides an efficient way to eliminate these species efficiently, cost-effectively, and more importantly, without the associated mechanism of resistance. The hemisynthesis and synthesis of photosensitizers such as polyaminated chlorin-p6 and 5-(4-aminophenyl)-10,15,20-tris(4-[Formula: see text]-methylpyridinium)porphyrin triiodide and their water stable and soluble formulation with hyaluronic acid bio-polymer (PS-HA) is reported. Structures of porphyrin-HA formulations were characterized by IR, DSC, DLS, zeta potential, SEM imaging, UV-vis analysis and rheological evaluation confirming the covalent conjugation of PSs on conjugate platform (hyaluronic acid). These conjugate formulations were tested against the Gram-negative Escherichia coli (CIP 53.126) and Gram-positive Staphylococcus aureus (CIP 76.25) bacteria for their potency for aPDT.
Analytical and Numerical Investigation on Dynamic Behavior of Rectangular FML Sandwich Tubes with Metal Foam Core Under Low-Velocity Impact
Authors: Song Yan , Yuan Hui , Du Jinlong , Sun Hao , Han Zelin , Zhang Jianxun
Published: April 2022

In this work, the dynamic behavior for clamp-supported rectangular fiber metal laminate (FML) sandwich tubes with metal foam core under low-velocity impact is studied by analytical solution and numerical method analysis. The yield criterion of the FML sandwich tube with metal foam core is proposed. Based on yield criterion, the theoretical solution for rectangular FML sandwich tubes dynamic behavior under low-velocity impact is developed considering the strength and the coupling effect of bending and tension. Finite element study is conducted. Theoretical results are well consistent in the finite element ones. Finally, the influences of material and geometric parameters, and impact position on impact force and maximum deflection of FML sandwich tubes are analyzed systematically. The results reveal that the FML sandwich tubes’ impact forces increase with the increase of the strength, number and thickness of the metal layer, the strength and thickness of the composite layer and foam strength; and impact forces increase with the decrease of the metal volume fraction of FML. Also, the impact force increases with the decrease of the distance between the impact position and the clamp-supported end.
Quantitative tracing of bioprobes by simultaneously monitoring radiative and nonradiative relaxations
Authors: Chen Hongjiang , Tang Xiaoyu , Nie Guangshuai , Wang Zhen , Hu Jia , Hu Jun , Qin Huan
Published: April 2022

Bioprobe based on fluorescence is widely used in biological and medical research due to its high sensitivity and selectivity. Yet, its quantification in vivo is complicated and often compromised by the interaction between the fluorophore with the environmental factors, as well as the optical scattering and absorption by the tissue. A high florescence quantum yield and minimal interference by the environment are key requirements for designing an effective bioprobe, and the pre-requisitions severely limit the available options. We propose that a comprehensive evaluation of potential bioprobe can be achieved by simultaneously measuring both radiative and non-radiative transitions, the two fundamental and complementary pathways for the energy de-excitation. This approach will not only improve the accuracy of the quantification by catching the information from a broader spectrum of the energy, but also provide additional information of the probe environment that often impacts the balance between the two forms of the energy transition. This work first analyzes the underlying mechanism of the hypothesis. The practical feasibility is then tested by means of simultaneous measurements of photoacoustic signal for the non-radiative and fluorescence for the radiative energy processes, respectively. It is demonstrated that the systematic evaluation of the probe energy de-excitation results in an improved quantitative tracing of a bioprobe in complex environment.
Hamming distance between the strings generated by adjacency matrix of a subgraph complementary graph and their sum
Authors: Nayak Swati , Upadhyay Shankar , D’Souza Sabitha , Bhat Pradeep G.
Published: April 2022

Let [Formula: see text] be the adjacency matrix of a graph [Formula: see text]. Let [Formula: see text] denote the row entries of [Formula: see text] corresponding to the vertex [Formula: see text] of [Formula: see text]. The Hamming distance between the strings [Formula: see text] and [Formula: see text] is the number of positions in which [Formula: see text] and [Formula: see text] differ. In this paper, we study the Hamming distance between the strings generated by the adjacency matrix of subgraph complement of a graph. We also compute sum of Hamming distances between all pairs of strings generated by the adjacency matrix of [Formula: see text].
Quantum invasive weed optimization-based energy aware task scheduling for cyber–physical system environment
Authors: Neelakandan S. , Keerthika K. , Ilanchezhian P. , Madeswaran TamilSelvi , Hardas Vedanti B. , Sakthi U.
Published: April 2022

Cyber–physical systems (CPSs) can be treated as an emerging technology that has the ability to handle the physical process and computational view of interlinked systems. At the same time, the high-performing processing capability provides assurance of CPS applications in real time. Besides, task scheduling is considered as the Nondeterministic Polynomial (NP)-hard problem and optimal allocation of tasks is important for the CPS environment. The primary concept of the optimum energy-based scheduling approach searches for the physical host allocation vector to the allotted virtual machine with an aim of reducing energy utilization. The multiple processor packet scheduling technique defined that every task in the system is already divided into processors by the task allocating scheme and every process can execute on the distinct or identical single processor scheduling technique. With this motivation, this paper presents a new quantum invasive weed optimization-based energy-aware scheduling (QIWO-EATS) technique for the CPS environment. The goal of the QIWO-EATS technique is to assign [Formula: see text] autonomous tasks to [Formula: see text] dissimilar resources, and thereby the whole task completion duration gets reduced and resources are completely used. The proposed model has been simulated using the MATLAB tool. The experimental results highlighted the better outcomes of the QIWO-EATS technique over the recent approaches in terms of several evaluation metrics.
Critical condition identification and simulation of a continuous synergetic growth model based on dynamic software geogebra
Authors: Hu Zhixing
Published: April 2022

Artificial Intelligence (AI), the emergence and development of social system model, are gradually affecting the development of system engineering technology and methods. AI mainly focuses on acquiring new knowledge or skills by looking for rules from observation data (samples); social system model mainly focuses on the ability of description and model demonstration from the current situation to the future. The combination of AI and social system model can promote the research of social problems related to system engineering. The synergetic growth of various sectors of the economic system depends on the initial level of output of each sector and its internal relations. This paper focuses on the internal relationship of the two-sector economic model and explores the impact of distribution relations on the synergetic growth of sectors. The study found that the necessary conditions for synergetic growth is a function of the profit rate, the difference between the labor income (or capital income) of the two sectors, and the marginal consumption propensity. This function has a more complex and nonlinear characteristic. By demonstrating the effects of changes in some parameters, we find that an increase in the profit rate requires that the income distribution structure of the two sectors tend to be the same; an increase in the marginal consumption propensity can allow for greater differences in the income distribution structure of the two sectors.
Real-time 3D UAV Path Planning in Dynamic Environments with Uncertainty
Authors: Zammit Christian , van Kampen Erik-Jan
Published: April 2022

The integration of Unmanned Aerial Vehicles (UAVs) is being proposed in a spectrum of applications varying from military to civil. In these applications, UAVs are required to safely navigate in real-time in dynamic and uncertain environments. Uncertainty can be present in both the UAV itself and the environment. Through a literature study, this paper first identifies, quantifies and models different uncertainty sources using bounding shapes. Then, the UAV model, path planner parameters and four scenarios of different complexity are defined. To investigate the effect of uncertainty on path planning performance, uncertainty in obstacle position and orientation and UAV position is varied between 2% and 20% for each uncertainty source first separately and then concurrently. Results show a deterioration in path planning performance with the inclusion of both uncertainty types for all scenarios for both A* and the Rapidly-Exploring Random Tree (RRT) algorithms, especially for RRT. Faster and shorter paths with similar same success rates (>95%) result for the RRT algorithm with respect to the A* algorithm only for simple scenarios. The A* algorithm performs better than the RRT algorithm in complex scenarios.
Distributions of Flood Risk: The Implications of Alternative Measures of Flood Risk
Authors: Noonan Douglas , Richardson Lilliard , Sun Pin
Published: April 2022

Flooding imposes considerable property risk, and flood maps and flood insurance help prospective and existing property owners assess the potential risk. The US Federal Emergency Management Agency (FEMA) works with local and state officials to produce flood maps. Using these flood maps and demographic attributes, prior research has demonstrated correlations between the percent of a tract identified as disadvantaged and the percent of the tract covered by flood zones. Until recently, FEMA flood maps were the primary assessment tool for flood risk, but First Street Foundation (FSF) has developed its own flood risk tools. This paper compares these alternative flood risk measures as a percent of census tracts in the Southeastern US states and assesses models of the risk measures with demographic, housing, policy and control variables. The main results are first that the FEMA and FSF maps often reveal diverging levels of risk per tract. Second, the demographics correlating with tract-level risk differ markedly for the two risk measures. Third, the results vary considerably by state with more divergence in some states than others, and who is at risk of flooding across the states varies between the FEMA and FSF measures.
Surgical Tool Segmentation with Pose-Informed Morphological Polar Transform of Endoscopic Images
Authors: Huang Kevin , Chitrakar Digesh , Jiang Wenfan , Yung Isabella , Su Yun-Hsuan
Published: April 2022

This paper presents a tool-pose-informed variable center morphological polar transform to enhance segmentation of endoscopic images. The representation, while not loss-less, transforms rigid tool shapes into morphologies consistently more rectangular that may be more amenable to image segmentation networks. The proposed method was evaluated using the U-Net convolutional neural network, and the input images from endoscopy were represented in one of the four different coordinate formats (1) the original rectangular image representation, (2) the morphological polar coordinate transform, (3) the proposed variable center transform about the tool-tip pixel and (4) the proposed variable center transform about the tool vanishing point pixel. Previous work relied on the observations that endoscopic images typically exhibit unused border regions with content in the shape of a circle (since the image sensor is designed to be larger than the image circle to maximize available visual information in the constrained environment) and that the region of interest (ROI) was most ideally near the endoscopic image center. That work sought an intelligent method for, given an input image, carefully selecting between methods (1) and (2) for best image segmentation prediction. In this extension, the image center reference constraint for polar transformation in method (2) is relaxed via the development of a variable center morphological transformation. Transform center selection leads to different spatial distributions of image loss, and the transform-center location can be informed by robot kinematic model and endoscopic image data. In particular, this work is examined using the tool-tip and tool vanishing point on the image plane as candidate centers. The experiments were conducted for each of the four image representations using a data set of 8360 endoscopic images from real sinus surgery. The segmentation performance was evaluated with standard metrics, and some insight about loss and tool location effects on performance are provided. Overall, the results are promising, showing that selecting a transform center based on tool shape features using the proposed method can improve segmentation performance.
Auto-Icon+
: An Automated End-to-End Code Generation Tool for Icon Designs in UI Development
Authors: Feng Sidong , Jiang Minmin , Zhou Tingting , Zhen Yankun , Chen Chunyang
Published: April 2022

Approximately 50% of development resources are devoted to user interface (UI) development tasks [
9
]. Occupying a large proportion of development resources, developing icons can be a time-consuming task, because developers need to consider not only effective implementation methods but also easy-to-understand descriptions. In this article, we present
Auto-Icon+
, an approach for automatically generating readable and efficient code for icons from design artifacts. According to our interviews to understand the gap between designers (icons are assembled from multiple components) and developers (icons as single images), we apply a heuristic clustering algorithm to compose the components into an icon image. We then propose an approach based on a deep learning model and computer vision methods to convert the composed icon image to fonts with descriptive labels, thereby reducing the laborious manual effort for developers and facilitating UI development. We quantitatively evaluate the quality of our method in the real-world UI development environment and demonstrate that our method offers developers accurate, efficient, readable, and usable code for icon designs, in terms of saving 65.2% implementing time.
Decoding the Human Face: Progress and Challenges in Understanding the Genetics of Craniofacial Morphology
Authors: Naqvi Sahin , Hoskens Hanne , Wilke Franziska , Weinberg Seth M. , Shaffer John R. , Walsh Susan , Shriver Mark D. , Wysocka Joanna , Claes Peter
Published: April 2022

Variations in the form of the human face, which plays a role in our individual identities and societal interactions, have fascinated scientists and artists alike. Here, we review our current understanding of the genetics underlying variation in craniofacial morphology and disease-associated dysmorphology, synthesizing decades of progress on Mendelian syndromes in addition to more recent results from genome-wide association studies of human facial shape and disease risk. We also discuss the various approaches used to phenotype and quantify facial shape, which are of particular importance due to the complex, multipartite nature of the craniofacial form. We close by discussing how experimental studies have contributed and will further contribute to our understanding of human genetic variation and then proposing future directions and applications for the field.
Exploring the Emergence and Evolution of Plant Pathogenic Microbes Using Historical and Paleontological Sources
Authors: Malmstrom Carolyn M. , Martin Michael D. , Gagnevin Lionel
Published: April 2022

Biotechnological advances now permit broad exploration of past microbial communities preserved in diverse substrates. Despite biomolecular degradation, high-throughput sequencing of preserved materials can yield invaluable genomic and metagenomic data from the past. This line of research has expanded from its initial human- and animal-centric foci to include plant-associated microbes (viruses, archaea, bacteria, fungi, and oomycetes), for which historical, archaeological, and paleontological data illuminate past epidemics and evolutionary history. Genetic mechanisms underlying the acquisition of microbial pathogenicity, including hybridization, polyploidization, and horizontal gene transfer, can now be reconstructed, as can gene-for-gene coevolution with plant hosts. Epidemiological parameters, such as geographic origin and range expansion, can also be assessed. Building on published case studies with individual phytomicrobial taxa, the stage is now set for broader, community-wide studies of preserved plant microbiomes to strengthen mechanistic understanding of microbial interactions and plant disease emergence.
Sodium Polyacrylate Hydrogel Electrolyte Hybridized with Layered Double Hydroxide for Solid-State NiCo/Zinc Battery
Authors: Patrick Dedetemo Kimilita , Karasawa Akira , Sonoyama Noriyuki
Published: April 2022

Zinc-based batteries have attracted attention for their safety in aqueous electrolytes with low cost, environmental friendliness, and high capacity. In this study, layered double hydroxide, a solid-state OH− ion conductor, was hybridized with sodium polyacrylate hydrogel to construct a strong elastic hydrogel electrolyte (PANa-LDH) with high OH− ion conductivity. PANa-LDH, KOH was introduced by dipping into 6.0 M KOH solution, showed a significantly high ionic conductivity of 0.213 S cm−1 at 30 °C. A solid-state battery was fabricated using nickel-cobalt hydroxide cathode, PANa-LDH electrolyte, and zinc anode. The high specific capacity of 287 mAh g−1 was obtained at 0.1 A g−1 with high energy and power densities of 212 Wh kg−1 and 73 kW kg−1 (based on the cathode weight), respectively.
Taking Advantage of Teamwork: Unsupported Cobalt Molybdenum Sulfide as an Active HER Electrocatalyst in Alkaline Media
Authors: Inocêncio Carlos V. M. , Rousseau Julie , Guignard Nadia , Canaff Christine , Morisset Sophie , Comminges Clément , Morais Cláudia , Kokoh K. Boniface
Published: April 2022

A bimetallic cobalt molybdenum sulfide (Co0.5Mo0.5Sx) material was studied as candidate electrocatalyst to replace platinum-based cathode for HER reaction in alkaline media. The Co0.5Mo0.5Sx was obtained from a hydrothermal synthesis methodology employing sodium diethyldithiocarbamate as sulfurizing agent, a non-conventional compound. The recovered sulfide material was physicochemically characterized by XRD, Raman spectroscopy, TEM and XPS measurements. Analogous monometallic sulfides were also synthesized to compare their HER activities to that of Co0.5Mo0.5Sx. Such electrochemical characterization was performed by the application of polarization and EIS analyzes in 1 M KOH. An evident synergistic effect emerged in the bimetallic sulfide and it was associated with the design of a catalyst less susceptible to air-oxidation added to the roles performed by cobalt- and molybdenum-based species in the HER mechanism. Finally, a physical mixture of Co0.5Mo0.5Sx and Carbon Vulcan was prepared aiming to enhance the electronic conductivity of the electrode. As result, an overpotential of 131 mV was requested to achieve −10 mA cm−2. In addition, to achieve −200 mA cm−2, this electrode only needed an overpotential 66 mV higher than the one necessary for the benchmarking 40% Pt/C electrocatalyst.
Electrodeposited Ni-Mo Surface Alloy @ Ni-Foam for Electrocatalytic Hydrogen Generation in Acidic and Alkaline Media
Authors: Shaikh Naznin , Pati Ranjan , Mukhopadhyay Indrajit , Ray Abhijit
Published: April 2022

Surface alloys using transition metal elements have been regarded as one of the intelligent choices in electrocatalytic hydrogen generation. Herein, hierarchical Ni-Mo bimetallic surface alloy @ microporous 3D Ni support is fabricated by controlled electrodeposition followed by annealing to exhibit hydrogen evolution performance comparable to Pt benchmark, both in the acidic and alkaline media. Precisely controlled formation of Mo-layer on Ni-foam during the electrodeposition through underpotential causes the formation of surface alloy, Ni-Mo. The optimized electrocatalyst shows low overpotentials of 58 mV and 50 mV at a current density of 10 mA cm−2 in 0.5 M H2SO4 and 1 M NaOH solutions, respectively. Moreover, the developed electrocatalyst also shows low Tafel slopes of 58.8 mV dec−1 and 86.8 mV dec−1 in acidic and alkaline media, respectively. The density functional theory based approach suggests that the free-energy of hydrogen adsorption-desorption is lower for a lesser number of Mo layers deposited on the Ni-matrix to keep it very close to that of Pt.
Electrodeposition vs Slurry Casting: How Fabrication Affects Electrochemical Reactions of Sb Electrodes in Sodium-Ion Batteries
Authors: Nieto Kelly , Gimble Nathan J. , Rudolph Layton J. , Kale Amanda R. , Prieto Amy L.
Published: April 2022

Antimony (Sb) electrodes are an ideal anode material for sodium-ion batteries, which are an attractive energy storage system to support grid-level energy storage. These anodes have high thermal stability, good rate performance, and good electronic conductivity, but there are limitations on the fundamental understanding of phases present as the material is sodiated and desodiated. Therefore, detailed investigations of the impact of the structure-property relationships on the performance of Sb electrodes are crucial for understanding how the degradation mechanisms of these electrodes can be controlled. Although significant work has gone into understanding the sodiation/desodiation mechanism of Sb-based anodes, the fabrication method, electrode composition and experimental parameters vary tremendously and there are discrepancies in the reported sodiation/desodiation reactions. Here we report the use of electrodeposition and slurry casting to fabricate Sb composite films to investigate how different fabrication techniques influence observed sodiation/desodiation reactions. We report that electrode fabrication techniques can dramatically impact the sodiation/desodiation reaction mechanism due to mechanical stability, morphology, and composition of the film. Electrodeposition has been shown to be a viable fabrication technique to process anode materials and to study reaction mechanisms at longer lengths scales without the convolution of binders and additives.
Bidirectional Ventricular Tachycardia with Stress-Induced Cardiomyopathy
Authors: Schreiber Ariyon , Gardner Michael , Sossou Chris , Greene Natasha , Ahsan Chowdhury
Published: April 2022

Bidirectional ventricular tachycardia (BDVT) is a rare electrocardiographic finding characterized by rapid, wide complex, alternating QRS morphology with 180-degree swings in the frontal plane axis or, less commonly, alternating right bundle branch and left bundle branch block morphology. The most proposed mechanisms for BDVT involve triggered activity or enhanced automaticity resulting from calcium dysregulation. Catecholamine surge can cause myocardial injury as well as calcium dysregulation resulting in enhanced automaticity that can lead to arrhythmias such as BDVT. This case report stands to describe a unique presentation of BDVT and stress-induced cardiomyopathy, resulting from catecholamine surge following multiple traumatic gunshot wounds in the setting of methamphetamine use.
MDL-800, the SIRT6 Activator, Suppresses Inflammation via the NF-κB Pathway and Promotes Angiogenesis to Accelerate Cutaneous Wound Healing in Mice
Authors: Jiang Xiaoqi , Yao Zhe , Wang Kangyan , Lou Lihua , Xue Kaikai , Chen Jinghao , Zhang Guojian , Zhang Yu , Du Jiqing , Lin Cai , Xiao Jian
Published: April 2022

Sirtuin 6 (SIRT6) is an NAD+-dependent deacetylase belonging to the sirtuin family. It has been shown to participate in wound healing and some inflammation-related disorders. However, the effect of MDL-800, a highly efficient and selective SIRT6 activator, on wound healing and inflammation has not been reported. Therefore, this study investigated whether MDL-800 confers anti-inflammatory effects and promotes wound healing and uncovered the molecular mechanisms involved. This was achieved using mouse models of full-thickness wounds. Results showed that MDL-800 significantly downregulated inflammation by attenuating the release of inflammatory mediators and improved collagen deposition and neovascularization of wounds, thereby accelerating cutaneous wound healing. Furthermore, MDL-800 significantly downregulated expression levels of TNF-α and IL-6 in the dorsal skin tissue of mice via the NF-κB pathway. These results demonstrated that MDL-800 exerted anti-inflammatory and prohealing effects, indicating that the SIRT6/NF-κB/IκB signaling pathway may play an important role in wound healing.
A BP Neural Network‐Based GIS‐Data‐Driven Automated Valuation Framework for Benchmark Land Price
Authors: Wu Lei , Zhang Yu , Wei Yongchang , Chen Fangyu
Published: April 2022

The automated valuation of benchmark land price plays an essential role in regulating land demand in Chinese real‐estate market as the big data are currently accumulated rapidly. However, this problem becomes highly challenging due to the multidimension, large volume, and nonlinearity of the land price‐influencing factors. In this paper, an effective data‐driven automated valuation framework is proposed for valuing real estate assets by combining a GIS (geographic information system) and neural network technologies. This framework can automatically obtain the values of spatial factors affecting land price from GIS and generate training set data for training the neural network to identify the complex relationship between all kinds of factors and benchmark land prices. The effectiveness and universality of the framework is verified via the data of benchmark land prices in Wuhan. The framework can be applied for automated benchmark land price valuation in other cities.
Ultrasound of Fetal Cardiac Function Changes in Pregnancy-Induced Hypertension Syndrome
Authors: Lv Maoting , Yu Shanshan , Li Yongzhen , Zhang Xiaoting , Zhao Dan
Published: April 2022

Pregnancy-induced hypertension syndrome (PIH) is a common pregnancy syndrome that could cause varying degrees of maternal and fetal organic damage and even endanger their lives. This study aimed to investigate ultrasound of fetal cardiac function changes in PIH. Totally 40 cases of gestational hypertension admitted to Cangzhou Central Hospital between October 2018 and September 2019 were enrolled in the hypertension group, and 40 women with healthy pregnancies during the same period were assigned to the normal group. Ultrasound results showed that PIH was associated with a significantly higher fetal cardiac septal thickness, fetal left ventricular end-diastolic area and end-systolic area, fetal right ventricular end-diastolic area and end-systolic area, fetal left ventricular systolic fraction 1 (VSF1), fetal left ventricular systolic fraction 2 (VSF2), fetal right VSF1, and fetal right VSF2 versus healthy pregnancy. The PIH fetuses had significantly lower neonatal weights versus healthy fetuses. Newborns of hypertensive pregnancies have larger hearts, faster heart rates, increased cardiac contractility, and lower weights versus newborns of healthy pregnancies.
[Retracted] Morphological Failure Study of Low Nickel Austenitic Grade SS: Metal Spinning
Authors: Vivek R. , Prakash B. , Sivamani S. , Selvaganapathy V. , Kumar S. Pradeep , Ramesh B. , Karthik R. , Jayakumar V. , Masi Chandran
Published: April 2022

The formability of the austenitic grade of low Ni‐treated steels (SSLNA) was examined by metal turning measure. The treated steel items are considered for choice as prepared with consumption safe properties. In monetary terms, they can contend with greater expense designing metals and amalgams dependent on nickel or titanium, while offering a scope of consumption opposing properties reasonable for a wide scope of utilizations. In this investigation, the austenitic grade of low nickel‐tempered steel material was spun and met with the crack. The deformation of spinning is done on the various angles with change in percentage of thickness from 14 to 80%. The characterization of the fracture has been concentrated by the field emission scanning electron microscope to notice the morphological states of the material. The 12.5 mm WD of sample provides clear rupture in the grain boundaries of microstructure. The essential investigation was inspected by energy‐dispersive spectroscopy. A solid connection was seen with both examinations approving the presence of voids in the material that causes the remaining anxieties which prompts the break on the SSLNA material.
Enamel Matrix Derivative Enhances the Odontoblastic Differentiation of Dental Pulp Stem Cells via Activating MAPK Signaling Pathways
Authors: Zhang Beidi , Xiao Min , Cheng Xiaogang , Bai Yu , Chen Hanze , Yu Qing , Qiu Lihong
Published: April 2022

The odontoblastic differentiation of dental pulp stem cells (DPSCs) contributes to pulp-dentin regeneration. Enamel matrix derivative (EMD) is considered to be a critical epithelial signal to induce cell differentiation during odontogenesis and has been widely applied to clinical periodontal tissue regeneration. The purpose of this study was to explore the effect of EMD on DPSCs proliferation and odontoblastic differentiation, as well as the underlying mechanisms. We conducted in vitro and in vivo researches to get a comprehensive understanding of EMD. In vitro phase: cell proliferation was assessed by a cell counting kit-8 (CCK-8) assay; then, alkaline phosphatase (ALP) activity and staining, alizarin red staining, real-time RT-PCR, and western blot analysis were conducted to determine the odontoblastic potential and involvement of MAPK signaling pathways. In vivo phase: after ensuring the biocompatibility of VitroGel 3D-RGD via scanning electron microscopy (SEM), the hydrogel mixture was subcutaneously injected into nude mice followed by histological and immunohistochemical analyses. The results revealed that EMD did not interfere with DPSCs proliferation but promoted the odontoblastic differentiation of DPSCs in vitro and in vivo. Furthermore, blocking the MAPK pathways suppressed the EMD-enhanced differentiation of DPSCs. Finally, VitroGel 3D-RGD could well support the proliferation, differentiation, and regeneration of DPSCs. Overall, this study demonstrates that EMD enhances the odontoblastic differentiation of DPSCs through triggering MAPK signaling pathways. The findings provide a new insight into the mechanism by which EMD affects DPSCs differentiation and proposes EMD as a promising candidate for future stem cell therapy in endodontics.
A Recognition Method Based on Speech Feature Parameters-English Teaching Practice
Authors: Zhu Lili , Yan Xiujing , Wang Jing
Published: April 2022

In order to improve the effect of English teaching practice, this paper constructs an intelligent English phonetic teaching system combined with the method of phonetic feature parameter recognition. Moreover, this paper simulates the self-mixing interference signal containing noise by establishing a simulation, analyzes the size of the noise and its various possibilities, and selects the EEMD method as the English speech denoising algorithm. In addition, with the support of an intelligent denoising algorithm, this paper implements an English intelligent teaching system based on the recognition algorithm of English speech feature parameters. Finally, this paper evaluates the teaching effect of the intelligent English speech feature recognition algorithm proposed in this paper and the intelligent teaching system of this paper by means of simulation teaching. The research shows that the English teaching system based on the intelligent speech feature recognition algorithm proposed in this paper has a good effect.