bluuebunny/crossref_metadata_2025 huggingface dataset:
Low-Power Anti-Glitch Double-Edge Triggered Flip-Flop Based on Robust C-Elements
Authors: Huang Zhengfeng , Zhong Wanshu , Duan Lanxi , Zhang Yue , Liang Huaguo , Wang Jianan , Song Tai , Lu Yingchun
Published: April 2022

Glitch at the input can increase the power consumption of flip-flop greatly. To solve this problem effectively, a Low-Power Anti-Glitch Double-Edge Triggered Flip-Flop Based on Robust C-Elements (LARC) is proposed in this paper. The proposed Latch Multiplexer-A Double-edge Triggered Flip-flop (LARC-DET) can effectively block the glitch at the input and prevent the redundant transition at internal nodes. As a result, the extra power consumption caused by the glitch at the input is effectively reduced. The simulation was performed using HSPICE under 32[Formula: see text]nm complementary metal oxide semiconductor (CMOS) process. The simulation results show that, compared with 12 double edge flip-flops, the proposed LARC-DET is the lowest in terms of power consumption and power delay product. Process voltage temperature (PVT) variation analysis shows its insensitivity to voltage variation, temperature variation and process variation.
SCASA: A Spark-Based Parallel Approach for Net Primary Productivity Calculation with CASA Model
Authors: Zhang Hui , Ren Kaijun , Li Xiaoyong
Published: April 2022

Net primary productivity (NPP) research is an essential aspect of carbon cycle research. Remote sensing combined with CASA (Carnegie–Ames–Stanford Approach) model is a mainstream method to calculate the NPP, which is generally based on the ENVI or ArcGIS in the standalone mode. However, with the enhancement of spatial and temporal resolution of remote sensing images, the volume of data has also grown rapidly, which makes the centralized methods not well adapted to the NPP calculation. In this paper, we propose SCASA, a Spark-based parallel approach for NPP calculation with CASA model. Based on the distributed storage characteristics of HDFS, we propose a storage strategy specifically for CASA model. Based on the characteristics of CASA model and Spark’s parallel computing rules, we redesign the computation process to maximize parallelism to further improve the calculation speed. Extensive comparative experiments based on ArcGIS and Spark demonstrate the proposed approach outperform the existing CASA model.
Statistical Model Checking for Stochastic and Hybrid Autonomous Driving Based on Spatio-Clock Constraints
Authors: Wang Jinyong , Huang Zhiqiu , Zhu Yi , Shen Guohua
Published: April 2022

Autonomous driving vehicles are a kind of typical cyber-physical systems integrating complex interactions between hardware and software components such as collaborative computation, distributed communication, and spatio-clock synchronous control with surrounding traffic environment. They can percept the environment, communicate with surroundings, and react fast enough to control independently. The purpose of autonomous driving emergence is to improve driving safety, reduce environmental pollution, and ease the traffic congestion. However, new features with surrounding open and dynamic environment make systems design and verification becoming more and more complex than ever, such as stochastic communication delay, hardware spontaneous failure distribution, and natively hybrid behaviors described by ordinary differential equations. Spatial and time collision avoidance remains crucial obstacles on the path to becoming ubiquitous and dependable. In this paper, we adopt statistical model checking (SMC) to enlighten possible hazards affected by stochastic and hybrid features in the design phase of autonomous driving systems. In order to provide safety and accountability, we first propose a dedicated multi-lane spatio-clock stochastic specification language (MLSCL) to describe safety invariants and guards in domain-specific autonomous driving systems. Then, we present the semantic mapping rules between MLSCL and UPPAAL SMC models, and design the spatio-clock stochastic and hybrid automata based on MLSCL in order to model inherently stochastic and hybrid behaviors. Finally, we present an illustrative lane-change case study to verify spatio-clock stochastic and hybrid-related properties adopting SMC, and demonstrate the effectiveness of our proposed approach.
An Empirical Study on Bugs in PHP
Authors: Wang Ziyuan , Bu Dexin , Xuan Xingpeng , Gu Jia
Published: April 2022

PHP (Hypertext Preprocessor) is a scripting language that has been widely used in web development. This paper conducts an empirical study on bugs in PHP. By analyzing 35,921 bug reports, 6524 revisions, and root causes of randomly selected 500 bugs, we find that: (1) Among all the 385 versions involved in these bugs, there are the most bugs in PHP 4.0.4, PHP 4.0.6, and PHP 4.0.3; Documentation bugs are mainly distributed in PHP 4.y.z and PHP 5.y.z; Security bugs are distributed primarily in the relatively later normal versions of PHP 5.y.z. (2) Documentation, Compile, and Scripting Engine packages are greatly affected by bugs; 73.71% of documentation bugs affect documentation; PHAR, EXIF, and GD are more affected by security bugs. (3) It may be not difficult to repair most bugs since the number of modified lines of code and files are limited; However, nearly 11% of bugs need more than one year to repair; Compared with documentation bugs, security bugs are more difficult to be repaired; The duration of bugs in PHP 8.y.z is shorter than in other versions. (4) Semantic bugs and documentation bugs are the more common root causes of bugs than others. Besides, among semantic bugs, the “Missing Features” bugs and “Processing” bugs are more than others. These results could indicate some potential problems during the detecting and repairing of PHP’s bugs. These findings reveal some laws of bugs in PHP. It could assist developers of PHP in improving their development quality, assist maintainers of PHP in detecting and repairing bugs more effectively, and suggest users of PHP evade potential risks.
Convergence analysis of the discrete consensus-based optimization algorithm with random batch interactions and heterogeneous noises
Authors: Ko Dongnam , Ha Seung-Yeal , Jin Shi , Kim Doheon
Published: April 2022

We present stochastic consensus and convergence of the discrete consensus-based optimization (CBO) algorithm with random batch interactions and heterogeneous external noises. Despite the wide applications and successful performance in many practical simulations, the convergence of the discrete CBO algorithm was not rigorously investigated in such a generality. In this work, we introduce a generalized discrete CBO algorithm with a weighted representative point and random batch interactions, and show that the proposed discrete CBO algorithm exhibits stochastic consensus and convergence toward the common equilibrium state exponentially fast under suitable assumptions on system parameters. For this, we recast the given CBO algorithm with random batch interactions as a discrete consensus model with a random switching network topology, and then we use the mixing property of interactions over sufficiently long time interval to derive stochastic consensus and convergence estimates in mean square and almost sure senses. Our proposed analysis significantly improves earlier works on the convergence analysis of CBO models with full batch interactions and homogeneous external noises.
Existence analysis and numerical approximation for a second-order model of traffic with orderliness marker
Authors: Andreianov Boris , Sylla Abraham
Published: April 2022

We propose a toy model for self-organized road traffic taking into account the state of orderliness in drivers’ behavior. The model is reminiscent of the wide family of generalized second-order models (GSOM) of road traffic. It can also be seen as a phase-transition model. The orderliness marker is evolved along vehicles’ trajectories and it influences the fundamental diagram of the traffic flow. The coupling we have in mind is non-local, leading to a kind of “weak decoupling” of the resulting [Formula: see text] system; this makes the mathematical analysis similar to the analysis of the classical Keyfitz–Kranzer system. Taking advantage of the theory of weak and renormalized solutions of one-dimensional transport equations [Panov, 2008], which we further develop on this occasion in the Appendix, we prove the existence of admissible solutions defined via a mixture of the Kruzhkov and the Panov approaches; note that this approach to admissibility does not rely upon the classical hyperbolic structure for [Formula: see text] systems. First, approximate solutions are obtained via a splitting strategy; compactification effects proper to the notion of solution we rely upon are carefully exploited, under general assumptions on the data. Second, we also address fully discrete approximation of the system, constructing a BV-stable Finite Volume numerical scheme and proving its convergence under the no-vacuum assumption and for data of bounded variation. As a byproduct of our approach, an original treatment of local GSOM-like models in the BV setting is briefly discussed, in relation to discontinuous-flux LWR models.
Non-slice 3-stranded pretzel knots
Authors: Kim Min Hoon , Lee Changhee , Song Minkyoung
Published: April 2022

Greene-Jabuka and Lecuona confirmed the slice-ribbon conjecture for 3-stranded pretzel knots except for an infinite family [Formula: see text], where [Formula: see text] is an odd integer greater than [Formula: see text]. Lecuona and Miller showed that [Formula: see text] are not slice unless [Formula: see text]. In this note, we show that four-fifths of the remaining knots in the family are not slice.
INVESTIGATION ON THE THERMAL BEHAVIOR OF FRICTION STUD WELDING OF DISSIMILAR ALUMINUM/MILD STEEL JOINTS
Authors: THARMARAJ R. , HYNES N. RAJESH JESUDOSS
Published: April 2022

Friction stud welding process is a suitable candidate in joining stud fasteners for steel structure buildings, military vehicles, automobiles, aircraft, ocean liners, bridges, ship buildings, etc., The peak temperature for welding is achieved by converting mechanical energy to thermal energy at the sample interface without the use of electric energy from other sources because it is a solid-state process. The study of the thermal behavior of different metals during friction stud welding is very important since it is a thermal energy process. However, there is no good thermal model for the friction stud welding process. In this work, the generation of heat flux at the interfacial area of two distinct metals, namely aluminum and mild steel, is calculated using a mathematical model. The temperature at the interfacial region, which plays a significant role in the quality and strength of the weld component, is particularly focused on experimentation and analytical modeling. In the experimentation, a noncontact type infrared thermometer is used to measure temperature directly. The temperature profile was determined by the finite difference method based on thermal resistance and capacitance formulation at transient conditions. The obtained mathematical results are compared with the experimental results at the distance of 5 and 10[Formula: see text]mm from the welded interface. The computed temperature profile is in good agreement with the experimental data on the heating side and with a minimum degree of deviation in the cooling part. The maximum percentage of error for the 5[Formula: see text]mm interface is 3.349 and for the 10[Formula: see text]mm interface is 2.857. This deviation is due to the zero-axial shortening assumption in the analytical model. Besides, the temperature characteristics of the welded are analyzed at various time increments by numerical simulation. As a result, the predicted temperature is more on the aluminum side compared to the mild steel due to a change in thermal properties. This proposed thermal model would be helpful to improve the design and manufacture of welding machines.
From braces to Hecke algebras and quantum groups
Authors: Doikou Anastasia , Smoktunowicz Agata
Published: April 2022

We examine links between the theory of braces and set-theoretical solutions of the Yang–Baxter equation, and fundamental concepts from the theory of quantum integrable systems. More precisely, we make connections with Hecke algebras and we identify new quantum groups associated to set-theoretic solutions coming from braces. We also construct a novel class of quantum discrete integrable systems and we derive symmetries for the corresponding periodic transfer matrices.
Flux balance network expansion predicts stage-specific human peri_implantation embryo metabolism
Authors: Dadashi Andisheh , Martinez Derek
Published: April 2022

Metabolism is an essential cellular process for the growth and maintenance of organisms. A better understanding of metabolism during embryogenesis may shed light on the developmental origins of human disease. Metabolic networks, however, are vastly complex with many redundant pathways and interconnected circuits. Thus, computational approaches serve as a practical solution for unraveling the genetic basis of embryo metabolism to help guide future experimental investigations. RNA-sequencing and other profiling technologies make it possible to elucidate metabolic genotype–phenotype relationships and yet our understanding of metabolism is limited. Very few studies have examined the temporal or spatial metabolomics of the human embryo, and prohibitively small sample sizes traditionally observed in human embryo research have presented logistical challenges for metabolic studies, hindering progress towards the reconstruction of the human embryonic metabolome. We employed a network expansion algorithm to evolve the metabolic network of the peri-implantation embryo metabolism and we utilized flux balance analysis (FBA) to examine the viability of the evolved networks. We found that modulating oxygen uptake promotes lactate diffusion across the outer mitochondrial layer, providing in-silico support for a proposed lactate–malate–aspartate shuttle. We developed a stage-specific model to serve as a proof-of-concept for the reconstruction of future metabolic models of development. Our work shows that it is feasible to model human metabolism with respect to time-dependent changes characteristic of peri-implantation development.
Relevance of the Coadaptation Dimension in Technological Cooperation
Authors: Alves Fernanda Salvador , De-Carli Eduardo , Segatto Andréa Paula
Published: April 2022

Coadaptation is one of the relational capabilities (RC) dimensions and it refers to the ability organizations have to adapt resources to increase the benefits provided by their partnerships. It is in this scenario that this research lies since it aimed to compare the similarities of the coadaptation dimension in cooperations for the development of non-profit (Group N) and profit-oriented (Group P) technologies. Factors such as “adaptation to partners” were mentioned in Group P. However, in Group N, “increased social credibility” was more cited. This research helps deepen the knowledge about non-profit-oriented technologies cooperation and the coadaptation dimension. Future research can discuss similar issues but addressing the other dimensions.
A Triaxial Viscoplastic Model with Temperature Dependence for Asphalt Concrete Permanent Deformation
Authors: Cao Wei , Kim Y. Richard
Published: April 2022

Asphalt concrete is a composite material comprised of aggregate skeleton and asphalt cement. Its permanent or viscoplastic (VP) deformation is characterized by time and temperature dependence, memory effect, and pressure sensitivity. To the best knowledge of the authors, there have been no VP models explicitly considering the nonlinear temperature effects in permanent deformation of asphalt concrete. In previous work, the authors developed a triaxial VP model that featured a VP relaxation spectrum and a modulus parameter [Formula: see text],[Formula: see text]. The spectrum was postulated as a material function representing the time dependence and memory effect, while [Formula: see text],[Formula: see text] was only a function of the stress condition to capture the pressure dependence. The objective of this study was to incorporate temperature dependence into the model. It was achieved by introducing the concept of VP shift factor solely to translate the relaxation spectrum. This strategy was inspired by the time–temperature superposition principle in the viscoelastic (VE) theory. The shift factor was identified experimentally at three temperatures different from the model calibration temperature. The VP shift factor function was thus established, and comparison with its VE counterpart showed that the VP response exhibited greater temperature sensitivity. Numerical simulation was conducted at several temperatures to illustrate the nonlinear temperature effects on the VP deformation and relaxation of the internal stress that served as the hardening/softening variable.
Experimental Analysis of the Static and Dynamic Behavior of 3D Printed Bio-Based Conventional and Auxetic Architectural Materials
Authors: Hamrouni Anis , Rebiere Jean-Luc , El Mahi Abderrahim , Beyaoui Moez , Haddar Mohamed
Published: April 2022

This paper presents the results of experimental analyses of the static and dynamic behavior of bio-sourced conventional and auxetic architectural materials. Three different configurations were studied. The specimens were made with the technology of additive manufacturing (3D printing) and were made of the same material which is polylactic acid reinforced with flax fibers (PFF). Several tensile tests were performed on four relative densities for each configuration of the composite to understand their influence on the static behavior of the material. Taking into account the insufficiency of the static tests to correctly predict the behavior of the composite, vibration tests were carried out on the same densities and composite configurations. The focus will be mainly on the study of the influence of the 2D lattice structures for each density on the evolution of the dynamic stiffness and damping properties.
Response Statistics of Single-Degree-of-Freedom Systems with Lévy Noise by Improved Path Integral Method
Authors: Zan Wanrong , Jia Wantao , Xu Yong
Published: April 2022

In this paper, we put forward an improved version of the path integral (PI) method for the response statistics of single-degree-of-freedom (SDOF) system excited by Lévy noise. To overcome the problem of large amount of calculation and storage, the PI method is simplified and parallelized, which makes the PI method for SDOF system with Lévy noise feasible and efficient. As the key to the PI method, the short-time transition probability density function (PDF) of the SDOF system is derived and verified by proving that the PI solution satisfies the corresponding fractional Fokker–Planck–Kolmogorov (FPK) equation. The fractional FPK equation, which is the governing equation of the SDOF system, is derived through the characteristic function and the Chapman–Kolmogorov equation. To solve the problem of large storage and calculations in the PI method, we simplify the one-step iteration formula and perform parallel calculations on the simplified formula. The simplification of the one-step iteration formula reduces one-fold integration, thereby reducing the storage capacity of the one-step transition matrix. Parallel calculation by domain decomposition can effectively reduce the calculation time, which can be seen from the running time of two prototypical examples. Besides, to show the effectiveness of the improved PI method, Monte Carlo solutions and analytical solutions are used as reference solutions.
The Dimension Splitting Interpolating Element-Free Galerkin Method for Solving 3D Wave Equations
Authors: Wang Shihan , Peng Miaojuan
Published: April 2022

Based on the idea of dimension splitting method, a dimension splitting interpolating element-free Galerkin (DSIEFG) method for 3D wave propagation problems is proposed. In the splitting direction, the 3D domain of a problem is divided into a series of related 2D subdomains. Using the improved interpolating moving least-squares (IMLS) method to acquire the shape function in the 2D subdomains, the discretized equations are formed based on Galerkin weak form of 2D problem. The discretized equations are coupled by using the difference method in the splitting direction. Then, the final equations of the DSIEFG method for 3D wave propagation problems are obtained. Numerical examples are given to study the effects of node distribution, number of split layers, influence domain parameters, splitting direction, and time step on the computational accuracy of the DSIEFG method. The results of numerical examples show that the DSIEFG method is more efficient and accurate compared with the improved EFG method for 3D wave equations.
Constructing CoO Nanoneedle Hierarchical Structure Based on Cassie States for Highly Efficient Fog Harvesting
Authors: Jin Lian-Lian , Zhang Jia-Yi , He Zhao-Cheng , He Wen-Xin , Sun Chang , Chu Zheng-Wen , Wang Xue-Wei , Yuan Zhi-Hao
Published: April 2022

Collecting water from the fog becomes a promising strategy to address the water shortage. In this work, the CoO nanoneedle hierarchical structure was designed and prepared on the surface of the copper mesh by hydrothermal synthesis. The number of nanoclusters on the CoO nanoneedle array was changed by adjusting the mass concentration of the precursor solution. CoO nanoneedle array and nanoclusters form a hierarchical structure, which is conducive to the binding of air and the aggregation of water droplets. The results show that the surface of CoO nanoneedle hierarchical structure with good orientation and moderate sparsity has weak adhesion and stronger air binding capacity. Compared with other CoO nanoneedle structures, the hierarchical structure can effectively maintain the Cassie state wetting model for a long time, which improves the fog harvesting efficiency. This research offers a new strategy to design nanostructures for efficient fog collection, which has important implications on water harvesting from the air.
One-Pot Fabrication of Superhydrophilic/Underwater Superoleophobic Membrane Based on Mussel-Inspired Chemistry for High-Efficiency Oil-Water Separation
Authors: Yan Zhuo , Zhou Zhiping , Zhang Ziwei , Zhang Ruilong , Cui Jiuyun , Dai Jiangdong
Published: April 2022

Membrane separation technology is attracting a broad spectrum of attention because of its low energy consumption and superior availability in oily wastewater treatment. Poly(vinylidene fluoride) (PVDF) membranes play an important role in membrane separation field. Herein, a kind of superhydrophilic/underwater superoleophobic nanoparticles modified PVDF membrane based on mussel-inspired chemistry was prepared via a one-pot method. This method applied the Michael addition/Schiff base reactions between dopamine (DA) and alkoxy hydrolysis of (3-Aminopropyl) trimethoxysilane (APTMS). The water contact angle (WCA) decreased from 117∘ to 12.6∘ after the modification. The resultant superhydrophilic/underwater superoleophobic membrane exhibited the outstanding water flux (12280.4[Formula: see text]L m[Formula: see text] h[Formula: see text] bar[Formula: see text], which was a sixfold increment compared to Pristine PVDF. Besides, the resultant membranes showed the effective separation of various oil–water emulsions [Formula: see text], and a high recoverability in multiple-iterations presented the membrane possessing the performance of persistent separation. With the simplicity of one-pot method preparation, outstanding performance, and environmental friendliness, this work provided a potential strategy to large-scale modified membrane materials for the treatment of oily wastewater.
Primality, criticality and minimality problems in trees
Authors: Marweni Walid
Published: April 2022

In a graph [Formula: see text], a module is a vertex subset [Formula: see text] of [Formula: see text] such that every vertex outside [Formula: see text] is adjacent to all or none of [Formula: see text]. For example, [Formula: see text], [Formula: see text][Formula: see text] and [Formula: see text] are modules of [Formula: see text], called trivial modules. A graph, all the modules of which are trivial, is prime; otherwise, it is decomposable. A vertex [Formula: see text] of a prime graph [Formula: see text] is critical if [Formula: see text] is decomposable. Moreover, a prime graph with [Formula: see text] noncritical vertices is called [Formula: see text]-critical graph. A prime graph [Formula: see text] is [Formula: see text]-minimal if there is some [Formula: see text]-vertex set [Formula: see text] of vertices such that there is no proper induced subgraph of [Formula: see text] containing [Formula: see text] is prime. From this perspective, Boudabbous proposes to find the [Formula: see text]-critical graphs and [Formula: see text]-minimal graphs for some integer [Formula: see text] even in a particular case of graphs. This research paper attempts to answer Boudabbous’s question. First, we describe the [Formula: see text]-critical tree. As a corollary, we determine the number of nonisomorphic [Formula: see text]-critical tree with [Formula: see text] vertices where [Formula: see text]. Second, we provide a complete characterization of the [Formula: see text]-minimal tree. As a corollary, we determine the number of nonisomorphic [Formula: see text]-minimal tree with [Formula: see text] vertices where [Formula: see text].
A multi-optimization-based genetic algorithm mapper design for three transmit uncoded space-time diversity systems
Authors: Solwa Shaheen , Bamisaye Ayodeji James , Ayanda Dauda
Published: April 2022

Three transmit antennas Uncoded Space-Time Labeling Diversity (USTLD) systems were recently proposed as a direct extension to the two transmit antennas USTLD system. By employing more antennas at the transmitter, antenna — as well as — labeling diversity (LD) can be further achieved. Existing mapper designs for three transmit antennas USTLD systems are based on symmetrical heuristics, and hence no asymmetrical mapper designs can be produced. This paper proposes a multi-function optimization genetic algorithm for the three transmit antennas USTLD system that produces mapper designs irrespective of size or symmetry. The genetic algorithm was tested on 16-, 32QAM, 16-, 32APSK and 16APSK constellations that do not exhibit diagonal symmetry. The proposed genetic algorithm had produced mapper designs that match but did not improve upon existing mapper designs for 16QAM and 32QAM, respectively. The 16APSK and 32APSK mapper designs produced achieved diversity gains of [Formula: see text] and [Formula: see text] when compared to existing third mapper designs, as well as [Formula: see text] and [Formula: see text] gain over the two transmit antennas USTLD scheme at the BER of [Formula: see text]. Furthermore, when tested on 16APSK constellations that do not exhibit diagonal symmetry, these mappers achieved diversity gains between [Formula: see text], [Formula: see text] and [Formula: see text] over the two-transmit USTLD scheme at the BER of [Formula: see text], respectively. The computational complexity of the proposed genetic algorithm was analyzed based on a previous study, which was shown to be [Formula: see text].
The Application of Deep Learning Imputation and Other Advanced Methods for Handling Missing Values in Network Intrusion Detection
Authors: Szczepański Mateusz , Pawlicki Marek , Kozik Rafał , Choraś Michał
Published: April 2022

In intelligent information systems data play a critical role. The issue of missing data is one of the commonplace problems occurring in data collected in the real world. The problem stems directly from the very nature of data collection. In this paper, the notion of handling missing values in a real-world application of computational intelligence is considered. Two experimental campaigns were conducted, evaluating different approaches to the missing values imputation on Random Forest-based classifiers, trained using modern cybersecurity benchmarks datasets: CICIDS2017 and IoT-23. In result of the experiments it transpired that the chosen algorithm for data imputation has a severe impact on the results of the classifier used for network intrusion detection. It also comes to light that one of the most popular approaches to handling missing data — complete case analysis — should never be used in cybersecurity.
Consistent Extended Kalman Filter Design for Maneuvering Target Tracking and Its Application on Hand Position Tracking
Authors: Tian Lin , Xu Yang , Xue Wenchao , Cheng Long
Published: April 2022

This paper proposes the consistent extended Kalman filter (CEKF) for the maneuvering target tracking (MTT) with nonlinear uncertain dynamics, and applies it on hand position tracking. The general model of the MTT system is presented with unmodeled dynamics in terms of nonlinear unknown function of states. The CEKF is proposed to ensure that the bounds of the estimation error’s covariance matrix are available through the filter algorithm. As a result, the corresponding accuracy of the filter approach can be achieved online. Furthermore, a CEKF-based MTT algorithm is constructed via the tuning law of the critical parameter matrix [Formula: see text]. Finally, the effectiveness of CEKF is verified by MTT numerical simulations and hand tracking experiments under different maneuvers. Specifically, two indices are employed to compare the CEKF with extended Kalman filter (EKF): the mean square errors (MSEs) and the bounded percentage, i.e. the percentage of the range where the estimation error is enclosed by the bound calculated by algorithms. All MSEs of CEKF are smaller than those of EKF, where the worst MSEs of CEKF and EKF are 0.14 and 4.18 in the simulation, as well as 0.11 and 0.59 in the experiments, respectively; all bounded percentages of CEKF are larger than those of EKF, where the worst average bounded percentages of CEKF and EKF are 87.86% and 14.58%, as well as 97.41% and 41.79% in the experiments, respectively.
Detection and Recognition of Driver Distraction Using Multimodal Signals
Authors: Das Kapotaksha , Papakostas Michalis , Riani Kais , Gasiorowski Andrew , Abouelenien Mohamed , Burzo Mihai , Mihalcea Rada
Published: April 2022

Distracted driving is a leading cause of accidents worldwide. The tasks of distraction detection and recognition have been traditionally addressed as computer vision problems. However, distracted behaviors are not always expressed in a visually observable way. In this work, we introduce a novel multimodal dataset of distracted driver behaviors, consisting of data collected using twelve information channels coming from visual, acoustic, near-infrared, thermal, physiological and linguistic modalities. The data were collected from 45 subjects while being exposed to four different distractions (three cognitive and one physical). For the purposes of this paper, we performed experiments with visual, physiological, and thermal information to explore potential of multimodal modeling for distraction recognition. In addition, we analyze the value of different modalities by identifying specific visual, physiological, and thermal groups of features that contribute the most to distraction characterization. Our results highlight the advantage of multimodal representations and reveal valuable insights for the role played by the three modalities on identifying different types of driving distractions.
GO-Finder: A Registration-free Wearable System for Assisting Users in Finding Lost Hand-held Objects
Authors: Yagi Takuma , Nishiyasu Takumi , Kawasaki Kunimasa , Matsuki Moe , Sato Yoichi
Published: April 2022

People spend an enormous amount of time and effort looking for lost objects. To help remind people of the location of lost objects, various computational systems that provide information on their locations have been developed. However, prior systems for assisting people in finding objects require users to register the target objects in advance. This requirement imposes a cumbersome burden on the users, and the system cannot help remind them of unexpectedly lost objects. We propose GO-Finder (“Generic Object Finder”), a registration-free wearable camera-based system for assisting people in finding an arbitrary number of objects based on two key features: automatic discovery of hand-held objects and image-based candidate selection. Given a video taken from a wearable camera, GO-Finder automatically detects and groups hand-held objects to form a visual timeline of the objects. Users can retrieve the last appearance of the object by browsing the timeline through a smartphone app. We conducted user studies to investigate how users benefit from using GO-Finder. In the first study, we asked participants to perform an object retrieval task and confirmed improved accuracy and reduced mental load in the object search task by providing clear visual cues on object locations. In the second study, the system’s usability on a longer and more realistic scenario was verified, accompanied by an additional feature of context-based candidate filtering. Participant feedback suggested the usefulness of GO-Finder also in realistic scenarios where more than one hundred objects appear.
Atmospheres of Rocky Exoplanets
Authors: Wordsworth Robin , Kreidberg Laura
Published: April 2022

Rocky planets are common around other stars, but their atmospheric properties remain largely unconstrained. Thanks to a wealth of recent planet discoveries and upcoming advances in observing capability, we are poised to characterize the atmospheres of dozens of rocky exoplanets in this decade. The theoretical understanding of rocky exoplanet atmospheres has advanced considerably in the last few years, yielding testable predictions of their evolution, chemistry, dynamics, and even possible biosignatures. We review key progress in this field to date and discuss future objectives. Our major conclusions are as follows: ▪ Many rocky planets may form with initial H2–He envelopes that are later lost to space, likely due to a combination of stellar UV/X-ray irradiation and internal heating. ▪ After the early stages of evolution, a wide diversity of atmospheric compositions is expected as a result of variations in host star flux, atmospheric escape rates, interior exchange, and other factors. ▪ Observations have ruled out both the presence of H2-dominated atmospheres on several nearby rocky exoplanets and the presence of any thick atmosphere on one target. A more detailed atmospheric characterization of these planets and others will become possible in the near future. ▪ Exoplanet biosphere searches are an exciting future goal. However, reliable detections for a representative sample of planets will require further advances in observing capability and improvements in our understanding of abiotic planetary processes.
Open Structural Data in Precision Medicine
Authors: Nussinov Ruth , Jang Hyunbum , Nir Guy , Tsai Chung-Jung , Cheng Feixiong
Published: April 2022

Three-dimensional protein structural data at the molecular level are pivotal for successful precision medicine. Such data are crucial not only for discovering drugs that act to block the active site of the target mutant protein but also for clarifying to the patient and the clinician how the mutations harbored by the patient work. The relative paucity of structural data reflects their cost, challenges in their interpretation, and lack of clinical guidelines for their utilization. Rapid technological advancements in experimental high-resolution structural determination increasingly generate structures. Computationally, modeling algorithms, including molecular dynamics simulations, are becoming more powerful, as are compute-intensive hardware, particularly graphics processing units, overlapping with the inception of the exascale era. Accessible, freely available, and detailed structural and dynamical data can be merged with big data to powerfully transform personalizedpharmacology. Here we review protein and emerging genome high-resolution data, along with means, applications, and examples underscoring their usefulness in precision medicine.
Relational Contracts and Development
Authors: Macchiavello Rocco
Published: April 2022

This article reviews an emerging body of evidence on relational contracts, defined as informal arrangements sustained by the value of future interactions. We focus on developing and international markets, which are often characterized as contexts with weak formal contract enforcement. We introduce relational contracting between firms as a governance form alternative to both firms and markets. We then review evidence on the prevalence of long-term relationships between firms and discuss why this governance form might be particularly common in developing countries. After introducing a simple framework, we discuss the measurement of relational contracting between firms. We review an approach that takes dynamic incentive compatibility constraints to the data to quantify the value of future interactions and illustrate how different types of shocks can be used to uncover the inner functioning of relational contracting. We also review structural models and conclude with policy implications and promising avenues for future research.
The Economics of Agricultural Productivity in South Africa
Authors: Vink Nick , Conradie Beatrice , Matthews Nicolette
Published: April 2022

Accurate measures of productivity growth are an important policy tool but are difficult to obtain in South African circumstances. In this article, we review work on the measurement of farm-level productivity in South Africa since the earliest attempts at multifactor indices in the early 1990s. The focus is on total factor productivity, but single input measures such as labor and land productivity (yields) are also discussed. Measurements using time-series and cross-sectional data are discussed separately, along with measures to explain the effect of climate change. Data deficiencies are also pointed out. The article concludes that international collaboration should be maintained if important issues such as the COVID-19 impact, food security, climate change, and labor market shocks are to be successfully addressed.
Cross-bridge thermodynamics in pulmonary arterial hypertensive right-ventricular failure
Authors: Pham Toan , Tran Kenneth , Taberner Andrew J. , Loiselle Denis S. , Han June-Chiew
Published: April 2022

This study characterizes cross-bridge mechano-energetics and dynamic stiffness of right-ventricular trabeculae isolated from a rat model of pulmonary hypertensive right-ventricular failure. Failing trabeculae showed increased passive force but normal active force. Their lower mechanical efficiency is found to be driven by an increase in the energy expenditure arising from contractile activation. This does not reflect a change in their cross-bridge stiffness and efficiency.
Skeletal muscle properties show collagen organization and immune cell content are associated with resistance exercise response heterogeneity in older persons
Authors: Long Douglas E. , Peck Bailey D. , Lavin Kaleen M. , Dungan Cory M. , Kosmac Kate , Tuggle Steven C. , Bamman Marcas M. , Kern Philip A. , Peterson Charlotte A.
Published: April 2022

Extensive analyses of muscle features associated with muscle size and resistance training response in older persons, including sex differences, and evaluation of multiple measures of hypertrophy are discussed. New skeletal muscle features, such as collagen organization and CD11b-expressing immune cells, both CD206+ and CD206−, offer potential new targets to increase resistance training response in older individuals. A composite score using three indices of muscle growth reveal that changes in immune cells, myonuclei, and capillary density are critically important for overall muscle growth in older persons. Evidence exists for macrophage heterogeneity.
A HIF-1 signature dominates the attenuation in the human skeletal muscle transcriptional response to high-intensity interval training
Authors: Norrbom Jessica Maria , Ydfors Mia , Lovric Alen , Perry Christopher G.R. , Rundqvist Helene , Rullman Eric
Published: April 2022

This is the first study to address the phenomena of attenuation of the acute exercise response on a global genomic scale with a focus on underlying regulatory machinery and it is, to the best of our knowledge, the first study conducted in humans was exercise-induced regulation of different canonical pathways and transcription factors are contrasted with regards to attenuation after a period with regular exercise training. These results provide evidence for a pathway-specific regulated augmentation of the response to acute exercise over time that tracks with the successive adaptation on the systemic level.
What are the effects of acute exercise and exercise training on cerebrovascular hemodynamics following stroke? A systematic review and meta-analysis
Authors: Moncion Kevin , Allison Elric Y. , Al-Khazraji Baraa K. , MacDonald Maureen J. , Roig Marc , Tang Ada
Published: April 2022

Limited data exist regarding the effects of acute exercise and exercise training on cerebrovascular hemodynamic variables after stroke. This systematic review and meta-analysis 1) examined the effects of acute exercise and exercise training on cerebrovascular hemodynamic variables reported in the stroke exercise literature and 2) synthesized the peak middle cerebral artery blood velocity (MCAv) achieved during an acute bout of moderate-intensity exercise in individuals after stroke. Six databases (Medline, Embase, Web of Science, CINAHL, PsycINFO, AMED) were searched from inception to December 1st, 2021 for studies that examined the effect of acute exercise or exercise training on cerebrovascular hemodynamics in adults after stroke. Two reviewers conducted title and abstract screening, full-text evaluation, data extraction, and quality appraisal. Random-effects models were used in meta-analysis. Nine studies, including four acute exercise ( n = 61) and five exercise training studies ( n = 193), were included. Meta-analyses were not statistically feasible for several cerebrovascular hemodynamic variables. Descriptive analysis reveals that exercise training may increase cerebral blood flow and cerebrovascular reactivity to carbon dioxide among individuals after stroke. Meta-analysis of three acute exercise studies revealed no significant changes in MCAv during acute moderate-intensity exercise [ n = 48 participants, mean difference = 5.2 cm/s, 95% confidence interval (CI) [−0.6, 11.0], P = 0.08] compared with resting MCAv values. This review suggests that individuals after stroke may have attenuated cerebrovascular hemodynamics as measured by the MCAv during acute moderate-intensity exercise. Aerobic exercise training is beneficial for improving cardiovascular health and function after stroke; higher-quality research utilizing agreed-upon hemodynamic variables is needed to synthesize the effects of exercise training on poststroke cerebrovascular hemodynamics.
A Hyperelliptic Curve Cryptosystem Based Proxy Promised Signcryption Scheme
Authors: Khan Farhad Ullah , Algarni Fahad , Ullah Insaf , Karamti Hanen , Manzar Muhammad Anwaar , Alzahrani Ahmed Saeed , Aziz Muhammad Adnan , Khan Muhammad Asghar
Published: April 2022

Signcryption is the method of combining a digital signature with encryption in a single logical step to get the cryptographic primitives of a public key. However, in addition to signcryption, we sometimes require anonymity and delegation of rights. In this paper, we propose a scheme called proxy promised signcryption to address all of these objectives simultaneously. In this scheme, the actual sender or signer delegates authority to an agent known as signcrypter for signcryption of the actual ciphertext. The agent entity is facilitated to generate a promised signcrypted text. The signcrypted text is then communicated to the intended recipient. The proposed work aims to reduce computation and communication costs, which has been tested by comparing it to existing schemes. The results obtained from this comparison support the aims of our scheme. The proposed scheme’s security has also been evaluated using the Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. The results validate that our scheme resists well-known cyberattacks.
New Subclass of Analytic Function Related with Generalized Conic Domain Associated with q− Differential Operator
Authors: Khan Shahid , Hussain Saqib , Khan Ilyas , Al-johani Amnah s. , Andualem Mulugeta
Published: April 2022

The quantum (or q‐) calculus is widely applied in various operators which include the q‐difference (q‐derivative) operator, and this operator plays an important role in geometric function theory (GFT) as well as in the theory of hypergeometric series. In our present investigation, we introduce and study q‐differential operator associated with q‐Mittag–Leffler function which is an extension of the Salagean q‐differential operator. By using this newly defined operator, we define a new subclass of analytic function and studied certain subclass of analytic function in generalized conic domain Ωk,q,γ. For this class, we investigate structural formula, coefficient estimates, sufficient condition, Fekete–Szegö problem, and also some subordination results.
Application Scenarios and Promotion Strategies of High-Quality Development of Sports Service Industry Empowered by Digital Technology
Authors: Liu Qing , Liu Yufei , Liu Shangli
Published: April 2022

The new generation of digital technology brings new opportunities and new momentum to the development of sports service industry. Reviewing literature and case analysis were used in this study as the methods. Examine the important value and theoretical mechanism of high-quality development of sports service industry empowered by digital technology. Research analyzes the following practical application scenarios and typical cases systematically: The sports competition and performance industry enabled by 5G technology, the sports and health promotion industry empowered by blockchain technology, and the sports venue service industry empowered by Internet technology. And put forward the overall promotion strategy based on macro, medium, and micro levels. It is concluded that the rise and application of digital technology provide important technical support for the high-quality development of modern sports service industry. And it keeps great value to the optimization of sports service structure, the integration of formats, the matching of supply and demand, and the improvement of efficiency. Digital technology enables high-quality development of modern sports service industry. At the macro level, the top-level design led by the government is supposed to be strengthened. At the middle level, a multi-industry coordination mechanism is supposed to be established. At the micro level, we should perfect the professional talent cultivation system oriented by market demand.
Myxedema Coma Associated with Macroprolactinoma: Case Report and Review of the Literature
Authors: Omoniyi Elizabeth Jasola , Robbins Richard J.
Published: April 2022

Myxedema coma is a rare life-threatening presentation of severe hypothyroidism associated with a high mortality rate. Although most cases are due to primary thyroid failure, a minority have central hypothyroidism as the underlying cause. We report the case of a 69-year-old man who presented with obtundation, hypoglycemia, and hyponatremia. The patient’s initial thyroid-stimulating hormone (TSH) was within normal limits. Subsequent evaluation revealed critical anterior pituitary insufficiency due to a macroprolactinoma and a diagnosis of myxedema coma after appropriate workup The finding of a normal serum TSH should not eliminate the possibility of myxedema coma.