bluuebunny/crossref_metadata_2025 huggingface dataset:
Anatomical basis of fascial plane blocks
Authors: Chin Ki Jinn , Versyck Barbara , Elsharkawy Hesham , Rojas Gomez Maria Fernanda , Sala-Blanch Xavier , Reina Miguel A
Published: June 2021

Fascial plane blocks (FPBs) are regional anesthesia techniques in which the space (“plane”) between two discrete fascial layers is the target of needle insertion and injection. Analgesia is primarily achieved by local anesthetic spread to nerves traveling within this plane and adjacent tissues. This narrative review discusses key fundamental anatomical concepts relevant to FPBs, with a focus on blocks of the torso. Fascia, in this context, refers to any sheet of connective tissue that encloses or separates muscles and internal organs. The basic composition of fascia is a latticework of collagen fibers filled with a hydrated glycosaminoglycan matrix and infiltrated by adipocytes and fibroblasts; fluid can cross this by diffusion but not bulk flow. The plane between fascial layers is filled with a similar fat-glycosaminoglycan matric and provides gliding and cushioning between structures, as well as a pathway for nerves and vessels. The planes between the various muscle layers of the thorax, abdomen, and paraspinal area close to the thoracic paravertebral space and vertebral canal, are popular targets for ultrasound-guided local anesthetic injection. The pertinent musculofascial anatomy of these regions, together with the nerves involved in somatic and visceral innervation, are summarized. This knowledge will aid not only sonographic identification of landmarks and block performance, but also understanding of the potential pathways and barriers for spread of local anesthetic. It is also critical as the basis for further exploration and refinement of FPBs, with an emphasis on improving their clinical utility, efficacy, and safety.
Postembryonic developmental changes in ovarian histology and associated 17β-oestradiol and progesterone profiles in guinea hens (Numida meleagris)
Authors: Abdul-Rahman Ibn Iddriss , Jeffcoate Ian
Published: June 2021

There is a paucity of information on the reproductive biology of guinea hens. A study was conducted to document postembryonic developmental changes in the ovarian histology and associated progesterone and 17β-oestradiol profiles until 32 wk of age (WOA). Highly significant increases (P < 0.001) were noticed in oocyte and follicular diameters beyond 16 WOA. Other ovarian follicular morphometric traits showed inconsistent increases until 16 WOA. The first phase of yolk deposition occurred between hatching and 20 WOA, the second phase between 20 and 26 WOA, and the third and final phase between 27 and 28 WOA. Peripheral 17β-oestradiol concentrations increased from 20 WOA until it peaked at 28 WOA, whereas peripheral progesterone concentrations fluctuated considerably during sexual development. Both oestradiol and progesterone concentrations were negatively and moderately correlated (P < 0.01) with oocyte nuclei diameter, granulosa and theca layer heights. However, oestradiol concentrations were positively and strongly correlated (P < 0.001) with oocyte and follicular diameters, and moderately with progesterone concentrations. Three phases of yolk depositions were found in the guinea hen, with the final phase terminating at 28 WOA, at a much smaller oocyte diameter than in the domestic chicken. Oestradiol might play a role in yolk deposition in this species.
Reassessing species boundaries in the Syagrus glaucescens complex (Arecaceae) using leaf anatomy
Authors: Firmo D.H.T. , Santos S.A. , Perez M.E.M.P. , Soffiatti P. , Sant’Anna-Santos B.F.
Published: June 2021

The Syagrus glaucescens complex comprises three species: Syagrus glaucescens Glaz. ex Becc., Syagrus duartei Glassman, and Syagrus evansiana Noblick. Recently, a new population of S. evansiana that possesses a high degree of endemism was reported in the Serra do Cabral mountain. Here we intend to study the leaf anatomy of the S. glaucescens complex and confirm whether this newly found population (from now on called Syagrus aff. evansiana) belongs to S. evansiana or not. Specimens were collected to investigate their leaf anatomy, which showed distinct differences between S. aff. evansiana and S. evansiana. The midrib anatomy revealed novelties for the S. glauscecens complex, proving useful for species diagnosis. Features such as accessory vascular bundles around the vascular system of the midrib and the number of collateral bundles are diagnostic for species identification. In addition, morphological and anatomical analyses indicated a correlation with the species occurrence. We found greater similarity between S. glaucescens and S. duartei, while S. evansiana and S. aff. evansiana are more alike. Here, we propose a new identification key based only on the leaf anatomy. Despite their morphological similarities, S. aff. evansiana and S. evansiana presented differences in leaf anatomy, which — when associated with their geographical isolation — suggests a fourth taxon in the complex.
Statistical analysis of tipping pathways in agent-based models
Authors: Helfmann Luzie , Heitzig Jobst , Koltai Péter , Kurths Jürgen , Schütte Christof
Published: June 2021

Agent-based models are a natural choice for modeling complex social systems. In such models simple stochastic interaction rules for a large population of individuals on the microscopic scale can lead to emergent dynamics on the macroscopic scale, for instance a sudden shift of majority opinion or behavior. Here we are introducing a methodology for studying noise-induced tipping between relevant subsets of the agent state space representing characteristic configurations. Due to a large number of interacting individuals, agent-based models are high-dimensional, though usually a lower-dimensional structure of the emerging collective behaviour exists. We therefore apply Diffusion Maps, a non-linear dimension reduction technique, to reveal the intrinsic low-dimensional structure. We characterize the tipping behaviour by means of Transition Path Theory, which helps gaining a statistical understanding of the tipping paths such as their distribution, flux and rate. By systematically studying two agent-based models that exhibit a multitude of tipping pathways and cascading effects, we illustrate the practicability of our approach.
A multipurpose end-station for atomic, molecular and optical sciences and coherent diffractive imaging at ELI beamlines
Authors: Klimešová Eva , Kulyk Olena , Hoque Ziaul , Roos Andreas Hult , Khakurel Krishna P. , Rebarz Mateusz , Jurkovičová Lucie , Albrecht Martin , Finke Ondřej , Lera Roberto , Hort Ondřej , Mai Dong-Du , Nejdl Jaroslav , Sokol Martin , Fink Rasmus Burlund , Ben Ltaief Ltaief , Westphal Daniel , Wolf Adam , Laštovička Tomáš , Frassetto Fabio , Poletto Luca , Andreasson Jakob , Krikunova Maria
Published: June 2021

We report on the status of a users’ end-station, MAC: a Multipurpose station for Atomic, molecular and optical sciences and Coherent diffractive imaging, designed for studies of structure and dynamics of matter in the femtosecond time-domain. MAC is located in the E1 experimental hall on the high harmonic generation (HHG) beamline of the ELI Beamlines facility. The extreme ultraviolet beam from the HHG beamline can be used at the MAC end-station together with a synchronized pump beam (which will cover the NIR/Vis/UV or THz range) for time-resolved experiments on different samples. Sample delivery systems at the MAC end-station include a molecular beam, a source for pure or doped clusters, ultrathin cylindrical or flat liquid jets, and focused beams of substrate-free nanoparticles produced by an electrospray or a gas dynamic virtual nozzle combined with an aerodynamic lens stack. We further present the available detectors: electron/ion time-of-flight and velocity map imaging spectrometers and an X-ray camera, and discuss future upgrades: a magnetic bottle electron spectrometer, production of doped nanodroplets and the planned developments of beam capabilities at the MAC end-station.
Design of a Smart Maximum Power Point Tracker (MPPT) for RF Energy Harvester
Authors: Parvin Dilruba , Hassan Omiya , Oh Taeho , Islam Syed Kamrul
Published: June 2021

Continuous enhancement of the performance of energy harvesters in recent years has broadened their arenas of applications. On the other hand, ample availability of IoT devices has made radio frequency (RF) a viable source of energy harvesting. Integration of a maximum power point tracking (MPPT) controller in RF energy harvester is a necessity that ensures maximum available power transfer with variable input power conditions. In this paper, FPGA implementation of a machine learning (ML) model for maximum power point tracking in RF energy harvesters is presented. A supervised learning-based ML model-feedforward neural network (FNN) has been designed which is capable of tracking maximum power point with optimal accuracy. The model was designed using stochastic gradient descent (SGD) optimizer and mean square error (MSE) loss function. Simulation results of the VHDL translated model demonstrated a good agreement between the expected and the obtained values. The proposed ML based MPPT controller was implemented in Artix-7 Field Programmable Gate Array (FPGA).
Optimizing modularity with nonnegative matrix factorization
Authors: Chang Zhenhai , Zhang Zhong-Yuan , Cheng Huimin , Yan Chao , Yin Xianjun
Published: June 2021

Community structure detection is one of the fundamental problems in complex network analysis towards understanding the topology structure and function of the network. Modularity is a criterion to evaluate the quality of community structures, and optimization of this quality function over the possible divisions of a network is a sensitive detection method for community structure. However, the direct application of this method is computationally costly. Nonnegative matrix factorization (NMF) is a widely used method for community detection. In this paper, we show that modularity maximization can be approximately reformulated under the framework of NMF with Frobenius norm, especially when [Formula: see text] is large. A new algorithm for detecting community structure is proposed based on the above finding. The new method is compared with four state-of-the-art methods on both synthetic and real-world networks, showing its higher clustering quality over the existing methods.
Designing Twin Memristor-Based Multiscroll Systems by Varying the Flux Variable of Memristor
Authors: Yan Dengwei , Wang Lidan , Duan Shukai , Chen Jiahao
Published: June 2021

Memristor, as a nonlinear element in nanometer size, is feasible to generate chaotic signals. Especially, it can improve the randomness of the signals and the complexity of chaotic systems. A novel multiscroll hyperchaotic system based on the flux-controlled memristor is designed. Its twin system with a different topological structure is obtained by varying only the flux variable of the memristor, which is a considerable difference from other chaotic systems existing in the literature. Scroll numbers of the proposed system and its twin, especially, are sensitive to the system parameters. To further investigate the characteristics of the system and its twin, their behaviors with respect to the strengths of the memristor, simulation time and coexistence of multiscroll hyperchaotic attractors are analyzed. Moreover, complex dynamical behaviors of the system and its twin are analyzed by phase diagrams, Poincaré cross-sections, Lyapunov indexes, power spectra, 0-1 test diagrams, and time series. Finally, a novel image encryption scheme is proposed based on the system and its twin. The system and its twin have independent key spaces, and the proposed algorithm makes them have an intersection, which greatly improves the key spaces. In addition, the security and reliability of the image encryption algorithm are demonstrated by different security analysis methods, including correlation analysis, robustness analysis and information entropy test. The results of all experiments prove that the proposed image encryption scheme is superior to other existing ones.
Boundedness of a Class of Complex Lorenz Systems
Authors: Zhang Xu
Published: June 2021

The estimate of the ultimate bound for a dynamical system is an important problem, which is useful for chaos control and synchronization. In this paper, the estimated ultimate bound of a class of complex Lorenz systems is provided, which extends the parameter regions identified in the current literature on this problem. Based on these results, a kind of complex Lorenz-type systems is constructed, which might have many or infinitely many strange nonchaotic attractors, chaotic attractors, or an infinitely-many-scroll attractor.
Chaos for Differential Equations with Multivalued Impulses
Authors: Andres Jan
Published: June 2021

The deterministic chaos in the sense of a positive topological entropy is investigated for differential equations with multivalued impulses. Two definitions of topological entropy are examined for three classes of multivalued maps: [Formula: see text]-valued maps, [Formula: see text]-maps and admissible maps in the sense of Górniewicz. The principal tool for its lower estimates and, in particular, its positivity are the Ivanov-type inequalities in terms of the asymptotic Nielsen numbers. The obtained results are then applied to impulsive differential equations via the associated Poincaré translation operators along their trajectories. The main theorems for chaotic differential equations with multivalued impulses are formulated separately on compact subsets of Euclidean spaces and on tori. Several illustrative examples are supplied.
Collective dynamics in science and society
Authors: Bellomo N. , Brezzi F.
Published: June 2021

This editorial paper presents the articles published in a special issue devoted to active particle methods applied to modeling, qualitative analysis, and simulation of the collective dynamics of large systems of interacting living entities in science and society. The modeling approach refers to the mathematical tools of behavioral swarms theory and to the kinetic theory of active particles. Applications focus on classical problems of swarms theory, on crowd dynamics related to virus contagion problems, and to multiscale problems related to the derivation of models at a large scale from the mathematical description at the microscopic scale. A critical analysis of the overall contents of the issue is proposed, with the aim to provide a forward look to research perspectives.
On Pillai’s problem with X-coordinates of Pell equations and powers of 2 II
Authors: Erazo Harold S. , Gómez Carlos A. , Luca Florian
Published: June 2021

In this paper, we show that if [Formula: see text] is the [Formula: see text]th solution of the Pell equation [Formula: see text] for some non-square [Formula: see text], then given any integer [Formula: see text], the equation [Formula: see text] has at most [Formula: see text] integer solutions [Formula: see text] with [Formula: see text] and [Formula: see text], except for the only pair [Formula: see text]. Moreover, we show that this bound is optimal. Additionally, we propose a conjecture about the number of solutions of Pillai’s problem in linear recurrent sequences.
The Network Structure Formation of Cu-CNTs Composites During Multi-Directional Forging Process and its Mechanical Properties
Authors: Liu Endian , Li Zaijiu , Li Fei , Wang Bin
Published: June 2021

Cu–[Formula: see text] CNTs composites ([Formula: see text], 1, 2, 3 vol.%) were successfully prepared using a combination of pre-treatment, powder metallurgy and multi-directional forging processes, which provides a solution for the industrial manufacture of the composites with network CNTs structures. During the multi-directional forging process, the CNTs in the composites were distributed in a network under the synergy of metal flow and copper particle squeeze. Compared with other structure modes, the network CNTs can effectively carry and transfer loads resulting in the promotion of mechanical properties (such as, the tensile strength approximately 1.5 times higher than those of composites with the same volume fraction without network structure). The composite with 2 vol.% CNTs had the highest elongation in this experiment (41%), which is about 5 times higher than the composites with other CNTs distribution patterns. At a low CNTs content level (1[Formula: see text]vol.%), a complete load transfer network cannot be formed, resulting in a relatively insufficient mechanical properties of the composites. As the content level is exceeded (3vol.%), it caused significant agglomeration of the CNTs, which lead to fracture in the agglomerated CNTs and elongation degradation of the composites.
Restricted growth and grain boundary reinforcement of MAPbBr3 film by graphene quantum dots with enhanced luminescence and stability
Authors: Zheng Ronghong , Huang Dong , Luo Chengzhao , Sun Xiaojuan , Shen Dongyang , Li Qinyi , Chen Song , Chen Yu
Published: June 2021

Organic-inorganic hybrid perovskite (OIHP) attracted much attention in the optoelectronic applications owing to its high yield, adjustable color and good mono-chromaticity. However, the defective sites at MAPbBr3 film boundaries greatly jeopardize their luminescent property. In this study, graphene quantum dots (GQDs) are incorporated into the MAPbBr3 film and pushed to the grain boundaries during perovskite crystallization via a modified freeze casting approach. The rich carboxyl groups of GQDs interact with the dangling lead atoms at grain boundaries, thus reducing non-radiative recombination centers within the film. On the other hand, GQDs create additional nucleation sites, which helps to form a uniformly covered luminescent film with small grains. As a result, the incorporation of GQDs increases the photoluminescence (PL) intensity of the emission film by about six times and well preserves the crystal phase for 36-day storage in ambient air.
Computational Nanosatellite Constellations
Authors: Lucia Brandon , Denby Brad , Manchester Zachary , Desai Harsh , Ruppel Emily , Colin Alexei
Published: June 2021

As rocket launch cadences increase, access to space rises dramatically - setting the stage for the next space industry surge. New, smaller, and less expensive satellites - now "nanosatellites" - can be deployed en masse to form constellations of hundreds, thousands, or even tens of thousands of devices [27, 40, 41, 16, 17, 18, 43]. A constellation of nanosatellites equipped with sensors (e.g., visual or hyperspectral cameras, particle detectors, or magnetometers) and radios provides a first-time opportunity for orbital swarm sensing to synthesize data from the unique vantage point of low-Earth orbit (LEO).
Zero-Wire
Authors: Oostvogels Jonathan , Yang Fan , Michiels Sam , Joosen Wouter , Hughes Danny
Published: June 2021

Latency-sensitive applications for the Internet of Things (IoT) often require performance guarantees that contemporary wireless networks fail to offer. Application scenarios involving real-time control of industrial machinery, robotics, or delay-sensitive actuation therefore typically still rely on cables: today's wireless networks cannot deliver messages in a sufficiently small and predictable amount of time. Drop-in wireless replacements for these cabled systems would nevertheless provide great benefit by eliminating the high cost and complexity associated with running cables in harsh industrial environments [1]. The symbolsynchronous bus, introduced in this article and embodied in a platform called Zero-Wire, is a novel wireless networking paradigm that addresses this gap. Using concurrent optical transmissions, it strives to bring low-latency deterministic networking to the wireless IoT.
Chiller
Authors: Zamanian Erfan , Shun Julian , Binnig Carsten , Kraska Tim
Published: June 2021

Distributed transactions on high-overhead TCP/IP-based networks were conventionally considered to be prohibitively expensive. In fact, the primary goal of existing partitioning schemes is to minimize the number of cross-partition transactions. However, with the new generation of fast RDMAenabled networks, this assumption is no longer valid.

In this paper, we first make the case that the new bottleneck which hinders truly scalable transaction processing in modern RDMA-enabled databases is data contention, and that optimizing for data contention leads to different partitioning layouts than optimizing for the number of distributed transactions. We then present Chiller, a new approach to data partitioning and transaction execution, which aims to minimize data contention for both local and distributed transactions.
DIAMetrics
Authors: Deep Shaleen , Gruenheid Anja , Nagaraj Kruthi , Naito Hiro , Naughton Jeff , Viglas Stratis
Published: June 2021

This paper introduces DIAMetrics: a novel framework for end-to-end benchmarking and performance monitoring of query engines. DIAMetrics consists of a number of components supporting tasks such as automated workload summarization, data anonymization, benchmark execution, monitoring, regression identification, and alerting. The architecture of DIAMetrics is highly modular and supports multiple systems by abstracting their implementation details and relying on common canonical formats and pluggable software drivers. The end result is a powerful unified framework that is capable of supporting every aspect of benchmarking production systems and workloads. DIAMetrics has been developed in Google and is being used to benchmark various internal query engines. In this paper, we give an overview of DIAMetrics and discuss its design and implementation. Furthermore, we provide details about its deployment and example use cases. Given the variety of supported systems and use cases within Google, we argue that its core concepts can be used more widely to enable comparative end-to-end benchmarking in other industrial environments.
Technical Perspective of Efficient Directed Densest Subgraph Discovery
Authors: Tao Yufei
Published: June 2021

The problem is useful in graph mining because dense subgraphs often represent patterns deserving special attention. They could indicate, for example, an authoritative community in a social network, a building brick of more complex biology structures, or even a type of malicious behavior such as spamming. See [1, 3] and the references therein for an extensive discussion on the applications of DDS.
Fair near neighbor search via sampling
Authors: Aumuller Martin , Har-Peled Sariel , Mahabadi Sepideh , Pagh Rasmus , Silvestri Francesco
Published: June 2021

Similarity search is a fundamental algorithmic primitive, widely used in many computer science disciplines. Given a set of points S and a radius parameter r > 0, the rnear neighbor (r-NN) problem asks for a data structure that, given any query point q, returns a point p within distance at most r from q. In this paper, we study the r-NN problem in the light of individual fairness and providing equal opportunities: all points that are within distance r from the query should have the same probability to be returned. In the low-dimensional case, this problem was first studied by Hu, Qiao, and Tao (PODS 2014). Locality sensitive hashing (LSH), the theoretically strongest approach to similarity search in high dimensions, does not provide such a fairness guarantee.
From Sketching to Natural Language
Authors: Siddiqui Tarique , Luh Paul , Wang Zesheng , Karahalios Karrie , Parameswaran Aditya G.
Published: June 2021

Data visualization is the primary means by which data analysts explore patterns, trends, and insights in their data. Unfortunately, existing visual analytics tools offer limited expressiveness and scalability when it comes to searching for visualizations over large datasets, making visual data exploration labor-intensive and timeconsuming. We first discuss our prior work on Zenvisage that helps accelerate exploratory data analysis via an interactive interface and an expressive visualization query language, but offers limited flexibility when the pattern of interest is under-specified and approximate. Motivated from our findings from Zenvisage, we develop ShapeSearch, an efficient and flexible pattern-searching tool that enables the search for desired patterns via multiple mechanisms: sketch, natural-language, and visual regular expressions. ShapeSearch leverages a novel shape querying algebra that can express a large class of shape queries and supports query-aware and perceptually-aware optimizations to execute shape queries within interactive response times. To further improve the usability and performance of both Zenvisage and ShapeSearch, we discuss a number of open research problems.
Query Games in Databases
Authors: Livshits Ester , Bertossi Leopoldo , Kimelfeld Benny , Sebag Moshe
Published: June 2021

Database tuples can be seen as players in the game of jointly realizing the answer to a query. Some tuples may contribute more than others to the outcome, which can be a binary value in the case of a Boolean query, a number for a numerical aggregate query, and so on. To quantify the contributions of tuples, we use the Shapley value that was introduced in cooperative game theory and has found applications in a plethora of domains. Specifically, the Shapley value of an individual tuple quantifies its contribution to the query. We investigate the applicability of the Shapley value in this setting, as well as the computational aspects of its calculation in terms of complexity, algorithms, and approximation.
Switching from face-to-face to an online teaching strategy: how anatomy and physiology teaching transformed post-COVID-19 for a university preprofessional program
Authors: Memon Ismail , Feroz Zeeshan , Alkushi Abdulmohsen , Qamar Nabeel , Ismail Farwa
Published: June 2021

The College of Science and Health Professions offers a university preprofessional program. Like most medical schools in Saudi Arabia, the teaching delivery strategy in the university preprofessional program is on campus and face-to-face. During the month of March 2020, teaching activities of the spring semester were proceeding as normal; however, the sudden emergence of COVID-19 disturbed routine activities and compelled authorities to switch all teaching activities from face-to-face to online. Training sessions and workshops for all stakeholders on online delivery methods were arranged. Blackboard and other online facilities were utilized. All teaching materials, including newly made video clips for anatomy and physiology practicals, were uploaded on Blackboard and discussed online with students. Students’ anxiety related to the exam was reassured by giving them the option of open book quizzes during summative continuous assessment. All scheduled teaching sessions, lectures, and practicals were conducted proficiently. Revision sessions and assessment quizzes were conducted with students’ satisfaction. At the end of the semester, a final exam was conducted online as an open book exam. Students with technical issues while attempting the exam were given an opportunity to make up for it. After a successful final exam, the cumulative block grades showed students secured higher grades in the open book exam. Following that, the King Saud bin Abdulaziz University for Health Sciences has managed to conduct on-campus close book exams that abide by self-distancing and standard operating procedure policies.
Prenatal ethanol exposure impairs the conduction delay at the atrioventricular junction in the looping heart
Authors: Ling Shan , Jenkins Michael W. , Watanabe Michiko , Ford Stephanie M. , Rollins Andrew M.
Published: June 2021

To the best of our knowledge, this is the first study investigating the impact of ethanol exposure on the early cardiac conduction system. Our results showed that ethanol-exposed embryos exhibited abnormally fast atrioventricular conduction. In addition, our findings, in CV measurements and endocardial cushion thickness, reveal regional differences in the AVJ myocardium even at this early stage in heart development, suggesting that the differentiation and maturation at this site are complex and warrant further studies.
Ethanol: striking the cardiovascular system by harming the gut microbiota
Authors: Silva Carla B. P. , Elias-Oliveira Jefferson , McCarthy Cameron G. , Wenceslau Camilla F. , Carlos Daniela , Tostes Rita C.
Published: June 2021

Ethanol consumption represents a significant public health problem, and excessive ethanol intake is a risk factor for cardiovascular disease (CVD), one of the leading causes of death and disability worldwide. The mechanisms underlying the effects of ethanol on the cardiovascular system are complex and not fully comprehended. The gut microbiota and their metabolites are indispensable symbionts essential for health and homeostasis and therefore, have emerged as potential contributors to ethanol-induced cardiovascular system dysfunction. By mechanisms that are not completely understood, the gut microbiota modulates the immune system and activates several signaling pathways that stimulate inflammatory responses, which in turn, contribute to the development and progression of CVD. This review summarizes preclinical and clinical evidence on the effects of ethanol in the gut microbiota and discusses the mechanisms by which ethanol-induced gut dysbiosis leads to the activation of the immune system and cardiovascular dysfunction. The cross talk between ethanol consumption and the gut microbiota and its implications are detailed. In summary, an imbalance in the symbiotic relationship between the host and the commensal microbiota in a holobiont, as seen with ethanol consumption, may contribute to CVD. Therefore, manipulating the gut microbiota, by using antibiotics, probiotics, prebiotics, and fecal microbiota transplantation might prove a valuable opportunity to prevent/mitigate the deleterious effects of ethanol and improve cardiovascular health and risk prevention.
Pore Structure Characteristics and Evolution Law of Different-Rank Coal Samples
Authors: Wen Zhihui , Wang Qi , Yang Yunpeng , Si Leilei
Published: June 2021

In this study, the full-size pore structure characteristics of six different-rank coal samples were investigated and analyzed from three perspectives, namely, pore shape, pore volume, and pore specific surface area, by performing a high-pressure mercury injection experiment and a low-temperature nitrogen adsorption experiment. Next, the full-size pore volumes and pore specific surface areas of the six coal samples were accurately characterized through a combination of the two experiments. Furthermore, the relationships between volatile matter content and pore volume and between volatile matter content and pore specific surface area were fitted and analyzed. Finally, the influences of metamorphic degree on pore structure were discussed. The following conclusions were obtained. The pore shapes of different-rank coal samples differ significantly. With the increase of metamorphic degree, the full-size pore volume and pore specific surface area both decrease first and then increase. Among the pores with various sizes, micropores are the largest contributor to the full-size pore volume and pore specific surface area. The fitting curves between volatile matter content and pore volume and between volatile matter content and pore specific surface area can well reflect the influence and control of metamorphic degree on pore volume and pore specific surface area, respectively. With the increase of volatile matter content, the pore volume and the pore specific surface area both vary in a trend resembling a reverse parabola.
The Influence of Investor Emotion on the Stock Market: Evidence from an Infectious Disease Model
Authors: Chen Yutao , Zhu Shuzhen , He Haoyuan
Published: June 2021

In March 2020, four consecutive circuit breakers in the US stock market underscored the impact of investor sentiment on the stock market. With the development of technology, public opinion and other information now spread easily through social media and other channels, indirectly affecting investor sentiment. This makes it important to understand the underlying dynamics of such situations to help manage the market impact of such events going forward. To that end, we analyze investor sentiment, investor structures, and the capital market fuse mechanism using infectious disease dynamics. We use an extension of the SIR (susceptible, infectious, and recovered) model, called the dynamic SIRS model (where individuals return to a susceptible state), to simulate the impact of investor sentiment on the stock market. Accordingly, we study the circuit breakers in the US stock market and the simulation results of the model to analyze the fuse mechanism process in China that triggers a pause in the market based on volatile trading. The results of our study show that when the influence rate of investor mutual communication increases or when the emotional calm rate decreases, investor emotions will start to diffuse, leading to an increase in the probability of either a serious stampede or zealous overbuying in the stock market. At the same time, the trading frequency of investors and the ratio of investors in both buying and selling directions will have a certain formal impact on the direction of the stock market, with the final impact determined by the ratio of normal investors to emotional investors. When emotional investors dominate the market, their emotions are diffused throughout. Our study provides the reference for relevant agencies to monitor and improve the stock market fuse mechanism in the future.
Degenerate Four-Wave Mixing in Phycoerythrin Dye-Doped Nanoparticles
Authors: Tsuchiya Tomoki , Egami Chikara
Published: June 2021

We have generated a phase-conjugate (PC) wave from nanoparticles with a new microscopic system proposed. The microscope includes a confocal system with a degenerate four-wave mixing (DFWM) system, which plays a major role in generating the phase-conjugate wave to compensate phase distortion in the optical path toward targets. The proposed optical system detects feeble PC wave and imagines 3D particles while improving the inplane contrast resolution of the microscopic image.
A 14-Year-Old Male Patient with Kawasaki Disease Presented with Stroke after COVID-19
Authors: Shala Nexhmedin , Jashari Fisnik , Boshnjaku Dren , Shala Argjend , Ibrahimi Pranvera , Kukaj Vera , Dreshaj Shemsedin
Published: June 2021

According to several studies, children represent only about 2% of the patients affected by the current SARS-CoV-2, and most often, they are asymptomatic. However, there is a concern about a vascular inflammatory disease which is similar to Kawasaki disease observed in children and adolescents weeks after infection. We report a case of Kawasaki disease presented with ischemic stroke in a 14-year-old male patient following SARS-Cov-2 infection.
Application of the Base Transceiver Station with Smart Antennas in the Power Distribution Sector
Authors: Kleinau B. A. , de Melo D. L. , de Melo M. T. , Barbosa D. C. P. , Oliveira A. J. B. , Silva C. P. N. , de Oliveira J. M. A. M.
Published: June 2021

The use of distribution automation systems has grown significantly in electricity companies in recent years. The main reason for this is the need to have a smarter network, in order to reduce the time of power interruption. For such applications, communication using radio frequency is preferred because this solution is more reliable than 3G/4G and cheaper than fiber optics. In this context, it is of utmost importance to have a more efficient base transceiver station (BTS) that can cover the communication of a larger area. In this paper, the mathematical concepts of an intelligent antenna array, as well as the logical operation of an intelligent radiation system controller, are presented. Such system receives as inputs the geographic coordinates of network elements and automatically feeds an intelligent Yagi–Uda antenna array with the appropriate parameters, in order to optimize the radiation pattern into the desired directions. The presented model uses a stochastic optimization method to automatically achieve a set of optimal electrical parameters to excite the array and efficiently direct its beams in a fully controlled way. Thus, the results obtained indicate that the proposed intelligent scheme allows the energy optimization of the antenna system, reducing in 61% the number of BTS needed to cover the same area, when compared to traditional collinear antenna systems.
Effect of Compressive Behaviours of Tail Salt Filling Materials on Roof Deformation in Potash Mine
Authors: Wang Jiaqi , Zhang Qiang , Li Meng , Liu Hengfeng , Zhu Cunli
Published: June 2021

To resolve the problem of top mine instability and the consequent ecological damage caused by different grades of ore deposits in the layered mining process, layered filling‐pillar‐mining‐displacement method (LFPMD) is proposed using a potash mine as an example. Based on the operation principles of the tail salt filling system, the mechanical behaviours of the tail salt under initial tamping and overburden loading were obtained through compaction tests in the laboratory. In addition, the mining‐filling mass ratio of tail salt was derived. Based on the mining geological conditions of a potash mine in Laos and the compaction characteristics of tail salt, a mechanical model of top control by tail salt and a numerical model of top control by the pillars were established to discuss the stability of the upper‐layer top mine and the lower‐layer top mine. It was found that when the elastic foundation coefficient of the tail salt is greater than 550 MN·m−3, and the width of the retained pillars is 10 m, stability of the upper layer and the lower layer can be guaranteed. The results revealed that the LFPMD method can ensure stability of the overburden in the stope and reduce environmental damage while treating tail salt underground.
Long‐Term Predictions of COVID‐19 in Some Countries by the SIRD Model
Authors: Pei Lijun , Zhang Mengyu
Published: June 2021

As COVID‐19 in some countries has increasingly become more severe, there have been significant efforts to develop models that forecast its evolution there. These models can help to control and prevent the outbreak of these infections. In this paper, we make long‐term predictions based on the number of current confirmed cases, accumulative recovered cases, and dead cases of COVID‐19 in some countries by the modeling approach. We use the SIRD (S: susceptible, I: infected, R: recovered, D: dead) epidemic model which is a nonautonomous dynamic system with incubation time delay to study the evolution of COVID‐19 in some countries. From the analysis of the recent data, we find that the cure and death rates may not be constant and, in some countries, they are piecewise functions. They can be estimated from the delayed SIRD model by the finite difference method. According to the recent data and its subsequent cure and death rates, we can accurately estimate the parameters of the model and then predict the evolution of COVID‐19 there. Through the predicted results, we can obtain the turning points, the plateau period, and the maximum number of COVID‐19 cases. The predicted results suggest that the epidemic situation in some countries is very serious. It is advisable for the governments of these countries to take more stringent and scientific containment measures. Finally, we studied the impact of the infection rate β on COVID‐19. We find that when the infection rate β decreases, the cumulative number of confirmed cases and the maximum number of currently infected cases will greatly decrease. The results further affirm that the containment techniques taken by these countries to curb the spread of COVID‐19 should be strengthened further.
Takagi–Sugeno Fuzzy Controller and Sliding Mode Controller for a Nonholonomic Mobile Robot
Authors: Abid Hafedh
Published: June 2021

This paper focuses on the nonholonomic wheeled mobile robot. We have presented a scheme to develop controllers. Two controllers have been developed. The first concerns the kinematic behavior, while the second relates to the dynamic behavior of the mobile robot. For the kinematic controller, we have used a Takagi–Sugeno fuzzy system to overcome the nonlinearities present in model, whereas for the second controller, we have used the sliding mode approach. The sliding surface has the identical structure as the proportional integral controller. The stability of the system has been proved based on the Lyapunov approach. The simulation results show the efficiency of the proposed control laws.
Treatment of Growth Hormone Deficiency via Daily Intravascular Injections in a Child with Bleeding Disorder
Authors: Tas Emir , Uzun Serife E. , Tas Vildan , Mejia-Otero Juan D.
Published: June 2021

Objectives. The standard of treatment for pediatric growth hormone deficiency (GHD) is daily subcutaneous recombinant human growth hormone (rhGH) injections. The efficacy of rhGH treatment given as daily intravenous (IV) boluses is not known. Case Presentation. A female with protein C deficiency, a severe bleeding disorder characterized by thrombosis formation, was diagnosed with GHD at age four years. She has been receiving daily protein C infusion through a permanent port since the newborn period. GHD was treated with daily IV rhGH boluses given through the port following protein C infusion. She has reached a growth rate of 12 cm/year and had no side effects. Surprisingly, serum insulin-like growth factor-1 (IGF1) levels did not rise despite an excellent clinical response. Conclusions. IV administration may be an alternative route for GHD treatment in eligible patients with permanent vascular access. A rise in serum IGF1 levels may not be needed to achieve the growth-promoting effect of rhGH.
A Boundary Construction Algorithm for a Complex Planar Point Set
Authors: Liao Zhenxiu , Shi Guodong
Published: June 2021

It is difficult to extract the boundary of complex planar points with nonuniform distribution of point density, concave envelopes, and holes. To solve this problem, an algorithm is proposed in this paper. Based on Delaunay triangulation, the maximum boundary angle threshold is introduced as the parameter in the extraction of the rough boundary. Then, the point looseness threshold is introduced, and the fine boundary extraction is conducted for the local areas such as concave envelopes and holes. Finally, the complete boundary result of the whole point set is obtained. The effectiveness of the proposed algorithm is verified by experiments on the simulated point set and practical measured point set. The experimental results indicate that it has wider applicability and more effectiveness in engineering applications than the state‐of‐the‐art boundary construction algorithms based on Delaunay triangulation.
Topic Detection and Tracking Techniques on Twitter: A Systematic Review
Authors: Asgari-Chenaghlu Meysam , Feizi-Derakhshi Mohammad-Reza , Farzinvash Leili , Balafar Mohammad-Ali , Motamed Cina
Published: June 2021

Social networks are real‐time platforms formed by users involving conversations and interactions. This phenomenon of the new information era results in a very huge amount of data in different forms and modalities such as text, images, videos, and voice. The data with such characteristics are also known as big data with 5‐V properties and in some cases are also referred to as social big data. To find useful information from such valuable data, many researchers tried to address different aspects of it for different modalities. In the case of text, NLP researchers conducted many research studies and scientific works to extract valuable information such as topics. Many enlightening works on different platforms of social media, like Twitter, tried to address the problem of finding important topics from different aspects and utilized it to propose solutions for diverse use cases. The importance of Twitter in this scope lies in its content and the behavior of its users. For example, it is also known as first‐hand news reporting social media which has been a news reporting and informing platform even for political influencers or catastrophic news reporting. In this review article, we cover more than 50 research articles in the scope of topic detection from Twitter. We also address deep learning‐based methods.
The Staged Financing Selection Mechanism for Government to Maximize the Green Benefits of Start-Ups
Authors: Yang Wenke , Ma Qianting , Tian Meile , Wang Lei , He Jianmin
Published: June 2021

In this study, we investigate the most common forms of government grant in green start-ups, which are appropriation, interest-free bank loans, and tax subsidies. These mechanisms are used to mitigate the problem of higher research costs and sunk costs of start-ups on green innovation and help venture investors better monitor the business plan, asset use, and agency cost and regularly collect information of start-ups to retain the right to terminate financing projects and improve the efficiency of them. The aim of this work is to develop a theoretical model of the agency among the government, the venture capitalists who only pursue monetary income, the strategy investors who pursue strategic objectives and monetary income, and the entrepreneur who takes into account both the influence of different forms of government grant on entrepreneur financing at a different stage and the improved monitoring process of venture investors owe to the staged capital infusion of government. The model shows that the optimal staged financing decision is given when the first target of the government is to achieve social welfare optimization and the secondary goal of maximizing green benefits. Moreover, the model explains the optimal staged financing decision of venture investors and equity stake share in different rounds. Ultimately, we find the optimal staged financing portfolios for green start-ups to acquire venture investment, reduce the staged financing uncertainty, and help the government realize a national green innovation strategy.
A Novel QoS‐Oriented Intrusion Detection Mechanism for IoT Applications
Authors: Noorwali Abdulfattah , Alvi Ahmad Naseem , Khan Mohammad Zubair , Javed Muhammad Awais , Boulila Wadii , Pattanaik Priyadarshini A.
Published: June 2021

Wireless sensor network (WSN) is an integral part of Internet of Things (IoT). The sensor nodes in WSN generate large sensing data which is disseminated to intelligent servers using multiple wireless networks. This large data is prone to attacks from malicious nodes which become part of the network, and it is difficult to find these adversaries. The work in this paper presents a mechanism to detect adversaries for the IEEE 802.15.4 standard which is a central medium access protocol used in WSN‐based IoT applications. The collisions and exhaustion attacks are detected based on a soft decision‐based algorithm. In case the QoS of the network is compromised due to large data traffic, the proposed protocol adaptively varies the duty cycle of the IEEE 802.15.4. Simulation results show that the proposed intrusion detection and adaptive duty cycle algorithm improves the energy efficiency of a WSN with a reduced network delay.