bluuebunny/crossref_metadata_2025 huggingface dataset:
Double‐loop cerclage resists greater loads for more cycles than twist and single‐loop cerclage
Authors: Butare‐Smith Lauren , Roe Simon C.
Published: December 2021

Objective

To compare the mechanical performance of cerclage secured with twist, single‐loop, and double‐loop knots subjected to cyclic loading.

Study design

In vitro biomechanical study.

Sample population

Twist, single‐loop and double‐loop cerclage configurations of 1.0 mm wire.

Methods

The peak load resisted by each cerclage type was determined (n = 6). Cerclage were loaded cyclically to 80%, 60%, 40%, or 20% of its peak load (n = 8 per load level). The number of cycles until each cerclage loosened (residual tension <10 N) was recorded.

Results

All wires that failed did so by loosening. Twist cerclage cycled to 390 N and 290 N loosened within the first 10 cycles, and, when cycled to 100 N, they loosened by 250 cycles. All twist knots loosened by untwisting. Single‐loop cerclage cycled to 320 N loosened within 10 cycles. At 240 N, 5 single‐loop cerclage resisted 250 cycles before loosening. At 160 N, 2 of the 8 single‐loop cerclage did not loosen by 100 000 cycles. When cycled to 640 N, one of the double‐loop cerclage did not loosen following 500 000 cycles. When cycled to 480 N, 3 of the 8 wires did not loosen.

Conclusion

Double‐loop cerclage will be tighter and are better able to resist cycling than twist or single‐loop cerclage.

Clinical significance

Use of double‐loop cerclage to stabilize bone fragments or prevent fissure propagation can be expected to provide greater resistance to loosening than twist or single‐loop cerclage, both initially and with repeated loading.
HUMAN EVOLUTION AND THE CHRISTIAN CALL TO LOVE
Authors: Poister David
Published: December 2021

This article will examine the Christian call to love as an invitation to participate in an ongoing evolutionary transformation of humanity. This interpretation recognizes that the ability to love others is both a product and driver of evolutionary change. Through natural selection, humans evolved the neurological capacity to benefit from the cooperation generated by empathy. Additionally, these evolutionary origins have created constraints on altruism such as the tendency to favor members of one's own group. Christianity and other religions are well‐suited to encourage the specific behaviors and cultural conditions that allow humans to overcome these constraints. Religions can provide consistent reinforcement of the symbolic and behavioral information that establishes empathy as a desirable trait and steers human evolution in a prosocial direction. Also, religious concepts such as the kingdom of God and Teilhard's Omega Point can inspire cooperation by associating even small acts of kindness with the evolutionary transformation to improve the human condition.
A graph-based narrowband matched-field source localization method
Authors: Xiao Peng , Yang Jianmin
Published: December 2021

Matched field processing (MFP) has been regarded as one of the most successful acoustical methods for positioning underwater sources. In this paper, the narrowband MFP method is combined with a recently developed framework—the graph signal processing (GSP) method. Following the paradigm of GSP, a spatial adjacency matrix is constructed for the arbitrary distributed sensors based on the Green's function, then the source is located by utilizing the graph Fourier transform. The simulation results illustrate that the graph-based MFP outperforms the conventional MFP processors for its better accuracy and fewer requirements for sensor numbers.
Impact of Sled Loads on Performance and Kinematics of Elite Sprinters and Rugby Players
Authors: Pareja-Blanco Fernando , Pereira Lucas A. , Reis Valter P. , Fernandes Victor , Arruda Ademir F.S. , Guerriero Aristide , Alcaraz Pedro E. , Freitas Tomás T. , Loturco Irineu
Published: December 2021

Purpose: To examine the changes in resisted sprint performance and kinematics provoked by different sled loads in elite sprinters and rugby players. Methods: Eight elite male sprinters and 10 rugby union players performed 20-m sprints under 3 loading conditions (0%, 20%, and 60% body mass [BM]). Sprint time was measured in 0 to 5, 5 to 10, and 10 to 20 m, while stride length and hip, knee, and ankle angles were measured using an 8-sensor motion analysis system at the same distances. Results: Sprinters were significantly faster than rugby players in unresisted and resisted sprints using 20% BM (effect size, “ES” [90% confidence limit, CL] range: 0.65 [0.03 to 1.27]; 3.95 [3.10 to 4.81]), but these differences were not significant at 60% BM. Compared to rugby players, sprinters showed lower velocity decrement in resisted sprints using 20% BM (ES [90% CL] range: 0.75 [0.06 to 1.44]; 2.43 [0.83 to 4.02], but higher velocity decrement using 60% BM (ES [90% CL] range: 1.13 [0.43 to 1.82]; 1.46 [0.81 to 2.11]). No significant differences were detected in stride length between sprinters and rugby players for any sprint condition (ES [90% CL] range: 0.02 [−0.72 to 0.76]; 0.84 [0.13 to 1.54]). Rugby players showed higher hip flexion in resisted sprints (ES [90% CL] range: 0.30 [−0.54 to 1.14]; 1.17 [0.20 to 2.15]) and lower plantar flexion in both unresisted and resisted sprints (ES [90% CL] range: 0.78 [0.18 to 1.38]; 1.69 [1.00 to 2.38] than sprinters. Conclusions: The alterations induced by resisted sprints in sprint velocity and running technique differed between sprinters and rugby players. Some caution should be taken with general sled loads prescriptions, especially when relative loads are based on distinct percentages of BM, as training responses vary among sports and individuals.
Defining Training and Performance Caliber: A Participant Classification Framework
Authors: McKay Alannah K.A. , Stellingwerff Trent , Smith Ella S. , Martin David T. , Mujika Iñigo , Goosey-Tolfrey Vicky L. , Sheppard Jeremy , Burke Louise M.
Published: December 2021

Throughout the sport-science and sports-medicine literature, the term “elite” subjects might be one of the most overused and ill-defined terms. Currently, there is no common perspective or terminology to characterize the caliber and training status of an individual or cohort. This paper presents a 6-tiered Participant Classification Framework whereby all individuals across a spectrum of exercise backgrounds and athletic abilities can be classified. The Participant Classification Framework uses training volume and performance metrics to classify a participant to one of the following: Tier 0: Sedentary; Tier 1: Recreationally Active; Tier 2: Trained/Developmental; Tier 3: Highly Trained/National Level; Tier 4: Elite/International Level; or Tier 5: World Class. We suggest the Participant Classification Framework can be used to classify participants both prospectively (as part of study participant recruitment) and retrospectively (during systematic reviews and/or meta-analyses). Discussion around how the Participant Classification Framework can be tailored toward different sports, athletes, and/or events has occurred, and sport-specific examples provided. Additional nuances such as depth of sport participation, nationality differences, and gender parity within a sport are all discussed. Finally, chronological age with reference to the junior and masters athlete, as well as the Paralympic athlete, and their inclusion within the Participant Classification Framework has also been considered. It is our intention that this framework be widely implemented to systematically classify participants in research featuring exercise, sport, performance, health, and/or fitness outcomes going forward, providing the much-needed uniformity to classification practices.
Dense melt residues drive mid-ocean-ridge “hotspots”
Authors: Phethean* Jordan J.J. , Papadopoulou Martha , Peace Alexander L.
Published: December 2021

The geodynamic origin of melting anomalies found at the surface, often referred to as “hotspots,” is classically attributed to a mantle plume process. The distribution of hotspots along mid-ocean-ridge spreading systems around the globe, however, questions the universal validity of this concept. Here, the preferential association of hotspots with slow- to intermediate-spreading centers and not fast-spreading centers, an observation contrary to the expected effect of ridge suction forces on upwelling mantle plumes, is explained by a new mechanism for producing melting anomalies at shallow (<2.3 GPa) depths. By combining the effects of both chemical and thermal density changes during partial melting of the mantle (using appropriate latent heat and depth-dependent thermal expansivity parameters), we find that mantle residues experience an overall instantaneous increase in density when melting occurs at <2.3 GPa. This controversial finding is due to thermal contraction of material during melting, which outweighs the chemical buoyancy due to melting at shallow pressures (where thermal expansivities are highest). These dense mantle residues are likely to locally sink beneath spreading centers if ridge suction forces are modest, thus driving an increase in the flow of fertile mantle through the melting window and increasing magmatic production. This leads us to question our understanding of sub–spreading center dynamics, where we now suggest a portion of locally inverted mantle flow results in hotspots. Such inverted flow presents an alternative mechanism to upwelling hot mantle plumes for the generation of excess melt at near-ridge hotspots, i.e., dense downwelling of mantle residue locally increasing the flow of fertile mantle through the melting window. Near-ridge hotspots, therefore, may not require the elevated temperatures commonly invoked to account for excess melting. The proposed mechanism also satisfies counterintuitive observations of ridge-bound hotspots at slow- to intermediate-spreading centers, yet not at fast-spreading centers, where large dynamic ridge suction forces likely overwhelm density-driven downwelling.

The lack of observations of such downwelling in numerical modeling studies to date reflects the generally high chemical depletion buoyancy and/or low thermal expansivity parameter values employed in simulations, which we find to be unrepresentative for melting at <2.3 GPa. We therefore invite future studies to review the values used for parameters affecting density changes during melting (e.g., depletion buoyancy, latent heat of melting, specific heat capacity, thermal expansivity), which quite literally have the potential to turn our understanding of mantle dynamics upside down.
On the Schwarzschild-Anti-de Sitter black hole with an f(R) global monopole
Authors: Vieira H. S.
Published: December 2021

In this work, we follow the recently revisited f(R) theory of gravity for studying the interaction between quantum scalar particles and the gravitational field of a generalized black hole with an f(R) global monopole. This background has a term playing the role of an effective cosmological constant, which permits us to call it as Schwarzschild-Anti-de Sitter (SAdS) black hole with an f(R) global monopole. We examine the separability of the Klein–Gordon equation with a non-minimal coupling and then we discuss both the massless and massive cases for a conformal coupling. We investigate some physical phenomena related to the asymptotic behavior of the radial function, namely, the black hole radiation, the quasibound states, and the wave eigenfunctions.
The Pharmacological Rationales and Molecular Mechanisms ofGanoderma lucidumPolysaccharides for the Therapeutic Applications of Multiple Diseases
Authors: Luo Hua , Tan Dechao , Peng Bo , Zhang Siyuan , Vong Chi Teng , Yang Zizhao , Wang Yitao , Lin Zhibin
Published: December 2021

As a versatile Chinese herb, Ganoderma lucidum (Leyss. ex Fr.) Karst (G. lucidum) has been applied to treat multiple diseases in clinics and improve the quality of life of patients. Among all of its extracts, the main bioactive components are G. lucidum polysaccharides (GLPs), which possess many therapeutic effects, such as antitumor, immunoregulatory, anti-oxidant, antidiabetic, antibacterial, and antifungal effects and neuroprotection activities. This review briefly summarized the recent studies of the pharmacological rationales of GLPs and their underlying molecular signaling transmission mechanisms in treating diseases. Until now, the clear mechanisms of GLPs for treating diseases have not been reported. In this review, we used the keywords of “Ganoderma lucidum polysaccharides” and “tumor” to search in PubMed (years of 1992–2020), then screened and obtained 160 targets of antitumor activities in the literatures. The network pharmacology and mechanism framework were employed in this study as powerful approaches to systematically analyze the complicated potential antitumor mechanisms and targets of GLPs in cancer. We then found that there are 69 targets and 21 network pathways in “Pathways in cancer”. Besides, we summarized the effects of GLPs and the models and methods used in the research of GLPs. In conclusion, GLPs have been studied extensively, but more in-depth research is still needed to determine the exact mechanisms and pathways. Therefore, this review might provide new insights into the vital targets and pathways for researchers to study the pharmacological mechanisms of GLPs for the treatment of diseases.
Noninertial effects on a composite system
Authors: Guvendi Abdullah , Hassanabadi Hassan
Published: December 2021

In this paper, we investigate the relativistic dynamics of a fermion–antifermion pair holding through Dirac oscillator interaction in the rotating frame of [Formula: see text]-dimensional topological defect-generated geometric background. We obtain an exact energy spectrum for the system in question by solving the corresponding form of a fully covariant two-body Dirac equation. This energy spectrum depends on the angular velocity [Formula: see text] of uniformly rotating frame and angular deficit [Formula: see text] in the geometric background. Our results show that the effects of [Formula: see text] on each energy level of the system are not same and the [Formula: see text] impacts on the strength of interaction between the particles. Furthermore, we observe that it seems to be possible to actively tune the dynamics of such a fermion–antifermion system, in principle.
Software Architecture Design of Animation Studies Platform Using Structure-Behavior Coalescence Method
Authors: Chen Rui-Rui , Lin Chien-Chung , Wang Lin , Chao William S.
Published: December 2021

Animation education in the new media era is moving toward the goal of cultivating high-end talents. The development of an architecture-oriented animation studies platform provides guarantee for the training of talents in terms of teaching quality. This research uses the Internet as the medium and mobile phones and computer clients as the main technology platforms, starting from the software architecture and constructing the system model of the animation studies platform according to the Structure-Behavior Coalescence (SBC) method. The core theme of Model-Based Systems Engineering (MBSE) is a modeling language with model consistency of systems structure and systems behavior. This paper developed Structure-Behavior Coalescence State Machine (SBC-SM) as the formal language for the MBSE animation studies platform design model singularity. The model consistency will be fully guaranteed in the MBSE animation studies platform design when the SBC state machine approach is adopted. It not only improves the efficiency of platform development but also reduces the difficulty and risk of platform development.
Analysis of the Deformation Characteristics of Loess Based on Thermal–Mechanical Coupling under an Energy Internet
Authors: Li Zengle , Zhi Bin , Liu Enlong
Published: December 2021

In response to the major challenges faced by China’s transition to green low-carbon energy under the dual-carbon goal, the use of energy Internet cross-boundary thinking will help to develop research on the integration of renewable clean energy and buildings. Energy piles are a new building-energy-saving technology that uses geothermal energy in the shallow soil of the Earth’s surface as a source of cold (heat) to achieve heating in winter and cooling in summer. It is a complex thermomechanical working process that changes the temperature of the rock and soil around the pile, and the temperature change significantly influences the mechanical properties of natural loess. Although the soil temperature can be easily and quickly obtained by using sensors connected to the Internet of Things, the mechanical properties of natural loess will change greatly under the influence of temperature. To explore the influence of temperature on the stress–strain relationship of structural loess, the undrained triaxial consolidation tests were carried out under different temperatures (5, 20, 50 and 70∘C) and different confining pressures (50, 100, 200 and 400[Formula: see text]kPa), and a binary-medium model was introduced to simulate the stress–strain relationship. By introducing the damage rate under temperature change conditions, a binary-medium model of structural loess under variable temperature conditions was established, and the calculation method of the model parameters was proposed. Finally, the calculated results were compared with the test results. The calculation results showed that the established model has good applicability.
Effective Communication-Based Reactive Power Sharing Scheme for Meshed Microgrid in an Islanded Mode
Authors: Daniel Anitha , Dayalan Suchitra
Published: December 2021

Microgrids (MGs) are the most sought out and feasible solution for the present energy crisis. MG is a group of Distributed Generators (DGs) interacting with each other to provide energy to a defined local area. The inclusion of DGs into the conventional power system at various voltage levels has altered the topology of the power system and their control techniques. Hence, the MGs can no longer be considered as a traditional radial network but rather a meshed network. The control and operation of such practical MGs become a challenge, especially when operated in the islanded mode. This research paper considers a realistic meshed MG operating in an islanded mode for study. In an islanded MG, the issues of real and reactive power sharing among DGs are addressed so that the power contribution of each DG is proportional to its rating, thus preventing overload and ensuring reliable operation. A communication-based virtual impedance estimation is proposed in addition to the droop controller for proportionate real and reactive power sharing among DGs in a meshed MG. With the increased complexity of meshed MG, the proposed communication-based control scheme offers an efficient reactive power sharing between DGs without the feeder and network impedance requirements. A MATLAB simulation study proves the effectiveness of the proposed control strategy for a meshed MG with equal DG ratings and unequal DG ratings under changing load conditions.
An Energy-Efficient Low-Area Double-Node-Upset-Hardened Latch Design
Authors: Kumar Chaudhry Indra
Published: December 2021

The energy-efficient circuits, though important in IoT and biomedical applications, are vulnerable to soft errors due to their low voltages and small node capacitances. This paper presents an energy-efficient low-area double-node-upset-hardened latch (EEDHL). The proposed latch enhances the radiation hardness by employing a restorer circuit based on a Muller C-element and a memory element. The post-layout simulations show that the EEDHL improves the area–energy–delay product (AEDP) by [Formula: see text]80% compared to the newly reported double-node-upset-resilient latch (DNURL) in STMicroelectronics 65-nm CMOS technology. Synopsys TCAD mixed-mode simulations in 32-nm CMOS technology framework are also used to validate the proposed DNU-hardened latch. The proposed EEDHL effectively mitigates the DNU at the strike with a linear energy transfer (LET) equal to 160[Formula: see text][Formula: see text]/mg in 32-nm CMOS technology.
THE EFFECT OF STOCHASTIC VARIABILITY ON TRANSMISSION DYNAMICS OF ECHINOCOCCOSIS
Authors: WANG LEI , WANG KAI , FENG XIAOMEI , ZHAO YU , JIANG DAQING
Published: December 2021

Echinococcosis, one of the most serious zoonotic diseases, has a severe impact on the human health and economic development. This paper mainly focuses on the effect of stochastic variability on transmission dynamics of echinococcosis. A stochastic model describing the transmission of echinococcus granulosus in dog-livestock-human is proposed. By using the Itô formula, strong law of large numbers for martingale and the inequality analysis, the criteria on the extinction with probability one for the disease are obtained. In addition, by constructing an appropriate stochastic Lyapunov function, the existence of a unique ergodic stationary distribution is established. Furthermore, numerical simulations have been performed to not only support our analytical results but also display that noise intensities would have significant impact on the speed of the extinction for the echinococcosis disease, and as well as the shape for the probability density curve of the stationary distribution of the solution for this model.
Firefly-Based Maintainability Prediction for Enhancing Quality of Software
Authors: Yenduri Gokul , Gadekallu Thippa Reddy
Published: December 2021

In a broad spectrum, software metrics play a vital role in attribute assessment, which successively moves software projects. The metrics measure gives many crucial facets of the system, enhancing the system quality of software developed. Moreover, maintenance is the correction process that works out in the software system once the software is initially made. The noteworthy characteristic of any software is ‘change,’ and as a result, additional concern ought to be taken in developing software. So, the software is expected to be modified effortlessly (maintainable). Predicting software maintainability is still challenging, and accurate prediction models with low error rates are required. Since there are so many modern programming languages on the horizon. To accurately measure software maintainability, new techniques have to been introduced. This paper proposes a maintainability index (MI) by considering various software metrics by which the error gets minimized. It also intends to adopt a renowned optimization algorithm, namely Firefly (FF), for the optimum result. The proposed Base Model-FF is compared to other traditional models like BM-Differential Evolution (BM-DE), BM-Artificial Bee Colony (BM-ABC), BM-Particle Swarm Optimization (BM-PSO), and BM-Genetic Algorithm (BM- GA) in terms of performance metrics like Differential ratio, correlation coefficient, and Random Mean Square Error (RMSE).
Integration of ARAS and MOORA MCDM Techniques for Measuring the Performance of Private Sector Banks in India
Authors: Rao Sama Hamumantha , Kalvakolanu Sripathi , Chakraborty Chinmay
Published: December 2021

This current research paper measures the performance of Indian private sector banks through various multi-criteria decision-making (MCDM) techniques. To measure the performance of the banks the data about various criteria such as profit after tax, borrowings, advances, adjusted EPS, enterprise value, and NPAs from the Annual reports of the banks were extracted. The MCDM techniques, SDV (standard deviation) CRITIC (CRiteria Importance Through Intercriteria Correlation), ARAS (Additive Ratio Assessment), MOORA (Multi-objective Optimization on the basis of Ratio Analysis) are applied to analyze the data and measure the performance of the banks. In MCDM techniques, different methods provide different weights of the criteria, and also different ranks are obtained by different methods. Sensitivity analysis was carried out by measuring the criteria weights by SDV and CRITIC and the alternatives are ranked using two MCDM techniques, ARAS and MOORA. The results of the study show that among the private banks, HDFC created a benchmark and leading while Yes bank has shown poor performance on the basis of annual reports of 2020.
Black-Hole Attack Mitigation in Medical Sensor Networks Using the Enhanced Gravitational Search Algorithm
Authors: Dhanaraj Rajesh Kumar , Jhaveri Rutvij H. , Krishnasamy Lalitha , Srivastava Gautam , Maddikunta Praveen Kumar Reddy
Published: December 2021

In today’s world, one of the most severe attacks that wireless sensor networks (WSNs) face is a Black-Hole (BH) attack which is a type of Denial of Service (DoS) attack. This attack blocks data and injects infected programs into a set of sensors in a group to capture packets before reached to the target. Therefore, raw data in the BH region is thwarted and is unable to reach its destination. The network is susceptible to various types of attacks as it is accessible to all types of users and minimizing the energy depletion without compromising the network lifetime is an NP-hard problem. Even though numerous protocols came into effect to overcome the BH attack and to enhance the security of packet delivery in WSNs, Simulated Annealing Black-hole attack Detection (SABD) based Enhanced Gravitational Search Algorithm (EGSA) is yet another implemented strategy to reduce the BH attacks. EGSA-SABD detects and isolates the BH infectors in WSNs. Initially, sensor nodes are hierarchically clustered using similar residual energy to reduce energy consumption. Then, the BH attack possibility in a deployed node is evaluated to find the existence of BH nodes in the region. In the end, EGSA-SABD is employed to detect and quarantine BH attackers in WSNs. The performance of EGSA-SABD is evaluated with certain metrics such as BH attack detection probability rate (BHatt_Prate), energy consumption (Ec), Duration of BH attack detection (Attduration), Packet delivery ratio (Pdr). Based on the experimental observations, the EGSA-SABD outperforms the BHatt_Prate by 13% and also reduces the energy consumption by 21%.
A Lossless Compression Technique for Huffman-based Differential Encoding in IoT for Smart Agriculture
Authors: Kagita Mohan Krishna , Thilakarathne Navod , Bojja Giridhar Reddy , Kaosar Mohammed
Published: December 2021

Agriculture faces several uncertain problems in terms of making the best use of its natural resources. As a result, and in light of the growing threat of changing weather conditions, we must closely track local soil conditions and meteorological data to expedite the adoption of culture-friendly decisions. In the Internet of Things (IoT) era, deploying Wireless Sensor Networks (WSN) as a low-cost remote monitoring and management system for these types of features is a viable choice. However, the WSN is hampered by the motes’ insufficient energy sources, which reduces the network’s overall lifespan. Each mote collects the tracked feature regularly and sends the data to the sink for further analysis. This method of transmitting large amounts of data requires the sensor node to use a lot of energy and a lot of network bandwidth. We propose a lightweight lossless compression algorithm based on Differential Encoding (DE) and Huffman techniques in this paper, which is especially useful for IoT sensor nodes that track environmental features, especially those with limited computing and memory resources. Rather than attempting to create novel ad hoc algorithms, we show that, given a general understanding of the features to be monitored, classical Huffman coding can be used to effectively represent the same features that measure at different times and locations. Even though the proposed system does not achieve the theoretical limit, results using temperature measurements show that it outperforms standard methods built specifically for WSNs.
A Hybrid Multi-Feature Semantic Similarity Based Online Social Recommendation System Using CNN
Authors: Saraswathi K. , Mohanraj V. , Suresh Y. , Senthilkumar J.
Published: December 2021

Modern organizations are keen to work towards their customer needs. To achieve this, analyzing their activities and identifying their interest in any entity becomes important. Every user has been identified as the most important factor in point of organization, and they never give up even a single user. Several approaches have been discussed earlier, which use artificial intelligence to mine the users and their interest in the problem. However, the deep learning algorithms are identified as most efficient in identifying the user interest but suffer to achieve higher performance. Towards this issue, an efficient multi-feature semantic similarity-based online social recommendation system has been proposed. The method uses Convolution Neural Network (CNN) to train and predict user interest in any topic. Each layer has been identified as a single interest, and neurons of the layers are initialized with huge data set. The neuron estimates the Multi-Feature Semantic Similarity (MFSS) towards each interest of the user. Finally, the method identifies the single interest for the user by ranking each interest to produce recommendations to the user. The proposed algorithm improves the performance of recommendation generation with less false ratio.
OPTIMIZATION OF PROCESS PARAMETERS AFFECTING CUTTING FORCE, POWER CONSUMPTION AND SURFACE ROUGHNESS USING TAGUCHI-BASED GRAY RELATIONAL ANALYSIS IN TURNING AISI 1040 STEEL
Authors: AKGÜN MAHIR
Published: December 2021

This study focuses on optimization of cutting conditions and modeling of cutting force ([Formula: see text]), power consumption ([Formula: see text]), and surface roughness ([Formula: see text]) in machining AISI 1040 steel using cutting tools with 0.4[Formula: see text]mm and 0.8[Formula: see text]mm nose radius. The turning experiments have been performed in CNC turning machining at three different cutting speeds [Formula: see text] (150, 210 and 270[Formula: see text]m/min), three different feed rates [Formula: see text] (0.12 0.18 and 0.24[Formula: see text]mm/rev), and constant depth of cut (1[Formula: see text]mm) according to Taguchi L18 orthogonal array. Kistler 9257A type dynamometer and equipment’s have been used in measuring the main cutting force ([Formula: see text]) in turning experiments. Taguchi-based gray relational analysis (GRA) was also applied to simultaneously optimize the output parameters ([Formula: see text], [Formula: see text] and [Formula: see text]). Moreover, analysis of variance (ANOVA) has been performed to determine the effect levels of the turning parameters on [Formula: see text], [Formula: see text] and [Formula: see text]. Then, the mathematical models for the output parameters ([Formula: see text], [Formula: see text] and [Formula: see text]) have been developed using linear and quadratic regression models. The analysis results indicate that the feed rate is the most important factor affecting [Formula: see text] and [Formula: see text], whereas the cutting speed is the most important factor affecting [Formula: see text]. Moreover, the validation tests indicate that the system optimization for the output parameters ([Formula: see text], [Formula: see text] and [Formula: see text]) is successfully completed with the Taguchi method at a significance level of 95%.
EFFECT OF ASYMMETRIC LATERAL LINKING GROUPS ON THE ELECTRONIC TRANSPORT IN MOLECULAR DEVICE
Authors: WU YAMIN , LIAO BIN , WANG GUOLIANG , BIAN BAOAN
Published: December 2021

The effect of asymmetric lateral linking groups on the electronic transport is investigated in the biphenyl molecule-based device with gold electrodes with the framework of density functional theory and nonequilibrium Green’s function. The asymmetric lateral linking groups reduce the currents of molecular junctions, and result in the reverse rectifying behavior. The devices with asymmetric lateral linking groups –SH and –SCH3 have maximum rectifying ratios, while the asymmetric lateral linking group –SH and –NH2 cause minimum rectifying ratios. The calculated results suggest that the asymmetric lateral linking group induces the reduced coupling between molecule and right electrode, asymmetric distribution of frontier molecular orbital and asymmetric evolution of the molecular orbital eigenenergies, accounting for the rectifying behavior.
Lateral Impact Response of Elliptical Hollow and Partially Concrete-Filled Cold-Formed Steel Columns Under Static Axial Compression Load
Authors: Rana Nayyer Mohammadi , Ghandi Elham , Niari Shirin Esmaeili
Published: December 2021

In recent years, the use of partially concrete-filled steel tubular (PCFST) columns has been considered due to their cost-effectiveness and reduction of structural weight in bridge piers and building columns. One of the critical discussions about these columns is their impact resistance. In this article, the dynamic response of hollow and PCFST columns with elliptical cross-section under simultaneous loading of static axial compressive load and lateral impact load is presented using finite element modeling in ABAQUS software (FEA). To ensure the accuracy of the numerical modeling, the analysis results are compared with the results of previous works. The effects of different parameters such as impact velocity, the height of the impact location, the impact direction, the impact block mass, the size and shape of the impact block are investigated in this paper. The results of the numerical analysis showed that the partially filled specimens had better performance than the hollow specimens. The changes in impact direction and impact block mass parameters have a significant effect on the failure of the columns, especially when they are under high impact velocity. Changing the impact velocity significantly affects the impact resistance of specimens. However, the size and shape of the impact block did not have a significant effect on the displacement of the column against the impact loading.
THE TALENT VERSUS LUCK MODEL AS AN ENSEMBLE OF ONE-DIMENSIONAL RANDOM WALKS
Authors: SIMÃO RICARDO , ROSENDO FRANCISCO , WARDIL LUCAS
Published: December 2021

The role of luck on individual success is hard to be investigated empirically. Simplified mathematical models are often used to shed light on the subtle relations between success and luck. Recently, a simple model called “Talent versus Luck” showed that the most successful individual in a population can be just an average talented individual that is subjected to a very fortunate sequence of events. Here, we modify the framework of the TvL model such that in our model the individuals’ success is modelled as an ensemble of one-dimensional random walks. Our model reproduces the original TvL results and, due to the mathematical simplicity, it shows clearly that the original conclusions of the TvL model are the consequence of two factors: first, the normal distribution of talents with low standard deviation, which creates a large number of average talented individuals; second, the low number of steps considered, which allows the observation of large fluctuations. We also show that the results strongly depend on the relative frequency of good and bad luck events, which defines a critical value for the talent: in the long run, the individuals with high talent end up very successful and those with low talent end up ruined. Last, we considered two variations to illustrate applications of the ensemble of random walks model.
NON-CENTRAL MOMENTS OF THE TRUNCATED NORMAL VARIABLE IN FINANCE
Authors: CORRADIN FAUSTO , SARTORE DOMENICO
Published: December 2021

This paper computes the Non-central Moments of the Truncated Normal variable, i.e. a Normal constrained to assume values in the interval with bounds that may be finite or infinite. We define two recursive expressions where one can be expressed in closed form. Another closed form is defined using the Lower Incomplete Gamma Function. Moreover, an upper bound for the absolute value of the Non-central Moments is determined. The numerical results of the expressions are compared and the different behavior for high value of the order of the moments is shown. The limitations to the use of Truncated Normal distributions with a lower negative limit regarding financial products are considered. Limitations in the application of Truncated Normal distributions also arise when considering a CRRA utility function.
A Primer on the Conditional Mediation Analysis in PLS-SEM
Authors: Cheah Jun-Hwa , Nitzl Christian , Roldán José L. , Cepeda-Carrion Gabriel , Gudergan Siegfried P.
Published: December 2021

Conditional mediation (CoMe) analysis integrates mediation and moderation analyses to examine and test hypotheses about how mediated relationships vary as a function of context, boundaries, or individual differences. Although CoMe analysis can be a crucial element of empirical studies that seek to advance theory in information systems, applications of such analysis are scarce, in general, and in partial least squares structural equation modeling (PLS-SEM), in particular. This paper clarifies conceptual fundamentals of and develops guidelines for CoMe analysis within the PLS-SEM context. Furthermore, the paper outlines the illustrative use of CoMe analysis in PLS-SEM and presents detailed step-by-step procedures to do so in the PLS-SEM setting. Overall, this paper provides researchers and practitioners with the required knowledge to properly carry out, report, and interpret CoMe analysis in PLS-SEM.
Reflections on SEM
Authors: Hair Joseph F.
Published: December 2021

For almost 40 years structural equation modeling (SEM) has been the statistical tool of choice for the assessing measurement and structural relationships in the social sciences. During the initial 30 years almost all applications of SEM utilized what has become known as covariance-based SEM. But in the past ten years an alternative structural equation modeling method, composite-based SEM, has increasingly been applied. In fact, a substantial number of social sciences scholars consider composite-based SEM the method of choice for structural equation modeling applications. In this paper, I provide an overview of the evolution of SEM, from the early years when factor-based SEM was the dominant method to the more recent years as composite-based methods have become much more prevalent. I also summarize several relevant composite-based topics including the emergence of composite-based SEM, confirmatory composite analysis (CCA), and a new method of generalized structured component analysis (GSCA). In the final section I propose some observations about current developments and future opportunities for composite-based SEM methods.
Whole Lotta COVID Goin' On
Authors: Stafford Tom , Tazkarji Mohamed
Published: December 2021

It's been a long year-and-a-half or since the initial outbreak arose down here in Louisiana, right after Mardi Gras 2020, February. New Orleans and its widely attended Mardi Gras looked to be the "spreader event" of our region, it seemed like.
Addiction to Social Networking Sites and User Responses
Authors: Qahri-Saremi Hamed , Vaghefi Isaac , Turel Ofir
Published: December 2021

Prior studies have primarily used "variable-centered" perspectives to identify factors underlying user responses to social networking site (SNS) addiction, their predictors and outcomes. This paper extends this perspective by taking a person-centered approach to examine (1) the prototypical subpopulations (profiles) of users' extent of SNS addiction and responses to it, (2) how affiliations with these profiles can explain user behaviors toward SNS use, and (3) how personality traits can predict affiliations with these profiles. To this end, we propose a typological theory of SNS addiction and user responses to it via two empirical, personcentered studies. Study 1 draws on survey data from 188 SNS users to develop a typology of users based on the extent of their SNS addiction and their responses to it. It further examines the relations between affiliation with these profiles and users' SNS discontinuance intention, as a typical behavioral response to SNS addiction. Study 2 uses survey data from 284 SNS users to validate the user typology developed in Study 1 and investigate its relations to users' Big Five personality traits. Our findings shed light on a typology of five prototypical profiles of SNS users-cautious, regular, consonant, dissonant, and hooked-who differ in their extent of SNS addiction and their cognitive, emotional, and behavioral responses to it. Our findings also demonstrate how Big Five personality traits can predict user affiliations with these prototypical profiles.
Mitochondrial quality surveillance: mitophagy in cardiovascular health and disease
Authors: Diao Rachel Y. , Gustafsson Åsa B.
Published: December 2021

Selective autophagy of mitochondria, known as mitophagy, is a major quality control pathway in the heart that is involved in removing unwanted or dysfunctional mitochondria from the cell. Baseline mitophagy is critical for maintaining fitness of the mitochondrial network by continuous turnover of aged and less-functional mitochondria. Mitophagy is also critical in adapting to stress associated with mitochondrial damage or dysfunction. The removal of damaged mitochondria prevents reactive oxygen species-mediated damage to proteins and DNA and suppresses activation of inflammation and cell death. Impairments in mitophagy are associated with the pathogenesis of many diseases, including cancers, inflammatory diseases, neurodegeneration, and cardiovascular disease. Mitophagy is a highly regulated and complex process that requires the coordination of labeling dysfunctional mitochondria for degradation while simultaneously promoting de novo autophagosome biogenesis adjacent to the cargo. In this review, we provide an update on our current understanding of these steps in mitophagy induction and discuss the physiological and pathophysiological consequences of altered mitophagy in the heart.
[Retracted] miR‐10b‐5p Suppresses the Proliferation and Invasion of Primary Hepatic Carcinoma Cells by Downregulating EphA2
Authors: Niu Xu , Sun Haitao , Qiu Feng , Liu Jing , Yang Tianchi , Han Wei
Published: December 2021

Objective. To analyze the function of miR‐10b‐5p in suppressing the invasion and proliferation of primary hepatic carcinoma cells by downregulating erythropoietin‐producing hepatocellular receptor A2 (EphA2). Material and Methods. Eighty‐six hepatic carcinoma (HCC) tissue specimens and 86 corresponding adjacent tissue specimens were collected, and the mRNA expression of miR‐10b‐5p and Ephrin type‐A receptor 2 (EphA2) in the specimens was determined using a reverse transcription‐polymerase chain reaction (RT‐PCR) assay. Western blot was employed to quantify EphA2, B‐cell chronic lymphocytic leukemia/lymphoma‐2 (Bcl‐2), Bcl‐2‐associated X protein (Bax), and Caspase‐3 in the cells, and CCK8, Transwell assay, and flow cytometry were applied to evaluate the proliferation, invasion, and apoptosis of cells, respectively. Moreover, the dual luciferase reporter assay was utilized for correlation analysis between miR‐10b‐5p and EphA2. Results. miR‐10b‐5p was lowly expressed in HCC, while EphA2 was highly expressed. Cell experiments revealed that miR‐10b‐5p overexpression or EphA2 knockdown could reduce cell proliferation, accelerate apoptosis, strongly upregulate Bax and Caspase‐3, and downregulate Bcl‐2. In contrast, miR‐10b‐5p knockdown or EphA2 overexpression gave rise to reverse biological phenotypes. Furthermore, dual luciferase reporter assay verified that miR‐10b‐5p was a target of EphA2, and the rescue experiment implied that transfection of pCMV‐EphA2 or Si‐EphA2 could reverse EphA2 expression and cell biological functions caused by miR‐10b‐5p overexpression or knockdown. Conclusions. miR‐10b‐5p reduced HCC cell proliferation but accelerate apoptosis by regulating EphA2, suggesting it has the potential to be a clinical target for HCC.
Multistage Polymerization Network for Multiperson Pose Estimation
Authors: Bai Yu-Fei , Zhang Hong-Bo , Lei Qing , Du Ji-Xiang
Published: December 2021

Multiperson pose estimation is an important and complex problem in computer vision. It is regarded as the problem of human skeleton joint detection and solved by the joint heat map regression network in recent years. The key of achieving accurate pose estimation is to learn robust and discriminative feature maps. Although the current methods have made significant progress through interlayer fusion and intralevel fusion of feature maps, few works pay attention to the combination of the two methods. In this paper, we propose a multistage polymerization network (MPN) for multiperson pose estimation. The MPN continuously learns rich underlying spatial information by fusing features within the layers. The MPN also adds hierarchical connections between feature maps at the same resolution for interlayer fusion, so as to reuse low‐level spatial information and refine high‐level semantic information to obtain accurate keypoint representation. In addition, we observe a lack of connection between the output low‐level information and the high‐level information. To solve this problem, an effective shuffled attention mechanism (SAM) is proposed. The shuffle aims to promote the cross‐channel information exchange between pyramid feature maps, while attention makes a trade‐off between the low‐level and high‐level representations of the output features. As a result, the relationship between the space and the channel of the feature map is further enhanced. Evaluation of the proposed method is carried out on public datasets, and experimental results show that our method has better performance than current methods.
Optimization of STP Innovation Management Mechanisms Driven by Advanced Evolutionary IoT Arithmetic
Authors: Wang Tianxiang , Ma Qingqing , Li Jinxi
Published: December 2021

Since industrialization, manufacturing has been an important pillar of a country’s economic development. Under the dual pressure of the new trend of global manufacturing development and the loss of competitive advantage of manufacturing industry, it is especially important to accelerate the enhancement of national high technology innovation capacity and the optimization of high technology policy innovation management mechanism driven by advanced evolutionary Internet of Things (IoT) arithmetic. The main of this paper thus introduces the effective method of optimization of high technology policy innovation management mechanism driven by advanced evolutionary IoT arithmetic. To study the optimization of high technology policy innovation management mechanism, a conceptual analysis of currently popular information technologies, such as big data technologies, artificial intelligence technologies, and Internet of Things technologies, and an overview of the application of these technologies in microgrids are given. In the paper, all factors are studied using the STP innovation management mechanism‐based approach, and finally, all factors are classified into two categories of cause and effect factors by this approach, and the importance of all factors is ranked. Secondly, a wind power prediction algorithm based on data mining technology and an improved algorithm and a PV power prediction algorithm based on a deep neural network were established with the technical support of high‐tech information technology such as big data and artificial intelligence. Finally, the majorization of high technology policy innovation management mechanism driven by advanced evolutionary IoT arithmetic is proposed.