bluuebunny/crossref_metadata_2025 huggingface dataset:
Iterative Fusion and Dual Enhancement for Accurate and Efficient Object Detection
Authors: Duan Zhipeng , Zhang Zhiqiang , Liu Xinzhi , Cheng Guoan , Xu Liangfeng , Zhan Shu
Published: February 2023

Single Shot Multibox Detector (SSD) uses multi-scale feature maps to detect and recognize objects, which considers the advantages of both accuracy and speed, but it is still limited to detecting small-sized objects. Many researchers design new detectors to improve the accuracy by changing the structure of the multi-scale feature pyramid which has proved very useful. But most of them only simply merge several feature maps without making full use of the close connection between features with different scales. In contrast, a novel feature fusion module and an effective feature enhancement module is proposed, which can significantly improve the performance of the original SSD. In the feature fusion module, the feature pyramid is produced through iteratively fusing three feature maps with different receptive fields to obtain contextual information. In the feature enhancement module, the features are enhanced along the channel and spatial dimensions at the same time to improve their expression ability. Our network can achieve 82.5% mean Average Precision (mAP) on the VOC 2007 [Formula: see text], 81.4% mAP on the VOC 2012 [Formula: see text] and 34.8% mAP on COCO [Formula: see text]-[Formula: see text]2017, respectively, with the input size [Formula: see text]. Comparative experiments prove that our method outperforms many state-of-the-art detectors in both aspects of accuracy and speed.
A Deep Neural Network-Based Intelligent Detection Model for Manufacturing Defects of Automobile Parts
Authors: Xu Wenbo , Liu Gang , Wang Mengmeng
Published: February 2023

Image defect detection of casting parts is a key part of the production process in the machinery manufacturing industry. The traditional methods are ineffective because traditional computer image processing methods require a large number of manual features to be set artificially, and the detection time is too long. In order to save human resources and improve the efficiency of image defect detection, this paper proposes a deep learning-based defect detection method for automobile parts. This paper selects EfficientNetB0 as the backbone framework of the target detection network, which significantly reduces the memory usage of the model and shortens the model inference time, while improving the model detection accuracy. Facing the problem of small samples of defect image dataset, we analyze the image characteristics of the dataset and introduce shape transformation and scale scaling as the basic online data enhancement method according to the industrial field image projection law. Then, it is expected to combine the traditional image processing algorithms according to the characteristics of casting parts with different depth distribution and multiple morphological changes, and develop a special image defect data enhancement method. This further improves the performance of the model and increases the detection accuracy of the algorithm by 22.3% without increasing the data.
TERMINAL VALUE PROBLEM FOR STOCHASTIC FRACTIONAL EQUATION WITHIN AN OPERATOR WITH EXPONENTIAL KERNEL
Authors: PHUONG NGUYEN DUC , HOAN LUU VU CAM , BALEANU DUMITRU , NGUYEN ANH TUAN
Published: February 2023

In this paper, we investigate a terminal value problem for stochastic fractional diffusion equations with Caputo–Fabrizio derivative. The stochastic noise we consider here is the white noise taken value in the Hilbert space [Formula: see text]. The main contribution is to investigate the well-posedness and ill-posedness of such problem in two distinct cases of the smoothness of the Hilbert scale space [Formula: see text] (see Assumption 3.1), which is a subspace of [Formula: see text]. When [Formula: see text] is smooth enough, i.e. the parameter [Formula: see text] is sufficiently large, our problem is well-posed and it has a unique solution in the space of Hölder continuous functions. In contract, in the different case when [Formula: see text] is smaller, our problem is ill-posed; therefore, we construct a regularization result.
A NOVEL NUMERICAL METHOD FOR SOLVING FUZZY VARIABLE-ORDER DIFFERENTIAL EQUATIONS WITH MITTAG-LEFFLER KERNELS
Authors: JAFARI HOSSEIN , GANJI ROGHAYEH MOALLEM , GANJI DAVOOD DOMIRI , HAMMOUCH ZAKIA , GASIMOV YUSIF S.
Published: February 2023

In the fuzzy calculus, the study of fuzzy differential equations (FDEs) created a proper setting to model real problems which contain vagueness or uncertainties factors. In this paper, we consider a class fuzzy differential equations (FFDEs) with non-integer or variable order (VO). The variable order derivative is defined in the Atangana–Baleanu–Caputo sense on fuzzy set-valued functions. The main problem under the fuzzy initial condition is converted to a new problem by the [Formula: see text]-cut representation of fuzzy-valued function. For solving the new problem, we use the operational matrices (OMs) based on the shifted Legendre polynomials (SLPs). By approximating the unknown function and its derivative in terms of the SLPs and substituting these approximations into the equation, the main problem is converted to a system of nonlinear algebraic equations. An error estimate of the numerical solution is proved. Finally, an example is considered to confirm the accuracy of the proposed technique.
ANALYTICAL SOLUTIONS FOR TIME-FRACTIONAL RADHAKRISHNAN–KUNDU–LAKSHMANAN EQUATION
Authors: ZHANG JIQIANG , KADKHODA NEMATOLLAH , BAYMANI MOJTABA , JAFARI HOSSEIN
Published: February 2023

In this paper, two algebraic methods are applied for solving a class of conformable fractional partial differential equations (FPDEs). We use these methods for the time-fractional Radhakrishnan–Kundu–Lakshmanan equation. With these methods, further solutions can be obtained compared with other approaches and techniques. The exact particular solutions include the exponential solution, trigonometric function solution, rational solution and hyperbolic function solution. These methods are very effective to obtain exact solutions of many fractional differential equations.
Imputed Expert Decision Recommendation System for QFD-based Omnichannel Strategy Selection for Financial Services
Authors: Kou Gang , Dinçer Hasan , Yüksel Serhat , Alotaibi Fahd S.
Published: February 2023

In this study, a novel hybrid fuzzy decision-making model is constructed for the effective omnichannel strategy selection of financial services. The first phase of this model is related to inputting missing expert decisions for the quality function deployment (QFD) stages and omnichannel service strategies. The QFD stages of financial services are then weighted by bipolar [Formula: see text]-rung orthopair fuzzy ([Formula: see text]-ROF) multi-stepwise weight assessment ratio analysis ([Formula: see text]-SWARA) based on the golden ratio. The QFD-based omnichannel strategy alternatives for financial services are then ranked using bipolar [Formula: see text]-ROF ELECTRE. These calculations are also performed by considering PFSs and IFSs. Finally, the TOPSIS methodology is used to rank the alternatives so that comparative results can be obtained. The main contribution of this study is the creation of effective omnichannel strategies to improve financial services using a novel hybrid fuzzy decision-making methodology based on bipolar [Formula: see text]-rung orthopair fuzzy sets ([Formula: see text]-ROFSs), [Formula: see text]-SWARA, ELECTRE, and the imputation of expert evaluations with collaborative filtering. The analysis results obtained will facilitate determination of the most appropriate omnichannel strategies for businesses to provide effective financial services. In this manner, companies will be able to determine appropriate marketing strategies without incurring excessive costs. Because the analysis results are the same for all fuzzy sets, the proposed model is coherent and reliable. The findings demonstrate that online financial services are the most critical strategy for improving omnichannel. Thus, companies should prioritize online channels to provide financial services that are more effective.
Families of identities involving universal mock theta functions
Authors: Song Hanfei , Wang Chun
Published: February 2023

The purpose of this paper is to establish several families of identities involving universal mock theta functions and express them in terms of Appell–Lerch sums. The subsequent consequences of these results are a variety of interesting identities on theta series and classical mock theta functions.
On a variant of Pillai’s problem with binary recurrences and S-units
Authors: Ziegler Volker
Published: February 2023

Let [Formula: see text] be a fixed binary recurrence with real characteristic roots [Formula: see text] satisfying [Formula: see text] and let [Formula: see text] be fixed distinct prime numbers. In this paper, we show that there exist effectively computable, positive constants [Formula: see text] and [Formula: see text] such that the Diophantine equation [Formula: see text] has at most [Formula: see text] solutions [Formula: see text] if [Formula: see text] and at most [Formula: see text] solutions [Formula: see text] if [Formula: see text]. In order to demonstrate the strength of our method we show that for the binary recurrence sequence [Formula: see text], with [Formula: see text] for [Formula: see text], [Formula: see text] and [Formula: see text], the Diophantine equation [Formula: see text] has at most six solutions [Formula: see text] unless [Formula: see text] in which case it has exactly seven solutions.
Torsion groups of elliptic curves over ℚ(μp∞)
Authors: Gužvić Tomislav , Vukorepa Borna
Published: February 2023

Let [Formula: see text] be an elliptic curve and [Formula: see text] be a prime. We determine the possibilities for [Formula: see text]. Additionally, we determine all the possibilities for [Formula: see text] and [Formula: see text]. Using these results, we can determine the possibilities for [Formula: see text] for [Formula: see text].
Knowledge Graph-Based Explainable Artificial Intelligence for Business Process Analysis
Authors: Füßl Anne , Nissen Volker , Heringklee Stefan Horst
Published: February 2023

For critical operational decisions (e.g. consulting services), explanations and interpretable results of powerful Artificial Intelligence (AI) systems are becoming increasingly important. Knowledge graphs possess a semantic model that integrates heterogeneous information sources and represents knowledge elements in a machine-readable form. The integration of knowledge graphs and machine learning methods represents a new form of hybrid intelligent systems that benefit from each other’s strengths. Our research aims at an explainable system with a specific knowledge graph architecture that generates human-understandable results even when no suitable domain experts are available. Against this background, the interpretability of a knowledge graph-based explainable AI approach for business process analysis is focused. We design a framework of interpretation, show how interpretable models are generated by a single case study and evaluate the applicability of our approach by different expert interviews. Result paths on weaknesses and improvement measures related to a business process are used to produce stochastic decision trees, which improve the interpretability of results. This can lead to interesting consulting self-services for clients or be applied as a device for accelerating classical consulting projects.
Knowledge Graph-Based Integration of Autonomous Driving Datasets
Authors: Halilaj Lavdim , Luettin Juergen , Monka Sebastian , Henson Cory , Schmid Stefan
Published: February 2023

Autonomous Driving (AD) datasets, when used in combination with deep learning techniques, have enabled significant progress on difficult AD tasks such as perception, trajectory prediction, and motion planning. These datasets represent the content of driving scenes as captured by various sensors, including cameras, RADAR, and LiDAR, along with 2D/3D annotations of traffic participants. Such datasets, however, often fail to capture and to represent the spatial, temporal, and semantic relations between entities in a scene. This lack of knowledge leads to a shallow understanding of the true complexity and dynamics inherent in a driving scene. In this paper, we argue that a Knowledge Graph (KG)-based representation of driving scenes, that provides a richer structure and semantics, will lead to further improvements in AD. Towards this goal, we developed a layered architecture and ontologies for specific AD datasets and a fundamental ontology of shared concepts. We also built KGs for three different AD datasets. We perform an analysis with respect to information contained in the AD KGs and outline how the additional semantic information contained in the KGs could improve the performance of different AD tasks. Moreover, example queries are provided to retrieve relevant information that can be exploited for augmenting the AD pipelines. All artifacts needed for reproducibility purposes are provided via a GitHub repository. ( https://github.com/boschresearch/dskg-constructor  — Note that we removed our internal namespaces of reused ontologies, because of confidentiality and to provide self-contained ontologies. As the original datasets are under specific licences, the KGs are not published, but we provide the scripts to generate them.)
A high-performance solid-state polymer electrolyte for lithium-metal battery
Authors: Wang Yumei , Yi Qiang , Xu Xiaoyu , Lu Li
Published: February 2023

Solid-state polymer electrolyte is a promising alternative to the flammable liquid electrolyte due to its improved safety. In this work, we develop a novel polymer electrolyte with fire-retardant property and excellent electrochemical performance. This fire-proof polymer electrolyte (FPE) demonstrates an outstanding ionic conductivity of 6.7 × [Formula: see text]S [Formula: see text] at [Formula: see text]C. The Li//FPE//Li symmetric cell using such FPE could stably charge/discharge for 500 h at a current density of 0.5 mA [Formula: see text] and an areal capacity of 0.5 mAh [Formula: see text]. The Li//FPE//LiFePO4 lithium-metal cell also presents a good cycling performance with a discharge capacity of 127.8 mAh [Formula: see text] after 450 cycles at 0.5 C.
Preparation and acoustic properties of high-temperature acoustic emission sensor based on La3Ga5SiO14 crystal
Authors: Si Jingxiang , Yang Changhong , Guo Rui , Wu Yifan , Lin Xiujuan , Huang Shifeng
Published: February 2023

With the rapid development of modern industries, the high-temperature piezoelectric sensors that can work in extreme environments are in great demand. In this work, langasite (La3Ga5SiO[Formula: see text], LGS), as a high-temperature piezoelectric crystal with stable electro-elastic performance, is used as core element, and air and porous Al2O3are selected as backing layers respectively to prepare two kinds of high-temperature acoustic emission (AE) sensors. The detection sensitivities at 25–500∘C are analyzed by the ball falling test and Hsu–Nielsen experiment. Under the condition of 25–500∘C, the received amplitude signals by both sensors are maintained above 90[Formula: see text]dB stimulated by the ZrO2ceramic ball dropping. In the Hsu–Nielsen experiment, as the temperature rising from 25∘C to 500∘C, the signal amplitude of sensor with air backing layer decays from 447[Formula: see text]mV to 365[Formula: see text]mV, while the signal amplitude varies from 270[Formula: see text]mV to 203[Formula: see text]mV for the sensor with porous Al2O3backing layer. Significantly, compared with the bandwidth of the air-backing sensor (37–183[Formula: see text]kHz), the sensor with porous Al2O3backing layer broadens bandwidth to 28–273[Formula: see text]kHz. These results show that both these AE sensors have strong and stable response ability to AE signals at high-temperature of 500∘C. Therefore, piezoelectric AE sensor based on LGS has great potential application in the field of high-temperature structural health monitoring.
BreatheBand: A Fine-grained and Robust Respiration Monitor System Using WiFi Signals
Authors: Guo Zhengxin , Yuan Wenyang , Gui Linqing , Sheng Biyun , Xiao Fu
Published: February 2023

Respiration is a vital indicator of the state of the human body. Monitoring human respiration enables the realization of a variety of intelligent applications, including smart medical and sleep monitoring. Traditional methods that are dependent upon wearable devices are more costly and inconvenient for users. Recent studies have evidenced that low-cost commodity WiFi devices can be used to accomplish contactless respiration monitoring. In this article, we present BreatheBand, a fine-grained and robust respiration monitoring system based on commercial WiFi signals. We first remove the time-varying phase shift in the channel state information (CSI) by developing the Multi-antenna CSI–Subpopulation Genetic algorithm. Then we separate human respiratory components from WiFi signals by employing subcarrier selection and Independent Component Analysis. Next, applying a Mixed Cluster Gaussian–Hidden Markov Model, we generate a respiration signal resembling that of wearable devices. Finally, we integrate the BreatheBand system into commercial WiFi infrastructure. The results show that the BreatheBand’s respiration signal is remarkably identical to the signal collected by the wearable device in various scenarios. In particular, the mean absolute error of the BreatheBand’s respiration rate is approximately 0.1 bpm, outperforming state-of-the-art algorithms.
Effect of Biased Field Rings to Improve Charge Removal after Heavy-Ion Strikes in Vertical Geometry β-Ga2O3 Rectifiers
Authors: Sharma Ribhu , Li Jian-Sian , Law Mark E. , Ren Fan , Pearton S. J.
Published: February 2023

In this study, the response to a heavy-ion strike and the resulting single effect burnout on beta-Ga2O3 Schottky diodes with biased field rings is investigated via TCAD. The model used to simulate the device under high-reverse bias is validated using experimental current-voltage (I-V) curves. A field ring configuration for the device demonstrates an improved charge removal after simulated heavy-ion strikes. If the time scale for charge removal is faster than single event burnout, this can be an effective mechanism for reducing the effect of single ion strikes. This study explores various configurations of the termination structure and shows the impact of different design parameters in terms of a transient response after the ion strike.
Photo-Oxidation of Organic Dye by Fe2O3 Nanoparticles: Catalyst, Electron Acceptor, and Polyurethane Membrane (PU-Fe2O3) Effects
Authors: Yaou Balarabe Bachir , Illiassou Oumarou Maman Nasser , Koroney Abdoul Salam , Adjama Irédon , Ibrahim Baraze Abdoul Razak
Published: February 2023

The textile industry’s discharges have long been regarded as severe water pollution. The photocatalytic degradation of dyes using semiconductors is one of the crucial methods. The present study efficiently used the mechanical method to synthesize Iron oxide Nanoparticles. XRD, FT-IR, UV-Vis DRS, and Raman analyses were performed to analyze the structural and optical. From the data provided by XRD and Raman data, we believed that the as-synthesized Iron oxide was pure hematite (α-Fe2O3) with a hexagonal structure. Additionally, the EDS results show that the synthesized material is pure. By adjusting specific parameters, including the dye concentration, the catalyst dosage, the pH, and the oxidizing agent such as H2O2 and K2S2O8, the degradation of eosin yellowish using Fe2O3 as a photocatalyst has been discussed. Additionally, the kinetics of eosin yellowish degradation has been studied. A study was also conducted using Fe2O3 nanoparticles attached to polyurethane polymer (PU) to investigate its photocatalytic activity on methylene blue, methyl orange, and indigo carmine. In 30 minutes, nearly 90% of the dyes had degraded. The total organic carbon (TOC) analysis confirmed this result.
Mitophagy and Traumatic Brain Injury: Regulatory Mechanisms and Therapeutic Potentials
Authors: Luan Yi , Jiang Lulu , Luan Ying , Xie Yi , Yang Yang , Ren Kai-Di
Published: February 2023

Traumatic brain injury (TBI), a kind of external trauma-induced brain function alteration, has posed a financial burden on the public health system. TBI pathogenesis involves a complicated set of events, including primary and secondary injuries that can cause mitochondrial damage. Mitophagy, a process in which defective mitochondria are specifically degraded, segregates and degrades defective mitochondria allowing a healthier mitochondrial network. Mitophagy ensures that mitochondria remain healthy during TBI, determining whether neurons live or die. Mitophagy acts as a critical regulator in maintaining neuronal survival and healthy. This review will discuss the TBI pathophysiology and the consequences of the damage it causes to mitochondria. This review article will explore the mitophagy process, its key factors, and pathways and reveal the role of mitophagy in TBI. Mitophagy will be further recognized as a therapeutic approach in TBI. This review will offer new insights into mitophagy’s role in TBI progression.
Optimal Preference Satisfaction for Conflict-Free Joint Decisions
Authors: Shinkawa Hiroaki , Chauvet Nicolas , Bachelier Guillaume , Röhm André , Horisaki Ryoichi , Naruse Makoto
Published: February 2023

When presented with multiple choices, we all have a preference; we may suffer loss because of conflicts arising from identical selections made by other people if we insist on satisfying only our preferences. Such a scenario is applicable when a choice cannot be divided into multiple pieces owing to the intrinsic nature of the resource. Earlier studies examined how to conduct fair joint decision-making while avoiding decision conflicts in terms of game theory when multiple players have their own deterministic preference profiles. However, probabilistic preferences appear naturally in relation to the stochastic decision-making of humans, and therefore, we theoretically derive conflict-free joint decision-making that satisfies the probabilistic preferences of all individual players. To this end, we mathematically prove conditions wherein the deviation of the resultant chance of obtaining each choice from the individual preference profile (loss) becomes zero; i.e., the satisfaction of all players is appreciated while avoiding conflicts. Further, even in scenarios where zero-loss conflict-free joint decision-making is unachievable, we present approaches to derive joint decision-making that can accomplish the theoretical minimum loss while ensuring conflict-free choices. Numerical demonstrations are presented with several benchmarks.
The Optimization of Multimode Fiber Speckle Sensor for Microvibration
Authors: Song Haoyang , Sun Feiyu , Sun Yunxu , Liu Wei
Published: February 2023

A vibration sensing system with optical fiber speckles is demonstrated and optimized with different optical fiber diameters and speckle statistical algorithms. The types of fiber diameter and material lead to a different performance of fiber specklegram sensor (FSS), which has been experimentally explored. The signal intensity, demodulated from the speckles, is different when using multimode fibers with different diameters. At the same time, the sensing effect of different fibers depends on the speckle statistical algorithms. Accordingly, we use different statistical methods in theory and experiment to analyze the influence of fiber diameter and speckle statistical methods on the sensing performance. A vibration sensing system with optimized performance is achieved by the optimized types of optical fiber and the corresponding optimized algorithms, which are promising for sensing weak vibration, such as detecting.
An Image Classification Method Based on Adaptive Attention Mechanism and Feature Extraction Network
Authors: Luo Juanjuan , Hu Defa
Published: February 2023

The convolution neural network (CNN) not only has high fault tolerance but also has high computing capacity. The image classification performance of CNN has an important relationship with its network depth. The network depth is deeper, and the fitting ability of CNN is stronger. However, a further increase in the depth of CNN will not improve the accuracy of the network but will produce higher training errors, which will reduce the image classification performance of CNN. In order to solve the above problems, this paper proposes a feature extraction network, AA‐ResNet with an adaptive attention mechanism. The residual module of the adaptive attention mechanism is embedded for image classification. It consists of a feature extraction network guided by the pattern, a generator trained in advance, and a complementary network. The feature extraction network guided by the pattern is used to extract different levels of features to describe different aspects of an image. The design of the model effectively uses the image information of the whole level and the local level, and the feature representation ability is enhanced. The whole model is trained as a loss function, which is about a multitask problem and has a specially designed classification, which helps to reduce overfitting and make the model focus on easily confused categories. The experimental results show that the method in this paper performs well in image classification for the relatively simple Cifar‐10 dataset, the moderately difficult Caltech‐101 dataset, and the Caltech‐256 dataset with large differences in object size and location. The fitting speed and accuracy are high.
Adaptive Control Algorithm for Trajectory Tracking of Underactuated Unmanned Surface Vehicle (UUSV)
Authors: Karnani Chandanlal , Raza Syed Akhter , Asif Muhammad , Ilyas Muhammad
Published: February 2023

The ability to track the trajectory or path on the sea surface remains a key measurement in the control system of an unmanned surface vehicle (USV). In this research, the designed algorithm defines the path and minimizes the disturbances to zero. Underactuated USVs are ships or boats, which operate on the water surface without a crew and the underactuated system has low actuators than its degree of freedom (DOF). The adaptive control strategy is applied to the unbounded system as the ocean due to its high performance, while the robust control system attains high performance in the bounded system. To consider the trajectory tracking of UUSV and provide an optimal control strategy for a ship in the presence of external disturbances, the study presents a controller-based on model reference adaptive control with an integrator (MRACI), which guarantees the stability of a closed-loop system. The vehicle experiences variations in the system response due to external disturbance. This abovementioned scheme reduces the variations to nearly equal to zero making the vehicle stable. First, use computer-based simulation to verify the proposed controller under two different scenarios. Then, simulation results show that the designed scheme lowers the errors and performs well.
Effects of Teachers’ Written Corrective Feedback on the Writing Achievement of First-Year Ethiopian University Students
Authors: Wondim Baymot Mekuriaw , Bishaw Kassie Shifere , Zeleke Yinager Teklesellassie
Published: February 2023

An increasing number of studies have confirmed that written corrective feedback (hereafter WCF) is vital for improving learners’ L2 writing. However, many scholars could not agree whether this improvement was due to direct, indirect, or both forms of WCF. Thus, this study first investigated the role of WCF students’ writing achievement; it then investigated if there was a statistically significant difference in writing achievement between groups that received direct and indirect WCF forms. To this end, a quasi-experimental research design involving three intact first-year classes from a university found in northwest Ethiopia was used. Two experimental groups and one comparison group of learners were participants in this study. Test scores analyzed by analysis of covariance (ANCOVA) revealed that WCF has an influential role in enhancing learners’ writing performance. Moreover, this study showed that learners in the direct WCF accompanied by a metalinguistic explanation group outperformed their counterparts in the indirect WCF group in writing paragraphs. Based on the study’s findings, it is possible to conclude that the provision of WCF is vital in the Ethiopian context; moreover, learners could benefit more from using linguistic structures correctly if metalinguistic explanations accompany the provision of direct WCF.
Slow Heat‐Based Hybrid Simulated Annealing Algorithm in Vehicular Ad Hoc Network
Authors: Pagadala Pavan Kumar , Kumari P. Lalitha Surya , Thakur Deepak , Bhardwaj Vivek , Shahid Mohammad , Buradi Abdulrajak , Razak Abdul , Ketema Abiot
Published: February 2023

Vehicular ad hoc networks (VANETs) using reliable protocols of routing have become crucial in identifying the changes to topology on a continuous basis for a large collection of vehicles. For this purpose, it becomes important to identify an optimal configuration of these protocols. There are several possible configurations that have been preventing the configuration of efficient protocols that do not make use of automatic and intelligent design tools. It can further motivate using the techniques of metaheuristics like the tools, which are well‐suited to be able to solve these problems. The glowworm swarm optimization (GSO), simulated annealing (SA), and slow heat‐based SA‐GSO algorithms have been proposed in this work. The SA is a method of optimization, which imitates the manner in which the thermal system has been frozen down to its lowest state of energy. In the GSO, there is guidance to the rules of feasibility, where the swarm converges to its feasible regions very fast. Additionally, for overcoming any premature convergence, there is a local search strategy that is based on the SA and is used for making a search that is near to its true optimum solutions. Finally, this sluggish temperature‐based SA‐GSO algorithm will be employed to solve routing problems and problems of heat transfer. There is a hybrid slow heat SA‐GSO algorithm with a faster speed of convergence and higher precision of computation that is more effective in solving problems of constrained engineering.
The paleoenvironment of southeastern São Paulo: contributions from Itapeva shelter to a discussion on anthropic and natural insertion
Authors: Souza Tatiane de , Chueng Karina , Rizzi Carlos Alberto
Published: February 2023

Paleoclimate reconstitution for the state of São Paulo results from past and ongoing research efforts in palynology, anthracology, and stable isotope studies. In cases such as southern São Paulo, however, researchers are required to extrapolate data from the states of Paraná, Santa Catarina, and Rio Grande do Sul for comparisons. Phytoliths and seeds were collected from sediments retrieved from excavation units D18 and G6 at the Abrigo de Itapeva [Itapeva Shelter] archeological site and analyzed. Seed results indicate that Ocotea (Lauraceae) is present in the initial levels, whereas Syagrus romanzoffiana predominates at all other stratigraphic levels. The former is a species of Atlantic Forest that occurs in Araucaria Forests; the latter is a palm species found in southeastern and southern Brazil. Phytoliths analysis reveals a change from a drier climate with grassland vegetation to a woody forest in the later periods of shelter occupation. As such, grassland and forest vegetation types occur from base stratigraphic levels up to level seven, dating from 5,510 cal BP to 730 cal BP. Conversely, from level seven up to the surface levels, dated from 730 cal BP to 560 cal BP, we see species linked to Araucaria Forest proliferation which may indicate the presence of Jê groups in the study area, thus corroborating studies on the possible anthropization of São Paulo forests from 1,000 BP.
Systemic Hypoxemia Induces Cardiomyocyte Hypertrophy and Right Ventricular Specific Induction of Proliferation
Authors: Johnson Jaslyn , Yang Yijun , Bian Zilin , Schena Giana , Li Yijia , Zhang Xiaoying , Eaton Deborah M. , Gross Polina , Angheloiu Alexandra , Shaik Arshadullah , Foster Michael , Berretta Remus , Kubo Hajime , Mohsin Sadia , Tian Ying , Houser Steven R.
Published: February 2023

Background:

A recent study suggests that systemic hypoxemia in adult male mice can induce cardiac myocytes to proliferate. The goal of the present experiments was to confirm these results, provide new insights on the mechanisms that induce adult cardiomyocyte cell cycle reentry, and to determine if hypoxemia also induces cardiomyocyte proliferation in female mice.

Methods:

EdU-containing mini pumps were implanted in 3-month-old, male and female C57BL/6 mice. Mice were placed in a hypoxia chamber, and the oxygen was lowered by 1% every day for 14 days to reach 7% oxygen. The animals remained in 7% oxygen for 2 weeks before terminal studies. Myocyte proliferation was also studied with a mosaic analysis with double markers mouse model.

Results:

Hypoxia induced cardiac hypertrophy in both left ventricular (LV) and right ventricular (RV) myocytes, with LV myocytes lengthening and RV myocytes widening and lengthening. Hypoxia induced an increase (0.01±0.01% in normoxia to 0.11±0.09% in hypoxia) in the number of EdU+ RV cardiomyocytes, with no effect on LV myocytes in male C57BL/6 mice. Similar results were observed in female mice. Furthermore, in mosaic analysis with double markers mice, hypoxia induced a significant increase in RV myocyte proliferation (0.03±0.03% in normoxia to 0.32±0.15% in hypoxia of RFP+ myocytes), with no significant change in LV myocyte proliferation. RNA sequencing showed upregulation of mitotic cell cycle genes and a downregulation of Cullin genes, which promote the G1 to S phase transition in hypoxic mice. There was significant proliferation of nonmyocytes and mild cardiac fibrosis in hypoxic mice that did not disrupt cardiac function. Male and female mice exhibited similar gene expression following hypoxia.

Conclusions:

Systemic hypoxia induces a global hypertrophic stress response that was associated with increased RV proliferation, and while LV myocytes did not show increased proliferation, our results minimally confirm previous reports that hypoxia can induce cardiomyocyte cell cycle activity in vivo.
Underlying Microphysical Processes in the Melting Layer during Moderate Precipitation: Evidence from Ground-Based Data
Authors: Fujiyoshi Yasushi
Published: February 2023

We performed a detailed analysis of ground-based data to investigate changes in the morphological properties and particle size distribution of precipitation particles as they fall through the melting layer (ML). In July 2013, we started continuous precipitation monitoring in Sapporo (Japan) with a two-dimensional video disdrometer, an electrical balance–type snow gauge, and an X-band marine radar. We used data collected from 0943 to 1040 Japan standard time (JST) 10 March 2015 for analysis, when the bright band progressively descended to the ground surface and precipitation intensity was moderate and approximately steady (∼10 mm h−1). We found that the aggregation of aggregates in the upper half of the ML did not necessarily result in large raindrops. Almost all of the snow particles with a melted diameter (Dm) ≥ 4 mm broke up before they melted into raindrops of equivalent size. The apparent one-to-one relationship between melting snow particles and raindrops held for particles with 2 < Dm < 3 mm. Most small raindrops were generated by the successive breakup of melting particles in the lower half of the ML.
The Effect of BMI on eFAST Accuracy in Trauma by Residents in the Emergency Room
Authors: Armstrong Landon R. , Rutherford Noah R. , Heidel Robert E. , Smith Lou M. , Butts Christine
Published: February 2023

Blunt trauma patients are often evaluated with extended focused assessment with sonography for trauma (eFAST). eFAST is a noninvasive, rapid, ultrasound-guided assessment for hemoperitoneum, pericardial effusion, and hemopneumothorax. Specificity and sensitivity are as high as 95% and 74%, respectively. Research suggests obesity confers increased morbidity and mortality and is an independent risk factor for trauma death. A previous study demonstrated that a BMI change from 36 to 40 changed the odds ratio for inaccurate eFAST from 1.85 to 3.12. Our current prospective data collection is 202 consecutive blunt trauma patients from 5/13/22 to 8/18/22 receiving an eFAST and a CT/OR for comparison. Odds ratio of inaccurate eFAST increased by 5.65% for each increase of 1 kg/m3 of BMI (95% Cl 0.1%-10.8%). This research also investigated surgical resident eFAST accuracy to improve patient outcomes through the implementation of individualized training in normal and obese models.
Study of the Impact of Air Pollution on Convulsions in Children: A Hospital-Based Retrospective Study in Hangzhou, China
Authors: Yang Lin , Sun LiXia , Chu Wei , Zhu YaFei , Wu GuangSheng
Published: February 2023

Background:

To investigate the relationship between the occurrence of convulsions in children and air pollution in Hangzhou.

Methods:

From January 1, 2018, to December 31, 2020, 775 children admitted with convulsion to the pediatric outpatient clinic of The Affiliated Hospital of Hangzhou Normal University (Hangzhou, China) were enrolled in this study. The clinical data and the corresponding weather data of the day in Hangzhou were collected and analyzed. Also, the monthly etiological classification of convulsions and the monthly average air data of Hangzhou were statistically analyzed.

Results:

The highest incidence of convulsion was observed in children 1 to 2 years old, and higher in boys than in girls. The top three main causes were febrile seizure, benign infantile convulsion with mild gastroenteritis, and epilepsy. Among the meteorological factors, the increase in the level of 2.5 micron particulate matter (PM 2.5) in the air per month led to an increase in the number of patients with febrile seizure, benign infantile convulsion with mild gastroenteritis, and epilepsy, where the increase of ozone in 8 hours (O3-8h) per month led to a decrease in the number of patients with such conditions.

Conclusions:

PM2.5, PM10, and SO2 are the main meteorological factors affecting the occurrence of convulsions in children in Hangzhou, and PM2.5 and SO2 are risk factors. The increase in the level of PM2.5 in the air per month could increase occurrence of child convulsions, but the increase of O3-8h per month could decrease occurrence of child convulsions.
Screening and Counseling Practices for Parental Combustible Versus Electronic Cigarette Use in Pediatric Primary Care: A Pilot Study
Authors: Heinly Allison , Baird Janette , Riese Alison
Published: February 2023

Objective:

Tobacco exposure plays an important role in children’s health. Little is known about pediatrician’s experience with parental e-cigarette use. This pilot study aimed to assess pediatrician’s knowledge, attitude, and behaviors regarding parental e-cigarette use.

Methods:

This cross-sectional survey at an academic clinic assessed residents’ and attendings’ knowledge, attitudes, and behaviors regarding parental combustible and e-cigarette use and counseling and cessation barriers.

Results:

Sixty of 69 care providers completed the survey. Participants reported asking about parental use (5% vs 58%, Δ = 53% [95% CI Δ = 40%-67%]), advising about harms (5% vs 52%, Δ = 47% [95% CI Δ = 33%-61%]), and assisting with quitting (2% vs 28%, Δ = 27% [95% CI Δ = 15%-39%]) significantly less for e-cigarettes than for combustible cigarettes. The most common barrier to discussing use was lack of time. Lack of knowledge, unsure of harm, and lack of training were reported significantly more for e-cigarettes than for combustible cigarettes.

Conclusion:

Parental screening and counseling rates are significantly lower for e-cigarettes than for combustible cigarettes in this pilot study. Increased training could help pediatricians better protect children from tobacco exposure.
Determinants of Learning Outcome in the Nigerian Primary Schools
Authors: Oluwatayo Isaac B. , Ojo Ayodeji O. , Isah Salamatu I. , Odeleye Anthonia T.
Published: February 2023

Despite huge investments in the educational sector, many countries in Africa have not fared well in the education indices. This study examined the effect of teaching equipment and teachers’ effort on learning outcomes in 744 Nigerian primary schools using Stochastic Frontier and Ordinary Least Square regression. The mean technical efficiency was 0.43 which showed most of the surveyed schools were technically inefficient. Also, 42.8% of public primary schools operate below 20% efficiency level as against 12.3% in private primary schools. Factors influencing efficiency include school ownership type, visits from the Local Government Education Authority Student-Teacher ratio, and school hygiene.
Retiring in a Prison Cell: The South African Sentenced Older Adult Male Offender
Authors: Booyens Karen , Geyer Stephan , Masenge Andries
Published: February 2023

The purpose of this study was to create a profile of the sentenced older adult male offender incarcerated in South African prisons. The findings of this investigation are based on face-to-face surveys with 88 older adult male inmates. In order to develop a comprehensive profile, the study explored offenders’ backgrounds, previous and current offenses, lifestyle patterns, physical and mental health, institutional living conditions, release, reintegration, and mortality in prison. These domains are discussed in detail, and recommendations are offered for the treatment and care of this offender group. The recommendations may be applicable to other developing countries in the Global South.
The Familiar and the Self: Reflections from Teaching Sociology Online in India
Authors: Patgiri Rituparna
Published: February 2023

Interrogating the familiar is seen as a benchmark of good sociological research. As teachers of Sociology, we have to teach courses that question and critique the familiar regularly. It is a mammoth task. The enormity of the job is further increased by the fact that the teacher is part of the same social institutions as the students. As such, how does a teacher deal with their own assumptions while teaching? How does one teach young students to question and challenge the familiar that all of us are a part of? How does one teach the self which is a part of the familiar? I try to address some of these questions in this piece drawing from my own teaching experience. It has been my experience that the challenges of teaching the familiar and the self are augmented by the online mode. With the boundaries between the home and the university getting blurred in the online mode, the difficulties in defamiliarizing are even stronger. This challenges the core itself of Sociology. Apart from limiting the interaction between students and the teacher, there is also less scope for peer-based learning in the online classroom. Thus, there is a need to re-think the nature of the online classroom and the teacher that can help Sociology in continuing to question the familiar.
PRESIDENT CLINTON'S INTERVENTION INTO BOSNIA, 1995
Authors: Szandzik Eric James
Published: February 2023

This article analyzes Clinton's decision to intervene in Bosnia in 1995. The methodology used is a historical analysis of primary and secondary source material and an interpretation of that material. The available evidence shows that after not intervening in Rwanda, Clinton evolved toward a more assertive foreign policy. Clinton eventually fought against pressures to employ a containment strategy in Bosnia, pushed to lift the arms embargo on the Bosnian Muslims, and strike at the Bosnian Serbs. After multiple failed attempts at diplomacy to accomplish these goals, Clinton managed to achieve his objectives through indirect methods. He set the stage for a major military offensive against Bosnian Serb forces before the massacre at Srebrenica, which is an important correction to the traditional narrative on the topic. Clinton then initiated a massive U.S.-led bombing campaign, achieved military objectives, negotiated a peace agreement, and deployed U.S. troops to enforce the peace agreement.
The Jury After Abolition
Authors: Chakravarti Sonali
Published: February 2023

This essay is part of a special issue celebrating 50 years of Political Theory. The ambition of the editors was to mark this half century not with a retrospective but with a confabulation of futures. Contributors were asked: What will political theory look and sound like in the next century and beyond? What claims might political theorists or their descendants be making in ten, twenty-five, fifty, a hundred years’ time? How might they vindicate those claims in their future contexts? How will the consistent concerns of political theorists evolve into the questions critical for people decades or centuries from now? What new problems will engage the political theorists (or their rough equivalents) of the future? What forms might those take? What follows is one of the many confabulations published in response to these queries.
The Nation-State 1648–2148
Authors: El Amine Loubna
Published: February 2023

This essay is part of a special issue celebrating 50 years of Political Theory. The ambition of the editors was to mark this half century not with a retrospective but with a confabulation of futures. Contributors were asked: What will political theory look and sound like in the next century and beyond? What claims might political theorists or their descendants be making in ten, twenty-five, fifty, a hundred years’ time? How might they vindicate those claims in their future contexts? How will the consistent concerns of political theorists evolve into the questions critical for people decades or centuries from now? What new problems will engage the political theorists (or their rough equivalents) of the future? What forms might those take? What follows is one of the many confabulations published in response to these queries.
Our Declaration
Authors: Hayward Clarissa , Dovi Suzanne
Published: February 2023

This essay is part of a special issue celebrating 50 years of Political Theory. The ambition of the editors was to mark this half century not with a retrospective but with a confabulation of futures. Contributors were asked: What will political theory look and sound like in the next century and beyond? What claims might political theorists or their descendants be making in ten, twenty-five, fifty, a hundred years’ time? How might they vindicate those claims in their future contexts? How will the consistent concerns of political theorists evolve into the questions critical for people decades or centuries from now? What new problems will engage the political theorists (or their rough equivalents) of the future? What forms might those take? What follows is one of the many confabulations published in response to these queries.
Whistling Past the Graveyard
Authors: Loggins Jared
Published: February 2023

This essay is part of a special issue celebrating 50 years of Political Theory. The ambition of the editors was to mark this half century not with a retrospective but with a confabulation of futures. Contributors were asked: What will political theory look and sound like in the next century and beyond? What claims might political theorists or their descendants be making in ten, twenty-five, fifty, a hundred years’ time? How might they vindicate those claims in their future contexts? How will the consistent concerns of political theorists evolve into the questions critical for people decades or centuries from now? What new problems will engage the political theorists (or their rough equivalents) of the future? What forms might those take? What follows is one of the many confabulations published in response to these queries.