bluuebunny/crossref_metadata_2025 huggingface dataset:
Unequal exposure to heatwaves in Los Angeles: Impact of uneven green spaces
Authors: Yin Yi , He Liyin , Wennberg Paul O. , Frankenberg Christian
Published: April 2023

Cities worldwide are experiencing record-breaking summer temperatures. Urban environments exacerbate extreme heat, resulting in not only the urban heat island but also intracity variations in heat exposure. Understanding these disparities is crucial to support equitable climate mitigation and adaptation efforts. We found persistent negative correlations between daytime land surface temperature (LST) and median household income across the Los Angeles metropolitan area based on Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station observations from 2018 to 2021. Lower evapotranspiration resulting from the unequal distribution of vegetation cover is a major factor leading to higher LST in low-income neighborhoods. Disparities worsen with higher regional mean surface temperature, with a $10,000 decrease in income leading to ~0.2°C LST increase at 20°C and up to ~0.7°C at 45°C. With more frequent and intense heat waves projected in the future, equitable mitigation measures, such as increasing surface albedo and tree cover in low-income neighborhoods, are necessary to address these disparities.
Hydrocephalus: a rare complication of primary central nervous system vasculitis
Authors: Lopes Joana , Doria Hugo , Taipa Ricardo , Samões Raquel Fonseca
Published: April 2023

Hydrocephalus is a known complication of central nervous system (CNS) vasculitis secondary to infectious diseases. We present an unusual case of primary CNS vasculitis (PCNSV) complicated by communicating hydrocephalus. A patient in their 50s with a few months’ history of headache, psychomotor slowing and frequent falls presented with an acute left temporo-parieto-occipital infarction. Angiography revealed multiple arterial irregularities in the anterior circulation bilaterally, CSF was inflammatory and the remaining study was negative, fulfilling criteria for possible PCNSV. One month after successful treatment with corticosteroid, there was worsening of gait, urinary incontinence and neuropsychiatric symptoms. The investigation was remarkable only for active hydrocephalus. An external ventricular shunt was placed, followed by a ventriculoperitoneal shunt, and cyclophosphamide was started with subsequent recovery. Our discussion is that communicating hydrocephalus in PCNSV, due to impaired CSF flow, should be considered on subacute/chronic worsening of patients with PCNSV.
PivNG primers and probes set used in the cobas omni Utility Channel is a reliable supplemental test for detection ofNeisseria gonorrhoeaein oropharyngeal, urogenital and rectal specimens collected in cobas PCR Media
Authors: Hopkins Mark , Arcenas Rodney , Couto-Parada Xose , Lewinski Michael , Njoya Merlin , Perinpanathan Deva , Sheriff Rizwaan , Hansra Avneet , Singh Selena
Published: April 2023

Objective

To evaluate the clinical performance of the novel PivNG primers and probes set (PivNG test) used in the cobas omni Utility Channel for supplemental testing ofNeisseria gonorrhoeae(NG).

Methods

Oropharyngeal, urogenital and rectal samples were self-collected during routine testing at Barts Health sexual health clinics, London, UK. Samples were tested by the cobas CT/NG test and PivNG cobas omni Utility Channel test on cobas 6800/8800 Systems. Supplemental testing was carried out with the Xpert CT/NG test. PivNG overall percent agreements, positive percent agreements (PPAs)/negative percent agreements (NPAs) and positive/negative predictive values were calculated for each sample type. Microscopy and/or culture data were included for a randomised subset of concordant/discordant results, and a composite reference standard (cobas CT/NG, Xpert CT/NG and culture results) adjusted for partial verification bias was used to determine PivNG PPA and NPA.

Results

Of 447 evaluable samples with valid results from all three assays (cobas CT/NG, PivNG and Xpert CT/NG), 288 (64.4%) were NG-positive by both PivNG and cobas CT/NG; 117 (26.2%) were NG-negative in both tests; and 42 (9.4%) had discordant results (with NG-negative supplementary Xpert) CT/NG results in 40/42 instances). Of 19 PivNG/Xpert CT/NG-discordant samples, 11 were confirmed NG-positive by microscopy and/or culture results. PivNG PPA and NPA were 100% and 91% for oropharyngeal swabs, 100% and 100% for vaginal swabs, 100% and 100% for male urine samples, and 100% and 97% for rectal swabs, respectively, compared with the partially adjusted composite reference standard.

Conclusions

PivNG is a reliable supplementary test with high sensitivity for confirming NG infection when used in conjunction with the cobas CT/NG test and samples collected in cobas PCR Media. Moreover, the PivNG test offers a convenient, high-throughput solution for supplemental NG testing of various sample types, with the potential to reduce the number of indeterminate reports.
Charged fluids in higher order gravity
Authors: Naicker Shavani , Maharaj Sunil D. , Brassel Byron P.
Published: April 2023

We generate the field equations for a charged gravitating perfect fluid in Einstein–Gauss–Bonnet gravity for all spacetime dimensions. The spacetime is static and spherically symmetric which gives rise to the charged condition of pressure isotropy that is an Abel differential equation of the second kind. We show that this equation can be reduced to a canonical differential equation that is first order and nonlinear in nature, in higher dimensions. The canonical form admits an exact solution generating algorithm, yielding implicit solutions in general, by choosing one of the potentials and the electromagnetic field. An exact solution to the canonical equation is found that reduces to the neutral model found earlier. In addition, three new classes of solutions arise without specifying the gravitational potentials and the electromagnetic field; instead constraints are placed on the canonical differential equation. This is due to the fact that the presence of the electromagnetic field allows for a greater degree of freedom, and there is no correspondence with neutral matter. Other classes of exact solutions are presented in terms of elementary and special functions (the Heun confluent functions) when the canonical form cannot be applied.
Bifurcation Structures of the Homographic γ-Ricker Maps and Their Cusp Points Organization
Authors: Rocha J. Leonel , Taha Abdel-Kaddous
Published: April 2023

This paper aims to study the bifurcation structures of the homographic [Formula: see text]-Ricker maps in a four-dimensional parameter space. The generalized Lambert [Formula: see text] functions are used to establish upper bounds for the number of fixed points of these population growth models. The variation of the number of fixed points and the cusp points organization is stipulated. This study also observes a vital characteristic on the Allee effect phenomenon in a class of bimodal Allee’s maps. Some numerical studies are included to illustrate the Allee effect and big bang local bifurcations.
Oscillating Behavior of a Compartmental Model with Retarded Noisy Dynamic Infection Rate
Authors: Bestehorn Michael , Michelitsch Thomas M.
Published: April 2023

Our study is based on an epidemiological compartmental model, the SIRS model. In the SIRS model, each individual is in one of the states susceptible (S), infected (I) or recovered (R), depending on its state of health. In compartment R, an individual is assumed to stay immune within a finite time interval only and then transfers back to the S compartment. We extend the model and allow for a feedback control of the infection rate by mitigation measures which are related to the number of infections. A finite response time of the feedback mechanism is supposed that changes the low-dimensional SIRS model into an infinite-dimensional set of integro-differential (delay-differential) equations. It turns out that the retarded feedback renders the originally stable endemic equilibrium of SIRS (stable focus) to an unstable focus if the delay exceeds a certain critical value. Nonlinear solutions show persistent regular oscillations of the number of infected and susceptible individuals. In the last part we include noise effects from the environment and allow for a fluctuating infection rate. This results in multiplicative noise terms and our model turns into a set of stochastic nonlinear integro-differential equations. Numerical solutions reveal an irregular behavior of repeated disease outbreaks in the form of infection waves with a variety of frequencies and amplitudes.
Computing Invariant Densities of a Class of Piecewise Increasing Mappings
Authors: Wang Zi , Ding Jiu , Rhee Noah
Published: April 2023

Let [Formula: see text] be a piecewise increasing mapping satisfying some generalized convexity condition, so that it possesses an invariant density that is a decreasing function. We show that this invariant density can be computed by a family of Markov finite approximations that preserve the monotonicity of integrable functions. We also construct a quadratic spline Markov method and demonstrate its merits numerically.
Turing Bifurcation Induced by Cross-Diffusion and Amplitude Equation in Oncolytic Therapeutic Model: Viruses as Anti-Tumor Means
Authors: Najm Fatiha , Yafia Radouane , Aziz Alaoui M. A.
Published: April 2023

In this paper, we propose a reaction–diffusion mathematical model augmented with self/cross-diffusion in 2D domain which describes the oncolytic virotherapy treatment of a tumor with its growth following the logistic law. The tumor cells are divided into uninfected and infected cells and the virus transmission is supposed to be in a direct mode (from cell to cell). In the absence of cross-diffusion, we establish well posedness of the problem, non-negativity and boundedness of solutions, nonexistence of positive solutions, local and global stability of the nontrivial steady-state and the nonoccurrence of Turing instability. In the presence of cross-diffusion, we prove the occurrence of Turing instability by using the cross-diffusion coefficient of infected cells as a parameter. To have an idea about different patterns, we derive the corresponding amplitude equation by using the nonlinear analysis theory. In the end, we perform some numerical simulations to illustrate the obtained theoretical results.
Wisdom and Veterans: Enhancing the Workforce with Self-Insight, Experience, and Sound Judgement
Authors: Eaves T. , Allen J. , Rosellini A. , Bank N.
Published: April 2023

Military veterans bring many unique and desirable traits to the workforce, including self-insight, experience, and sound judgment. Through their service in the American military branches, veterans have experience in heightened leadership roles in high stress and high stakes environments that shape their personalities, leadership skills, and behaviours. Because of this experience, veterans often demonstrate wisdom as they apply self-awareness and judgment through different ranks and roles in their service to the country. Hiring these experienced and seasoned workers to the benefit of businesses can be part of the solution in addressing the current labour shortage. Research is warranted in seeking to understand why veterans experience difficulties in their transition from the military into their business careers in higher numbers compared to the general population. The misinformation and misconceptions about hiring veterans are depriving businesses of a talented and unique population that can bring more wisdom to their workforce.
A Generative Model for the Mycenaean Linear B Script and Its Application in Infilling Text from Ancient Tablets
Authors: Papavassileiou Katerina , Kosmopoulos Dimitrios I. , Owens Gareth
Published: April 2023

We present a generative neural language model for the most ancient proven stage of the Greek language, the Mycenaean Greek attributed by the Linear B script. To capture the statistical structure of the Mycenaean documents, we present a Bidirectional Recurrent Neural Network and compare it to the traditionally used
n
-grams. The model is used to supplement the damaged parts of the Mycenaean texts, namely the incomplete, to a greater or lesser extent, words, which are typically discovered on partially damaged clay tablets. We verify our method experimentally using ground-truth, then we demonstrate our results on real cases and compare with experts’ opinions. We also present a methodology to augment our dataset, which turns out to improve our results.
The Security in Optical Wireless Communication: A Survey
Authors: Zhang Xiao , Klevering Griffin , Lei Xinyu , Hu Yiwen , Xiao Li , Tu Guan-Hua
Published: April 2023

With the demand for economical and high-speed wireless services, Optical Wireless Communication (OWC) has attracted increasing attention in both research and the market. In the past decades, numerous optical-related techniques (e.g., LEDs, displays, cameras) and systems (e.g., VLC, LiFi, LiDAR) have been invented. OWC techniques, which are considered as a competitive mechanics in next-generation networks as an alternative to RF approaches, offer 10,000 times more bandwidth than conventional radio frequency (RF)-based wireless techniques (e.g., WiFi, LoRa, Bluetooth, LTE), as well as tremendous spatial reuse potential with even less interference. Because optical communications have a limited wavelength and travel in the line of sight (LoS) manner, the OWC is commonly thought as a secure wireless approach to confine light transmissions within physical bounds. However, in the real world, it is completely untrue. The privacy leakages and security risks broadly exist in the optical-related wireless applications including OWC networks. These threats and weaknesses have recently been the subject of several initial studies. However, they lack systematic analysis and are isolated. This survey first presents a general workflow of OWC systems, which consists of three stages: before signal emission (BSE), during signal propagation (DSP), and after signal receiving (ASV). For each stage, related risks are reviewed. Then, we summarize existing attacks in optical-related wireless applications and corresponding counter-attack solutions. Finally, we outline the future trends for improving OWC security.
Positioning Paradata: A Conceptual Frame for AI Processual Documentation in Archives and Recordkeeping Contexts
Authors: Cameron Scott , Franks Pat , Hamidzadeh Babak
Published: April 2023

The emergence of sophisticated Artificial Intelligence (AI) and machine learning tools poses a challenge to archives and records professionals, who are accustomed to understanding and documenting the activities of human agents rather than the often-opaque processes of sophisticated AI functioning. Preliminary work has proposed the term
paradata
to describe the unique documentation needs that emerge for archivists using AI tools to process records in their collections. For the purposes of archivists working with AI, paradata is conceptualized here as information recorded and preserved about records’ processing with AI tools; it is a category of data that is defined both by its relationship with other datasets and by the documentary purpose it serves. This article surveys relevant literature across three contexts to scope the relevant scholarship that archivists may draw upon to develop appropriate AI documentation practices. From the statistical social sciences and the visual heritage fields, the article discusses existing definitions of paradata and its ambiguous, often contextually dependent relationship with existing metadata categories. Approaching the problem from a sociotechnical perspective, literature on Explainable Artificial Intelligence (XAI) insists pointedly that explainability be attuned to specific users’ stated needs—needs that archivists may better articulate using the framework of paradata. Most importantly, the article situates AI as a challenge to accountability, transparency, and impartiality in archives by introducing an unfamiliar non-human agency, one that pushes the limits of existing archival practice and demands the development of new concepts and vocabularies to shape future technological and methodological developments in archives.
Interpreting Adversarial Examples in Deep Learning: A Review
Authors: Han Sicong , Lin Chenhao , Shen Chao , Wang Qian , Guan Xiaohong
Published: April 2023

Deep learning technology is increasingly being applied in safety-critical scenarios but has recently been found to be susceptible to imperceptible adversarial perturbations. This raises a serious concern regarding the adversarial robustness of deep neural network (DNN)–based applications. Accordingly, various adversarial attacks and defense approaches have been proposed. However, current studies implement different types of attacks and defenses with certain assumptions. There is still a lack of full theoretical understanding and interpretation of adversarial examples. Instead of reviewing technical progress in adversarial attacks and defenses, this article presents a framework consisting of three perspectives to discuss recent works focusing on theoretically explaining adversarial examples comprehensively. In each perspective, various hypotheses are further categorized and summarized into several subcategories and introduced systematically. To the best of our knowledge, this study is the first to concentrate on surveying existing research on adversarial examples and adversarial robustness from the interpretability perspective. By drawing on the reviewed literature, this survey characterizes current problems and challenges that need to be addressed and highlights potential future research directions to further investigate adversarial examples.
Enhancing the Paddy Disease Classification by Using Cross‐Validation Strategy for Artificial Neural Network over Baseline Classifiers
Authors: Malathi V. , Gopinath M. P. , Kumar Manoj , Bhushan Shashi , Jayaprakash Sujith
Published: April 2023

Pathogens, including viruses, bacteria, and fungus, are the biotic agents that cause illnesses in crops and are the major cause of yield losses of up to 16 percent in certain parts of the globe. Pathogens are the primary cause of yield losses in some parts of the world. Deep learning algorithms, which are at the cutting edge of technology, are now being used to identify crop disease at an earlier stage. Supervised learning (support vector machine and K‐nearest neighbor), ensemble learning (random forest and AdaBoost), and deep learning approaches were used in this study to suggest a classification of paddy leaf diseases, including bacteria leaf blight, blast, hispa, leaf spot, and leaf folder (neural networks). In order to evaluate the performance of the learning approaches, accuracy, recall, precision, F1 score, and area under the receiver operating characteristic curve were used to evaluate the performance of the interpretation (ROC and AUC). According to the results of the investigation, when the fold value grows, the value of the evaluation metrics (AUC, CA, F1, precision, and recall) increases in a progressive manner, i.e., the 0.001 value increases as compared to the values obtained with the previous folds. When comparing the neural network to the baseline classifiers, the assessment metrics demonstrate that the neural network performs much better.
Sitting and Standing Intention Detection Based on Dynamical Region Connectivity and Entropy of EEG
Authors: Chang Wenwen , Nie Wenchao , Yuan Yueting , Zhang Yuchan , Lv Renjie , Zheng Lei , Yan Guanghui
Published: April 2023

Based on the brain signals, decoding and analyzing the gait features to make a reliable prediction of action intention are the core issues in the brain computer interface (BCI)-based hybrid rehabilitation and intelligent walking aid robot system. In order to realize the classification and recognition of the most basic gait processes such as standing, sitting, and quiet, this paper proposes a feature representation method based on the signal complexity and entropy of each brain region. Through the statistical analysis of these parameters between different conditions, these characteristics which sensitive to different actions are determined as a feature vector, and the classification and recognition of these actions are completed by combing support vector machine, linear discriminant analysis, and logistic regression. Experimental results show the proposed method can better realize the recognition of the aforementioned action intention. The recognition accuracy of standing, sitting, and quiet of 13 subjects is higher than 80.9%, and the highest one can reach 86.8%. Directed dynamic brain network analysis of the 8 brain regions shows that the occurrence of lower limb movement will weaken the dependence between brain regions, resulting in the weakening of network topological connection. The result has significant value for understanding human’s brain cognitive characteristics in the process of lower limb movement and carrying out the study of BCI based strategy and system for lower limb rehabilitation.
Red Blood Cell Alloimmunization and Autoimmunization in Blood Transfusion-Dependent Sickle Cell Disease and β-Thalassemia Patients in Al-Ahsa Region, Saudi Arabia
Authors: Kuriri Fahd A. , Ahmed Abdulrahman , Alanazi Fehaid , Alhumud Fahad , Ageeli Hakami Mohammed , Atiatalla Babiker Ahmed Osama
Published: April 2023

Introduction. The risk of developing transfusion-related complications, especially alloimmunization, is an ongoing concern for transfusion-dependent patients. It is important to determine the rate of alloimmunization and autoimmunization in Al-Ahsa Region, Saudi Arabia, where sickle cell disease (SCD) and thalassemia incidence rates are the highest in Saudi Arabia. Methods. A cross-sectional study was conducted to review the transfusion history of patients with SCD and thalassemia at the King Fahad Hospital (KFH) in Al-Ahsa, Saudi Arabia. 364 transfusion-dependent patients were included in this study. Results. Alloimmunization rates in patients with SCD and thalassemia were 16.7% and 11.97%, respectively, while autoimmunization rates in patients with SCD and thalassemia were 5.3% and 0.7%, respectively. The most frequent alloantibodies among the study participants were against Kell, Rh blood group systems. Conclusion. Blood transfusion-related alloimmunization and autoimmunization compromise the proper management of chronically transfused patients. Ideally, extended matched phenotyping should be implemented to prevent alloimmunization and reduce the risk of developing blood transfusion-related alloantibodies.
Antioxidant, Anti-Inflammatory, and Anticarcinogenic Efficacy of an Ayurvedic Formulation: Amritotharanam Kashyam
Authors: Raman Lakshmi Sundaram , Shanmuganathan Anitha , Chandrashekar Sangeeta , Kaliyaperumal Prabhu , Perumal Elumalai , Mudiganti Ram Krishna Rao , Nachammai K. T. , Kulanthaivel Langeswaran , Subbaraj Gowtham Kumar , Chandrasekaran Kirubhanand , Ramrao Sontakke Bharat , Subramanian Senthilkumar
Published: April 2023

Amritotharanam Kashyam, a specific Ayurvedic drug, was the focus of the current inquiry to evaluate its efficacy. For liver and digestive-related issues, this medication is suggested. This was obtained from a standard Ayurvedic vendor in Chennai (India), and GC-MS analysis was carried out according to the standard procedure. A few critical biomolecules include benzoic acid, hexadecanoic acid, 6,9-octadecadienoic acid, 9-octadecenoic acid, methyl ester (E)-, heptadecanoic acid, 16-methyl, methyl ester, methyl 18-methylnonadecanoate, tetracosanoic acid, distearin, hexadecanoic acid, and 1-(hydroxymethyl)-1,2-ethanediol ester. The obtained biomolecules exhibited some significant therapeutic functions, including acidification, inhibition of arachidonic acid formation, increase in the aromatic amino acid decarboxylase, suppression of uric acid generation, inhibitors of catechol-O-methyltransferase, urine acidifiers, etc. The anticancer and antiviral potential of these phytocompounds were investigated using molecular docking and dynamics. The phytocompounds pharmacokinetic characteristics were investigated using ADME analysis. Through docking and dynamics simulation, in silico tests demonstrated the phytocompounds' inhibitory efficiency against the target proteins. These functions reasonably relate to the medicinal function of Amritotharanam Kashyam. The MTT assay findings demonstrated this medication’s anticancer effects. The ability to be an effective drug is demonstrated by its antioxidant, anti-inflammatory, and membrane-stabilizing properties.
Study on Construction and Optimization of the Life-Saving Passage in Building Ruins Based on Numerical Simulation Method
Authors: Xu Defeng , Dai Junwu , Chen Limei , Yang Yongqiang , Agyare Richard , Tao Ning
Published: April 2023

It is a very important task to construct a life-saving passage in building ruins rapidly and scientifically in the process of earthquake rescue. Currently, the virtual scene is built to train rescuers to construct the life-saving passage quickly and scientifically. However, there are problems such as high cost, small quantity, and single form. A new method of constructing building ruins and life-saving passage was proposed based on the combined finite element (FE) and finite-discrete element (F-DE) method and restarted function of LS-DYNA program. First, taking the RC frame structure ruins as research objection, the different types of life-saving passages were constructed. What’s more, a simple and reasonable optimization method of life-saving passage is proposed based on the rescue technologies with the shortest time. Meanwhile, the timing test of four typical rescue technologies was performed considering the influence factors of various rescue situations. Finally, the practicability and validation of the optimization method was verified through comparing with actual earthquake rescue case. The results show that the restart function of ANSYS/LS-DYNA program can construct the life-saving passage rapidly and reasonably, and simultaneously, the optimal method of life-saving passage can give the optimal rescue route intuitively and accurately. The numerical simulation method of construction and optimization of life-saving passages is expected to provide theoretical guidance for rescue drills for on-site earthquake rescue.
Epiisopiloturine, an Alkaloid from Pilocarpus microphyllus, Attenuates LPS-Induced Neuroinflammation by Interfering in the TLR4/NF-κB-MAPK Signaling Pathway in Microglial Cells
Authors: de Sousa João Antônio Costa , Azul Francisco Vinícius Clemente Serra , de Araújo Ana Bruna , Tomé Rebeca Colares , Silva Francisca Raysse Mesquita , de Vasconcelos Silvânia Maria Mendes , Rios Francisco José , Leal Luzia Kalyne Almeida Moreira
Published: April 2023

Neuroinflammation is present in the pathophysiological mechanisms of several diseases that affect the central nervous system (CNS). Microglia have a prominent role in initiating and sustaining the inflammatory process. Epiisopiloturine (EPI) is an imidazole alkaloid obtained as a by-product of pilocarpine extracted from Pilocarpus microphyllus (jaborandi) and has shown promising anti-inflammatory and antinociceptive properties. In the present study, we investigated the effects of EPI on the inflammatory response in microglial cells (BV-2 cells) induced by lipopolysaccharide (LPS) and explored putative underlying molecular mechanisms. Cell viability was not affected by EPI (1-100 μg/mL) as assessed by both LDH activity and the MTT test. Pretreatment with EPI (25, 50, and 100 μg/mL) significantly reduced the proinflammatory response induced by LPS, as observed by a decrease in nitrite oxide production and iNOS protein expression. EPI (25 μg/mL) reduced IL-6 and TNF-α production, by 40% and 34%, respectively. However, no changes were observed in the anti-inflammatory IL-10 production. Mechanistically, EPI inhibited the TLR4 expression and phosphorylation of NF-κB p65 and MAPKs (JNK and ERK1/2) induced by LPS, but no changes were observed in TREM2 receptor expression in LPS-stimulated cells. In conclusion, our data demonstrated the potent anti-inflammatory properties of EPI in microglial cells. These effects are associated with the reduction of TLR4 expression and inhibition of intracellular signaling cascades, including NF-κB and MAPKs (JNK and ERK1/2).
Cardioprotection of mAb2G4/ODN/lip on Myocardial Ischemia-Reperfusion Injury via Inhibiting the NF-κB Signaling Pathway
Authors: Xu Zujin , Wei Zhuoran , Zhu Yali , Jing Guoqing , Chen Liufang , Zhan Jia , Wu Yun
Published: April 2023

Substantial evidence suggests that the interventions of NF-κB would likely effectively prevent inflammatory response and reduce myocardial damage in the ischemic myocardium. And the NF-кB decoy ODN is a specific inhibitor that suppresses the expression of NF-κB. Herein, we revealed the effect and possible mechanism of mAb2G4/ODN/lip on myocardial ischemia-reperfusion injury (MI/RI). As shown in the results, post-treatment with mAb2G4/ODN/lip improved the impaired histological morphology in the MI/RI model and elevated cell viability in the H/R model. The mAb2G4/ODN/lip complex inhibited the NLRP3 signaling pathway and decreased the expression of LDH, IL-1β, TNF-α, IL-6, and MDA. Mechanistically, we demonstrated that post-treatment with mAb2G4/ODN/lip exerted protective effects against I/R injuries by inhibiting the NF-кB-related inflammatory response. In summary, the present study may offer a novel therapeutic strategy for treating MI/RI.
[Retracted] Optimized IANSegNet: Deep Segmentation for the Detection of Inferior Alveolar Nerve Canal
Authors: Krishnan V. Gokula , Navaneethakrishnan M. , Ganesan Sangeetha , Saradhi M. V. Vijaya , Hemapriya K. , Selvaraj D. , Deepa J. , Murthy K. Sreerama , Doss Srinath
Published: April 2023

Imaging studies in dentistry and maxillofacial pathology have recently concentrated on detecting the inferior alveolar nerve (IAN) canal. In spite of the minor dimensions of 3D maxillofacial datasets, deep learning‐based algorithms have shown encouraging consequences in this study area. This study describes a mandibular cone‐beam CT (CBCT) dataset with 2D and 3D hand comments. It is huge and freely available. It was possible to utilise this dataset by applying the residual neural network (IANSegNet), which consumed less GPU memory and computational complexity. As an encoder, IANSegNet uses the computationally efficient 3D ShuffleNetV2 network to reduce graphics processing unit (GPU) memory usage and improve efficiency. After that, a decoder with leftover blocks is added to keep the quality high. To address network convergence and data inequity, Dice’s loss and cross‐entropy loss were created. Optimized postprocessing techniques are also recommended for fine‐tuning the coarse segmentation findings that are generated by IANSegNet. The results of the validation show that IANSegNet outperformed other deep learning models in a variety of criteria.
The Smart Network Management Automation Algorithm for Administration of Reliable 5G Communication Networks
Authors: Ramesh G. , Logeshwaran J. , Kumar Avvaru Praveen
Published: April 2023

Smart network management automation (SNMA) is a technology that enables the automation of network management tasks. It provides a platform for automating network management, allowing administrators to manage their networks more reliably and efficiently. It provides the tools to monitor and manage network performance, identify and troubleshoot problems, and automate the deployment of new services and applications. SNMA also allows for scalability to meet the needs of any organization, regardless of size or complexity. With SNMA, network administrators can quickly and accurately identify problems, increase network uptime, and reduce time spent on manual tasks. The SNMA provides the ability to adjust configurations quickly and respond to changes in the network environment. It can help reduce costs and improve the efficiency of network operations. This paper proposed an intelligent network management automation algorithm for network administration and management in 5G communication networks. The proposed algorithm achieved 91.82% of remote network administration, 95.25% of global network administration, 96.59% of urban network administration, and 95.07% of local network administration. It creates a single submission to the network to make configuration changes, register network resources, manage users’ IP addresses, and filter packets to ensure information security and other tasks.
Settlement Prediction Based on the Relationship between the Empirical and Analytical Solutions of a Cylindrical Cavity under Undrained Conditions
Authors: Mabe Fogang Pieride , Liu Yang , Yu Pengqiang
Published: April 2023

Settlements on the ground surface often relate to excavating an underground cavity in cities. Movement on the ground surface can create a void between the wall of the cylindrical cavity and the lining. Thus, this study proposes an approximate solution under undrained conditions, based on the relationship between the empirical and analytical methods for predicting ground settlement around a cylindrical cavity. Based on mathematical formulas, the results obtained by the geometrical representation are then associated with the experimental data. The study revealed that the settlement prediction is related either to ground surface loads or to the ground failure point. The expansion of the cylindrical cavity is solved as a linear elasticity problem using a system of first-order ordinary differential equations containing two components in the Cartesian coordinates. The stress distribution around the cylindrical cavity is evaluated based on a biaxial force. The proposed approaches show that the results (empirical and analytical) obtained are approximately similar. Hence, the relationship between the two methods can be best suited for predicting the settlement around a cylindrical cavity by evaluating both the maximum settlement and the maximum surface displacement.
Optimization Strategy of a Stacked Autoencoder and Deep Belief Network in a Hyperspectral Remote-Sensing Image Classification Model
Authors: Dai Xiaoai , Cheng Junying , Guo Shouheng , Wang Chengchen , Qu Ge , Liu Wenxin , Li Weile , Lu Heng , Wang Youlin , Zeng Binyang , Peng Yunjie , Liang Shuneng
Published: April 2023

Improvements in hyperspectral image technology, diversification methods, and cost reductions have increased the convenience of hyperspectral data acquisitions. However, because of their multiband and multiredundant characteristics, hyperspectral data processing is still complex. Two feature extraction algorithms, the autoencoder (AE) and restricted Boltzmann machine (RBM), were used to optimize the classification model parameters. The optimal classification model was obtained by comparing a stacked autoencoder (SAE) and a deep belief network (DBN). Finally, the SAE was further optimized by adding sparse representation constraints and GPU parallel computation to improve classification accuracy and speed. The research results show that the SAE enhanced by deep learning is superior to the traditional feature extraction algorithm. The optimal classification model based on deep learning, namely, the stacked sparse autoencoder, achieved 93.41% and 94.92% classification accuracy using two experimental datasets. The use of parallel computing increased the model’s training speed by more than seven times, solving the model’s lengthy training time limitation.
Factors of Spreading the Aggressive Behavior among Kindergarteners from the Perspective of Their Teachers in East Jerusalem
Authors: Shanti Dua , Moreno Eliana M.
Published: April 2023

This research aims to investigate the factors behind the spread of aggressive behavior in kindergartens from the point of view of educators in East Jerusalem. The descriptive analytical approach and quantitative research methods were used, which included t-test, independent sample t-test, and analysis of variance. Before collecting data, the reliability and validity of the questionnaire were checked. The questionnaire tool was distributed to a sample of 150 kindergarten teachers working in educational centers located in East Jerusalem. The research reached a number of results, the most important of which is that there are statistically significant differences in the factors of the spread of aggressive behavior in kindergartens due to the variable of academic specialization in the questionnaire, except for the dimension. Findings of the study show that there is a lack of understanding of the factors that lead to aggressive behavior, which requires understanding the types and manifestations of aggressive behavior in detail. Familial reasons have a great influence on the aggressive behaviors and actions that some children practice in kindergartens, and social factors, such as the child’s lack of social skills, have a substantial impact on the child’s behaviors and expressions of aggression. The researcher recommended the necessity of holding seminars, lectures, meetings, and workshops specialized in raising and caring for children to overcome their developmental and behavioral problems. The study offers significant new information about the causes that lead to the spread of violent behavior among kindergarteners in East Jerusalem, as seen from the teachers’ perspective. To fully comprehend the elements that lead to violent behavior in this population, more study is necessary. This can assist in creating treatments and techniques that are more successful in reducing aggressive behavior in kindergarteners.
Naturally Occurring Plant Food Toxicants and the Role of Food Processing Methods in Their Detoxification
Authors: Urugo Markos Makiso , Tringo Tadele Tuba
Published: April 2023

Some plant foods evolve defense mechanisms to protect themselves from predators by producing inherent chemicals as secondary metabolites such as cyanogenic glycosides, glycoalkaloids, glucosinolates, pyrrolizidine alkaloids, and lectins. These metabolites are beneficial for the plant itself but toxic to other organisms, including human beings. Some of these toxic chemicals are believed to have therapeutic benefits and are therefore used to protect against chronic health complications such as cancer. Inversely, short- and long-term exposure to significant amounts of these phytotoxins may end up with chronic irreversible negative health problems in important organ systems, and in severe cases, they can be carcinogenic and fatal. A systematic literature search of relevant published articles indexed in Google Scholar®, PubMed®, Scopus®, Springer Link®, Web of Science®, MDPI®, and ScienceDirect databases was used to obtain the necessary information. Various traditional and emerging food-processing techniques have been found to considerably reduce most of the toxicants in the food to their safest level. Despite their ability to preserve the nutritional value of processed foods, emerging food processing methods have limited application and accessibility in middle- and low-income countries. As a consequence, much more work is recommended on the implementation of emerging technologies, with additional scientific work on food processing methods that are effective against these naturally occurring plant food toxicants, particularly pyrrolizidine alkaloids.
Clonal Hematopoiesis in Young Women Treated for Breast Cancer
Authors: Gibson Christopher J. , Fell Geoffrey , Sella Tal , Sperling Adam S. , Snow Craig , Rosenberg Shoshana M. , Kirkner Greg , Patel Ashka , Dillon Deborah , Bick Alexander G. , Neuberg Donna , Partridge Ann H. , Miller Peter G.
Published: April 2023

Purpose:

Young women treated for breast cancer with cytotoxic therapies are at risk for clonal hematopoiesis of indeterminate potential (CHIP), a condition in which blood cells carrying a somatic mutation associated with hematologic malignancy comprise at least 4% of the total blood system. CHIP has primarily been studied in older patient cohorts with limited clinical phenotyping.

Experimental Design:

We performed targeted sequencing on longitudinal blood samples to characterize the clonal hematopoietic landscape of 878 women treated for breast cancer enrolled in the prospective Young Women's Breast Cancer Study.

Results:

We identified somatic driver mutations in 252 study subjects (28.7%), but only 24 (2.7%) had clones large enough to meet criteria for CHIP. The most commonly mutated genes were DNMT3A and TET2, similar to mutations observed in noncancer cohorts. At 9-year median follow-up, we found no association between the presence of a somatic blood mutation (regardless of clone size) and adverse breast cancer (distant relapse-free survival) or non–breast cancer-related outcomes in this cohort. A subset of paired blood samples obtained over 4 years showed no evidence of mutant clonal expansion, regardless of genotype. Finally, we identified a subset of patients with likely germline mutations in genes known to contribute to inherited cancer risk, such as TP53 and ATM.

Conclusions:

Our data show that for young women with early-stage breast cancer, CHIP is uncommon after cytotoxic exposure, is unlikely to contribute to adverse outcomes over the decade-long follow-up and may not require additional monitoring if discovered incidentally.
Instruments for Assessing Loneliness in Older People in Portugal: A Scoping Review
Authors: Carvalho Rita , Sousa Liliana , Tavares João
Published: April 2023

Background: Loneliness is a public health problem that affects many older adults. The subjective nature of loneliness challenges its assessment. Thus, assessing loneliness with valid and reliable instruments is crucial to characterizing the phenomenon and planning adequate interventions. Summary: This study mapped the instruments validated for the Portuguese older population that assess loneliness. A scoping review was performed. The search for studies was carried out in SciELO, PsycInfo, Scopus, MEDLINE, MedicLatina, Nursing & Allied Health Collection: Comprehensive, CINAHL, and Open Access Scientific Repositories of Portugal. The findings showed three instruments validated for the Portuguese older population: ULS-16, ULS-6, and SELSA-S. Key Messages: Future testing of those instruments is required to update and accumulate psychometric evidence. In addition, it is important to translate and validate other instruments to the Portuguese older adults population, namely de Jong Gierveld and UCLA-R (most used internationally), as well as the ALONE scale (new and brief).
The Body in Question in the Existence of Hysteric Persons: A Phenomenological Perspective
Authors: Esposito Cecilia Maria , Stanghellini Giovanni
Published: April 2023

The concept of hysteria, although apparently surpassed by contemporary nosographic classifications, continues to be talked about. Following Charbonneau’s attempt to de-feminize and de-sexualize hysteria, clinical phenomenology can offer a perspective which, freed from stigma and prejudices through the suspension of judgement, allows us to understand hysteria not as a diagnostic category but as an existential position. In this sense, hysteria would be based on a hypo-sufficiency of the embodied self, which is not perceived as solid and continuous and needs external confirmations of its adequacy. According to the optical-coenaesthetic disproportion hypothesis, the hypo-sufficiency of the embodied self originates from the difficulty of experiencing one’s body from the first-person perspective and from the consequent use of the gaze of others as a prosthesis to achieve a sense of selfhood and identity. Hysteric persons develop a mode of access to their corporeality mediated by visual representations – hence the theatricalization, centrality, and seductiveness of hysteric persons’ behaviour. We suggest to call “figural body” the visual apprehension of one’s body which tries to compensate for the weakness of coenaesthetic apprehension of the lived body. Over time, the figural body ends up superimposing itself on the immediate experience of the lived body. Placing itself on a representative register, this image conveys not only individual ghosts but also cultural aspects, social prejudices, gender stereotypes. Thus, the attempt to experience one’s own body with the mediation of the other’s gaze becomes an involuntary and unaware throwing of oneself into the meshes of representation that are necessarily alienating for the person. Hysterical persons remain stuck in their inability to access an experience of their body that is not figurative, alienating themselves in representations which always come from outside.
Association of Dental Infections with Intracranial Atherosclerotic Stenosis
Authors: Sen Souvik , Meyer Jaclyn , Mascari Rachel , Trivedi Tushar , Suri Fareed , Wasserman Bruce , Rosamond wayne , Moss Kevin , Beck James , Gottesman Rebecca F
Published: April 2023

Introduction: Periodontal disease (PD) and dental caries are oral infections leading to tooth loss that are associated with atherosclerosis and cerebrovascular disease. We assessed the hypothesis that PD and caries are associated with asymptomatic intracranial atherosclerosis (ICAS) in the Atherosclerosis Risk in Communities (ARIC) study. Methods: Full-mouth clinical periodontal measurements (7 indices) collected at 6 sites per tooth from 6,155 subjects from the Dental Atherosclerosis Risk in Communities Study (DARIC) without prior stroke were used to differentiate seven PD stages (Periodontal Profile Class [PPC]-I to -VII) and dental caries on coronal dental surface (DS) and dental root surface (DRS). A stratified subset underwent 3D time-of-flight MR angiogram and 3D high isotropic-resolution black blood MRI. ICAS was graded according to the criteria established by the Warfarin-Aspirin Symptomatic Intracranial Disease (WASID) trial. We evaluated the relationship between PD stage and dental caries with asymptomatic ICAS, graded as no ICAS, <50% ICAS, and ≥50% ICAS. Results: Among dentate subjects who underwent vascular imaging, 801 (70%) had no ICAS, 232 (20%) had <50% ICAS, and 112 (10%) had ≥50% ICAS. Compared to participants without gum disease (PPC-I), participants with mild-moderate tooth loss (PPC-VI), severe tooth loss (PPC-VII), and severe PD (PPC-IV) had higher odds of having <50% ICAS. Participants with extensive gingivitis (PPC-V) had significantly higher odds of having ≥50% ICAS. This association remained significant after adjusting for confounding variables: age, gender, race, hypertension, diabetes, dyslipidemia, 3-level education, and smoking status. There was no association between dental caries (DS and DRS) and ICAS <50% and ≥50%. Conclusion: We report significant associations between mild-moderate tooth loss, severe tooth loss, and severe PD with <50% ICAS as well as an association between extensive gingivitis and ≥50% ICAS. We did not find an association between dental caries and ICAS.
Perpetuating the Traditional Honour Crimes: The Machinery of the Criminal Justice System and Its Approach toward Honour and Passion Models in the West Bank
Authors: Randall Ayah-Omran
Published: April 2023

The purpose of this paper is to analyse the impact of the legislative approach to honour crimes to understand its effect on the judicial approach. This is done through the analysis of Abu Odeh’s argument that posits the legislature as progressive. This paper is a doctrinal analysis of the key articles of the Jordanian Penal Code No. 16 of 1960, still applicable in the West Bank. While Abu Odeh argues that the legislature acts as the progressive harbinger of change through the incorporation of some elements of the crime of passion into the Penal Code, this paper presents a different picture. This picture shows a reality in which the concepts of honour crimes as a form of cultural violence based on traditions and the crime of passion as a form of gender-based violence are conflated by legislators. This becomes apparent in Article 340 which presents a problematic definition of honour and passion which rather than providing clarity conflates the two. The feature of Article 340, in addition to the prevalence of traditional honour in the prosecution of sexual crimes, has led judges to put forth their own interpretation of the provocation defence implied by Article 98 in relation to honour crimes to resist progressive legal reform.