bluuebunny/crossref_metadata_2025 huggingface dataset:
Physics implication from higher weak isospin decomposition
Authors: Van Dong Phung , Van Loi Duong
Published: August 2023

The $$SU(3)_L\otimes U(1)_X$$

S
U

(
3
)

L

⊗
U

(
1
)

X

symmetry actually studied is directly broken to the electroweak symmetry $$SU(2)_L\otimes U(1)_Y$$

S
U

(
2
)

L

⊗
U

(
1
)

Y

by a Higgs triplet, predicting a relevant new physics at TeV scale. This work argues, by contrast, that the higher weak isospin $$SU(3)_L$$

S
U

(
3
)

L

might be broken at a high energy scale, much beyond 1 TeV, by a Higgs octet to an intermediate symmetry $$SU(2)_L\otimes U(1)_{T_8}$$

S
U

(
2
)

L

⊗
U

(
1
)

T
8

at TeV, before the latter $$U(1)_{T_8}$$

U

(
1
)

T
8

recombined with $$U(1)_X$$

U

(
1
)

X

defines (i.e., broken to) $$U(1)_Y$$

U

(
1
)

Y

by a Higgs singlet. The new physics coupled to $$SU(3)_L$$

S
U

(
3
)

L

breaking phase is decoupled, whereas what remains is a novel family-nonuniversal abelian model, $$U(1)_{T_8}\otimes U(1)_X$$

U

(
1
)

T
8

⊗
U

(
1
)

X

, significantly overhauling the standard model as well as yielding consistent results for neutrino mass, dark matter, W-mass anomaly, and FCNC, differently from the usual 3-3-1 model.
Charged particle dynamics in black hole split monopole magnetosphere
Authors: Khan Saeed Ullah , Chen Zhi-Min
Published: August 2023

This article examines particle dynamics and acceleration in the magnetic Penrose process (MPP) around Kerr black hole (BH) in a split monopole magnetic field. The characteristics of charged particle motion around magnetized BHs reveal four differen feasible regimes of ionized Keplerian disk behaviour: survival in regular epicyclic motion; changing into a chaotic toroidal state; collapse due to escaping along magnetic field lines and collapse due to falling into the BHs. By making use of the effective potential, we have investigated the position of stable circular orbits for both in- and off-equatorial planes. We observed that the positive magnetic field $${{\mathcal {P}}}>0$$

P
>
0

increases the stability of effective potential, whereas $${{\mathcal {P}}}<0$$

P
<
0

diminishes its stability. We show that ultra-efficient energy extraction from spinning supermassive BH controlled by the MPP can pay the bill. We anticipate neutral particle ionization, such as neutron beta-decay, edging closer to the BH horizon, charging protons to more than $$10^{20}$$

10
20

eV for a supermassive BH of mass $$10^9M_{\odot }$$

10
9

M
⊙

and a magnetic field of strength $$10^4$$

10
4

G.
Stochastic and corpuscular theory of (polarized) light
Authors: Procházka Jiří
Published: August 2023

Both the corpuscular theory of light and the theory of stochastic processes are well known in the literature. However, they are not systematically used together for description of optical phenomena. There are optical phenomena, such as the well-known three-polarizer experiment or other phenomena related to polarization of light, which have never been quantitatively and qualitatively explained using the concept of quantum of light (photon). The situation changed in 2022 when stochastic memoryless and independent (IM) process formulated within the framework of the theory of stochastic processes was introduced. It is suitable for determination of probability (density) functions characterizing interaction (transmission or reflection) of individual photons with optical elements on the basis of experimental data. The process has memoryless (Markov) property, and it is assumed that the interactions of individual photons with an optical system are independent. Formulae needed for analysis of data in the context of polarization of light are derived. An example analysis of the three-polarizer experiment is performed and numerical result of the probability (density) functions are determined. These original results were missing in the literature. The results imply that the possibilities of the corpuscular theory of light to describe optical phenomena can be significantly extended with the help of stochastic IM process and the theory of stochastic processes in general.
Heat transfer and entropy optimization for unsteady MHD Casson fluid flow through a porous cylinder: Applications in nuclear reactors
Authors: Raje Ankush , Koyani Foram , Bhise Ashlesha A. , Ramesh Katta
Published: August 2023

Heat transfer and entropy generation are crucial considerations in the nuclear industry, where the safe and efficient transfer of heat is essential for the operation of nuclear reactors and other nuclear systems. Casson fluid is a useful tool in the nuclear industry for simulating the flow behavior of nuclear fuels and coolants, and for optimizing the design and operation of nuclear reactors. In view of this, the current investigation deals with the heat and fluid flow of unsteady Casson fluid in a circular pipe under the influence of magnetic field, internal heat generation, entropy generation and porous media. The governing equations have been simplified under suitable assumptions and nondimensional quantities. The simplified dimensionless governing equations have been solved using the method of separation of variables along with Bessel functions. It is concluded from the investigation that the temperature increases with time. The Casson fluid parameter raises the temperature and entropy generation. The temperature, entropy generation and Bejan number are the decreasing functions of the Prandtl number.
Influence of nonlinear semiconductor layer on optical properties in one-dimensional photonic crystals
Authors: Gharaati Abdolrasoul , Mahmoodi Abdolreza
Published: August 2023

In this paper, an attempt has been made to investigate a one-dimensional photonic crystal containing N-doped germanium semiconductor as a nonlinear defect layer with an intensity-dependent refractive index, silica (SiO2) and zinc selenide (ZnSe) as crystal cells. Bistability of the TE polarization of the transmission spectrum due to the nonlinear property of the defect layer is investigated by the transfer matrix method (TMM). The refractive index of the germanium nonlinear semiconductor layer is simultaneously depending on the doping density and the intensity of the irradiated light. The changes in both factors are investigated. The impact on the transmission spectrum of the bistability threshold due to the change in the thickness of the defect layer, the thickness of other layers of crystal cells, and the angle of incident light are investigated. The nonlinear effect caused by light intensity as well as doped density effect on the germanium nonlinear semiconductor medium is used simultaneously. As a result, the nonlinear effect caused by the light intensity to create bistability is more than the doping density.
Dynamics of MHD Casson fluid in non-Darcy porous medium: The impact of thermal radiation, Dufour–Soret, and chemical reaction
Authors: Sharma Kushal , Kumar Laltesh , Singh Atar , Kumar Joshi Vimal
Published: August 2023

In this research, the dynamics of MHD Casson fluid flow has been discussed in the presence of non-Darcy Forchheimer porous medium. The investigation is focused on how thermal radiation, Soret–Dufour, and chemical reactions affect the incompressible Casson flow in a non-Darcy Forchheimer porous medium, taking account of pressure force. The mathematical model of the system is solved using the finite difference scheme followed by the shooting technique with bvp4c tool in MATLAB. The effects of physical parameters on velocity and transport (heat and mass) profile are illustrated through graphs. From the results, it is observed that Soret effect reduces the thermal boundary layer thickness which leads to the asymptotic increase in heat dissipation. The findings of the study on MHD Casson fluid model considering the non-Darcy Forchheimer porous medium are useful in engineering and science areas such as chemical machinery systems, geophysics, etc.
Pure-Attention-Based Multifunction Memristive Neuromorphic Circuit and System
Authors: Xiao He , Sun Haohang , Zhao Tianhao , Zhou Yue , Hu Xiaofang
Published: August 2023

The use of memristive neuromorphic circuit and system is a promising solution for next-generation Artificial Intelligence (AI) computing, as it offers possibilities that go beyond conventional GPU-based artificial neural network computing platforms. However, most of the existing memristive neuromorphic circuits and systems are designed for the specific networks, which is lack of universality and flexibility. Therefore, this paper proposes a universal memristive circuit and system framework for pure-attention-based transformer networks to implement multifunction applications on edge devices. Furthermore, the verification of image recognition and speech recognition was achieved by extending the size of the memristor crossbar array macros and reconfiguring the memristor weights without changing the memristive transformer circuit and framework. This paper not only provides a universal edge implementation framework for multifunction applications of the transformer, but also offers a low-power and promising solution for the application of pure-attention-based transformers on edge devices.
Porphycene conjugates for biomedical applications
Authors: Sánchez-García David
Published: August 2023

The aim of this review is to offer a brief account of the functionalization of porphycenes for the preparation of conjugates useful as photosensitizers for biomedical applications.
WHAT DO WE KNOW? FDI INFLOWS, MANAGERIAL SPILLOVERS AND INNOVATION OUTCOMES OF LOCAL FIRMS DURING GLOBAL CRISES
Authors: RIVIERE MONICA , ZAMBORSKY PETER
Published: August 2023

Global crises have become our business reality. How can local firms continue to sustain their competitiveness during these crises through innovation? Previous literature emphasized the role of foreign direct investment (FDI) inflows, but was generally inconclusive. This study examines FDI and managerial spillovers as antecedents of innovation outcomes in 369 local firms in 12 Eurasian countries during the 2008–2009 global financial crisis. The study finds that new product and service introductions by incumbent firms are driven by the local presence of the multinational enterprises (MNEs). Moreover, firms with more non-native managers and CEOs with substantial industry experience have a higher propensity to introduce new products and services. The study contributes to the theory of FDI spillovers and the literature on antecedents of innovation outcomes by showing that non-native managers can serve as channels of managerial spillovers. Furthermore, we conceptually distinguish between managerial spillovers from MNEs and managerial spillovers from abroad (e.g., via hiring managers born or educated abroad).
Does Water Resource Fee to Tax Policy Help Reduce Water Pollution in China?
Authors: Li Jiangyuan , Ding Tao , Liang Liang
Published: August 2023

This research uses a time-varying difference-in-differences (DID) model to assess the impact of the water resource fee to tax (WRFT) policy on water pollution in China from 2004 to 2020. The study finds that the WRFT policy can reduce chemical oxygen demand (COD) emissions by 17.7% and ammonia nitrogen (NH3-N) emissions by 31.6% on average. These findings are supported by various robustness tests, such as the parallel trend test, the placebo test, and the changing standard errors. The study also finds that the impact of the WRFT policy is stronger in regions with higher economic development levels and lower water pollution levels, but does not show heterogeneity in water resource abundance. The mechanism analysis suggests that the WRFT policy achieves the effect of reducing water pollution by reducing sewage discharge, increasing intensity of water pollution prevention, and promoting green R&D innovation. The study addresses potential endogeneity issues such as reverse causality, sample self-selection, and omitting variable bias. Based on these findings, the study offers some policy recommendations to further enhance the WRFT policy effects and reduce water pollution in China.
A Comprehensive Survey on Collaborative Data-access Enablers in the IIoT
Authors: Sun Danfeng , Hu Junjie , Wu Huifeng , Wu Jia , Yang Jian , Sheng Quan Z. , Dustdar Schahram
Published: August 2023

The scope of the Industrial Internet of Things (IIoT) has stretched beyond manufacturing to include energy, healthcare, transportation, and all that tomorrow’s smart cities will entail. The realm of IIoT includes smart sensors, actuators, programmable logic controllers, distributed control systems (DCS), embedded devices, supervisory control, and data acquisition systems—all produced by manufacturers for different purposes and with different data structures and formats; designed according to different standards and made to follow different protocols. In this sea of incompatibility, how can we flexibly acquire these heterogeneous data, and how can we uniformly structure them to suit thousands of different applications? In this article, we survey the four pillars of information science that enable collaborative data access in an IIoT—standardization, data acquisition, data fusion, and scalable architecture—to provide an up-to-date audit of current research in the field. Here, standardization in IIoT relies on standards and technologies to make things communicative; data acquisition attempts to transparently collect data through plug-and-play architectures, reconfigurable schemes, or hardware expansion; data fusion refers to the techniques and strategies for overcoming heterogeneity in data formats and sources; and scalable architecture provides basic techniques to support heterogeneous requirements. The article also concludes with an overview of the frontier researches and emerging technologies for supporting or challenging data access from the aspects of 5G, machine learning, blockchain, and semantic web.
Impacts of Social Media Advertising on Purchase Intention and Customer Loyalty in E-Commerce Systems
Authors: Duan Xingyu , Chen Chun-Nan , Shokouhifar Mohammad
Published: August 2023

The emergence of new technologies has had a noteworthy impact on communication systems, leading to the importance of conducting research in this area due to the significant influence of social media. Marketing operators must implement the necessary infrastructure to identify and fulfill customers' expectations, considering the advantages and the increasing number of users in social networks. This paper presents a comprehensive framework for evaluating the purchase intention of electronic commerce systems, taking into account the impact of social media advertising and customer loyalty. The paper aims to enhance purchase intention in e-commerce through social media advertising and examine influential factors that improve online shopping performance, including social media advertising's effectiveness on customer purchase behavior and brand loyalty. The paper develops a theoretical framework of nine hypotheses to evaluate purchase intention in e-commerce systems, with a focus on the effect of social media advertising on brand loyalty and purchase intention. To validate the proposed model and test the research hypotheses, we make use of information obtained from an international company located in China. The results demonstrate the positive effect of pleasurable motivation on purchase intention, with a significance level of 3.776 and a path coefficient of 0.279. Moreover, an investigation of the positive effect of customer loyalty on the recommended advertisement confirms the hypotheses, with a significance of 32.815 and a path coefficient of 0.788.
TLS-MHSA: An Efficient Detection Model for Encrypted Malicious Traffic based on Multi-Head Self-Attention Mechanism
Authors: Chen Jinfu , Song Luo , Cai Saihua , Xie Haodi , Yin Shang , Ahmad Bilal
Published: August 2023

In recent years, the use of TLS (Transport Layer Security) protocol to protect communication information has become increasingly popular as users are more aware of network security. However, hackers have also exploited the salient features of the TLS protocol to carry out covert malicious attacks, which threaten the security of network space. Currently, the commonly used traffic detection methods are not always reliable when applied to the problem of encrypted malicious traffic detection due to their limitations. The most significant problem is that these methods do not focus on the key features of encrypted traffic. To address this problem, this study proposes an efficient detection model for encrypted malicious traffic based on transport layer security protocol and a multi-head self-attention mechanism called TLS-MHSA. Firstly, we extract the features of TLS traffic during pre-processing and perform traffic statistics to filter redundant features. Then, we use a multi-head self-attention mechanism to focus on learning key features as well as generate the most important combined features to construct the detection model, thereby detecting the encrypted malicious traffic. Finally, we use a public dataset to verify the effectiveness and efficiency of the TLS-MHSA model, and the experimental results show that the proposed TLS-MHSA model has high precision, recall, F1-measure, AUC-ROC as well as higher stability than seven state-of-the-art detection models.
Distributed Cooperative Coevolution of Data Publishing Privacy and Transparency
Authors: Ge Yong-Feng , Bertino Elisa , Wang Hua , Cao Jinli , Zhang Yanchun
Published: August 2023

Data transparency is beneficial to data participants’ awareness, users’ fairness, and research work’s reproducibility. However, when addressing transparency requirements, we cannot ignore data privacy. This article defines the multi-objective data publishing (MODP) problem, optimizing data privacy and transparency at the same time. Accordingly, we propose a distributed cooperative coevolutionary genetic algorithm (DCCGA) to optimize the MODP problem. In the population of DCCGA, each individual represents an anonymization solution to MODP. Three modules in DCCGA, i.e., grouping module, cooperative coevolutionary module, and evolving module, are proposed for distributed sub-population update and evaluation, improving DCCGA’s optimization performance and parallel efficiency. Moreover, a matrix-based crossover operator and a matrix-based mutation operator are designed to exchange and adjust anonymization information in the individuals efficiently. Experimental results demonstrate that the proposed DCCGA outperforms the competitors with respect to solution accuracy, convergence speed, and scalability. Besides, we verify the effectiveness of all the proposed components in DCCGA.
Dysregulation of early gene response to a mixed meal in skeletal muscle in obesity and type 2 diabetes
Authors: Makhnovskii Pavel A. , Lednev Egor M. , Gavrilova Alina O. , Kurochkina Nadia S. , Vepkhvadze Tatiana F. , Shestakova Marina V. , Popov Daniil V.
Published: August 2023

In skeletal muscle of metabolically healthy subjects, a typical single meal normalized to body mass induces activation of various transcription factors, expression of numerous receptor tyrosine kinases associated with the insulin signaling cascade, and transcription regulators. In skeletal muscle of obese individuals without and with type 2 diabetes, this signaling network is poorly regulated at the transcriptional level, indicating dysregulation of the early gene response to a mixed meal.
Characterization and Potential of Samanea saman-Activated Carbon on Adsorption of Copper from an Aqueous Solution
Authors: Ni'am Achmad Chusnun , Suhar Muhamad , Fenelon Ernso
Published: August 2023

The mining and electroplating industries have resulted in the contamination of the environment with heavy metal. This has resulted in a serious threat to the ecological environment and human health due to the presence of copper pollution. To address this issue, extensive efforts have been made to develop effective methods for removing contaminants, particularly heavy metal, and Samanea saman (SS) was selected as precursor production of activated carbon. Therefore, this study is aimed at investigating Samanea saman-activated carbon (SSAC) to remove copper from an aqueous solution. SS was chemically activated by potassium carbonate and carbonized at 600°C for 5 hours, while SSAC was characterized by scanning electron microscopy-energy dispersive X-ray (SEM-EDS), Fourier-transform infrared (FTIR), and proximate tests. Copper adsorption on SSAC was evaluated by the Langmuir, Freundlich, Langmuir, Freundlich, Redlich-Peterson, Harkin-Jura, and Jovanovic models. Pseudo-first-order, pseudo-second-order, Elovich, and intraparticle diffusion models were used to identify adsorption process mechanism. SEM-EDS results presented that the pore of SSAC was heterogeneous, irregular in shape, and mesopore. In addition, FTIR analysis identified the main functional groups present in SSAC as C-H, C-O-C, and C-O. The proximate test conducted on SSAC determined the water content, volatile matter, ash content, and fixed carbon to be 0.61%, 22.26%, 9.77%, and 67.97%, respectively. The results showed that SSAC exhibited exceptional performance with copper removal efficiency of 99.49% under an adsorbent mass of 0.25 g, a reaction time of 30 minutes, and a concentration of 10 mg/L. Isotherm adsorption of SSAC followed the Redlich-Peterson model with an adsorption capacity (Qm) of 0.663 mg/g, correlation value ([Formula: see text]) of 0.9992, and pseudo-second-order pattern [Formula: see text]. Therefore, SSAC can be proposed as a potential and economical biomaterial to treat heavy metal in wastewater.
A Review of the Technological Advances in the Design of Highly Efficient Perovskite Solar Cells
Authors: Njema George G. , Kibet Joshua K.
Published: August 2023

The search for renewable and sustainable energy for energy security and better environmental protection against hazardous emissions from petro-based fuels has gained significant momentum in the last decade. Towards this end, energy from the sun has proven to be reliable and inexhaustible. Therefore, better light harvesting technologies have to be sought. Herein, the current trends in the development of perovskite solar cells with a focus on device engineering, band alignment, device fabrication with superior light harvesting properties, and numerical simulation of solar cell architectures are critically reviewed. This work will form the basis for future scientist to have a better scientific background on the design of highly efficient solar cell devices, which are cost-effective to fabricate, highly stable, and eco-friendly. This review presents thorough essential information on perovskite solar cell technology and tracks methodically their technological performance overtime. The photovoltaic (PV) technology can help to reduce pollution related to greenhouse gas emissions, criterion pollutant emissions, and emissions from heavy metals and radioactive species by nearly 90%. Following the introduction of highly efficient perovskite solar cell (PSC) technologies, the problems associated with stability, short life-time and lead-based perovskite solar cell configurations have significantly been minimized. The fabrication and simulation of perovskite solar cells has been made possible with advanced technologies and state-of-the-art computational codes. Furthermore, device simulation strategies have lately been used to understand, select appropriate materials, and gain insights into solar cell devices’ physical behavior in order to improve their performances. Numerical simulation softwares such as the 1-dimenional solar cell capacitance simulator (SCAPS-1D), Silvaco ATLAS, and wx-analysis of microelectronic and photonic structures (wxAMPS) used to understand the device engineering of solar cells are critically discussed. Because of the need to produce charge collection selectivity, hole transport materials (HTMs) as well as electron transport materials (ETMs) constitute essential PSC components. In this work, the synthesis of inorganic HTMs, as well as their characteristics and uses in various PSCs comprising mesoporous and planar designs, are explored in detail. It is anticipated that the performance of inorganic HTLs on PSCs would encourage further research which will have a significant influence on the future designs and fabrication of highly efficient solar cells.
Multilevel Feature Extraction Method for Adaptive Fault Diagnosis of Railway Axle Box Bearing
Authors: Liu Zhigang , Zhang Long , Xiong Guoliang
Published: August 2023

Railway axle box bearing fault signal contains high Q-factor resonance and low Q-factor transient shock components with periodic transient shock features that can characterize bearing faults. However, extracting fault features is usually difficult due to noise, transmission paths, and high-amplitude accidental shocks. Therefore, to address the abovementioned problems, the multilevel feature extraction method for adaptive fault diagnosis of railway axle box bearing was proposed. This paper used the maximum second-order cyclostationary blind convolution (CYCBD) to weaken the influence of disturbances, enhancing weak transient shock components. Resonant sparse decomposition(RSSD) is used for the selection of quality factor Q due to its excellent fault feature separation property. Considering the strict fault frequency component periodicity in the envelope spectrum, the envelope spectrum multipoint kurtosis (ESMK) is proposed as a metric. The Q factor is optimized using the gray wolf optimization algorithm (GWO) to obtain an adaptive sparse decomposition method (GWO-RSSD) for extracting bearing transient fault shocks to eliminate the signal effects of high-amplitude disturbance shocks and background noise. The simulation results and measured signal analysis of railway axle box bearing show that ESMK can effectively measure periodic transient shocks under strong shock interference compared with the MED-RSSD method. Thus, GWO-RSSD can adaptively separate the optimal low-Q resonance components, verifying the methods’ effectiveness and superiority.
University Students Behaviour Modelling Using the K‐Prototype Clustering Algorithm
Authors: Dake Delali Kwasi , Gyimah Esther , Buabeng-Andoh Charles
Published: August 2023

Counselling students remains a pre‐eminence for most tertiary institutions in Ghana to the extent that institutions now have counselling units that extend to the departmental level. This study used the K‐prototype machine learning algorithm to cluster students’ behaviour based on 28 relevant attributes and further proposed a classification model. The analysis of the experimental outcomes using the elbow method reveals the formation of three distinct clusters with decreasing intra‐cluster similarities and increasing inter‐cluster distances. The first cluster uniquely consists of active learners with three or more roommates, primarily in the first year. The second cluster with the highest membership consists mainly of second‐year students who exhibit passive classroom conduct and reside in a two‐occupancy hostel. The third cluster contains a mixture of third and final‐year students who are highly passive in class and live in a tenancy occupancy of two. After clustering, the K‐nearest neighbours, logistic regression, naïve Bayes (NB), and AdaBoost ensemble algorithms were implemented to create a model for future learner cluster prediction. Simulation results using the tenfold cross‐validation technique show that AdaBoost (NB) has the highest accuracy of 99.88% with an F‐measure score of 0.999 and receiver operating characteristic–area under the curve value of 1.00.
Anxiety and Somatic Symptoms in Children and Adolescents Diagnosed with Attention-Deficit Hyperactivity Disorder
Authors: Okyar Esra , Bozatlı Leyla , Görker Işık , Okyar Serap
Published: August 2023

Background. Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental condition typified by inattention, hyperactivity, and impulsivity. Comorbid psychiatric disorders are common among children and adolescents with ADHD. In this study, it was aimed to examine anxiety and somatic symptoms in children and adolescents with ADHD and the effect of methylphenidate treatment on these symptoms. Method. Three groups were formed, consisting of 37 children and adolescents diagnosed with ADHD and received methylphenidate treatment, 37 newly diagnosed, treatment-naive children and adolescents with ADHD diagnosis, and 37 children and adolescents without the diagnosis of ADHD. The symptoms of ADHD in children were examined by using the DSM-IV-based child and adolescent behavior disorders screening and rating scale, the symptoms of anxiety were examined by using the screen for child anxiety-related disorders (SCARED), and somatic symptoms were examined by using the DSM-5 level 2 somatic symptom scale. Results. In the newly diagnosed, treatment-naive with ADHD group, anxiety and somatic symptoms were found to be significantly higher compared to the ADHD group with methylphenidate treatment and the non-ADHD group. It was shown that the symptoms of panic disorder, generalized anxiety, and social phobia were observed more in the newly diagnosed, treatment-naive with ADHD group compared to the treatment group with ADHD. Conclusions. It was determined that children and adolescents diagnosed with ADHD had more anxiety and somatic symptoms. Anxiety and somatic symptoms increased as the severity of ADHD symptoms increased. Anxiety and somatic symptoms were lower than in ADHD children receiving methylphenidate treatment. Clinicians should keep in mind to evaluate anxiety and somatic symptoms in children and adolescents with ADHD before the treatment.
A Retrospective Analysis of Malaria Trends in Leka Dulecha Health Center over the Last Ten Years (2013‐2022), Western Oromia, East Wollega Zone
Authors: Tafesse Temesgen , Tolera Chimdessa , Amenu Desalegn
Published: August 2023

Background. Malaria is a serious public health concern in the world, and it causes a major socioeconomic problem in Ethiopia. Malaria data trend analysis of health facilities is useful to understand the prevalence and incidence of malaria cases and implementing evidence‐based malaria control strategies. Hence, the main objective of this study was to investigate the malaria trends over the last ten years (2013‐2022) at Leka Dulecha Health Center, East Wollega Zone, Western Oromia. Methodology. A retrospective study was conducted at Leka Dulecha Health Center to determine the trends of malaria prevalence by considering the malaria registration laboratory logbook for the last ten years from 2013 to 2022. Hence, to do this, sociodemographic data, years, months, and malaria prevalence were collected using a predesigned data collection sheet recorded from perspective between years. Results. In the last ten years, a total of 30,576.00 suspected malaria cases were examined at Leka Dulecha Health Center, and out of these, 7,413.00 (24.24%) confirmed malaria cases were reported. In this health center, malaria cases were reported among both sexes and all age categories, but male (3,951.00, 54%) and age groups ≥ 15 years (3,994, 54%) were the most affected. The highest peak of malaria cases was reported during the autumn season (September, October, and November) followed by the spring season (March, April, and May) in the years of 2013 and 2007. In this study, the prevalence of malaria species was identified as Plasmodium falciparum, Plasmodium vivax, and mixed cases, with 5,014 (68%), 1,123 (15%), and 1,848 (25%), while Plasmodium falciparum was reported as the highest recorded cases. Conclusion. Males and above 15 years old were more affected than the others. The highest peak malaria prevalence appeared from September to December of 2017 and 2013 years. Therefore, proper planning, implementation, and monitor of malaria prevention and control activities should be strengthened at all levels.
Determinants of Customer Loyalty toward Mobile Wallet Services in Post-COVID-19: The Moderating Role of Trust
Authors: Al-Hattami Hamood Mohammed , Al-Adwan Ahmad Samed , Abdullah Abdulwahid Ahmed Hashed , Al-Hakimi Mohammed A.
Published: August 2023

One of the highly acclaimed innovations is the mobile wallet. Mobile wallets ensure that customers can make purchases even if they forget their wallets at home. The use of these wallets has increased significantly with the spread of the COVID-19 pandemic as a preventive measure. However, with COVID-19 restrictions lifted and adaptation to the pandemic, customers are no longer forced to use mobile wallets. That is, things have returned to normal as before the pandemic, where the customer is left free to choose the method of payment. In this regard, businesses need to retain their customers and make sure that those customers will reuse their own mobile wallets even during this period (post-COVID-19). Hence, it is critical to explore customer loyalty determinants toward mobile wallet services in such a period. Therefore, using the Indian context, this paper sought to explore the determinants of customer loyalty toward mobile wallet services post-COVID-19. This study also investigated the role of trust as a moderator. Based on a sample size of 243 customers in India, the relationships in the proposed model were tested using SmartPLS statistical technology. The results revealed that service quality, privacy and security, and trust are the key determinants in gaining customer loyalty toward mobile wallets. Yet, the results did not support perceived usefulness and ease of use as determinants of customer loyalty. As for trust as a moderator, the results supported only one of the four proposed hypotheses. Specifically, the results supported that “trust has a significant moderating impact on the relationship between service quality and customer loyalty”. The results offer a more precise comprehension of the relationships between customer loyalty and customer loyalty determinants in post-COVID-19 and enable managers to make better management decisions.
The Genetic, Pharmacogenomic, and Immune Landscapes Associated with Protein Expression across Human Cancers
Authors: Chen Chengxuan , Liu Yuan , Li Qiang , Zhang Zhao , Luo Mei , Liu Yaoming , Han Leng
Published: August 2023

Proteomics is a powerful approach that can rapidly enhance our understanding of cancer development. Detailed characterization of the genetic, pharmacogenomic, and immune landscape in relation to protein expression in patients with cancer could provide new insights into the functional roles of proteins in cancer. By taking advantage of the genotype data from The Cancer Genome Atlas and protein expression data from The Cancer Proteome Atlas, we characterized the effects of genetic variants on protein expression across 31 cancer types and identified approximately 100,000 protein quantitative trait loci (pQTL). Among these, over 8000 pQTLs were associated with patient overall survival. Furthermore, characterization of the impact of protein expression on more than 350 imputed anticancer drug responses in patients revealed nearly 230,000 significant associations. In addition, approximately 21,000 significant associations were identified between protein expression and immune cell abundance. Finally, a user-friendly data portal, GPIP (https://hanlaboratory.com/GPIP), was developed featuring multiple modules that enable researchers to explore, visualize, and browse multidimensional data. This detailed analysis reveals the associations between the proteomic landscape and genetic variation, patient outcome, the immune microenvironment, and drug response across cancer types, providing a resource that may offer valuable clinical insights and encourage further functional investigations of proteins in cancer.

Significance:

Comprehensive characterization of the relationship between protein expression and the genetic, pharmacogenomic, and immune landscape of tumors across cancer types provides a foundation for investigating the role of protein expression in cancer development and treatment.
Protein Exaptation by Endogenous Retroviral Elements Shapes Tumor Cell Senescence and Downstream Immune Signaling
Authors: Walker Reddick R. , Chiappinelli Katherine B.
Published: August 2023

Cancer cell senescence in lung squamous cell carcinoma (LUSC) is associated with a poor response to chemotherapies and immunotherapies due to promotion of an immunosuppressive tumor microenvironment. This environment is shaped by the senescence-associated secretory pathway, which recruits suppressive immune cell populations. In a recent study, Attig and colleagues identified a transcription factor–activated molecular switch that circumvents cellular senescence through increased expression of the calbindin protein. A human endogenous retrovirus (HERV) sequence upstream of the calbindin gene, CALB1, promotes the transcription of an HERVH-CALB1 transcript through a splice event at the third CALB1 exon in a process known as protein exaptation. The KLF5 transcription factor mediates this transcriptional activity by binding at the HERVH sequence, subsequently initiating the chimeric HERVH-CALB1 transcription. This increased expression of calbindin reduces CXCL8 chemokine production and downstream neutrophil recruitment in LUSC tumor cells. CALB1 exaptation by HERVH is one example by which endogenous retroelements (ERE) regulate immunity in human cancers, highlighting the emerging role of EREs in tumor immunity.
Supplementary Data Tables from Niraparib for Advanced Breast Cancer with Germline BRCA1 and BRCA2 Mutations: the EORTC 1307-BCG/BIG5–13/TESARO PR-30–50–10-C BRAVO Study
Authors: Turner Nicholas C. , Balmaña Judith , Poncet Coralie , Goulioti Theodora , Tryfonidis Konstantinos , Honkoop Aafke H. , Zoppoli Gabriele , Razis Evangelia , Johannsson Oskar T. , Colleoni Marco , Tutt Andrew N. , Audeh William , Ignatiadis Michail , Mailliez Audrey , Trédan Olivier , Musolino Antonino , Vuylsteke Peter , Juan-Fita Maria Jose , Macpherson Iain R.J. , Kaufman Bella , Manso Luis , Goldstein Lori J. , Ellard Susan L. , Láng István , Jen Kai Yu , Adam Virginie , Litière Saskia , Erban John , Cameron David A.
Published: August 2023

supplementary data tables
Supplementary Table S3 from Development and validation of a 15-gene expression signature with superior prognostic ability in stage II colorectal cancer
Authors: Rokavec Matjaž , Özcan Elif , Neumann Jens , Hermeking Heiko
Published: August 2023

Supplementary Table S3 shows a summary and performance of prognostic signatures in CRC patient cohorts.
Supplementary Fig 8 from Whole genome CpG-resolution DNA methylation profiling of HNSCC reveals distinct mechanisms of carcinogenesis for fine-scale HPV+ cancer subtypes
Authors: Qin Tingting , Li Shiting , Henry Leanne E , Chou Elysia , Cavalcante Raymond G , Garb Bailey F , D'Silva Nisha J. , Rozek Laura S. , Sartor Maureen A
Published: August 2023

(A-D) MIRA profiles of strong and weak enhancers in the NHEK cell line (A), JunD binding sites in the K562 cell line (B), NFKB binding sites in the GM10847 cell line, and STAT3 binding sites in the HeLaS3 cell line (D) Samples are colored by HPV tumor subtype. (E) Correlations between CTCF MIRA scores and Strong Enhancer MIRA scores. (F) Box plot of MIRA scores separated by subtype for EZH2 binding sites and JunB binding sites from NHEK and K562 cell lines, respectively. (G) Correlations between JunD MIRA scores and gene expression-based keratinization scores. All scatter plots separate subtype by color and display the Pearson correlation coefficient (R) along with the corresponding p-value.
Supplementary Fig 7 from Whole genome CpG-resolution DNA methylation profiling of HNSCC reveals distinct mechanisms of carcinogenesis for fine-scale HPV+ cancer subtypes
Authors: Qin Tingting , Li Shiting , Henry Leanne E , Chou Elysia , Cavalcante Raymond G , Garb Bailey F , D'Silva Nisha J. , Rozek Laura S. , Sartor Maureen A
Published: August 2023

Methylation and expression profiles of the eleven genes that are hypermethylated in TCGA HNSC tumor vs normal, and hypermethylated in KRT vs IMU shown in Figure 5C.
Supplementary Fig 6 from Whole genome CpG-resolution DNA methylation profiling of HNSCC reveals distinct mechanisms of carcinogenesis for fine-scale HPV+ cancer subtypes
Authors: Qin Tingting , Li Shiting , Henry Leanne E , Chou Elysia , Cavalcante Raymond G , Garb Bailey F , D'Silva Nisha J. , Rozek Laura S. , Sartor Maureen A
Published: August 2023

Methylation and expression visualization of the genes selected from the 108 genes previously reported as differentially methylated in HPV(+) compared to HPV(-) HNSCC.
Supplementary Table 2 from Exploring the Onset and Progression of Prostate Cancer through a Multicellular Agent-based Model
Authors: Passier Margot , van Genderen Maisa N.G. , Zaalberg Anniek , Kneppers Jeroen , Bekers Elise M. , Bergman Andries M. , Zwart Wilbert , Eduati Federica
Published: August 2023

List of model parameters
Whole-genome CpG-resolution DNA Methylation Profiling of HNSCC Reveals Distinct Mechanisms of Carcinogenesis for Fine-scale HPV+ Cancer Subtypes
Authors: Qin Tingting , Li Shiting , Henry Leanne E. , Chou Elysia , Cavalcante Raymond G. , Garb Bailey F. , D'Silva Nisha J. , Rozek Laura S. , Sartor Maureen A.
Published: August 2023

DNA methylation is a vital early step in carcinogenesis. Most findings of aberrant DNA methylation in head and neck squamous cell carcinomas (HNSCC) are array based with limited coverage and resolution, and mainly explored by human papillomavirus (HPV) status, ignoring the high heterogeneity of this disease. In this study, we performed whole-genome bisulfite sequencing on a well-studied HNSCC cohort (n = 36) and investigated the methylation changes between fine-scaled HNSCC subtypes in relation to genomic instability, repetitive elements, gene expression, and key carcinogenic pathways. The previously observed hypermethylation phenotype in HPV-positive (HPV+) tumors compared with HPV-negative tumors was robustly present in the immune-strong (IMU) HPV+ subtype but absent in the highly keratinized (KRT) HPV+ subtype. Methylation levels of IMU tumors were significantly higher in repetitive elements, and methylation showed a significant correlation with genomic stability, consistent with the IMU subtype having more genomic stability and better prognosis. Expression quantitative trait methylation (cis-eQTM) analysis revealed extensive functionally-relevant differences, and differential methylation pathway analysis recapitulated gene expression pathway differences between subtypes. Consistent with their characteristics, KRT and HPV-negative tumors had high regulatory potential for multiple regulators of keratinocyte differentiation, which positively correlated with an expression-based keratinization score. Together, our findings revealed distinct mechanisms of carcinogenesis between subtypes in HPV+ HNSCC and uncovered previously ignored epigenomic differences and clinical implications, illustrating the importance of fine-scale subtype analysis in cancer.

Significance:

This study revealed that the previously observed hypermethylation of HPV(+) HNSCC is due solely to the IMU subtype, illustrating the importance of fine-scale subtype analysis in such a heterogeneous disease. Particularly, IMU has significantly higher methylation of transposable elements, which can be tested as a prognosis biomarker in future translational studies.
Association between Susceptibility to Systemic Lupus Erythematous and Polymorphisms in miR-146a and miR-499: A Meta-Analysis
Authors: Lee Young Ho , Song Gwan Gyu
Published: August 2023

Introduction: This study aimed to determine whether miR-146a and miR-499 polymorphisms are associated with susceptibility to systemic lupus erythematosus (SLE). Methods: We searched the MEDLINE, EMBASE, and Cochrane databases. We performed a meta-analysis on the association of miR-146a rs2910164, rs2431697, rs57095329, and miR-499 rs3746444 polymorphisms with susceptibility to SLE. Results: Twenty-one studies from 17 reports, with 18,910 patients and 29,622 controls, were included in the meta-analysis. Meta-analysis revealed no association between SLE and the rs2910164 C allele (odds ratio [OR] = 0.999, 95% confidence interval [CI] = 0.816–1.222, p = 0.990). Stratification by ethnicity indicated no association between the miR-146a C allele and SLE in Arab or Latin American populations. The meta-analysis revealed an association between SLE and the miR-499 rs374644 CC + CT genotype in the overall group (OR = 1.313, 95% CI = 1.015–1.698, p = 0.038). Furthermore, meta-analysis revealed a significant association between SLE and the miR-146a rs2431697 C allele in the overall group (OR = 0.746, 95% CI = 0.697–0.798, p = 0.038). The miR-146a rs2431697 C allele is protective against SLE risk. Stratification by ethnicity indicated an association between the miR-146a rs2431697 C allele and SLE in Asian and European, but not Arab populations. The meta-analysis showed an association between the miR-146a rs57095329 G allele and SLE in Asian, but not Arab populations. Discussion/Conclusion: This meta-analysis suggests that the miR-146a rs2431697 polymorphism is a protective factor against the risk of SLE, and that the miR-146a rs57095329 and miR-499 rs3746444 polymorphisms are associated with susceptibility to SLE. However, miR-146a rs2910164 was not associated with susceptibility to SLE.
IL-1β Derived Th17 Immune Responses Are a Critical Factor for Neutrophilic-Eosinophilic Airway Inflammation on Psychological Stress-Induced Immune Tolerance Breakdown in Mice
Authors: Sato Shinsuke , Kawano Tasuku , Ike Erina , Takahashi Kento , Sakurai Junji , Miyasaka Tomomitsu , Miyauchi Yasuo , Ishizawa Fumiaki , Takayanagi Motoaki , Takahashi Tomoko
Published: August 2023

Introduction: Asthma is an inflammatory reaction mediated by type 2 helper T (Th2) cells and is known to increase eosinophil levels. Our previous study showed that stress-related asthma can cause neutrophilic and eosinophilic airway inflammation by suppressing immune tolerance. However, the mechanism of stress-induced neutrophilic and eosinophilic airway inflammation remains unclear. Therefore, to elucidate the cause of neutrophilic and eosinophilic inflammation, we investigated the immune response during the induction of airway inflammation. In addition, we focused on the relationship between immune response modulation immediately after stress exposure and the development of airway inflammation. Methods: Asthmatic mice were induced by three phases using female BALB/c mice. During the first phase, the mice were made to inhale ovalbumin (OVA) to induce immune tolerance before sensitization. Some mice were exposed to restraint stress during the induction of immune tolerance. In the second phase, the mice were sensitized with OVA/alum intraperitoneal injections. In the final phase, onset of asthma was induced through OVA exposure. Asthma development was evaluated based on airway inflammation and T-cell differentiation. Microarray and qPCR analyses were used to enumerate candidate factors to investigate the starting point of immunological modification immediately after stress exposure. Furthermore, we focused on interleukin-1β (IL-1β), which initiates these immune modifications, and performed experiments using its receptor blocker interleukin-1 receptor antagonist (IL-1RA). Results: Stress exposure during immune tolerance induction increased eosinophil and neutrophil airway infiltration. This inflammation was associated with decreased T regulatory cell levels and increased Th2 and Th17 levels in bronchial lymph node cells. Microarray and qPCR analyses showed that the initiation of Th17 differentiation might be triggered by stress exposure during tolerance induction. IL-1RA administration during stress exposure suppressed neutrophilic and eosinophilic airway inflammation via Th17 reduction and Treg increase. Conclusions: Our results show that psychological stress causes both eosinophilic and neutrophilic inflammatory responses due to the breakdown of immune tolerance. Furthermore, stress-induced inflammation can be abolished using IL-1RA.