bluuebunny/crossref_metadata_2025 huggingface dataset:
URB597 attenuates stress-induced ventricular structural remodeling by modulating cytokines, NF-κB, and JAK2/STAT3 pathways in female and male rats
Authors: Ferizovic Harisa , Spasojevic Natasa , Puskas Nela , Stefanovic Bojana , Jankovic Milica , Djelic Ninoslav , Dronjak Sladjana
Published: May 2023

Endocannabinoids act as a stress response system; simultaneously, the modulation of this system has emerged a novel approach for the therapy of cardiovascular disorders. We investigated the protective effects of the chronic administration of the fatty acid amide hydrolase inhibitor URB597 on morphology, pro-inflammatory and anti-inflammatory cytokine, the cytoplasm-nuclear distribution of JAK2/STAT3, and NF-κB and Nrf2/HO-1 signaling in the left ventricle of female and male rats exposed to chronic unpredictable stress. Our results show that URB597 treatment exhibits an antidepressant-like effect, decreases the heart/body weight ratio, prevents the hypertrophy of cardiomyocytes, and reduces the increased level of IL-6 in the wall of the left ventricle of stressed female and male rats. The phosphorylation levels of JAK2 and STAT3 in the ventricle of male rats treated with URB597 were declined, whereas in female rats the decrease of STAT3 was observed. In addition, URB597 reduced increased NF-κB in both females and males and increased the expression of Nrf2 and HO-1 protein in the cytosol of male rats, whereas did not affect their levels in females. Cardioprotective effects of URB597 could be linked to the ability to inhibit the JAK2 in males and the STAT3 inflammatory signaling pathways in both females and males.
Application of climate change scenarios in the simulation of forest ecosystems: an overview
Authors: Liu Haoyun , Li Peng , Peng Changhui , Liu Cong , Zhou Xiaolu , Deng Zhengmiao , Zhang Cicheng , Liu Zelin
Published: May 2023

Climate change scenarios established by the Intergovernmental Panel on Climate Change have developed a significant tool for analyzing, modeling, and predicting future climate change impacts in different research fields after more than 30 years of development and refinement. In the wake of future climate change, the changes in forest structure and functions have become a frontier and focal area of global change research. This study mainly reviews and synthesizes climate change scenarios and their applications in forest ecosystem research over the past decade. These applications include changes in (1) forest structure and spatial vegetation distribution, (2) ecosystem structure, (3) ecosystem services, and (4) ecosystem stability. Although climate change scenarios are useful for predicting future climate change impacts on forest ecosystems, the accuracy of model simulations needs to be further improved. Based on existing studies, climate change scenarios are used in future simulation applications to construct a biomonitoring network platform integrating observations and predictions for better conservation of species diversity.
Quantum coherence and entanglement in neutral-current neutrino oscillation in matter
Authors: Ettefaghi M. M. , Ravari Z. Askaripour
Published: May 2023

Although neutrino–antineutrino states originating from neutral-current interactions are blind concerning the flavor state, an oscillation pattern is predicted provided that both neutrino and antineutrino are detected. This issue arises from both the coherence and entanglement of the neutrino–antineutrino states. Based on quantum resource theory, we use the $$l_1$$

l
1

-norm and concurrence to quantify quantum coherence and entanglement, respectively. Considering the localization properties by the wave packet approach and a matter potential which appears when neutrino and antineutrino propagate in a material medium, we obtain the $$l_1$$

l
1

-norm and concurrence. We see that the neutrino and antineutrino remain entangled for larger baseline lengths when they propagate in a material medium. In the case of the coherence property, the $$l_1$$

l
1

-norm decreases in comparison to the corresponding one in vacuum. However, its damping occurs for larger distances.
Community-based influence maximization in social networks under a competitive linear threshold model considering positive and negative user views
Authors: Bagheri Esmaeil , Mirtalaei Reyhaneh Sadat
Published: May 2023

Social networks are a collection of people or groups and interactions between them, which can include friendship activities or business relationships, and they play an important role in spreading information and maximizing influence on users. The effect of social networks in our daily life is undeniable and it shows new methods of communication and is used as a medium to spread news, opinions, thoughts and any other kind of information. The main goal in influence maximization is to find a subset of key users that maximize influence expansion under a particular diffusion model. A number of studies over the past several years have tried to solve this problem by considering a nonracist environment where there is only one player without competitors, whereas in the real world, there is always more than one player competing with other players. To influence most nodes, this problem is called competitive influence maximization (CIM). Therefore, we try to solve the problem of maximizing the competitive influence by proposing a new diffusion model, considering two positive and negative views towards advertising, which is an extension of the linear threshold (LT) model with the ability to decide on the expansion of input influence and leads to an improvement in selecting seeds with better quality and also by extracting the community structure from the input graph, it is used to calculate the expansion of each node locally within its own community, and by preventing the repetition of penetration calculations for each node, it significantly reduces the execution time. The purpose of the proposed algorithm is to find the minimum number of seed nodes that can achieve more expansion compared to the expansion of nodes selected by other competitors in an acceptable execution time. Real-world experiments and synthetic datasets show that the proposed approach can obtain the minimum node required to defeat the competitor more realistically and in less time. Competitor leads to budget cuts by reducing the number of seeds required to defeat. The obtained results show that if [Formula: see text] seed nodes are needed to defeat the competitor, the execution time of the proposed algorithm will be approximately [Formula: see text].
DOES ANTI-CORRUPTION FACILITATE OR HINDER TECHNOLOGICAL INNOVATION?
Authors: ZHAO QIAN , SU CHI-WEI
Published: May 2023

Innovation is a major economic growth contributor, which is often hindered by corruption. However, this relationship is not always supported. This study analyzes the interrelation between anti-corruption (AC) and technological innovation (TI) in China by applying the bootstrap rolling-window full-sample and subsample Granger causality test. The results confirm that the influence of AC on TI is two-fold. On the one hand, AC positively influences TI, indicating that it facilitates TI. This finding supports the “sanding-the-wheels” hypothesis, which postulates that corruption impedes innovation. On the other hand, there is a negative influence from AC to TI, which is mainly caused by the COVID-19 pandemic. Further, the results show that TI positively influences AC, implying that TI can affect government’s AC-related decisions. Based on these findings, governments should coordinate their efforts toward innovation and AC, while firms should adopt innovation-driven strategies for long-term growth.
Design and Simulation of a Novel 16T SRAM Cell for Low Power Memory Architecture
Authors: Nagarajan P. , Renuga M. , Manikandan A. , Dhanasekaran S.
Published: May 2023

Static random access memory (SRAM) is a sort of RAM where information is not permanently stored and does not require routine updating. To reduce leakage power without sacrificing performance, a variety of approaches have been applied to SRAM cells. In this study, we suggest a new 16T SRAM design that can function in active, park, standby, or hold modes. A fully static mode of operation for SRAM is made possible by the 16T SRAM structure, which also enhances write margin (WM) and removes charging conflict between devices during read and write operations. The key objectives of the suggested architecture are to retain logic state in park mode while maintaining stability and reducing standby time in active mode, as well as to reduce leakage current in standby mode. This is done by removing feedback from the back-to-back inverters during write operations via the data-dependent supply block. This makes it possible for the suggested bitcell to considerably increase the WM. A novel SRAM cell with 16 transistors is created with subthreshold operation and enhanced data stability. By using an equalized bit line technique to avoid leakage due to enhanced data pattern and RBL detection, the suggested single-ended SRAM cell with dynamic feedback control lowers the static noise margin for ultra-low power transfer. A sleep transistor is incorporated into the architecture to save power consumption when the system is in standby mode due to inefficient voltage transmission. Tanner EDA tool V.14.1 on 45-nm CMOS was used for design and simulation. The outcomes demonstrate a considerable decrease in no-load current and power loss.
Recollements and Φ-Cohen–Macaulay Auslander–Yoneda algebras
Authors: Qin Yongyun
Published: May 2023

It is shown that a [Formula: see text]-recollement of derived categories of algebras induces a [Formula: see text]-recollement of the corresponding [Formula: see text]-Cohen–Macaulay Auslander–Yoneda algebras. This result not only generalizes the main theorems of Pan [Derived equivalences for [Formula: see text]-Cohen–Macaulay Auslander–Yoneda algebras, Algebr. Represent. Theory 17 (2014) 885–903] and Pan [Derived equivalences for Cohen–Macaulay Auslander algebras, J. Pure Appl. Algebra 216 (2012) 355–363], but also provides us a useful method to construct a new recollement of derived module categories from a given one.
APPLICATION AND ANALYSIS OF CUSTOMIZED BONE GRAFT OF A PATIENT UNDERGOING MANDIBLE AUGMENTATION AND DENTAL IMPLANTATION
Authors: GHADERZADEH OMID , KATOOZIAN HAMID REZA , BAYAT MOHAMMAD , BAHRAMI NAGHMEH , JAFARI BAHRAM
Published: May 2023

The mandibular bone may be damaged for a variety of reasons. One of the methods used to facilitate and stimulate the bone to improve hard tissue formation is the use of bone grafts. In this study, a novel methodology was introduced to take a step towards making a custom xenograft for a patient with a mandibular bone defect. The application of the finite element method and evaluation of the graft simulation results was proposed, then the customized xenograft was provided using micro-milling. Also, 3D printing technology was used as a preoperative assessment of bone-graft interface conformity. Afterward, the graft was implemented for mandibular augmentation and the patient was prepared for further dental implantation. Finally, cone-based computer tomography images in different time intervals were taken for clinical assessment. Results showed that six months after the graft placement, the vertical distance from the alveolar ridge to the incisive canal and the mandibular canal was increased by 261% and 250%, respectively. Furthermore, the images taken after the insertion of dental implants and frequent observations by the dental surgeon approved the success of the treatment. Additionally, several quantitative parameters were compared to and established with the previous literature. Combining the conventional clinical examination method with an initial computational simulation by the criteria proposed in this study aided in predicting the success of mandibular augmentation and the subsequent dental implantation. More numerical analysis criteria can be added and assessed in future studies to improve the proposed method.
A NON-INVASIVE METHOD TO RECONSTRUCT PATIENT-SPECIFIC HUMAN FEMUR WITH IN-SITU DRILLING TEMPERATURE DATA USING PROBABILITY DENSITY FUNCTION
Authors: PANDITHEVAN PONNUSAMY , PRASANNAVENKADESAN VARATHARAJAN
Published: May 2023

Drilling through bone is widely performed in orthopedic surgeries to fix the plate and implant using bone screws. Clinical observation revealed that the mechanical and thermal damages driven by the uncontrolled drilling operations loosen the implants soon after their fixations. During fracture treatment and reconstruction surgery, the quality of the hole generated is to be considered as an important metric, and therefore drill feed rate and spindle speed, apparent bone density, drill bit geometry, and skill of the surgeon are the parameters to influence the success of the bone drilling procedure. The generation of temperature due to the conversion of mechanical work around the osteotomy site leads to irreversible thermal damage to the bone tissue, when it exceeds 47∘C. So, a non-invasive method which can identify the probability to not get a thermal osteonecrosis at the chosen drill spot can help the surgeon to strongly fix the implant around the defect site. To make this happen, the in-situ bone temperatures measured in the earlier study when drilling with a 3.20[Formula: see text]mm diameter drill bit was used for the investigation. As a procedure, the test statistics and critical test statistics values were calculated, and found that the log normal and gamma density functions could best describe the bone drilling temperatures, when drilling in the radial and circumferential directions, respectively. Additionally, the CT data sets of the patient-specific femur were used to reconstruct the bone both with geometry and drilling temperature data. The Kolmogrov–Smirnov test performed to check the validity of the temperature distribution models showed a good agreement with the experimental results. The outcomes of the method can help the surgeon to choose a suitable location for the strongest fixation using CT data sets of the patient as the only input.
EPILEPTIC EEG SIGNALS RHYTHMS ANALYSIS IN THE DETECTION OF FOCAL AND NON-FOCAL SEIZURES BASED ON OPTIMISED MACHINE LEARNING AND DEEP NEURAL NETWORK ARCHITECTURE
Authors: SAMINU SANI , XU GUIZHI , SHUAI ZHANG , ABD EL KADER ISSELMOU , JABIRE ADAMU HALILU , AHMED YUSUF KOLA , KARAYE IBRAHIM ABDULLAHI , AHMAD ISAH SALIM
Published: May 2023

Objective: Most studies in epileptic seizure detection and classification focused on classifying different types of epileptic seizures. However, localization of the epileptogenic zone in epilepsy patient brain’s is paramount to assist the doctor in locating a focal region in patients screened for surgery. Therefore, this paper proposed robust models for the localization of epileptogenic areas for the success of epilepsy surgery. Method: Advanced feature extraction techniques were proposed as effective feature extraction techniques based on Electroencephalogram (EEG) rhythms extracted from Fourier Basel Series Expansion Multivariate Empirical Wavelet Transform (FBSE-MEWT). The proposed extracted EEG rhythms of [Formula: see text] and [Formula: see text] features were used to obtain a joint instantaneous frequency and amplitude components using a sub-band alignment approach. The features are used in Sparse Autoencoder (SAE), Deep Belief Network (DBN), and Support Vector Machine (SVM) with the optimized capability to develop three new models: 1. FMEWT–SVM 2. FMEWT_SAE–SVM, and 3. FMEWT–DBN–SVM. The EEG signal was preprocessed using a proposed Multiscale Principal Component Analysis (mPCA) to denoise the noise embedded in the signal. Main results: The developed models show a significant performance improvement, with the SAE–SVM outperforming other proposed models and some recently reported works in literature with an accuracy of 99.7% using [Formula: see text]-rhythms in channels 1 and 2. Significance: This study validates the EEG rhythm as a means of discriminating the embedded features in epileptic EEG signals to locate the focal and non-focal regions in the epileptic patient’s brain to increase the success of the surgery and reduce computational cost.
Design a Four-Bar Mechanism for Specific Upper Limb Muscle Strength Rehabilitation Using Genetic Algorithm
Authors: Quarnstrom Joel , Zaman Rahid , Xiang Yujiang
Published: May 2023

In this study, a novel human-in-the-loop design method using a genetic algorithm (GA) is presented to design a low-cost and easy-to-use four-bar linkage medical device for upper limb muscle rehabilitation. The four-bar linkage can generate a variety of coupler point trajectories by using different link lengths. For this medical device, patients grab the coupler point handle and rotate the arm along the designed coupler point trajectory to exercise upper limb muscles. The design procedures include three basic steps: First, for a set of link lengths, a complete coupler point trajectory is generated from four-bar linkage kinematics; second, optimization-based motion prediction is utilized to predict arm motion (joint angle profiles) subjected to hand grasping and joint angle limit constraints; third, the predicted joint angles and given hand forces are imported into an OpenSim musculoskeletal arm model to calculate the muscle forces and activations by using the OpenSim static optimization. In the GA optimization formulation, the design variables are the four-bar link lengths. The objective function is to maximize a specific muscle’s exertion for a complete arm rotation. Finally, different four-bar configurations are designed for different muscle strength exercises. The proposed human-in-the-loop design approach successfully integrates GA with linkage kinematics, arm motion prediction, and OpenSim static optimization for four-bar linkage design for upper limb muscle strength rehabilitation.
Analysis of the Dynamic Response of Oil and Gas Long-Distance Pipelines Under Multipoint Excitation of Different Seismic Intensities
Authors: Wang Zhaocheng , Dai Jianbo , Wang Hao , Wang Zhiqiang , Zhu Jiang
Published: May 2023

In this study, a pipe-soil finite element analysis model was built using the shaking table test results of buried pipelines that were achieved through longitudinal multipoint excitation and multipoint excitation under different seismic intensities, so as to numerically simulate the seismic response of buried pipelines under longitudinal multipoint excitation and multipoint excitation under different seismic intensities. As indicated by the result of this study, the numerical calculations and the shaking table test findings in terms of long-distance oil and gas pipelines under longitudinal multipoint stimulation were well consistent, such that the validity of both sets of results was verified. The peak pipe stresses during the multipoint excitation under different seismic intensities declined by 13.8% to 30.9% compared with case 2 longitudinal multipoint stimulation. The acceleration of the pipe and the soil was reduced rapidly as the measuring point moved farther away from the pipe’s leftmost distance. The displacement variation of the oil and gas pipelines under longitudinal multipoint excitation suggested that the soil displacement was increased with the length of the monitoring point from the bottom of the soil box for different elevations of the same section. The soil displacement declined notably for the same stretch at the identical elevation with the reduction of seismic intensity. The findings of this study can lay a basis for in-depth research on the effect of multipoint stimulation with different seismic powers on the seismic response of underground pipes.
Microwave-induced thermoacoustic elastic imaging: A simulation study
Authors: Huang Lin , Liang Zheng , Qiao Shuaiqi , Wang Weipeng
Published: May 2023

Microwave-induced thermoacoustic imaging (MTI) has the advantages of high resolution, high contrast, non-ionization, and non-invasive. Recently, MTI was used in the field of breast cancer screening. In this paper, based on the finite element method (FEM) and COMSOL Multiphysics software, a three-dimensional breast cancer model suitable for exploring the MTI process is proposed to investigate the influence of Young’s modulus (YM) of breast cancer tissue on MTI. It is found that the process of electromagnetic heating and initial pressure generation of the entire breast tissue is earlier in time than the thermal expansion process. Besides, compared with normal breast tissue, tumor tissue has a greater temperature rise, displacement, and pressure rise. In particular, YM of the tumor is related to the speed of thermal expansion. In particular, the larger the YM of the tumor is, the higher the heating and contraction frequency is, and the greater the maximum pressure is. Different Young’s moduli correspond to different thermoacoustic signal spectra. In MTI, this study can be used to judge different degrees of breast cancer based on elastic imaging. In addition, this study is helpful in exploring the possibility of microwave-induced thermoacoustic elastic imaging (MTAE).
Classification of Alzheimer's using Deep-learning Methods on Webcam-based Gaze Data
Authors: Harisinghani Anuj , Sriram Harshinee , Conati Cristina , Carenini Giuseppe , Field Thalia , Jang Hyeju , Murray Gabriel
Published: May 2023

There has been increasing interest in non-invasive predictors of Alzheimer's disease (AD) as an initial screen for this condition. Previously, successful attempts leveraged eye-tracking and language data generated during picture narration and reading tasks. These results were obtained with high-end, expensive eye-trackers. Instead, we explore classification using eye-tracking data collected with a webcam, where our classifiers are built using a deep-learning approach. Our results show that the webcam gaze classifier is not as good as the classifier based on high-end eye-tracking data. However, the webcam-based classifier still beats the majority-class baseline classifier in terms of AU-ROC, indicating that predictive signals can be extracted from webcam gaze tracking. Hence, although our results indicate that there is still a long way to go before webcam gaze tracking can reach practical relevance, they still provide an encouraging proof of concept that this technology should be further explored as an affordable alternative to high-end eye-trackers for the detection of AD.
DynamicRead: Exploring Robust Gaze Interaction Methods for Reading on Handheld Mobile Devices under Dynamic Conditions
Authors: Lei Yaxiong , Wang Yuheng , Caslin Tyler , Wisowaty Alexander , Zhu Xu , Khamis Mohamed , Ye Juan
Published: May 2023

Enabling gaze interaction in real-time on handheld mobile devices has attracted significant attention in recent years. An increasing number of research projects have focused on sophisticated appearance-based deep learning models to enhance the precision of gaze estimation on smartphones. This inspires important research questions, including how the gaze can be used in a real-time application, and what type of gaze interaction methods are preferable under dynamic conditions in terms of both user acceptance and delivering reliable performance. To address these questions, we design four types of gaze scrolling techniques: three explicit technique based on Gaze Gesture, Dwell time, and Pursuit; and one implicit technique based on reading speed to support touch-free, page-scrolling on a reading application. We conduct a 20-participant user study under both sitting and walking settings and our results reveal that Gaze Gesture and Dwell time-based interfaces are more robust while walking and Gaze Gesture has achieved consistently good scores on usability while not causing high cognitive workload.
G-DAIC: A Gaze Initialized Framework for Description and Aesthetic-Based Image Cropping
Authors: Horanyi Nora , Hou Yuqi , Leonardis Ales , Chang Hyung Jin
Published: May 2023

We propose a new gaze-initialised optimisation framework to generate aesthetically pleasing image crops based on user description. We extended the existing description-based image cropping dataset by collecting user eye movements corresponding to the image captions. To best leverage the contextual information to initialise the optimisation framework using the collected gaze data, this work proposes two gaze-based initialisation strategies, Fixed Grid and Region Proposal. In addition, we propose the adaptive Mixed scaling method to find the optimal output despite the size of the generated initialisation region and the described part of the image. We address the runtime limitation of the state-of-the-art method by implementing the Early termination strategy to reduce the number of iterations required to produce the output. Our experiments show that G-DAIC reduced the runtime by 92.11%, and the quantitative and qualitative experiments demonstrated that the proposed framework produces higher quality and more accurate image crops w.r.t. user intention.
Investigating Privacy Perceptions and Subjective Acceptance of Eye Tracking on Handheld Mobile Devices
Authors: Alsakar Noora , Abdrabou Yasmeen , Stumpf Simone , Khamis Mohamed
Published: May 2023

Although eye tracking brings many benefits to users of mobile devices and developers of mobile applications, it poses significant privacy risks to both: the users of mobile devices, and the bystanders that surround users, are within the front-facing camera's field of view. Recent research demonstrates that tracking an individual's gaze reveals personal and sensitive information. This paper presents an investigation of the privacy perceptions and the subjective acceptance of users towards eye tracking on handheld mobile devices. In a four-phase user study (N=17), participants used a smartphone eye tracking app, were interviewed before and after viewing a video showing the amount of sensitive and personal data that could be derived from eye movements, and had their privacy concerns measured. Our findings 1) show factors that influence users' and bystanders' attitudes toward eye tracking on mobile devices such as the algorithms' transparency and the developers' credibility and 2) support designing mechanisms to allow for privacy-aware eye tracking solutions on mobile-devices.
(Mis)Matching Metadata: Improving Accessibility in Digital Visual Archives through the EyCon Project
Authors: Aske Katherine , Giardinetti Marina
Published: May 2023

Discussing the current AHRC/LABEX-funded EyCon (Early Conflict Photography 1890–1918 and Visual AI) project, this article considers potentially problematic metadata and how it affects the accessibility of digital visual archives. The authors deliberate how metadata creation and enrichment could be improved through Artificial Intelligence (AI) tools and explore the practical applications of AI-reliant tools to analyze a large corpus of photographs and create or enrich metadata. The amount of visual data created by digitization efforts is not always followed by the creation of contextual metadata, which is a major problem for archival institutions and their users, as metadata directly affects the accessibility of digitized records. Moreover, the scale of digitization efforts means it is often beyond the scope of archivists and other record managers to individually assess problematic or sensitive images and their metadata. Additionally, existing metadata for photographic and visual records are presenting issues in terms of outdated descriptions or inconsistent contextual information. As more attention is given to the creation of accessible digital content within archival institutions, we argue that too little is being given to the enrichment of record data. In this article, the authors ask how new tools can address incomplete or inaccurate metadata and improve the transparency and accessibility of digital visual records.
Local Search For Satisfiability Modulo Integer Arithmetic Theories
Authors: Cai Shaowei , Li Bohan , Zhang Xindi
Published: May 2023

Satisfiability Modulo Theories (SMT) refers to the problem of deciding the satisfiability of a formula with respect to certain background first-order theories. In this article, we focus on Satisfiablity Modulo Integer Arithmetic, which is referred to as SMT(IA), including both linear and non-linear integer arithmetic theories. Dominant approaches to SMT rely on calling a CDCL-based SAT solver, either in a lazy or eager flavour. Local search, a competitive approach to solving combinatorial problems including SAT, however, has not been well studied for SMT. We develop the first local-search algorithm for SMT(IA) by directly operating on variables, breaking through the traditional framework. We propose a local-search framework by considering the distinctions between Boolean and integer variables. Moreover, we design a novel operator and scoring functions tailored for integer arithmetic, as well as a two-level operation selection heuristic. Putting these together, we develop a local search SMT(IA) solver called LocalSMT. Experiments are carried out to evaluate LocalSMT on benchmark sets from SMT-LIB. The results show that LocalSMT is competitive and complementary with state-of-the-art SMT solvers, and performs particularly well on those formulae with only integer variables. A simple sequential portfolio with Z3 improves the state-of-the-art on satisfiable benchmark sets from SMT-LIB.
User Experience and the Role of Personalization in Critiquing-Based Conversational Recommendation
Authors: Rana Arpit , Sanner Scott , Bouadjenek Mohamed Reda , Di Carlantonio Ronald , Farmaner Gary
Published: May 2023

Critiquing—where users propose directional preferences to attribute values—has historically been a highly popular method for conversational recommendation. However, with the growing size of catalogs and item attributes, it becomes increasingly difficult and time-consuming to express all of one’s constraints and preferences in the form of critiquing. It is found to be even more confusing in case of critiquing failures: when the system returns no matching items in response to user critiques. To this end, it would seem important to combine a critiquing-based conversational system with a personalized recommendation component to capture implicit user preferences and thus reduce the user’s burden of providing explicit critiques. To examine the impact of such personalization on critiquing, this article reports on a user study with 228 participants to understand user critiquing behavior for two different recommendation algorithms: (i)
non-personalized
, that recommends any item consistent with the user critiques; and (ii)
personalized
, which leverages a user’s past preferences on top of user critiques. In the study, we ask users to find a restaurant that they think is the most suitable to a given scenario by critiquing the recommended restaurants at each round of the conversation on the dimensions of price, cuisine, category, and distance. We observe that the
non-personalized
recommender leads to more critiquing interactions, more severe critiquing failures, overall more time for users to express their preferences, and longer dialogs to find their item of interest. We also observe that
non-personalized
users were less satisfied with the system’s performance. They find its recommendations less relevant, more unexpected, and somewhat equally diverse and surprising than those of
personalized
ones. The results of our user study highlight an imperative for further research on the integration of the two complementary components of
personalization
and
critiquing
to achieve the best overall user experience in future critiquing-based conversational recommender systems.
Analytical Modelling and Simulation of Graphene Based Biosensor to Detect SARS-COV-2 from Aerosal Particles
Authors: Gifta G. , Jebalin I. V.Binola K. , Franklin S. Angen , Rani D. Gracia Nirmala , Nirmal D.
Published: May 2023

The health sector is focusing on the wellness of the society, is advancing in the phases of diagnosis and treatment. Biosensors based devices are used to diagnose a variety of human diseases. Recently, there was a sudden hike in the human mortality rate by chronic diseases caused by mutants of SARS-COV-2, on global scale. It is important to detect these kinds of diseases on an early stage to reduce the risk of spreading. For the analysis of Covid-19 influenza, tests such as Rapid Antigen Test (RAT), True NAT, CBNAAT and the commonly done RPT PCR were utilised. This proposal describes a non-invasive, quick and practical method for sensing the at-risk or infected persons with SARS-COV-2, aiming at controlling the epidemic. The proposed method employs a breath sensing device consisting of a Graphene Field Effect Transistor biosensor which can identify disease-specific biomarkers from exhaled sniff, hence allowing speedy and precise detection. This test aids screening of large populations as it is simple and quick and emerges as a promising candidate for SARS-COV-2 tests due to a high sensitivity. This work justifies the accurate diagnosis of Severe Acute Respiratory Syndrome COV 2 from aerosol particles by GFET Biosensor.
Review—Sustainable Biomass-Derived Carbon Materials for Energy Storage Applications
Authors: Akshay  , Srikanth Vadali Venkata Satya Siva
Published: May 2023

The world is rapidly moving towards growth, and energy has been a noteworthy aspect of achieving growth. Rapid growth has also led to the over-exploitation of the environment to meet energy demands. Natural resources such as coal, petroleum, and natural gas are rapidly depleting to fulfill the energy demands. Using natural resources has also increased pollution; consequently, detrimental climate change is knocking at our door. Many countries are trying to follow the Paris agreement to control the Earth’s rising temperature. One of the ways to achieve this is to utilize renewable resources for energy generation and storage. In this context, biomass waste is a sustainable resource for producing energy storage materials. The intangible outcomes of doing so are effectively recycling the waste and reducing pollution, which is the consequence of the uncontrolled burning of biomass waste. In this review, wide-ranging scrutiny has been done to showcase biomass-derived carbon materials as suitable electrode materials for supercapacitors, fuel for catalytic activity in fuel cells, anode materials for batteries, and excellent supporting material for shape stabilizing the phase change material for thermal heat storage applications.
Impact of rGO Concentration on the Physical Characteristics of CuO/rGO Nanocomposite for Sensing and Optoelectronic Applications
Authors: Banotra Arun , Singh Vishal , Khan Saleem , Parihar Usha , Singh Ajay , Gautam Seema , Sharma Sanjeev K. , Furukawa Hidemitsu , Khosla Ajit
Published: May 2023

Facile synthesis demonstrated formation of CuO/rGO composite for enhanced optical and electrical characteristics for sensing and photonic devices. CuO nanoparticles synthesized using sol-gel method and various rGO percentages (10%–30%) were loaded to form composite via ultra-sonic assisted technique. Structural study using XRD and TEM confirms the formation of CuO polyhedral nanoparticles with monoclinic structure showing deviations in the unit cell parameters, crystallite size, axis strain. These deviations cause transformation of polyhedral particles into rod shaped nanocomposites with embedded CuO single crystals with changed rGO. X-ray photoelectron spectroscopy showed varied elemental composition of CuO/rGO nanocomposites having Cu2+ chemical state. Optical measurements exhibit modified direct (1.54 eV–1.51 eV) and indirect bandgap (1.38 eV–1.31 eV) having higher absorption in Visible to NIR region for photovoltaic applications. Raman spectroscopy and FTIR confirms the presence of Raman active bands and functional groups corresponding to Cu-O. Electrical measurements shows decreased resistance with increased incorporation of rGO. The higher presence of oxygen sites and low resistance facilitate easy electron transport alongwith an optimum bandgap (1.51 eV) and higher absorption in Visible to NIR region showed possible utility of the grown nanoparticles and composites in gas/photo sensing and optoelectronic applications.
Simultaneous Switching Noise Effects in Graphene-Based Power Distribution Networks
Authors: Kumar Vobulapuram Ramesh
Published: May 2023

The simultaneous switching noise (SSN) effects in graphene nanoribbon field effect transistor (GNRFET) based ternary circuits are presented in this study. The performance in terms of SSN induced peak noise and propagation delay on power and ground rails are investigated in multilayer graphene nanoribbon (MLGNR) bundled power interconnects using Hewlett simulation program with integrated circuit emphasis (HSPICE) simulator. Furthermore, these investigations are compared to the copper (Cu) and multiwalled carbon nanotubes (MWCNT) based power interconnects. From the results, it is noticed that the proposed MLGNR interconnects shows performance improvements up to 74.9% and 33.8% over the Cu and MWCNT interconnects. Moreover, the SSN peak noise and delay are investigated for different interconnect lengths from 200 μm to 500 μm. It is observed that the SSN noise on power and ground rail is reduced and propagation delay is increased as interconnect length is increased.
Hands-on nephron activity during lecture of urine formation
Authors: Lehman Tom
Published: May 2023

A straightforward activity for students to demonstrate the steps of urine formation and apply it to clinical relevance, this easy-to-develop activity is utilized during lecture for students to tactically “see” how the various parts of the nephron function.
Prevalence and Associated Factors of Intestinal Parasites among Food Handlers Working in Food Service Establishments in Northwest Ethiopia, 2022
Authors: Wondimu Hailegebriel , Mihret Mestawut
Published: May 2023

Background. As in most of African countries, intestinal parasites have been widely distributed in Ethiopia and are among the 10 top causes of morbidity and mortality nationwide. Statistics for food-borne illness in various industrialized countries show that up to 60% of cases may be caused by poor food handling techniques and by contaminated food served in food service establishments. Epidemiological information on the prevalence of various intestinal parasitic infections in different regions/localities is a prerequisite to develop appropriate strategies. Objective. This study aimed to determine the magnitude of intestinal parasites among food handlers working in different food service establishments in Gondar city. Methods. A cross-sectional study was conducted with food handlers working in different food service establishments in Gondar city. Stool samples were collected from 350 food handlers and processed using the formol-ether concentration method and then microscopically examined for intestinal parasitic infections. Pre-tested and structured questionnaire was used to study the socio-demographic characteristics of food handlers. Chi-square test and

p

-value were used to assess the associations between risk factors and the parasite isolation rate. The

p

-value ≤0.05 was considered as statistically significant. Results. Of the 350 food handlers, 160 (45.71%) had parasites. Among the isolated parasites, Ascaris lumbricoides was found to be the most prevalent parasite 35.63%, followed by hookworm 19.38%, Entamoeba histolytica/dispar 16.25%, Trichuris trichiura 10.00%, Strongyloides stercoralis 8.13%, Schistosoma mansoni 6.88%, and Cystoisospora belli, Hymenolepis nana, and Taenia species each accounting 1.25%. Conclusion. The result of the study indicated that the magnitude of intestinal parasitosis among food handlers working at different levels of food establishments in Gondar, Ethiopia, was found to be high. Being at lower educational level and inactive role of the town’s municipality are determined as a risk factor for parasitic positivity of food handlers.
Optimization Design of Mountain and Water Landscape of Traditional Mountain Village Based on New Robot Visual Technology
Authors: Jia Xinxin , Liu Ruixin , Qiao Zhi
Published: May 2023

The reasonable application of the random sampling consistent algorithm can be used to eliminate the theoretically possible error points and then complete the initial aiming pairing. The interior points obtained after this algorithm are used to estimate the relative adjacent poses of the new robot in the operation of the least squares method, so as to make certain improvements to the ICP (iterative closest point) algorithm, making it useful for accurate aiming pairing. Finally, by using the optimization method of G20, the posture of the new mobile robot relative to the adjacent position is optimized to a certain extent. In order to reasonably plan and design the landscape of mountain villages, this paper proposes the corresponding solution by analyzing the multidimensional value and landscape design data of traditional mountain villages, which not only needs to adapt to modern economic development but also needs to live in harmony with the natural ecological environment. Taking a village as a case for analysis, the village houses, roads, services, greening, ecology, and other aspects were reconstructed, and then, the detailed landscape design of the multimedia multidimensional resource village was analyzed and implemented.
Ring-Opening Polymerization of Lactones Catalyzed by Silicon-Based Lewis Acid
Authors: Nakayama Yuushou , Katagi Keiya , Tanaka Ryo , Shiono Takeshi
Published: May 2023

Many catalysts containing various elements at their active sites have been reported for the ring-opening polymerization (ROP) of cyclic esters. However, to our knowledge, silicon-based catalysts for ROP have never been reported. Here we report the ROP of cyclic esters and cyclic carbonates catalyzed by the derivatives of bis(perchlorocatecholato)silane (Si(catCl)2), which is a neutral silicon-based Lewis acid recently reported by Greb et al. The catalyst systems show high activity for the ROP of seven- and six-membered ring monomers such as ε-caprolactone, δ-valerolactone, and trimethylene carbonate to produce the polymers with molecular weights up to 32 kg/mol. The matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and nuclear magnetic resonance analysis of the obtained polymers indicates the predominant formation of cyclic polymers.
On the Characterization of Antineutrosophic Subgroup
Authors: Gayen Sudipta , Edalatpanah S. A. , Jha Sripati , Kumar Ranjan
Published: May 2023

This article gives some essential scopes to study the characterizations of the antineutrosophic subgroup and antineutrosophic normal subgroup. Again, several theories and properties have been mentioned which are essential for analyzing their mathematical framework. Moreover, their homomorphic properties have been discussed.
Protein Phosphatase 2A: Role in T Cells and Diseases
Authors: Roy Suyasha , Batra Lalit
Published: May 2023

Protein phosphatase 2A (PP2A) is a serine–threonine phosphatase that plays an important role in the regulation of cell proliferation and signal transduction. The catalytic activity of PP2A is integral in the maintenance of physiological functions which gets severely impaired in its absence. PP2A plays an essential role in the activation, differentiation, and functions of T cells. PP2A suppresses Th1 cell differentiation while promoting Th2 cell differentiation. PP2A fosters Th17 cell differentiation which contributes to the pathogenesis of systemic lupus erythematosus (SLE) by enhancing the transactivation of the Il17 gene. Genetic deletion of PP2A in Tregs disrupts Foxp3 expression due to hyperactivation of mTORC1 signaling which impairs the development and immunosuppressive functions of Tregs. PP2A is important in the induction of Th9 cells and promotes their antitumor functions. PP2A activation has shown to reduce neuroinflammation in a mouse model of experimental autoimmune encephalomyelitis (EAE) and is now used to treat multiple sclerosis (MS) clinically. In this review, we will discuss the structure and functions of PP2A in T cell differentiation and diseases and therapeutic applications of PP2A-mediated immunotherapy.
Parasitological and Bacteriological Evaluation of Common Raw Fruits Collected from Two Major Markets in Iwo, Osun State, South-West Nigeria
Authors: Oladosu Oladipo O. , Olatunde David O. , Olatayo Adewale O. , Atobatele Bukola
Published: May 2023

Background. Fruits are a vital part of human nutrition because they contain the growth factors required to maintain normal health. Fruits are also known to harbour a wide range of parasites and bacteria. Consumption of unwashed raw fruits can lead to foodborne pathogens. This study was carried out to examine the presence of parasites and bacteria on fruits sold at two major markets in Iwo, Osun state, South-West Nigeria. Methods. Twelve different fresh fruits and seven different fresh fruits were purchased from different vendors from “Odo-ori” and “Adeeke” markets, respectively. The samples were transported to the microbiology laboratory of Bowen University, Iwo, Osun state for bacteriological and parasitological analysis. The parasites were concentrated by sedimentation and were examined using a light microscope, while for the microbial analysis, culturing and biochemical tests were also carried out on all the samples. Results. The parasites discovered include Fasciola hepatica eggs, Ascaris lumbricoides and Strongyloides stercoralis larvae, hookworm larvae, and Taenia and Trichuris trichiura eggs. Ascaris lumbricoides was most frequently detected (40.0%). Bacteria isolated from the sampled fruits include Klebsiella oxytoca, Klebsiella pneumoniae, Enterobacter aerogenes, Escherichia coli, Kluyvera ascorbata, Proteus mirabilis, Staphylococcus intermedius, Staphylococcus sp., Micrococcus sedentarius, Corynebacterium diphtheriae, and Streptococcus zooepidemicus. Conclusion. The presence of parasites and bacteria on the fruits observed indicates that public health diseases may arise from their consumption. Awareness and education among farmers, vendors, and consumers about the importance of personal and food hygiene through proper washing or disinfection of fruits could reduce the risk of parasites and bacterial fruit contamination.
The First Case of Cribriform-Morular Thyroid Carcinoma and FAP with APC Gene Mutation in China: A Case Report and Brief Review
Authors: Lyu Sucong , Zhong Guoqiang , Chen Hui , Li Jin , Li Mingsong
Published: May 2023

The cribriform-morular variant of papillary thyroid carcinoma (CMV-PTC) is now designated as morular cribriform thyroid carcinoma (CMTC) according to the 5th edition of the World Health Organization (WHO) Classification of Thyroid Tumors. CMTC can appear within a familial adenomatous polyposis (FAP) or be sporadic. We report the first case of a young female patient in China who was diagnosed with FAP and CMTC with a mutation in exon 16 of the APC gene underlying the disease. The main purpose of this case report is to provide a special pathological type of thyroid tumors, which is expected to be helpful for clinical work in the future.
Contract-Based Incentive Mechanism for Redactable Proof-of-Stake Blockchains
Authors: Wang Yumei , Wu Yongdong , Lai Junzuo
Published: May 2023

Blockchain has received a lot of attention due to its immutability. However, the immutability characteristic prohibits editing the blocks which need to be modified. Although the existing redactable blockchain enables to manipulate blocks in a controlled way, it may suffer from the security threats if the number of honest committee members (CMs) is insufficient. Thus, to attract honest CMs for validating and voting the editing blocks in permissionless blockchain, this paper presents a contract-based incentive mechanism between contract issuer and every CM. Firstly, it models the interaction between the contract issuer and each CM in the verifying and voting process. Secondly, it builds an incentive mechanism according to the contract issuer’s cost and the committee size. Finally, it selects a sufficiently large number of CMs with an optimization method. The analysis shows that the present mechanism is secure against Sybil attack, and the simulations demonstrate that the proposed mechanism is effective.