Current and further trajectories in designing functional materials for solid oxide electrochemical cells:A review of other reviews

Complex oxides are an important class of materials with enormous potential for electrochemical appli-cations.Depending on their composition and structure,such complex oxides can exhibit either a single conductivity(oxygen-ionic or protonic,or n-type,or p-type electronic)or a combination thereof gener-ating distinct dual-conducting or even triple-conducting materials.These properties enable their use as diverse functional materials for solid oxide fuel cells,solid oxide electrolysis cells,permeable membranes,and gas sensors.The literature review shows that the field of solid oxide materials and related electro-chemical cells has a significant level of research engagement,with over 8,000 publications published since 2020.The manual analysis of such a large volume of material is challenging.However,by examining the review articles,it is possible to identify key patterns,recent achievements,prospects,and remaining obstacles.To perform such an analysis,the present article provides,for the first time,a comprehensive summary of previous review publications that have been published since 2020,with a special focus on solid oxide materials and electrochemical systems.Thus,this study provides an important reference for researchers specializing in the fields of solid state ionics,high-temperature electrochemistry,and energyconversiontechnologies.

Hierarchical Privacy Protection Model in Advanced Metering Infrastructure Based on Cloud and Fog Assistance

The Advanced Metering Infrastructure(AMI),as a crucial subsystem in the smart grid,is responsible for measuring user electricity consumption and plays a vital role in communication between providers and consumers.However,with the advancement of information and communication technology,new security and privacy challenges have emerged for AMI.To address these challenges and enhance the security and privacy of user data in the smart grid,a Hierarchical Privacy Protection Model in Advanced Metering Infrastructure based on Cloud and Fog Assistance(HPPM-AMICFA)is proposed in this paper.The proposed model integrates cloud and fog computing with hierarchical threshold encryption,offering a flexible and efficient privacy protection solution that significantly enhances data security in the smart grid.The methodology involves setting user protection levels by processing missing data and utilizing fuzzy comprehensive analysis to evaluate user importance,thereby assigning appropriate protection levels.Furthermore,a hierarchical threshold encryption algorithm is developed to provide differentiated protection strategies for fog nodes based on user IDs,ensuring secure aggregation and encryption of user data.Experimental results demonstrate that HPPM-AMICFA effectively resists various attack strategies while minimizing time costs,thereby safeguarding user data in the smart grid.

Aggravation of Cancer,Heart Diseases and Diabetes Subsequent to COVID-19 Lockdown via Mathematical Modeling

The global populationhas beenandwill continue to be severely impacted by theCOVID-19 epidemic.The primary objective of this research is to demonstrate the future impact of COVID-19 on those who suffer from other fatal conditions such as cancer,heart disease,and diabetes.Here,using ordinary differential equations(ODEs),two mathematical models are developed to explain the association between COVID-19 and cancer and between COVID-19 and diabetes and heart disease.After that,we highlight the stability assessments that can be applied to these models.Sensitivity analysis is used to examine how changes in certain factors impact different aspects of disease.The sensitivity analysis showed that many people are still nervous about seeing a doctor due to COVID-19,which could result in a dramatic increase in the diagnosis of various ailments in the years to come.The correlation between diabetes and cardiovascular illness is also illustrated graphically.The effects of smoking and obesity are also found to be significant in disease compartments.Model fitting is also provided for interpreting the relationship between real data and the results of thiswork.Diabetic people,in particular,need tomonitor their health conditions closely and practice heart health maintenance.People with heart diseases should undergo regular checks so that they can protect themselves from diabetes and take some precautions including suitable diets.The main purpose of this study is to emphasize the importance of regular checks,to warn people about the effects of COVID-19(including avoiding healthcare centers and doctors because of the spread of infectious diseases)and to indicate the importance of family history of cancer,heart diseases and diabetes.The provision of the recommendations requires an increase in public consciousness.

An intelligent active probing and trace-back scheme for IoT anomaly detection

Due to their simple hardware,sensor nodes in IoT are vulnerable to attack,leading to data routing blockages or malicious tampering,which significantly disrupts secure data collection.An Intelligent Active Probing and Trace-back Scheme for IoT Anomaly Detection(APTAD)is proposed to collect integrated IoT data by recruiting Mobile Edge Users(MEUs).(a)An intelligent unsupervised learning approach is used to identify anomalous data from the collected data by MEUs and help to identify anomalous nodes.(b)Recruit MEUs to trace back and propose a series of trust calculation methods to determine the trust of nodes.(c)The last,the number of active detection packets and detection paths are designed,so as to accurately identify the trust of nodes in IoT at the minimum cost of the network.A large number of experimental results show that the recruiting cost and average anomaly detection time are reduced by 6.5 times and 34.33%respectively,while the accuracy of trust identification is improved by 20%.

A Stochastic Model to Assess the Epidemiological Impact of Vaccine Booster Doses on COVID-19 and Viral Hepatitis B Co-Dynamics with Real Data

A patient co-infected with COVID-19 and viral hepatitis B can be atmore risk of severe complications than the one infected with a single infection.This study develops a comprehensive stochastic model to assess the epidemiological impact of vaccine booster doses on the co-dynamics of viral hepatitis B and COVID-19.The model is fitted to real COVID-19 data from Pakistan.The proposed model incorporates logistic growth and saturated incidence functions.Rigorous analyses using the tools of stochastic calculus,are performed to study appropriate conditions for the existence of unique global solutions,stationary distribution in the sense of ergodicity and disease extinction.The stochastic threshold estimated from the data fitting is given by:R_(0)^(S)=3.0651.Numerical assessments are implemented to illustrate the impact of double-dose vaccination and saturated incidence functions on the dynamics of both diseases.The effects of stochastic white noise intensities are also highlighted.

Image Splicing Forgery Detection Using Feature-Based of Sonine Functions and Deep Features

The growing prevalence of fake images on the Internet and social media makes image integrity verification a crucial research topic.One of the most popular methods for manipulating digital images is image splicing,which involves copying a specific area from one image and pasting it into another.Attempts were made to mitigate the effects of image splicing,which continues to be a significant research challenge.This study proposes a new splicing detectionmodel,combining Sonine functions-derived convex-based features and deep features.Two stages make up the proposed method.The first step entails feature extraction,then classification using the“support vector machine”(SVM)to differentiate authentic and spliced images.The proposed Sonine functions-based feature extraction model reveals the spliced texture details by extracting some clues about the probability of image pixels.The proposed model achieved an accuracy of 98.93% when tested with the CASIA V2.0 dataset“Chinese Academy of Sciences,Institute of Automation”which is a publicly available dataset for forgery classification.The experimental results show that,for image splicing forgery detection,the proposed Sonine functions-derived convex-based features and deep features outperform state-of-the-art techniques in terms of accuracy,precision,and recall.Overall,the obtained detection accuracy attests to the benefit of using the Sonine functions alongside deep feature representations.Finding the regions or locations where image tampering has taken place is limited by the study.Future research will need to look into advanced image analysis techniques that can offer a higher degree of accuracy in identifying and localizing tampering regions.

Effect of hafnium and molybdenum addition on inclusion characteristics in Co-based dual-phase high-entropy alloys

Specific grades of high-entropy alloys(HEAs)can provide opportunities for optimizing properties toward high-temperature applications.In this work,the Co-based HEA with a chemical composition of Co_(47.5)Cr_(30)Fe_(7.5)Mn_(7.5)Ni_(7.5)(at%)was chosen.The refractory metallic elements hafnium(Hf)and molybdenum(Mo)were added in small amounts(1.5at%)because of their well-known positive effects on high-temperature properties.Inclusion characteristics were comprehensively explored by using a two-dimensional cross-sectional method and extracted by using a three-dimensional electrolytic extraction method.The results revealed that the addition of Hf can reduce Al_(2)O_(3)inclusions and lead to the formation of more stable Hf-rich inclusions as the main phase.Mo addition cannot influence the inclusion type but could influence the inclusion characteristics by affecting the physical parameters of the HEA melt.The calculated coagulation coefficient and collision rate of Al_(2)O_(3)inclusions were higher than those of HfO_(2)inclusions,but the inclusion amount played a larger role in the agglomeration behavior of HfO_(2)and Al_(2)O_(3)inclusions.The impurity level and active elements in HEAs were the crucial factors affecting inclusion formation.

Secure and Reliable Routing in the Internet of Vehicles Network:AODV-RL with BHA Attack Defense

Wireless technology is transforming the future of transportation through the development of the Internet of Vehicles(IoV).However,intricate security challenges are intertwinedwith technological progress:Vehicular ad hoc Networks(VANETs),a core component of IoV,face security issues,particularly the Black Hole Attack(BHA).This malicious attack disrupts the seamless flow of data and threatens the network’s overall reliability;also,BHA strategically disrupts communication pathways by dropping data packets from legitimate nodes altogether.Recognizing the importance of this challenge,we have introduced a new solution called ad hoc On-Demand Distance Vector-Reputation-based mechanism Local Outlier Factor(AODV-RL).The significance of AODVRL lies in its unique approach:it verifies and confirms the trustworthiness of network components,providing robust protection against BHA.An additional safety layer is established by implementing the Local Outlier Factor(LOF),which detects and addresses abnormal network behaviors.Rigorous testing of our solution has revealed its remarkable ability to enhance communication in VANETs.Specifically,Our experimental results achieve message delivery ratios of up to 94.25%andminimal packet loss ratios of just 0.297%.Based on our experimental results,the proposedmechanismsignificantly improves VANET communication reliability and security.These results promise a more secure and dependable future for IoV,capable of transforming transportation safety and efficiency.

Is endoscopic ultrasound a promising technique in the diagnosis and treatment of liver diseases?

Percutaneous ultrasound has been a longstanding method in the diagnostics and interventional procedures of liver diseases.In some countries,its use is restricted to radiologists,limiting access for other clinicians,such as gastroenterologists.Endoscopic ultrasound,as a novel technique,plays a crucial role in diagnosis and treatment of digestive diseases.However,its use is sometimes recommended for conditions where no clear advantage over percutaneous ultrasound exists,leaving the impression that clinicians sometimes resort to an endoscopic approach due to the unavailability of percutaneous options.

Intelligent Solution System for Cloud Security Based on Equity Distribution:Model and Algorithms

In the cloud environment,ensuring a high level of data security is in high demand.Data planning storage optimization is part of the whole security process in the cloud environment.It enables data security by avoiding the risk of data loss and data overlapping.The development of data flow scheduling approaches in the cloud environment taking security parameters into account is insufficient.In our work,we propose a data scheduling model for the cloud environment.Themodel is made up of three parts that together help dispatch user data flow to the appropriate cloudVMs.The first component is the Collector Agent whichmust periodically collect information on the state of the network links.The second one is the monitoring agent which must then analyze,classify,and make a decision on the state of the link and finally transmit this information to the scheduler.The third one is the scheduler who must consider previous information to transfer user data,including fair distribution and reliable paths.It should be noted that each part of the proposedmodel requires the development of its algorithms.In this article,we are interested in the development of data transfer algorithms,including fairness distribution with the consideration of a stable link state.These algorithms are based on the grouping of transmitted files and the iterative method.The proposed algorithms showthe performances to obtain an approximate solution to the studied problem which is an NP-hard(Non-Polynomial solution)problem.The experimental results show that the best algorithm is the half-grouped minimum excluding(HME),with a percentage of 91.3%,an average deviation of 0.042,and an execution time of 0.001 s.

Efficient and Secure IoT Based Smart Home Automation Using Multi-Model Learning and Blockchain Technology

The concept of smart houses has grown in prominence in recent years.Major challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device itself.Current home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical features.This paper proposes a smart home system based on ensemble learning of random forest(RF)and convolutional neural networks(CNN)for programmed decision-making tasks,such as categorizing gadgets as“OFF”or“ON”based on their normal routine in homes.We have integrated emerging blockchain technology to provide secure,decentralized,and trustworthy authentication and recognition of IoT devices.Our system consists of a 5V relay circuit,various sensors,and a Raspberry Pi server and database for managing devices.We have also developed an Android app that communicates with the server interface through an HTTP web interface and an Apache server.The feasibility and efficacy of the proposed smart home automation system have been evaluated in both laboratory and real-time settings.It is essential to use inexpensive,scalable,and readily available components and technologies in smart home automation systems.Additionally,we must incorporate a comprehensive security and privacy-centric design that emphasizes risk assessments,such as cyberattacks,hardware security,and other cyber threats.The trial results support the proposed system and demonstrate its potential for use in everyday life.

Could near focus endoscopy,narrow-band imaging,and acetic acid improve the visualization of microscopic features of stomach mucosa?

BACKGROUND Conventional magnifying endoscopy with narrow-band imaging(NBI)observation of the gastric body mucosa shows dominant patterns in relation to the regular arrangement of collecting venules,subepithelial capillary network,and gastric pits.AIM To evaluate the effectiveness of a new one-dual(near)focus,NBI mode in the assessment of the microscopic features of gastric body mucosa compared to conventional magnification.METHODS During 2021 and 2022,68 patients underwent proximal gastrointestinal endoscopy using magnification endoscopic modalities subsequently applying acetic acid(AA).The GIF-190HQ series NBI system with dual focus capability was used for the investigation of gastric mucosa.At the time of the endoscopy,the gastric body mucosa of all enrolled patients was photographed using the white light endoscopy(WLE),near focus(NF),NF-NBI,AA-NF,and AA-NF-NBI modes.RESULTS The WLE,NF and NF-NBI endoscopic modes for all patients(204 images)were classified in the same order into three groups.Two images from each patient for the AA-NF and AA-NF-NBI endoscopic modes were classified in the same order.According to all three observers who completed the work independently,NF magnification was significantly superior to WLE(P<0.01),and the NF-NBI mode was significantly superior to NF magnification(P<0.01).After applying AA,the three observers confirmed that AA-NF-NBI was significantly superior to AA-NF(P<0.01).Interobserver kappa values for WLE were 0.609,0.704,and 0.598,respectively and were 0.600,0.721,and 0.637,respectively,for NF magnification.For the NF-NBI mode,the values were 0.378,0.471,and 0.553,respectively.For AA-NF,they were 0.453,0.603,and 0.480,respectively,and for AA-NF-NBI,they were 0.643,0.506,and 0.354,respectively.CONCLUSION When investigating gastric mucosa in microscopic detail,NF-NBI was the most powerful endoscopic mode for assessing regular arrangement of collecting venules,subepithelial capillary network,and gastric pits among the five endoscopic modalities investigated in this study.AA-NF-NBI was the most powerful endoscopic mode for analyzing crypt opening and intervening part.

Synthesis, Characterization and Optical Morphology of ZnO Nanoparticles

The ZnO molecule plays an important role in the industry due to it special features, anti-corrosion anti-bacterial properties, as well as due to its low electrical conductivity and heat resistance. In these experimental researches, the sol-gel method was chosen, which enables control of nucleation, aging and growth of particles in the solution. ZnO synthesis was prepared utilizing chemical method with Zinc acetate dyhidrate and NaOH with the appropriate methanol solvent and heating (60˚C). The methods used in identification and characterization are FTIR, UV/VIS, OPTICAL MICROSCOPY, SEM and XRD. The FTIR spectra of synthesized ZnO with corresponding ones show characteristic bands at the corresponding wavelengths, which confirm the presence of ZnO nanoparticles. SEM characterization of ZnO shows the morphology of needle-shaped nanoparticles. XRD spectar in this research by chemical method indicates the particle size of 17.76 nm.

Chemical Determination of Base Status Metals in Soil Sediments and Particulate Matter in Wellington Industrial Estate Location

This research study explored the levels of base status metals in soil sediments and particulate matter in the wellington industrial estate location;the main objectives were to: 1) determine sodium and potassium, 2) determine calcium and magnesium, 3) determine available iron. The following hypotheses were put forward;H0a: there is no significant difference in the concentration levels between Ca and Mg in the study area, H1a: there is significant difference in the concentration levels between Ca and Mg in the study area, H0b: there is no significant difference in the concentration levels between Na and K in the study area, H1b: there is significant difference in the concentration levels between Na and K in the study area. Six locations were used to collect samples with the aid of scoop and gravel free auger (at varying depths of 0 - 5 cm and 5 - 10 cm) which are Wellington Industrial Estate Area 1 (WIEL 1), (WIEL 2), (WIEL 3), (WIEL 4), (WIEL 5), (WIEL 6);the samples were given laboratory treatment. Flame photometer, EDTA, and Spectrophotometer were used in the determinations of sodium and potassium, calcium and magnesium, and available iron respectively. The results indicated that levels of potassium were in medium range (moderately high);sodium levels were generally low when compared to Brook’s classification table. Levels of calcium were generally low and those of magnesium were moderate based on Brook’s table of classification. Levels of available iron which fall within the range of Quijano-Guerta (2003) were high;this implies such levels can lead to toxicity. In all locations, there was decrease in the levels of each metal in the samples with (5 - 10 cm) depth.

Current trends in acute pancreatitis:Diagnostic and therapeutic challenges

Acute pancreatitis(AP)is an inflammatory disease of the pancreas,which can progress to severe AP,with a high risk of death.It is one of the most complicated and clinically challenging of all disorders affecting the abdomen.The main causes of AP are gallstone migration and alcohol abuse.Other causes are uncommon,controversial and insufficiently explained.The disease is primarily characterized by inappropriate activation of trypsinogen,infiltration of inflammatory cells,and destruction of secretory cells.According to the revised Atlanta classification,severity of the disease is categorized into three levels:Mild,moderately severe and severe,depending upon organ failure and local as well as systemic complications.Various methods have been used for predicting the severity of AP and its outcome,such as clinical evaluation,imaging evaluation and testing of various biochemical markers.However,AP is a very complex disease and despite the fact that there are of several clinical,biochemical and imaging criteria for assessment of severity of AP,it is not an easy task to predict its subsequent course.Therefore,there are existing controversies regarding diagnostic and therapeutic modalities,their effectiveness and complications in the treatment of AP.The main reason being the fact,that the pathophysiologic mechanisms of AP have not been fully elucidated and need to be studied further.In this editorial article,we discuss the efficacy of the existing diagnostic and therapeutic modalities,complications and treatment failure in the management of AP.

Overview of priorities,threats,and challenges to biodiversity conservation in the southern Philippines

Human activities have severely impacted on many species and ecosystems.Thus,understanding the local biodiversity situation is crucial for implementing effective biodiversity conservation interventions.Mindanao in the southern Philippines is home to various unique species,particularly in its pristine ecosystems.However,the available biodiversity data for many terrestrial vertebrates and key areas remain incomplete.To address this issue,we synthesized published literature related to biodiversity from 2000 to 2022 in Mindanao.Moreover,this analysis used four key terrestrial vertebrates(amphibians,reptiles,birds,and mammals)in Mindanao as research objects.According to our findings,there was a significant and positive correlation between the number of biodiversity studies and species recorded.In terms of species richness,birds were the most recorded group(n=334 spp.),followed by reptiles(n=108 spp.),mammals(n=70 spp.),and amphibians(n=52 spp.).We also found that the number of endemic and threatened species varies geographically and across taxonomic groups.Yet,we discovered a significant disparity in the information available on biodiversity in different provinces of Mindanao.For example,the western provinces of Mindanao have had no record of biodiversity for more than two decades.Furthermore,we found that the changes in tree cover loss were consistent with biodiversity records,but this correlation is only significant for birds.Finally,we highlighted some critical threats and challenges to biodiversity,including deforestation,agricultural expansion,mining,and their impact on biodiversity conservation in Mindanao.Our findings suggested that biodiversity conservation should focus not only on areas with high levels of biodiversity but also on areas lacking biodiversity information.To do this,we call for strengthening collaboration among various institutions and digitizing and centralizing of information related to biodiversity.By gaining a deeper understanding of biodiversity in Mindanao,we can better and sustainably protect critical ecosystems in this region from the increasing threats posed by human activities.

Portal vein aneurysm-etiology,multimodal imaging and current management

Portal vein aneurysm(PVA)is a rare vascular abnormality,representing 3%of all venous aneurysms in the human body,and is not well understood.It can be congenital or acquired,located mainly at the level of confluence,main trunk,branches and bifurcation.A PVA as an abnormality of the portal venous system was first reported in 1956 by Barzilai and Kleckner.A review from 2015 entitled“Portal vein aneurysm:What to know”considered fewer than 200 cases.In the last seven years,there has been an increase in the number of PVAs diagnosed thanks to routine abdominal imaging.The aim of this review is to provide a comprehensive update of PVA,including aetiology,epidemiology,and clinical assessment,along with an evaluation of advanced multimodal imaging features of aneurysm and management approaches.

Advances and challenges of electrolyzers for large-scale CO_(2) electroreduction

CO_(2) electroreduction(CO_(2) ER)to high value-added chemicals is considered as a promising technology to achieve sustainable carbon neutralization.By virtue of the progressive research in recent years aiming at design and understanding of catalytic materials and electrolyte systems,the CO_(2) ER performance(such as current density,selectivity,stability,CO_(2) conversion,etc.)has been continually increased.Unfortunately,there has been relatively little attention paid to the large-scale CO 2 electrolyzers,which stand just as one obstacle,alongside series-parallel integration,challenging the practical application of this infant technology.In this review,the latest progress on the structures of low-temperature CO_(2) electrolyzers and scale-up studies was systematically overviewed.The influence of the CO_(2) electrolyzer configurations,such as the flow channel design,gas diffusion electrode(GDE)and ion exchange membrane(IEM),on the CO_(2) ER performance was further discussed.The review could provide inspiration for the design of large-scale CO_(2) electrolyzers so as to accelerate the industrial application of CO_(2) ER technology.

Understorey species distinguish late successional and ancient forests after decades of minimum human intervention: A case study from Slovenia

The main species composition drivers in temperate deciduous forests are environmental conditions, a stand?s age and the site history, e.g., the succession stage and past land use, as well as disturbance regime and current management. We compared plant species diversity and composition in late successional and ancient forests, cooccurring on the same small river island applying species accumulation curves and nonmetric multidimensional scaling, respectively. Given the island?s geomorphological characteristics, we expected these to be very similar before human intervention in the past. The forests experienced differing disturbance regimes in the past, while over the last 30 years, human intervention has been the same and reduced to a minimum. The ancient forest in this study had two major characteristics defining it as old, mature forest: continuity of presence for more than 200years and specific composition. The late successional forest experienced major disturbance in the 20th century and was allowed natural regeneration by bordering on the ancient forest, representing a potential species pool,and by decades of minimum human intervention. Our results showed that, even though there was no difference in species richness, we could still detect differences between the forests, particularly in the abundance and species composition of the understorey, among which geophytes had the most indicative importance. To make our results useful on a broader scale, we composed from the literature a species list of plants indicative for ancient forest and tested its application. These results are important for distinguishing between old and mature secondary stands and particularly for identifying old forest stands, which should be conserved and, in the case of fragmented landscapes, included in a network connecting forest fragments.

Dynamical analysis and anti-synchronization of a new 6D model with self-excited attractors

A novel 6D dissipative model with an unstable equilibrium point is introduced herein.Some of the dynamic characteristics of the proposed model were explored via analyses and numerical simulations including critical points,stability,Lyapunov exponents,time phase portraits,and circuit implementation.Also,anti-synchronization phenomena were implemented on the new system.Firstly,the error dynamics is found.Then,four different controllers are adopted to stabilize this error relying on the nonlinear control technique with two main ways:linearization and Lyapunov stability theory.In comparison with previous works,the present controllers realize anti-synchronization based on another method/linearization method.Finally,a comparison between the two ways was made.The simulation results show the effectiveness and accuracy of the first analytical strategy.