Pending Issues Research Articles

Desenvolvimento de plug-in BIM para verificação de conformidade de Projetos Arquitetônicos segundo as Leis Municipais – O Caso de Passo Fundo/RS

The construction industry plays a significant role in job creation and the socioeconomic development of cities. However, architects and urban planners face challenges due to the delay in the approval of architectural projects by municipal governments, attributed to the non-compliance of projects with local laws. In this context, this study proposes the use of programming in BIM (Building Information Modeling) software, with the aim of developing a plug-in to assist in the process of approving architectural projects in compliance with the municipal laws and regulations of Passo Fundo-RS. The methodology adopted was based on a thorough literature review, document analysis, and the development of a plug-in prototype for Revit, developed in Dynamo using the Python language. The proposed prototype involves the integration of urban data into Revit to automate the collection of information such as building dimensions, lot areas, setbacks, and other metrics. The results revealed that the implementation of programming routines in BIM, especially for Revit, has the potential to significantly reduce the waiting times for project approvals by the municipal government, improve their compliance with local regulations, and minimize pending issues and rework.

Deliberate metaphor (use) in translation and interpreting

Abstract This article responds to the latest theoretical and empirical developments in Deliberate Metaphor Theory (DMT) and explores the extension of deliberate metaphor and its use in translation and interpreting. Grounded on a comprehension-based and a production-based perspective of Deliberate Metaphor Theory, I argue that both deliberate metaphor and deliberate metaphor use are valid theoretical constructs for translation and interpreting research. I then discuss some pending issues in researching deliberate metaphor (use) in translation and interpreting.

Machine Learning-Assisted Raman Spectroscopy and SERS for Bacterial Pathogen Detection: Clinical, Food Safety, and Environmental Applications

Detecting pathogenic bacteria and their phenotypes including microbial resistance is crucial for preventing infection, ensuring food safety, and promoting environmental protection. Raman spectroscopy offers rapid, seamless, and label-free identification, rendering it superior to gold-standard detection techniques such as culture-based assays and polymerase chain reactions. However, its practical adoption is hindered by issues related to weak signals, complex spectra, limited datasets, and a lack of adaptability for detection and characterization of bacterial pathogens. This review focuses on addressing these issues with recent Raman spectroscopy breakthroughs enabled by machine learning (ML), particularly deep learning methods. Given the regulatory requirements, consumer demand for safe food products, and growing awareness of risks with environmental pathogens, this study emphasizes addressing pathogen detection in clinical, food safety, and environmental settings. Here, we highlight the use of convolutional neural networks for analyzing complex clinical data and surface enhanced Raman spectroscopy for sensitizing early and rapid detection of pathogens and analyzing food safety and potential environmental risks. Deep learning methods can tackle issues with the lack of adequate Raman datasets and adaptability across diverse bacterial samples. We highlight pending issues and future research directions needed for accelerating real-world impacts of ML-enabled Raman diagnostics for rapid and accurate diagnosis and surveillance of pathogens across critical fields.

GSK3: A potential target and pending issues for treatment of Alzheimer's disease.

Glycogen synthase kinase-3 (GSK3), consisting of GSK3α and GSK3β subtypes, is a complex protein kinase that regulates numerous substrates. Research has observed increased GSK3 expression in the brains of Alzheimer's disease (AD) patients and models. AD is a neurodegenerative disorder with diverse pathogenesis and notable cognitive impairments, characterized by Aβ aggregation and excessive tau phosphorylation. This article provides an overview of GSK3's structure and regulation, extensively analyzing its relationship with AD factors. GSK3 overactivation disrupts neural growth, development, and function. It directly promotes tau phosphorylation, regulates amyloid precursor protein (APP) cleavage, leading to Aβ formation, and directly or indirectly triggers neuroinflammation and oxidative damage. We also summarize preclinical research highlighting the inhibition of GSK3 activity as a primary therapeutic approach for AD. Finally, pending issues like the lack of highly specific and affinity-driven GSK3 inhibitors, are raised and expected to be addressed in future research. In conclusion, GSK3 represents a target in AD treatment, filled with hope, challenges, opportunities, and obstacles.

Ethical regulation of biomedical research in Brazil: a quality improvement initiative

BackgroundQ-CEP (Qualificação dos Comitês de Ética em Pesquisa que compõem o Sistema CEP/Conep) is a nationwide project resulting from a partnership between the Brazilian National Research Ethics Commission (Conep), the Ministry of Health and Hospital Moinhos de Vento (HMV). It was developed to consolidate policy for ethical review of research with human beings in all members of the CEP/Conep System, Brazil’s national system of institutional review boards. The aim of this study was therefore to report on the experience and results of the Q-CEP project.MethodsAn observational, retrospective study includes data from the Q-CEP, obtained from visits to all the institutional research ethics committees (RECs) in the country. The actions implemented by Q-CEP were part of a two-step process: (i) training visits to each REC; (ii) development of distance learning modules on strategic topics pertaining to research ethics evaluation. The data presented herein cover step one (training visits), defined by Q-CEP as the diagnostic stage of the project. For a country with social and economics inequalities such as Brazil, this is a particularly important stage; an accurate picture of reality is needed to inform planning of quality improvement strategies.ResultsIn 2019–2021, Q-CEP visited 832 RECs and trained 11,197 people. This sample covered almost all active RECs in the country; only 4 (0.5%) were not evaluated. Of the 94 items evaluated, 62% did not reach the target of at least 80% compliance and around 1/4 (26%) were below 50% compliance. The diagnostic stage of the process revealed inadequacies on the part of the RECs in their ethical reviews. The analysis of informed consent forms showed compliance in only 131 RECs (15.74%). The description of pending issues made by RECs in their reports was compliant in 19.33% (n = 161). Administrative and operational aspects were also considered inadequate by more than half of the RECs.ConclusionsOverall, Brazilian RECs showed poor compliance in several aspects of their operation, both in ethics evaluation and in other processes, which justifies additional training. The Q-CEP project is part of a quality improvement policy promoted by the Brazilian Ministry of Health. The data obtained in the diagnostic step of the project have contributed to the qualification and consolidation of one of the world’s largest research ethics evaluation systems.

Radiation-induced cross-linking polymerization: Recent developments for coating and composite applications

Abstract Radiation-initiated cross-linking polymerization of multifunctional monomers is an attractive method used for drying solvent-free liquid coatings, inks, and adhesive as well as for fabricating high-performance composite materials. The method offers a number of advantages compared with thermal curing processes. Free radical and cationic polymerization have been investigated in detail over the past years. A high degree of control over curing kinetics and material properties can be exerted by adjusting the composition of matrix precursors and/or by acting on the process parameters (overall dose, dose rate, dose increment, initial temperature). Several pending issues that require deeper investigations are as follows: (i) the fast polymerization of multifunctional monomers generates micro-heterogeneous networks requiring detailed characterization and quantification by microscopic, thermal, and spectroscopic analyses; (ii) the adhesion and surface properties of radiation-cured coatings are quite sensitive to processing parameters; and (iii) significant enhancement of the toughness is needed to qualify potential matrices based on simple difunctional monomers for high-performance composites. Recent results show that the bulk and surface properties of radiation-cured materials can be improved by advanced formulation of matrix precursors and by a parametric study of the processing factors.

A survey on graph neural networks for intrusion detection systems: Methods, trends and challenges

Intrusion detection systems (IDS) play a crucial role in maintaining network security. With the increasing sophistication of cyber attack methods, traditional detection approaches are encountering more challenges. In recent years, graph neural networks (GNNs) have garnered significant attention in the field of intrusion detection due to their unique ability to capture the relationships within the graph structure of data communications. In this review, we propose a novel taxonomy that categorizes advanced research into three distinct areas: tasks related to graph construction, network design, and GNN models deployment. We detail a generalized design process for GNN-based intrusion detection models, discussing the challenges encountered at each stage. Building upon these discussions, we conduct a systematic survey of existing works. Ultimately, we delve into a thorough exploration of the future research directions and the pending issues in this domain. By adopting a problem-oriented taxonomy and conducting a targeted survey, this review aims to provide scholars with a clear, systematic framework for deepening their understanding and further exploration of the field.

Chinese expert consensus on the surgical treatment for adenocarcinoma of esophagogastric junction (Edition 2024)

The publication of Chinese expert consensus on the surgical treatment for adenocarcinoma of esophagogastric junction (2018 edition) has widely accelerated the standardization and homogenization on the surgical treatment of adenocarcinoma of esophagogastric junction (AEG). In China, the surgical outcomes of AEG, the universality and practicability of this consensus has also been affirmed after the clinical practice during the past 5 years. Due to the persistent increasing incidence of AEG, the specificity on anatomic site, clinicopathological characteristics, molecular biological characteristics, AEG had been always the hotspot of many clinical trials and more clinical evidences had been published. However, its definition, classification, staging, surgical approach, resection pattern, extent of lymphadenectomy, and the digestive tract reconstruction etc. remain controversial. In light of the above, it is necessary to update the 2018 edition of consensus. The Chinese expert consensus on the surgical treatment for adenocarcinoma of esophagogastric junction (2024 edition) is generated based on the currently available and best clinical evidence, the latest global guidelines or consensuses, and the opinions from the Chinese expert panel. The present consensus focuses on the key points of surgical treatment and issues in dispute, and provides scientific recommendations. The goal of this expert consensus was to improve the homogeneity in understanding and practice between Chinese thoracic and gastrointestinal surgeons, and to further standardize surgical treatment of AEG. Those pending issues in this consensus need high-quality clinical research to further investigate.

Evaluation of Current Professional Practices of Perfusionists: Survey Study

Introduction: Cardiac surgical procedures performed with extracorporeal circulation or perfusion techniques retain their importance in treating heart disease and often represent an alternative method.
 Objective: This survey aimed to identify and evaluate the current practice of perfusionists in cardiovascular surgery clinics in Turkey.
 Materials and Methods: This study is a prospective and descriptive etiological study. Surveys regarding the current practices of perfusionists were created as part of the study. The created surveys were sent to perfusionists in Turkey voluntarily through the application "Google Forms", and the data were collected. The data obtained from the surveys were statistically analyzed.
 Results: In this study, 80 perfusionists from 28 centres participated in the survey. Thirty-four participants were under 30 years old, 12 were between 31 and 35 years old, 16 were between 36 and 40 years old, and 16 were over 40 years old. Of the participants, 46 were female and 34 were male. The study collected descriptive data, information on cardiac clinics, CPB practices, use of cardioplegia, and other assistive devices.
 Conclusion: There have been significant advances and changes in cardiac surgery surgeries performed with CPB over approximately 70 years from the past to the present. However, we believe that there are ongoing or pending issues.

Sequence-discrete species for prokaryotes and other microbes: A historical perspective and pending issues.

Whether prokaryotes, and other microorganisms, form distinct clusters that can be recognized as species remains an issue of paramount theoretical as well as practical consequence in identifying, regulating, and communicating about these organisms. In the past decade, comparisons of thousands of genomes of isolates and hundreds of metagenomes have shown that prokaryotic diversity may be predominantly organized in such sequence-discrete clusters, albeit organisms of intermediate relatedness between the identified clusters are also frequently found. Accumulating evidence suggests, however, that the latter "intermediate" organisms show enough ecological and/or functional distinctiveness to be considered different species. Notably, the area of discontinuity between clusters often-but not always-appears to be around 85%-95% genome-average nucleotide identity, consistently among different taxa. More recent studies have revealed remarkably similar diversity patterns for viruses and microbial eukaryotes as well. This high consistency across taxa implies a specific mechanistic process that underlies the maintenance of the clusters. The underlying mechanism may be a substantial reduction in the efficiency of homologous recombination, which mediates (successful) horizontal gene transfer, around 95% nucleotide identity. Deviations from the 95% threshold (e.g., species showing lower intraspecies diversity) may be caused by ecological differentiation that imposes barriers to otherwise frequent gene transfer. While this hypothesis that clusters are driven by ecological differentiation coupled to recombination frequency (i.e., higher recombination within vs. between groups) is appealing, the supporting evidence remains anecdotal. The data needed to rigorously test the hypothesis toward advancing the species concept are also outlined.

Optimization of Radiation Protection in Pediatric Interventional Radiology in Latin America and the Caribbean: Development, Advancements, Challenges and Achievements of the OPRIPALC Program.

This article presents the development, advancements, challenges and achievements of the "Optimization of Protection in Pediatric Interventional Radiology in Latin America and the Caribbean" (OPRIPALC) program. This international initiative is led by the World Health Organization, the Pan American Health Organization and the International Atomic Energy Agency. The main objectives of OPRIPALC are to foster a culture of radiological protection in pediatric interventions, enhance these procedures' quality, and define optimization strategies such as the use of diagnostic reference levels (DRLs). Currently, 33 centers from 12 countries participate actively in the program. Significant progress has been made towards the proposed objectives, overcoming the challenges posed by the COVID-19 pandemic. Through many virtual meetings for coordination, planning, training and follow-up, a comprehensive set of DRLs for both diagnostic and therapeutic procedures, categorized by weight and age, have been established and are in use. A consensus document on good practices is in the final stage of development. The program's continuation into at least a second phase is essential to address pending issues, including the integration of automatic dose management systems, the levels of occupational radiation doses, their correlation with pediatric patient doses, and strategies to reduce them.

고교학점제 연구 및 운영 경력이 있는 전문가가 인식한 일반학교 특수교육 대상 학생을 위한 고교학점제 운영 방안 탐색

The purpose of this study is to explore successful operation plans for the high school credit system for students with special needs in general schools. For this purpose, a focus group interview (FGI) was conducted targeting experts who have experience in researching the high school credit system and operating the pilot schools for the high school credit system. A total of eight experts participated in the online FGI meeting, and the collected data was analyzed based on a three-step coding process. As for the main results, first, it was necessary to clarify the directions in operating a high school credit system for students with special needs with an emphasis on inclusive education, and to design a balanced curriculum by expanding the scope of the role of special education. Second-in order to secure appropriate evaluation methods for students with special needs in general education settings-it was necessary to come to an agreement on applying different criteria for course completion, solve pending issues related to evaluation, and enhance teachers’ professionalism. Third, the need to improve various conditions was emphasized-such as supply and demand of teachers, utilization of resources outside school, and course opening for inclusive education in order to effectively operate the high school credit system. Fourth, it was needed to match both students’ educational needs and curriculum characteristics of high schools. Teachers need to provide students with career and academic guidance based on types within students’ career. Based on these results, implications such as the organization and operation of school curriculums aimed at inclusive education, the advancement for students’ evaluation, and the preparation in teachers’ guidance for career and academic design were discussed.

Numerical simulation of the deadliest flood event of Portugal: Unravelling the causes of the disaster

The flood event of November 25 and 26, 1967 corresponds to the deadliest storm affecting Portugal in recent centuries being responsible for >500 fatalities. The main trigger was the heavy rain that fell in just a few hours, provoking a rapid increase in river flows, although other concurrent circumstances had to occur to reach the dramatic water levels estimated in some affected places. However, even today, several important uncertainties related to water levels achieved and timing of floods remain. Here we aim to clarify some of the pending issues by applying suitable high performance numerical tools to elucidate the main conditioning factors that played a key role in the intensification of this dramatic flood. In particular, the analysis has been focused on Quintas village, the location most affected, where >100 fatalities were recorded, close to 2/3 of its total population at the time. The main conclusion provided by the numerical simulations was that a plugging of water flow downstream of Quintas village, favoured by a poor terrain maintenance coupled with the bottleneck created by topographic features, caused the critical over-elevation of water levels. Simulations also corroborate the rapid increase in water levels in Quintas village, with an estimated rise of >2 m in just two hours, as well as the occurrence of the flood during the night, preventing many people to be aware of the extreme danger they were facing and safeguarding themselves.

Novel strategy towards in-situ recycling of valuable metals from spent lithium-ion batteries through endogenous advanced oxidation process

Efficient and sustainable recycling of metal resources from spent lithium-ion batteries (LIBs) is critical for the metal resources security and environment protection. However, the intact exfoliation of cathode materials (CMs) from current collectors (Al foils) and selective extraction of Li towards the in-situ and sustainable recycling of cathodes from spent LIBs are still pending issues. A self-activated and ultrasonic-induced endogenous advanced oxidation process (EAOP) was proposed in this study for selective removal of PVDF and in-situ extraction of Li from CMs of waste LiFePO4 (LFP) to address the above issues. Over 99 wt% CMs can be detached from Al foils after EAOP treatment under the optimized operation conditions. High purity of Al foil can be directly recycled as metallic forms and nearly 100 % of Li can be in-situ extracted from the detached CMs and then recovered as Li2CO3 (>99.9 % in purity). With induction and reinforcement of ultrasonic, S2O82- was self-activated by LFP to generate an increased amount of SO4•− radicals that will attack the PVDF binders to ensure their degradation. The degradation pathway of PVDF and density functional theory (DFT) calculation can also support the analytical and experimental results. Then, the complete and in-situ ionization of Li can be achieved by the further oxidization of SO4•− radicals from LFP powders. This work provides a novel strategy towards efficient and in-situ recycling of valuable metals from spent LIBs with minimized environmental footprint.

Investigation on pore properties, thermal conductivity, and compressive behavior of fly ash/slag‐based geopolymer foam

AbstractGeopolymer foam has emerged as a promising inorganic porous material in the last decade. Despite of the numerous advantages, there are some pending issues to be addressed, on top of that is the low compressive strength. To overcome this, this study synthesizes a high‐strength geopolymer foam by the partial substitution of fly ash (FA) with ground granulated blast furnace slag and carries out an intensive investigation into its microstructure, pore properties, thermal conductivity as well as compressive behavior. The microstructure is firstly analyzed by X‐ray diffraction and Fourier transform infrared spectroscopy techniques. The pore characteristics are also scrutinized, including pore size distribution, total porosity and water absorption. Then, the thermal conductivity is investigated and the applicability of basic effective thermal conductivity models to characterize the relationship with total porosity is evaluated. Afterward, the compressive strength together with the softening coefficient is examined, and the relationship with total porosity is also studied. Finally, comparisons between the proposed geopolymer foam and other FA‐based geopolymer foams in the literature are performed. The results show that the proposed geopolymer foam possesses not only a comparable thermal conductivity but also a far superior compressive strength, which sheds light on the widespread applications in thermal insulation.

Deep probabilistic graphical modeling for robust multivariate time series anomaly detection with missing data

Multivariate time series anomaly detection with missing data is one of the most pending issues for industrial monitoring. Due to scarcity of labeled anomalies, most advanced data-driven anomaly detection approaches fall in the unsupervised learning paradigm. As a premise in the presence of missing data, one needs to improve the data quality through data imputation with a separate model. Our concern lies in the consistency between data imputation and unsupervised learning for robust anomaly detection, regarding accurately discovering the spatiotemporal dependence among multiple variables over time. However, the existing practice tends to overlook this consistency and decouple the training process for these two closely linked tasks. This article novelly proposes a probabilistic multivariate time series anomaly detection framework that unifies data imputation and unsupervised learning. A deep probabilistic graphical model abbreviated SCNF is first devised for unsupervised density estimation. A tailored expectation maximization-based optimization scheme is then developed to achieve the joint training of data imputation and unsupervised learning with missing data. The efficacy is experimentally corroborated in several industrial applications, including chemical process, water treatment and network traffic. Briefly, the joint training framework enhances the AUROC of SCNF by averagely 6.34% for three applications under 50% data missing rate.

해양경찰 간부 양성제도 연구

With the advent of the era of maritime competition over territorial sovereignty and marine resources worldwide, the role of the Coast Guard, a maritime executive agency, is becoming increasingly important. There is a growing demand from the public that wants to provide the highest level of administrative services internally and demands rational leadership in terms of fairness and justice. Coast Guard officers carry out important tasks to manage the organization, deal with pending issues, and design the future with a basic spirit of service and democracy to the people. Therefore, it is an important and urgent matter to be competitive in the organization and provide the best service to the people through the training of competent executive personnel.
 Despite its long history, the Korean Coast Guard maintains the previous system in its officer development system. It has been maintained until today without significant changes in the basic framework of Police Executive Candidate, which is the initial system. As a result, the overall organizational competitiveness has been weakened externally, and it has not been able to keep pace with the rapidly changing marine environment. Internally, it is deriving various problems such as lack of leadership, pure bloodism, and failure to promote its own director.
 In order for the Korean Coast Guard to become an institution that leads the pending maritime issues and provides high-quality services, it is necessary to diagnose the problems of the officer development system and seek alternatives. In consideration of the constraints of the scope of the study, this study will focus on the recruitment system and education and training of beginner officers among various categories related to officer development.
 First, we will look at the recruitment system for beginner officers and the current status of education and training for advanced foreign and domestic similar institutions. Next, we will identify the problems caused by the Korea Coast Guard officer development system. Finally, I would like to present a reasonable alternative to the development plan of Korea Coast Guard officers by focusing on the recruitment of beginner officers.

Investor preference analysis: An online optimization approach with missing information

How to derive an investor's preference is vital for investment advisors and online lending platforms for targeted marketing strategies, e.g., market segmentation and financial product recommendation. However, investor preference analysis usually depends on judgments from human investment experts, which are inherently subjective and costly. Intelligent investment advisors (or Robo-advisors), supported by cutting-edge technologies such as machine learning and artificial intelligence, are established to relieve these pending issues. This paper employs an online optimization framework to obtain investors' preferences for further financial product recommendations. This proposed method allows us to update the investor's preference for newly-arriving data sets and tackle the situation where plenty of missing values in investors' records are present. Unlike the black-box-like machine learning approach, our method can provide more managerial implications regarding why one financial product/service is preferred. Real-world data set from an online financial platform is used to compare the existing approaches and shows the stronger and more stable performance of our method when facing different data-missing types and situations with different missing degrees, followed by a recommendation system application.

Advances in the understanding of Blattodea evolution: Insights from phylotranscriptomics and spermathecae

Cockroaches, an ancient and diverse group of insects on earth that originated in the Carboniferous, displays a wide array of morphology or biology diversity. The spermatheca is an organ of the insect reproductive system; the diversity of spermathecae might be the adaption to different mating and sperm storage strategies. Yet a consensus about the phylogenetic relationships among the main lineages of Blattodea and the evolution of spermatheca has not been reached until now. Here we added the transcriptome data of Anaplectidae for the first time and supplemented other family level groups (such as Blaberidae, Corydiidae) to address the pending issues. Our results showed that Blattoidea was recovered as sister to Corydioidea, which was strongly supported by molecular evidence. In Blattoidea, (Lamproblattidae + Anaplectidae) + (Cryptocercidae + Termitoidae) was strongly supported by our molecular data. In Blaberoidea, Pseudophyllodromiidae and Blaberidae were recovered to be monophyletic, while Blattellidae was found to be paraphyletic with respect to Malaccina. Ectobius sylvestris + Malaccina discoidalis formed the sister group to other Blaberoidea; Blattellidae (except Malaccina discoidalis) + Nyctiboridae was found as the sister of Blaberidae. Corydiidae was recovered to be non-monophyletic due to the embedding of Nocticola sp. Our ASR analysis of spermatheca suggested that primary spermathecae were present in the common ancestor, and it transformed at least six times during the evolutionary history of Blattodea. The evolution of spermatheca could be described as a unidirectional trend: the increased size to accommodate more sperm. Furthermore, major splits within the existing genera of cockroaches occurred in the Upper Paleogene to Neogene. Our study provides strong support for the relationship among three superfamilies and offers some new insights into the phylogeny of cockroaches. Meanwhile, this study also provides basic knowledge on the evolution of spermathecae and reproductive patterns.

Glycosaminoglycans: What Remains To Be Deciphered?

Glycosaminoglycans (GAGs) are complex polysaccharides exhibiting a vast structural diversity and fulfilling various functions mediated by thousands of interactions in the extracellular matrix, at the cell surface, and within the cells where they have been detected in the nucleus. It is known that the chemical groups attached to GAGs and GAG conformations comprise "glycocodes" that are not yet fully deciphered. The molecular context also matters for GAG structures and functions, and the influence of the structure and functions of the proteoglycan core proteins on sulfated GAGs and vice versa warrants further investigation. The lack of dedicated bioinformatic tools for mining GAG data sets contributes to a partial characterization of the structural and functional landscape and interactions of GAGs. These pending issues will benefit from the development of new approaches reviewed here, namely (i) the synthesis of GAG oligosaccharides to build large and diverse GAG libraries, (ii) GAG analysis and sequencing by mass spectrometry (e.g., ion mobility-mass spectrometry), gas-phase infrared spectroscopy, recognition tunnelling nanopores, and molecular modeling to identify bioactive GAG sequences, biophysical methods to investigate binding interfaces, and to expand our knowledge and understanding of glycocodes governing GAG molecular recognition, and (iii) artificial intelligence for in-depth investigation of GAGomic data sets and their integration with proteomics.