bluuebunny/crossref_metadata_2025 huggingface dataset:
Market Impact Analysis of Financial Literacy among A-Share Market Investors: An Agent-Based Model
Authors: Zhou Rongtian , Xiong Xiong , Llacay Bàrbara , Peffer Gilbert
Published: November 2023

Financial literacy has become increasingly crucial in today’s complex financial markets. This paper explores the impact of financial literacy on the stock market by establishing an artificial financial market that aligns with the characteristics of the Chinese A-share market using agent-based modeling. The study incorporates financial literacy into investors’ mixed beliefs and simulates their behavior in the market. The results show that improving individual investors’ financial literacy can improve market quality and investor performance, as well as reduce the unequal distribution of wealth to some extent. However, the phenomenon of speculative trading and irrational behavior in the market can pose potential risks that require regulatory measures. Thus, policy recommendations to improve individual investors’ financial literacy and establish corresponding regulatory measures are proposed.
STEM-Based Curriculum and Creative Thinking in High School Students
Authors: Khalil Rana Y. , Tairab Hassan , Qablan Ahmad , Alarabi Khaleel , Mansour Yousef
Published: November 2023

Creative thinking as a 21st century skill is fundamental to human development and a catalyst for innovation. Researchers frequently study it as it encourages students to analyze, synthesize, and evaluate information from different angles, vital for making informed decisions and solving complex problems. Therefore, this study aimed to assess the impact of a STEM-based curriculum on the development of creative thinking in high school students studying physics. Employing a quasi-experimental design, data were collected from 94 high school students of mixed gender and grade levels using the Torrance Tests of Creative Thinking (TTCT). Data analyses involve multivariance analyses (MANOVA) to answer the research questions. The findings showed that a STEM-based curriculum significantly impacted the development of students’ creative thinking compared to students who studied under a traditional curriculum regarding the metrics of fluency, flexibility, and originality. However, the development of participants’ metric of elaboration remained the same. Furthermore, the findings showed a significant influence of the grade level of participants who studied under a STEM-based curriculum on the metrics of fluency and elaboration. On the other hand, the findings revealed that grade level did not relate to the STEM-based curriculum for the metrics of flexibility and originality. The findings are discussed in light of recent research on the impact of STEM education.
Co-Teaching Implementation: How Do School Leaders Support Teachers?
Authors: McTigue Erin M. , Gourvennec Aslaug F. , Solheim Oddny Judith , Jensen Maria Therese
Published: November 2023

School leaders play a pivotal role in fostering change and improvement, including via teacher-led interventions, such as co-teaching. Leaders’ vision and support create the conditions for teachers to maximize the effectiveness of school interventions. However, there is limited understanding of how school leaders provide support for the intervention of co-teaching. This gap in knowledge is crucial because co-teaching has the potential to be transformative, but teachers must actively drive pedagogical changes. We conducted a mixed-methods study involving 150 Norwegian elementary schools participating in a multi-year co-teaching initiative for literacy instruction. We collected data through open and closed survey questions, inquiring about school leaders’ beliefs and support practices regarding co-teaching. Our descriptive analysis examined school leaders’ practices and explored potential associations with their epistemological perspectives. Our findings indicate that leaders who approach co-teaching with cautious optimism tend to provide more thoughtful support compared to those who are overly optimistic and may underestimate implementation challenges. Moreover, most leaders prioritize structural support elements while potentially overlooking psychological and emotional support practices aligned with self-determination theory (SDT). We conclude with practical recommendations for school leaders to offer support to teachers that are grounded in the principles of SDT and organized according to implementation phases.
Bringing Critical Mathematics Education and Actor–Network Theory to a Statistics Course in Mathematics Teacher Education: Actants for Articulating Complexity in Student Teachers’ Foregrounds
Authors: Ödmo Magnus , Chronaki Anna , Bjorklund Boistrup Lisa
Published: November 2023

In this paper, we discuss how critical mathematics education (CME) and actor–network theory (ANT) come together in a mathematics teacher education course that focuses on the thematic context of climate change to study statistics. Acknowledging the complexity that student teachers encounter when asked to move from a mainly instrumental treatment of statistics toward a critical foreground of data in society, we turn to explore the actant networks, as theorized by ANT, utilized by student teachers when asked to imagine teaching from a CME perspective. For this, our study is based on a series of interviews with student teachers who participated in a statistics course where pollution data graphs were discussed, inquiring about their role as future critical mathematics teachers. The transcribed interviews, analyzed through ANT, inform us as to how student teachers’ foregrounds are being shaped by actants such as the curriculum, social justice, democracy, and source critique, among others. Based on the above, we recommend that teacher education should invite active discussion of the complexity created when a CME perspective is required. This move would allow for a critical approach to critical mathematics education itself that could prepare student teachers to navigate, instead of ignoring or opposing, such complexity.
Improved Model of Base Station Power System for the Optimal Capacity Planning of Photovoltaic and Energy Storage System
Authors: Zhu Binxin , Wang Yizhang , Guo Hao , Yang Nan , Lu Ling
Published: November 2023

The widespread installation of 5G base stations has caused a notable surge in energy consumption, and a situation that conflicts with the aim of attaining carbon neutrality. Numerous studies have affirmed that the incorporation of distributed photovoltaic (PV) and energy storage systems (ESS) is an effective measure to reduce energy consumption from the utility grid. The optimization of PV and ESS setup according to local conditions has a direct impact on the economic and ecological benefits of the base station power system. An improved base station power system model is proposed in this paper, which takes into consideration the behavior of converters. And through this, a multi-faceted assessment criterion that considers both economic and ecological factors is established. Then, the PV and ESS capacity optimization for base stations under multiple scenarios is realized. The case study indicates that the optimization process of PV and ESS is significantly influenced by the behavior of the converter.
Sign Language Recognition with Multimodal Sensors and Deep Learning Methods
Authors: Lu Chenghong , Kozakai Misaki , Jing Lei
Published: November 2023

Sign language recognition is essential in hearing-impaired people’s communication. Wearable data gloves and computer vision are partially complementary solutions. However, sign language recognition using a general monocular camera suffers from occlusion and recognition accuracy issues. In this research, we aim to improve accuracy through data fusion of 2-axis bending sensors and computer vision. We obtain the hand key point information of sign language movements captured by a monocular RGB camera and use key points to calculate hand joint angles. The system achieves higher recognition accuracy by fusing multimodal data of the skeleton, joint angles, and finger curvature. In order to effectively fuse data, we spliced multimodal data and used CNN-BiLSTM to extract effective features for sign language recognition. CNN is a method that can learn spatial information, and BiLSTM can learn time series data. We built a data collection system with bending sensor data gloves and cameras. A dataset was collected that contains 32 Japanese sign language movements of seven people, including 27 static movements and 5 dynamic movements. Each movement is repeated 10 times, totaling about 112 min. In particular, we obtained data containing occlusions. Experimental results show that our system can fuse multimodal information and perform better than using only skeletal information, with the accuracy increasing from 68.34% to 84.13%.
Autonomous Wireless Sensor System for Emergency Monitoring Roads with Low Communication Coverage
Authors: Postigo-Malaga Mauricio , Jimenez-Caceres Alexander M. , Pelegri-Sebastia Jose , Chilo Jose
Published: November 2023

Rural areas often face communication challenges due to limited mobile coverage on remote roads, posing significant difficulties in reporting emergencies and accidents. This study presented an autonomous vehicle tracking system using low-cost radar sensors to detect possible emergencies in the sections of roads with low cell coverage. The radar sensor system could determine the number of vehicles that passed through the nodes and classify them based on the vehicle type. Each node within the system is equipped with ten radars, a processor unit, and a radio transmitter to communicate with the network in real-time, achieving a rapid response time of just 0.2 s. To ensure seamless connectivity, two distinct wireless communication networks are employed, one for the connection between the towers in the same node and the other for the connection between nodes and a center with cellular coverage. The results of this study can be useful in conveying emergency messages, as well as traffic management.
Thermal Insulation Properties of Delignified Balsa and Paulownia Wood “Foams” with Polylactic Acid Coverings
Authors: Jin Yuanyuan , Tian Feiyu , She Yanan , Xu Haocheng , Zhu Chunfeng , Wu Yutao , Chen Hao , Wang Bingbing , Xu Xinwu
Published: November 2023

The energy-conserving performance of a building, normally realized by a variety of insulation materials, needs to be carefully considered, from the design to construction operations. Traditional mineral or chemically synthesized insulation materials are facing severer environment or health challenges. Hence, this work aims at developing an alternative thermal insulation material from wood. Two species, balsa and Paulownia, were chosen for their naturally low densities. Lignin and hemicellulose components were removed to create a “foamed” structure with more air induced. Polylactic acid (PLA) was applied to cover the delignified wood samples to further improve the hydrophobicity. The microstructure, physical properties, thermal conductivity and insulation properties of the treated wood samples were assessed. After lignin and hemicellulose removal, the original porous micro skeleton of balsa and Paulownia wood was retained, along with an increased porosity to 96.6% and 94%, respectively. Meanwhile, the thermal conductivity was successfully decreased by 22% to 0.053 W/(m·K) for balsa wood and by 27% to 0.067 W/(m·K) for Paulownia wood. PLA-covering treatment further enhanced the water resistance of the delignified wood samples without an evident change in the thermal conductivity. The above findings demonstrated the feasibility of applying delignified wood as a potential insulation material in modern construction operations, which may help set up a new pathway for a low-carbon and energy-saving construction industry.
The Thermal Regulator Role of Urban Green Spaces: The Case of Coimbra (Portugal)
Authors: Cordeiro António , Ornelas Alexandre , Lameiras José Miguel
Published: November 2023

Urban transformations, driven by human activities, result in unique urban ecosystems that significantly impact thermal environments. This study delves into the implications of anthropogenic climate change on diverse urban structures, aiming to enhance urban resilience. A key question arises: how do different urban structures affect the urban thermal environments at multiple scales? This study explores the relationship between urban morphology and temperature variations at both surface and vertical levels during different times of the day. Using data loggers and vertical temperature recordings through UAV, temperature data were collected on pre-established pedestrian pathways that cover different urban morphologies. The selection of the routes covered different densities of urbanized areas and green spaces. This facilitated the creation of a study examining the impact of both 2D and 3D urban green space structures on the thermal landscape of a Mediterranean city—Coimbra, Portugal. The gathered data provided insight into (1) the role of green spaces in the climatic regulation of the city, regardless of the time of the day; (2) the direct relation between surface temperatures and green space morphology; (3) the fact that green spaces act as a cell of fresh air, even in urban areas where there is a measurable urban heat island; (4) the fact that urban areas with green spaces with high tree density present great thermal inertia specific to each morphology in the first 30 m, whereas from 30 to 200 m all profiles present similarly; (5) urban areas with green spaces with high tree density show differentiated temperatures, both at the surface and at altitude. This research underscores the pivotal role of urban green spaces in city planning, emphasizing their importance for bolstering climate change resilience. Acknowledging the thermal regulation benefits offered by green spaces is imperative for aligning with sustainable development objectives in modern cities.
Developmental Dynamics and Driving Factors of Understory Vegetation: A Case Study of Three Typical Plantations in the Loess Plateau of China
Authors: Zhang Hengshuo , Jiao Xuehui , Zha Tonggang , Lv Xizhi , Ni Yongxin , Zhang Qiufen , Wang Jianwei , Ma Li
Published: November 2023

Understory vegetation is one of the most important links for improving forest biodiversity, and its restoration is conducive to sustainable forest development, energy flow, and nutrient cycling. However, little is known about the developmental dynamics and main driving factors of the long-time series coverage, biomass, diversity, and species composition of plantation understory vegetation. In a case study of three typical plantations, with a natural secondary forest as reference in the Loess Plateau of China, we collected understory vegetation from a Robinia pseudoacacia Linn. deciduous broad-leaved plantation, Pinus tabulaeformis Carr. evergreen coniferous plantation, and mixed plantation with an age span of 10 to 50 years. (1) The understory plantation coverage and biomass results of stands with different ages showed the R. pseudoacacia plantation to be significantly higher than the P. tabulaeformis plantation, and the species diversity of the P. tabulaeformis plantation changed the most with the stand age. However, the growth resource imbalance, and drastic changes in the stands’ environment caused by excessive intraspecific competition in the early stage of the P. tabulaeformis plantation vegetation restoration, are the main reasons that make the species diversity of undergrowth vegetation of P. tabulaeformis plantation lower than that of other stand types. (2) The understory species composition of the plantations revealed their degree of community stability. Compared to the R. pseudoacacia plantation and P. tabulaeformis plantation, the mixed plantation had higher stability, and its species composition closely resembled a natural secondary forest. The community stability of the P. tabulaeformis plantation was the lowest because it had the lowest coverage, biomass, and species diversity of understory vegetation. However, the understory species composition of the three plantation types converged, which was due to atypical species contribution. (3) The dynamic changes of canopy and soil nutrients were the main driving factors affecting the R. pseudoacacia plantation understory vegetation species composition. Stand density and elevation limited the understory vegetation communities of P. tabulaeformis plantation restoration. Soil bulk density is the key factor affecting understory vegetation in mixed plantations, and this effect weakens with the stand age. In future studies, the focus should be on the converged action and further development trend of atypical species, choosing an appropriate recovery strategy (active or passive), and providing more possibilities for the intensive management of vegetation under different plantations.
Secure Video Communication Using Multi-Equation Multi-Key Hybrid Cryptography
Authors: Fouzar Youcef , Lakhssassi Ahmed , Mundugar Ramakrishna
Published: November 2023

The safeguarding of intellectual property and maintaining privacy for video content are closely linked to the effectiveness of security protocols employed in internet streaming platforms. The inadequate implementation of security measures by content providers has resulted in security breaches within entertainment applications, hence causing a reduction in the client base. This research aimed to enhance the security measures employed for video content by implementing a multi-key approach for encryption and decryption processes. The aforementioned objective was successfully accomplished through the use of hybrid methodologies, the production of dynamic keys, and the implementation of user-attribute-based techniques. The main aim of the study was to improve the security measures associated with the process of generating video material. The proposed methodology integrates a system of mathematical equations and a pseudorandom key within its execution. This novel approach significantly augments the degree of security the encryption mechanism provides. The proposed methodology utilises a set of mathematical equations that are randomly employed to achieve encryption. Using a random selection procedure contributes to the overall enhancement of the system’s security. The suggested methodology entails the division of the video into smaller entities known as chunks. Following this, every segment is subjected to encryption using unique keys that are produced dynamically in real-time. The proposed methodology is executed via Android platforms. The transmitter application is tasked with the responsibility of facilitating the streaming of the video content, whereas the receiver application serves the purpose of presenting the video to the user. A careful study was conducted to compare and contrast the suggested method with other similar methods that were already in use. The results of the study strongly support the safety and dependability of the procedure that was made available.
A Droplet Digital PCR-Based Approach for Quantitative Analysis of the Adulteration of Atlantic Salmon with Rainbow Trout
Authors: Ma Xiao-Yu , Shao Zhu-Long , Yu Xiao-Ping , Wang Zheng-Liang
Published: November 2023

Low-cost fish species are often used to adulterate or substitute for Atlantic salmon products, posing a serious threat to market order and public health. Hence, reliable techniques are urgently needed to detect Atlantic salmon adulteration. In this study, a precise method for identifying and quantifying adulterated Atlantic salmon with rainbow trout based on droplet digital PCR (ddPCR) testing was developed. Species-specific primers and probes were designed targeting the single-copy nuclear gene myoglobin of two salmonids. A quantitative formula for calculating the mass fraction of adulterated Atlantic salmon with rainbow trout was established based on a one-step conversion strategy, in which the DNA copy number ratios were directly transformed to meat mass fractions by introducing a fixed constant (the transfer coefficient). The dynamic range of the established ddPCR method was from 1% to 90%, with a limit of detection (LOD) of 0.2% and a limit of quantification (LOQ) of 0.8% for rainbow trout in Atlantic salmon, respectively. The quantification method demonstrated an acceptable level of repeatability and reproducibility, as the values of the relative standard deviation (RSD) for the tested meat mixtures with the known fractions were all less than 5%. Thermal and freezing treatments, as well as adding food additives within the recommended dosage limits, had no significant effect on the quantification accuracy. The method was successfully applied to detect rainbow trout adulteration in commercial raw and processed Atlantic salmon products. In comparison to real-time quantitative PCR (qPCR) testing, the established ddPCR method exhibited a higher level of stability and accuracy. Overall, the ddPCR-based quantitative method exhibited high levels of accuracy, stability, sensitivity, and practicability, suitable for applications in the routine surveillance and quality assurance of salmon products.
Analysis of the Influence of Socio-Demographic Variables and Some Nutrition and Lifestyle Habits on Beverage Consumption in the Spanish Population
Authors: Sandri Elena , Modesto i Alapont Vicent , Cantín Larumbe Eva , Cerdá Olmedo Germán
Published: November 2023

Beverages and drinks play a significant role in maintaining the integral health of individuals. The aim of this study is to discover the pattern of beverage consumption in different groups of the Spanish population and to investigate its relationship with other nutritional variables and habits. To achieve the objectives, an observational, descriptive and cross-sectional study was conducted. For data collection, a questionnaire was designed and validated that explored different beverage and food consumption variables as well as socio-demographic and lifestyle variables. The instrument was disseminated, among the Spanish young adult population, through snowball sampling using social networks, collecting a sample of 17,541 valid surveys. Bivariate comparative analyses and correlation analyses were performed, and finally, the principal component analysis (PCA) method was used in order to study the relationships between variables related to drinking and health. The main results show significant differences in the pattern of beverage consumption between the socio-demographic variables of sex, age and educational level, as well as between different areas of Spain, while the PCA model shows the relationship between the consumption of sugar-sweetened beverages with the Healthy Nutrition Index of the population and sport practice. Based on the results of the study, the following conclusions were reached: the beverage consumption pattern of the Spanish population is affected by socio-demographic variables. Healthier drinking habits affect the nutrition and health of the population.
Characterization and In Vitro Antioxidant and Anti-Inflammatory Activities of Ginsenosides Extracted from Forest-Grown Wild Panax quinquefolius L.
Authors: Yang Yang , Xu Shan , Yang Kemeng , Sun Yuning , Yang Ruirui , Hu Yanan , Chen Guijie , Cai Huimei
Published: November 2023

American ginseng (Panax quinquefolius L.) is known for its health benefits, which are attributed to various terpenoids. However, the specific composition and activities of these terpenoids in forest-grown wild American ginseng remain understudied. This study aimed to characterize the terpenoid composition, particularly triterpene saponins, in forest-grown wild American ginseng. The analysis revealed that triterpene saponins, notably American ginseng ginsenosides (AGGs), are the predominant active components, as identified through LC-MS/MS and HPLC. A subsequent in vitro evaluation of AGGs showcased their potent antioxidant capabilities, displaying the dose-dependent scavenging of free radicals and reducing agents. Moreover, AGGs demonstrated efficacy in reducing oxidative injury and intracellular ROS levels in RAW 264.7 macrophages treated with H2O2. In addition to their antioxidant properties, AGGs exhibited anti-inflammatory effects, significantly inhibiting NO and inflammatory substance production in lipopolysaccharide-treated RAW 264.7 macrophages. These findings highlight the potential of AGG-rich forest-grown wild American ginseng as a functional food with promising implications for improving human health.
Increase in Lactulose Content in a Hot-Alkaline-Based System through Fermentation with a Selected Lactic Acid Bacteria Strain Followed by the β-Galactosidase Catalysis Process
Authors: Guo Yaozu , Ma Wenlong , Song Manxi , Wang Wenqiong , Yin Boxing , Gu Ruixia
Published: November 2023

In this study, lactic acid bacteria (LAB) fermentation and β-galactosidase catalysis methods were combined to increase the lactulose concentration and reduce the galactose and lactose content in a hot-alkaline-based system. The optimal conditions for chemical isomerization were 70 °C for 50 min for lactulose production, in which the concentration of lactulose was 31.3 ± 1.2%. Then, the selection and identification of LAB, which can utilize lactose and cannot affect lactulose content, were determined from 451 strains in the laboratory. It was found that Lactobacillus salivarius TM-2–8 had weak lactulose utilization and more robust lactose utilization. Lactobacillus rhamnosus grx.21 was weak in terms of lactulose utilization and strong in terms of galactose utilization. These two strains fermented the chemical isomerization system of lactulose to reduce the content of lactose and galactose. The results showed that the lactose concentration was 48.96 ± 2.92 g/L and the lactulose concentration was 59.73 ± 1. 8 g/L for fermentation lasting 18 h. The β-galactosidase was used to increase the content of lactulose in the fermented system at this time. The highest concentration of 74.89 ± 1.68 g/L lactulose was obtained at an enzymatic concentration of 3 U/mL and catalyzed at 50 °C for 3 h by β-galactosidase.
Internal Quality Assessment of East African Highland Cooking Banana (Musa spp.) Flour: Significance for Breeding and Industrial Applications
Authors: Khakasa Elizabeth , Muyanja Charles , Mugabi Robert , Mukasa Yusuf , Babirye Mary P. , Balikoowa Brian , Namanya Priver , Kubiriba Jerome , Arinaitwe Ivan K. , Nowakunda Kephas
Published: November 2023

This study assessed the internal quality traits of East African Highland cooking banana flours, exploring their significance for breeding and potential industrial applications. Twenty cultivars (nine hybrids and eleven landraces) were used. Swelling power capacity, water solubility, water absorption capacity, water absorption index, freeze–thawing stability, and pasting characteristics of banana flour were assessed using standard methods. The results showed that cultivars with high swelling power also exhibited a high water absorption capacity and water absorption index, thus making them suitable for bakery industries. The water absorption capacity ranged between 5.66% (N2) and 11.68% (N11). Landraces KBZ (9.01) and NKYK (8.05), and hybrids N11 (11.68) and N9 (8.48) are suitable as thickeners due to high WAC. Hybrids (N7, 27.83%, and N9, 22.59%) and landraces (NMZ, 32.69%, and NFK, 34.24%) had low freeze–thawing stability, hence it is applicable as a food stabilizer. Landrace NKT (19.14%) and hybrid N9 (16.95%) had the highest solubility, and landrace KBZ (6.93%) and hybrid N3 (6.66%) had the lowest solubility. Landraces MSK (6265), NKY (3980), and NFK (3957), and hybrids N6 (3608), N7 (3505), and N9 (3281 RVU) had high peak viscosity. The trough viscosity, final viscosity, and breakdown viscosity of cultivars varied from 422.5 to 5004 RVU. The landraces MSK (5021 RVU) and NFK (4111 RVU) had the highest final viscosity, making them suitable for application in the food industry for thick and stable sauces. Landrace TRZ had the lowest pasting temperature (62.7 °C), making it advantageous for use where fast gelatinization is required, hence saving energy costs and cooking time. These findings suggest that the genetic attributes inherent in cultivars can be incorporated into breeding programs targeting required traits for industrial application.
Fungal and Toxin Contaminants in Cereal Grains and Flours: Systematic Review and Meta-Analysis
Authors: Deligeorgakis Christodoulos , Magro Christopher , Skendi Adriana , Gebrehiwot Haileeyesus Habtegebriel , Valdramidis Vasilis , Papageorgiou Maria
Published: November 2023

Cereal grains serve as the cornerstone of global nutrition, providing a significant portion of humanity’s caloric requirements. However, the presence of fungal genera, such Fusarium, Penicillium, Aspergillus, and Alternaria, known for their mycotoxin-producing abilities, presents a significant threat to human health due to the adverse effects of these toxins. The primary objective of this study was to identify the predominant fungal contaminants in cereal grains utilized in breadmaking, as well as in flour and bread. Moreover, a systematic review, including meta-analysis, was conducted on the occurrence and levels of mycotoxins in wheat flour from the years 2013 to 2023. The genera most frequently reported were Fusarium, followed by Penicillium, Aspergillus, and Alternaria. Among the published reports, the majority focused on the analysis of Deoxynivalenol (DON), which garnered twice as many reports compared to those focusing on Aflatoxins, Zearalenone, and Ochratoxin A. The concentration of these toxins, in most cases determined by HPLC-MS/MS or HPLC coupled with a fluorescence detector (FLD), was occasionally observed to exceed the maximum limits established by national and/or international authorities. The prevalence of mycotoxins in flour samples from the European Union (EU) and China, as well as in foods intended for infants, exhibited a significant reduction compared to other commercial flours assessed by a meta-analysis investigation.
Assessing Awareness of Colorectal Cancer Symptoms among Outpatients: A Cross-Sectional Study at a Hospital in Vietnam
Authors: Nguyen Chon Kim , Phan Hieu Minh , Lee Chao-Hsien , Do Lan Anh Thi
Published: November 2023

Colorectal cancer (CRC) is a prevalent cancer globally, including in Vietnam where its incidence is rapidly increasing. The aim of this study was to evaluate the awareness of signs, symptoms, and risk factors of colorectal cancer among outpatients at Hoa Hao Medic Company Limited, Ho Chi Minh City, Vietnam. A cross-sectional study was conducted, and a total of 441 people who visited Hoa Hao Medic Company Limited for a general health check-up and voluntarily agreed to participate in this study were recruited through the convenience sampling method. Data were collected through face-to-face structured interviews using the Bowel CAM questionnaire. According to the results, the highest percentage of well-recalled warning signs were “change in bowel habit” (36.7%) followed by abdominal pain (35.4%). Other warning signs such as weight loss and rectal bleeding were reported by 19.0% and 18.1% of participants, respectively. Over 42% of participants stated that they were unaware of any signs or symptoms. The most commonly identified risk factors for CRC were pollution (66.9%), genetics (50.6%), and an unhealthy/poor diet (53.7%) for unprompted questions. The overall awareness score of participants was 3.46/9 (SD ± 2.91) for signs and symptoms of CRC and 5.90/10 (SD ± 1.62) for risk factors. Univariate linear regression identified education level and occupation as predictors of higher CRC awareness. In conclusion, this study highlights that overall awareness of CRC is low among outpatients at Hoa Hao Medic Company Limited. Strategies to increase awareness, knowledge, and education programs are necessary to promote early detection of CRC and reduce its burden in Vietnam.
Effects of Different Storage Temperatures and Methyl Jasmonate on Grape Quality and Antioxidant Activity
Authors: Elatafi Essam , Elshahat Abdelmonem , Xue Yu , Shaonan Li , Suwen Lu , Tianyu Dong , Fang Jinggui
Published: November 2023

The aim of this study was to find out how different postharvest temperatures and MeJA treatments affected the quality of table grapes, their antioxidant properties, and the amount of hydrogen peroxide and malondialdehyde they contained. For the investigation, postharvest Shine Muscat table grapes were treated with low and high temperatures and MeJA at concentrations of 10 and 100 μmol/L. The results indicated that treating grape berries with MeJA at concentrations of 10 and 100 μmol/L effectively reduced weight loss and mitigated the increase in soluble solid content while also mitigating the decrease in berry firmness and titratable acidity. Consequently, this treatment preserved the sensory and nutritional qualities of the berries and extended their shelf life. Meanwhile, the application of MeJA at a concentration of 10 μmol/L demonstrated superior effectiveness compared to the 100 μmol/L concentration and resulted in a significant enhancement of antioxidant activities by increasing levels of superoxide dismutase, catalase, ascorbate peroxidase, and polyphenol oxidase. Furthermore, the levels of hydrogen peroxide and malondialdehyde in the samples increased for all treatments throughout the storage period. Nevertheless, the levels of hydrogen peroxide and malondialdehyde generation following MeJA treatment remained much lower compared to samples treated at room temperature and low temperature. Therefore, the postharvest application of MeJA at a concentration of 10 μmol/L could play a critical role as a stimulator of fruit quality as well as enhance physicochemical parameters and antioxidant activities for extending the shelf life of grapes during storage.
Measuring the Multiple Functions and Tradeoffs among Streets: A New Framework Using the Deep Learning Method
Authors: Fu Shihang , Fang Ying , Wang Nannan , Tong Zhaomin , Liu Yaolin
Published: November 2023

With the sustainable and coordinated development of cities, the formulation of urban street policies requires multiangle analysis. In regard to the existing street research, a large number of studies have focused on specific landscapes or accessibility of streets, and there is a lack of research on the multiple functions of streets. Recent advances in sensor technology and digitization have produced a wealth of data and methods. Thus, we may comprehensively understand streets in a less labor-intensive way, not just single street functions. This paper defines an index system of the multiple functions of urban streets and proposes a framework for multifunctional street measurement. Via the application of deep learning to Baidu Street View (BSV) imagery, we generate three functions, namely, landscape, traffic, and economic functions. The results indicate that street facilities and features are suitably identified. According to the multifunctional perspective, this paper further classifies urban streets into multifunctional categories and provides targeted policy recommendations for urban street planning. There exist correlations among the various street functions, and the correlation between the street landscape and economic functions is highly significant. This framework can be widely applied in other countries and cities to better understand street differences in various cities.
Emerging Digital Technologies in Healthcare with a Spotlight on Cybersecurity: A Narrative Review
Authors: Arafa Ahmed , Sheerah Haytham A. , Alsalamah Shada
Published: November 2023

Emerging digital technologies, such as telemedicine, artificial intelligence, the Internet of Medical Things, blockchain, and visual and augmented reality, have revolutionized the delivery of and access to healthcare services. Such technologies allow for real-time health monitoring, disease diagnosis, chronic disease management, outbreak surveillance, and rehabilitation. They help personalize treatment plans, identify trends, contribute to drug development, and enhance public health management. While emerging digital technologies have numerous benefits, they may also introduce new risks and vulnerabilities that can compromise the confidentiality, integrity, and availability of sensitive healthcare information. This review article discussed, in brief, the key emerging digital technologies in the health sector and the unique threats introduced by these technologies. We also highlighted the risks relevant to digital health cybersecurity, such as data breaches, medical device vulnerabilities, phishing, insider and third-party risks, and ransomware attacks. We suggest that the cybersecurity framework should include developing a comprehensive cybersecurity strategy, conducting regular risk assessments, implementing strong access control, encrypting data, educating staff, implementing secure network segmentation, backing up data regularly, monitoring and detecting anomalies, establishing an incident response plan, sharing threat intelligence, and auditing third-party vendors.
Machine Learning for Prediction of the International Roughness Index on Flexible Pavements: A Review, Challenges, and Future Directions
Authors: Tamagusko Tiago , Ferreira Adelino
Published: November 2023

Timely maintenance of road pavements is crucial to ensure optimal performance. The accurate prediction of trends in pavement defects enables more efficient allocation of funds, leading to a safer, higher-quality road network. This article systematically reviews machine learning (ML) models for predicting the international roughness index (IRI), specifically focusing on flexible pavements, offering a comprehensive synthesis of the state-of-the-art. The study’s objective was to assess the effectiveness of various ML techniques in predicting IRI for flexible pavements. Among the evaluated ML models, tree ensembles and boosted trees are identified as the most effective, particularly in managing data related to traffic, pavement structure, and climatic conditions, which are essential for training these models. Our analysis reveals that traffic data are present in 89% of the studies, while pavement structure and climatic factors are featured in 78%. However, maintenance and rehabilitation history appears less frequently, included in 33% of the studies. This research underscores the need for high-quality, standardized datasets, and highlights the importance of model interpretability and computational efficiency. Addressing data consistency, model interpretability, and replicability across studies are crucial for leveraging ML’s full potential in fine-tuning IRI predictions. Future research directions include developing more interpretable, computationally efficient, and less complex models to maximize the impact of this research field in road infrastructure management.
Cyclic Detectors in the Fraction-of-Time Probability Framework
Authors: Dehay Dominique , Leśkow Jacek , Napolitano Antonio , Shevgunov Timofey
Published: November 2023

The signal detection problem for cyclostationary signals is addressed within the fraction-of-time probability framework, where statistical functions are constructed starting from a single time series, without introducing the concept of stochastic process. Single-cycle detectors and quadratic-form detectors based on measurements of the Fourier coefficients of the almost-periodically time-variant cumulative distribution and probability density functions are proposed. The adopted fraction-of-time approach provides both methodological and implementation advantages for the proposed detectors. For single-cycle detectors, the decision statistic is a function of the received signal and the threshold is derived using side data under the null hypothesis. For quadratic-form detectors, the decision statistic can be expressed as a function of the received signal without using side data, at the cost of some performance degradation. The threshold can be derived analytically. Performance analysis is carried out using Monte Carlo simulations in severe noise and interference environments, where the proposed detectors provide better performance with respect to the analogous detectors based on second- and higher-order cyclic statistic measurements.
Delivery of Topical Drugs to the Olfactory Cleft
Authors: Espehana Andreas , Lee Liam , Garden Elizabeth Mairenn , Klyvyte Gabija , Gokani Shyam , Jegatheeswaran Lavandan , Wong Jeremy Jonathan , Philpott Carl
Published: November 2023

Olfactory dysfunction affects approximately 20% of the population globally, with incidence increasing over the age of 60. The pathophysiology is complex, not yet fully understood, and depends on many factors, including the underlying cause. Despite this, the present literature on olfaction is limited due to significant heterogeneity in methodological approaches. This has resulted in limited effective treatments available for olfactory dysfunction. Medications for olfactory dysfunction can be administered locally (directly to the olfactory epithelium) or systemically (orally or intravenously). Currently, there are various methods for local drug delivery to the olfactory epithelium (nasal drops, nasal sprays, atomisers, pressured meter-dosed inhalers, rinses, and exhalation delivery systems). The aims of this review are to summarise the different methods of drug delivery to the olfactory cleft, evaluate the current literature to assess which method is the most effective in delivering drugs to the olfactory epithelium, and review the medications currently available to treat olfactory dysfunction topically. Going forward, further research is required to better establish effective methods of drug delivery to the olfactory epithelium to treat smell disorders.
The Use of Oral Anticoagulation Is Not Independently Associated with Mortality in Frail Older Patients with Repeated Falls
Authors: Zwart Lennaert A. R. , Walgers Jeske J. , Hemels Martin E. W. , Germans Tjeerd , de Groot Joris R. , Jansen René W. M. M.
Published: November 2023

Background: Particularly in frail patients, anticoagulation may be underused because of the fear of bleeding. Objective: To determine whether the use of antithrombotic medication is an independent risk factor for mortality in frail elderly with repeated falls. Methods: All patients aged 65 years or older at the Fall and Syncope Clinic were eligible. Frailty was calculated with a Frailty Index (FI) based on the accumulation of deficits model. Risks were calculated with a cox regression analysis, adjusted for age, sex, and Frailty Index. Results: 663 patients were included in this analysis. The median age was 80 years, 438 were women (66%), 73% had polypharmacy, and 380 patients (57%) had cognitive impairment. The mean FI was 0.23 (sd 0.09), 182 patients were moderately frail (27.5%), and 259 (39.1%) were severely frail. A total of 140 (21%) used oral anticoagulation and 223 (34%) used antiplatelet agents. A total of 196 patients (29.6%) died during follow-up. In the adjusted cox regression model, the use of neither antiplatelets nor anticoagulation was associated with mortality. A strong association was found with frailty (HR 74.0, 95% CI 13.1–417.3) and a weak association with age (HR 1.05, 95% CI 1.03–1.08). A lower risk of mortality was seen in women (HR 0.5, 95% CI 0.3–0.6). Conclusions: In this cohort of frail older patients, there was no independent association between the use of antithrombotic medication and mortality. A strong association with mortality was found with frailty, a weak association was found with age, and a lower mortality risk was found in women. Our data indicate that the fear of bleeding or increased mortality in frail patients with an indication for oral anticoagulation may be unjustified.
Role of the NeuroCuple™ Device for the Postoperative Pain Management of Patients Undergoing Unilateral Primary Total Knee and Hip Arthroplasty: A Pilot Prospective, Randomized, Open-Label Study
Authors: Chelly Jacques E. , Klatt Brian A. , Groff Yram , O’Malley Michael , Lin Hsing-Hua Sylvia , Sadhasivam Senthilkumar
Published: November 2023

Background: The potential effectiveness of the non-pharmacological and nanotechnology-based NeuroCuple™ device in reducing postoperative surgical pain and opioid consumption remains unknown. Methods: This randomized controlled open-label study was conducted in patients undergoing a primary unilateral total knee or total hip arthroplasty. In the recovery room, patients were randomized to receive either standard of care (control group) or standard of care plus two NeuroCuple™ devices. The outcome variables included pain and opioid consumption (oral morphine equivalent, OME in milligrams). Results: A total of 69 patients were randomized to either the NeuroCuple™ group (n = 38) or the control group (n = 31). Use of the NeuroCuple™ devices was associated with a significant 34% reduction in pain at rest (means of area under the curve: 6.3 vs. 9.5; p = 0.018) during postoperative days 1–3. Opioid consumption was reduced by 9%. More importantly, use of the NeuroCuple™ devices reduced the number of patients requesting an opioid prescription following discharge from the hospital by 52% (26% vs. 55%, p = 0.016). Conclusions: Our data suggest that the NeuroCuple™ device may be an effective non-pharmacological alternative to opioids to manage postoperative pain following unilateral arthroplasty due to its ability to reduce postoperative opioid use.
The Use of Methotrexate and Mifepristone for Treatment of Interstitial Pregnancies: An Overview of Effectiveness and Complications
Authors: Dealberti Davide , Franzò Simona , Bosoni David , Pisani Carla , Morales Victor , Gallesio Ivan , Bruno Matteo , Ricci Giuseppe , Carlucci Stefania , Stabile Guglielmo
Published: November 2023

Interstitial pregnancy is an unusual and potentially life-threatening form of ectopic pregnancy, accounting for approximately 1–6% of all ectopic pregnancies, with a maternal mortality rate of 2–2.5%. Implantation happens in the proximal portion of the fallopian tube as it passes through the myometrium. The resolution of interstitial pregnancy after medical treatment should be assessed by a decline in serum β-hCG, which occurs in about 85–90% of cases. Nonetheless, its effectiveness and consequences have been presented through case reports and case series. However, few cases of interstitial pregnancies treated totally medically with the use of methotrexate and mifepristone have been presented in the literature. Complications of this medical treatments have also never been reviewed before. In the present manuscript, we present a case of interstitial pregnancy treated with methotrexate and mifepristone. The patient after treatment developed a uterine arteriovenous malformation, treated with uterine artery embolization. Furthermore, we performed a systematic review of the literature using Scopus, PubMed and Google Scholar. A total of 186 papers were found, and 7 papers which included 10 cases were assessed for eligibility. The systemic medical treatment with the use of methotrexate and mifepristone was effective in 7 of the 10 cases. Two cases of hemoperitoneum following combined methotrexate and mifepristone treatment were reported. The applicability of this medical conservative treatment should be tailored to the patient, taking into account their obstetric history, gestational age at diagnosis and desire for future pregnancies. Complete resolution after this treatment was achieved in most of the cases reported without major complications. The appearance of uterine arteriovenous malformation can be managed conservatively, and we propose uterine artery embolization as an effective treatment of this rare complication.