bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of Risk Factors on the Prevalence of Cardiovascular Disease
Authors: Bakare Abiola Basirat , Ghafoor Mubeen , Mura Manuela , Ahmed Waqar
Published: September 2023

The growing rate of cardiovascular disease all over the globe is so alarming that urgent measures need to be put in place. Approximately 18 million deaths are recorded every year globally due to cardiovascular disease. People living with high blood pressure, diabetes, high cholesterol level, or living poor are at high risk of developing cardiovascular disease. Other factors include age, gender, family history, and ethnic group. Understanding the risks of cardiovascular disease can help individuals, organizations, and governments promote a healthy lifestyle. Cleveland heart disease dataset was collected from online and open source for the purpose of this study. The dataset includes 297 medical records of patients between the ages of 29-77. The dataset was processed and analyzed in Microsoft Excel using frequency counts and percentages. The risk factors are important risk factors of cardiovascular disease for the participant of the study. Discussion on the use of biomaterials in fabricating tissue-engineered nanofibers for the treatment of cardiovascular diseases is also presented.
Social Media Influencers
Authors: Rossanty Yossie , Masnita Yolanda , Riorini Sri Vandayuli , Nasution Muhammad Dharma Tuah Putra
Published: September 2023

In the realm of marketing, the rise of influencer marketing and its integration with social media platforms have brought about a significant change in communication strategies. This convergence has led to a transformative shift in the marketing field. This study aims to investigate the diverse roles of social media influencers in promoting Halal brands. Specifically, it focuses on how influencers shape consumer attitudes and perceptions. The research also examines the complex interactions among influencers, opinion leaders, and endorsers in modern marketing. These insights are valuable for marketers, advertisers, and scholars. By offering a comprehensive understanding, this study enriches our knowledge of the evolving marketing landscape, the impact of social media on consumer behavior, and the intricate aspects of brand perceptions. This contributes to existing knowledge and provides a basis for future research.
Understanding the Behavior of Qardhul Hassan Borrowers in Nano-Entrepreneurship
Authors: Musari Khairunnisa , Fajariyah Nur Alifah , Khotimah Khusnul
Published: September 2023

Most emerging countries have communities categorized as excluded and underserved, unbanked and underbanked, the bottom of the pyramid (BoP), and ultra poor which have no ability to access bank financing. They are often victims of loan sharks. They should be a target of microfinance, but most banks and also microfinance institutions (MFIs) do not yet do well in serving them. Likewise, Islamic microfinance in fact has also not succeeded in reaching these people. Islamic nanofinance through qardhul hassan is promoted as a new paradigm to fill the Islamic microfinance gap. Through a field experiment for eight months by providing a fund IDR5 million with a maximum loan IDR1 million to provide nanofinancing, this study investigated the financial behavior of the nano-entrepreneurs in managing the qardhul hassan in Indonesia. The outcome of this study is expected to be input for policymakers, especially for the Islamic micro-industry, to come up with financing schemes according to the characteristics of these communities.
Islamic Quadruple Helix
Authors: Musari Khairunnisa , Sayah Fatima
Published: September 2023

Rooted in sharia values, Islamic finance should have the eligibility to lead microfinance in contributing to financial inclusion in Islamic countries in the Maghreb region. However, Islamic microfinance in this region has not been going well. At least when compared to the Southeast Asian region, Islamic microfinance in this region is still lagging behind. Through a literature study, this conceptual chapter promotes the Islamic Quadruple Helix approach, which integrates the Islamic social finance partnership model and digitalization to accelerate financial inclusion in this region. Therefore, this chapter focuses on three issues: (1) Describe the facts and figures of Islamic finance in the Maghreb region; (2) Explain the role of Islamic social finance partnership and digitalization in fulfilling the lack of Islamic microfinance in this region; and (3) Map the digital financial inclusion ecosystem in this region by illustrating the role of involvement from a number of parties.
Involvement of Women in Islamic Finance in Pakistan
Authors: Nasir Nazia , Zafar Muhammad Bilal , Nawaz Muhammad
Published: September 2023

The purpose of the study is to explore challenges facing by women and avenues of future prospects available for women in Islamic finance in Pakistan. To achieve the purpose of the study, in-depth interviews from women working in academia and industry associated with Islamic finance were conducted through purposive and snowball sampling. The findings revealed that women prefer to earn HALAL money as a source of income and they have an opportunity to work in Islamic bank rather than traditional bank. Unfortunately, due to male-dominated society, women face inequalities at the workplace as well. Along with having challenges, obstacles and gender stereotype issues, women are trying to overcome the barriers. The findings of this study may motivate women to get education in order to assess their future potential in both academics and industry of Islamic finance in Pakistan. Moreover, this study draws the attention of government and regulatory agencies to develop policies that support women, and increasing the proportion of women in the Islamic finance sector.
Entrepreneurial Intentions From an Islamic Perspective
Authors: Hussain Zahid , Mari Asadullah , Arif Muhammad
Published: September 2023

In Islam, with its own method of doing business as stated in the Quran and Hadith, entrepreneurship is part of everyday life. In Islam, determining a person's intentions and personality traits when starting a business largely depends on his intentions. This study attempts to cast an Islamic perspective on Muslim business owners in Pakistan regarding the concept and element of business intent. A survey of over 250 Muslim business owners in Pakistan was conducted to collect primary data on the motivations and characteristics of Pakistani Muslim entrepreneurs, such as their reasons for deciding to pursue a career. According to previous studies, the two main characteristics of business intentions in Islam are honesty and worship of Allah (functions of a spiritual, personal, and socio-economic nature). This research shows that all human behavior, especially that related to entrepreneurship, has been consistently driven by the effects of five key traits on entrepreneurial personalities: amanah, tabligh, fathonah, istiqomah, and saddiq.
Islamic Entrepreneurship Application and Its Strategies
Authors: Pananjung Alfatih Gessan , Ala Ammar Ibna , Rafiki Ahmad
Published: September 2023

This study aims to explore various facets of entrepreneurship, particularly Islamic entrepreneurship, from a religious perspective, with a focus on its practice within the context of Bangladesh. In Bangladesh, diverse social enterprises, some profit-driven and rooted in Islamic principles like Zakat and Waqf, exemplify Islamic entrepreneurship. Examples include the Baitul Mukarram complex and the Islamic Bank Hospital, which generate income, promote Islamic culture, and address social needs. Social Islamic Bank Ltd. employs Cash Waqf, while organizations like Muslim Aid Bangladesh focus on economic empowerment. These approaches showcase the blend of profit motives, social impact, and religious values in Bangladeshi Islamic entrepreneurship.
Pre-Service Teacher Preparation for Inclusive Teaching in South Africa
Authors: Makoelle Tsediso Michael , Mosito Cina P.
Published: September 2023

Inclusive teaching should seek to promote teacher adaptation of their attitudes, teaching methods, and assessment approaches to respond to the needs of all their students in the classroom. Teacher support may ensure the success of all students in their learning process. Therefore, pre-service teacher training should ensure the enhancement of pre-service teacher skills such that pre-service teachers are able to deal with barriers to learning and support vulnerable students such as those with special educational needs and disability. This chapter gives an overview of teacher education in Africa and South Africa, conceptualises pre-service teacher preparation for inclusion, discusses various approaches used to prepare pre-service teachers. The challenges of pre-service teacher transition to inclusive teaching are highlighted. The role of the practicum in relation to teacher preparation for inclusive teaching is illuminated. Based on the critical analysis of the literature, lessons are drawn regarding pre-service teacher preparation and recommendations are made.
Catering for Learner Diversity
Authors: Goburdhun Seema , Ramsaha Prema
Published: September 2023

The chapter situates the discussion on learners' diversity at the primary classroom level in the context of the nine year continuous basic education (NYCBE), the educational reform which is geared to address the diversity and inclusion of Mauritian learners in the schooling setup. Learners' diversity in the Mauritian context can be due to their cultural, social, and economic backgrounds. With this demographic and varied profile of learners, teachers are faced with multiple and complex issues that may challenge many of their educational practices and assumptions. A qualitative research methodology was adopted to understand primary school teachers' perceptions of diversity. An in-depth interview with eight teachers was conducted to have insight into how they addressed diversity and what support and mechanism are in place to assist them in addressing the needs of learners. Findings point to the need for teacher preparedness and collaboration among stakeholders in establishing an inclusive school environment.
Machine Learning in Healthcare
Authors: Kasbe Tanmay
Published: September 2023

Applications of machine learning techniques (ML) are having a significant impact on a number of expanding industries, including the healthcare sector. ML is a part of artificial intelligence (AI) technology with the primary objective to increase the efficiency and precision of medical professionals' work. AI presents a significant opportunity in the healthcare sector as most countries are now struggling with overburdened healthcare systems and a dearth of competent medical personnel. Healthcare data is expanding daily and can be utilised to choose the best study sample, gather additional data points, and assess participant data from ongoing studies. ML-based methods/algorithms are employed in the early detection and diagnosis of numerous diseases. For a very long time, early disease prediction and detection have been crucial areas of research for the diagnosis of all diseases. Machine‐learning (ML) algorithms have proven to be quite efficient in disease detection and decision making in healthcare.
Artificial Intelligence Approach for Detecting Macrocephaly and Microcephaly in Avoiding Pregnancy Complications
Authors: Pandyan Uma Maheswari , Mohamed Mansoor Roomi S. , Priya K. , Sathyabama B. , Senthilarasi M.
Published: September 2023

Ultrasound imaging is one of the vital image processing techniques that aids doctors to access and diagnose the feotal growth process by measuring head circumference (HC). This chapter gives a detailed review of cephalic disorders and the importance of diagnosing disorders in the earlier stage using ultrasound images. Additionally, it proposes an approach that uses four primary stages: pre-processing, pixel-based feature extraction, classification, and modeling. A cascaded neural network model based on ultrasound images is recommended to identify and segment the HC of the feotus during the extraction phase. According to the findings of the experiments, both the rate of head circumference measurement detection and segmentation accuracy has significantly increased. The proposed method surpasses the state-of-the-art approaches in all criteria, two assessment criteria for HC measurement, is qualitatively distinct from other prior methods, and attained an accuracy of 96.12%.
Classification and Methods of Acute Lymphoblastic Leukemia Detection Using Neural Network
Authors: Mercy Bai G. , Venkadesh P. , Divya S. V.
Published: September 2023

Leukemia is a cancer of the blood that starts from bone marrow then spreads into the bloodstream and other vital organs. Based on lymphoid or myeloid stem cells becoming cancerous, leukemia can be divided into myeloid leukemia and lymphoblastic leukemia. The EM-algorithm-based method uses statistics techniques to classify three types of leukocytes (i.e., band neutrophils, eosinophils, and lymphocytes). This method projects the image patterns onto lower dimensional subspaces by PCA and uses EM-algorithm to find the maximum likelihood solution for the models with latent variable. The SVM-based method uses the texture, shape, and color as the features to describe leukocytes. This chapter includes blood, introduction of ALL disease with its types, steps of ALL disease detection, detection types of ALL disease detection, and conclusion.
Analysis of Fetus Image Using 2D Ultrasound Images
Authors: Naresh R. , Arunthathi S. , Vinoth Kumar C. N. S. , Senthilkumar S. , Deepa N.
Published: September 2023

This chapter proposes a novel approach for semi-automatic segmentation of 2D fetal ultrasound images using active contour level set method and measurement of fetus parameters such as bi-parietal diameter (BPD), head circumference (HC), femur length (FL), abdomen circumference (AC), and estimated fetal weight (EFW). After measurement of those parameters, those values are compared with standard values of the corresponding trimester and classify the fetus growth in each trimester using radial basis network (RBN) classifier. The need for computerized automatic fetus measurement technique has been increased in the medical domain. However, segmentation of ultrasound image has a variety of challenges such as high noise, low contrast boundaries and intensity variations. In order to minimize those problems, three filters are used in the preprocessing stage, namely wiener filter, median filter, and order filter, and its mean square error (MSE) and peak-signal to noise ratio (PSNR) values are calculated and compared for selecting the optimum filter.
Quantitative Analysis of Cervical Image to Predict the Complications of Pregnancy
Authors: Nagarani N. , Jothiraj Sivasankari , Venkatakrishnan P. , Senthil Kumar R.
Published: September 2023

The period of life during pregnancy for young parents is pleasant, especially for the mother. Many factors are taken into account during pregnancy, including the fetal heart, head position, cervical dilation, thickness, position, and length. The cervical length should be routinely assessed by ultrasound if it is less than 25 mm. The authors hope to use this participatory framework to generate new ideas for defining normal and abnormal cervical function during pregnancy. Recently, deep learning techniques have revolutionized artificial intelligence (AI) research in pregnancy. Cervical image data obtained by ultrasound are often compared using computer vision pattern analysis, which promises to be a major revolution. In further research and development in AI-based ultrasonography, the clinical application of AI in medical ultrasonography faces unique obstacles. This chapter focuses on the utilization of machine learning approaches in prenatal medicine, with a particular emphasis on interpretable ML applications that produce objective results and assist doctors in identifying key parameters
Investigating Detection Strategy of Gestational Diabetes Mellitus During Pregnancy Using Machine Learning
Authors: Gandhimathi Alias Usha S. , Janani V. G. , Anusuya V. , Selvarani A.
Published: September 2023

Artificial intelligence has been applied to numerous applications such as health, finance, social media, and online customer support systems. Machine learning (ML) is a subdivision of artificial intelligence and plays a vital role in health care prediction and diagnosis. It has been widely used to anticipate the mode of childbirth and evaluating the potential matriarchal hazards during pregnancy. This chapter aims to review the machine learning techniques to predict prenatal complications. Gestational diabetes mellitus (GDM) is a type of diabetes that develops during pregnancy. It is a condition in which the body is unable to produce enough insulin to meet the increased insulin needs of the mother and the developing fetus. This results in high blood sugar levels, which can cause complications for both the mother and the baby. This chapter explores the current research and development perspectives that utilize the ML techniques to anticipate the optimal mode of childbirth and to detect various complications during childbirth.
Complications in Pregnant Women
Authors: Natarajan Sumathi , Muthanantha Murugavel A. S. , Palanisamy Selvanayaki , Deepa S.
Published: September 2023

Some typical pregnancy issues will be discussed in this chapter. Despite a declining pregnancy rate throughout time, attaining pregnancy and having a healthy baby are two of today's most prized accomplishments. If pregnant women go for check-ups on a regular basis, most of the issues can be detected and treated successfully. The majority of pregnancies and births (80%) still have no difficulties. Lifestyle, diet, financial influence, and maternal age are major contributors in pregnancy complications. Pregnancy complications may occur in either first trimester, second trimester, or third trimester. High blood pressure, gestational diabetes, preeclampsia, premature labour, miscarriage, ectopic pregnancy, amniotic fluid, anaemia, stillbirth, placental difficulties, anxiety, depression, and stress during pregnancy are the major complications that might arise during pregnancy.
Solutions for Complications in Pregnant Women
Authors: Charanya J. , Renugadevi A. S. , Vennila A.
Published: September 2023

All pregnancies carry a risk, even though the majority of pregnancies and deliveries go smoothly. In order to assess a variety of health data, including patient information from multibiotic techniques, clinical, and medicine information, as well as from different information remembered for the biomedical literature, artificial intelligence can help experts in direction, limiting clinical blunders, upgrading exactness in the understanding of various judgments, and diminishing the weight they are exposed to. Placental adhesive disorders are seen in women who have had a previous caesarean section or placenta previa and can result in issues like neonatal hemorrhage and visceral damage. The tree-based pipeline advancement device has shown incredible execution of placental invasion with an AUC and a accuracy of 0.980 and 95.2%, individually. Convolutional neural networks had an accuracy 97.8%, 98.4% for predicting fetal acidemia, individually. Utilizing the AdaBoost model, one more tool that attempted to diagnose pre-eclampsia performed well, with an AUC of 0.964 and a precision of 89%.
Pregnancy in the Digital Age
Authors: Shanthalakshmi Revathy J. , Mangaiyarkkarasi J.
Published: September 2023

Digital healthcare technologies have the potential to revolutionize prenatal care by giving expectant moms real-time access to health information and assistance. This chapter reviews the current state of digital health technologies in pregnancy care. It discusses their capacity to enhance patient results, boost patient involvement, and lower healthcare expenses. Mobile apps have become increasingly popular for tracking pregnancy progress, providing educational resources and connecting patients with healthcare providers. Healthcare professionals can monitor vital signs using wearable technology like smart watches and activity trackers. The use of telemedicine enables patients in rural or underserved areas to receive healthcare services through remote consultations and virtual appointments. However, there are also limitations and challenges associated with digital health technologies in pregnancy care. This chapter is based on a survey of the most recent research findings and literature on the application of digital health technology, including articles from peer-reviewed journals.
Smart Street Lighting System for Smart Cities Using IoT (LoRa)
Authors: Babu C. V. Suresh , Monika R. , Dhanusha T. , Vishnuvaradhanan K. , Harish A.
Published: September 2023

Smart street light systems are being used more frequently in modern communities because they offer an effective and economical way to illuminate roads while reducing energy use and carbon emissions. Now, wireless networks can connect to and manage streetlights. With the aid of this technology, streetlights may be remotely monitored and controlled depending on variables such as traffic flow, weather, and the time of day. Energy is used as efficiently as possible, and maintenance costs are decreased. A smart streetlight system powered by IoT and LoRa can improve a city's efficiency and sustainability while also improving the quality of life for its residents. To maximize energy efficiency and reduce maintenance costs, the system may automatically adjust the streetlights' brightness and scheduling based on the data. This chapter provides a LoRa and IoT-based smart streetlight system with a cost-effective solution for modern smart cities.
Human-Computer Interaction for Knowledge Discovery for Management
Authors: Mahmood Faiq , Mehmood Khairia , Bari Wasim , Bashir Mohsin
Published: September 2023

The rising volume of data in our networked world is a huge problem that necessitates practical and user-friendly solutions. Computational approaches may be useful, but we must recognize that problem-solving knowledge is stored in the human mind, not in robots. A strategic goal for finding answers to data-intensive problems might be to combine two domains that provide optimal preconditions: human-computer interaction (HCI) and knowledge discovery (KDD). HCI is concerned with human vision, cognition, intelligence, decision-making, and interactive visualization approaches; hence, it focuses mostly on supervised methods. KDD is primarily concerned with intelligent machines and data mining, namely the creation of scalable algorithms for discovering previously undiscovered associations in data, and hence focuses on automatic computational approaches. A proverb illustrates this perfectly: “Computers are incredibly fast, accurate, but stupid. Humans are incredibly slow, inaccurate, but brilliant.”
Intelligent Data Encryption Classifying Complex Security Breaches Using Machine Learning Technique
Authors: Tripathi Somendra , Sharan Hari Om , Raghuvanshi C. S.
Published: September 2023

Attacks targeting cybersecurity are getting more widespread and complex over time. Additional innovation and rapid application development methodology within combative tactics have been required due to the increasing complexity and technological sophistication that have been developing. While still extensively used and encouraged, previous approaches to penetration detection and packet inspection are not sufficient for meeting the preferences of changing security threats. Machine learning is being touted as a supplementary justification for keyloggers, trojan horses, and other cyberattacks as computational capabilities and affordability keep on increasing. The total amount of information gathered by electronic objects has drastically increased in recent years as a consequence of the fast and easy efficiency innovations in some of those peripherals and their use in a range of applications.
Using Blockchain to Ensure Supply Chain Traceability
Authors: Azevedo Pedro , Gomes Jorge Vareda , Romão Mario
Published: September 2023

Supply chains can span a huge number of countries, cross many borders, and require interoperation of a multitude of organizations. This vastness impacts business competitiveness since it adds complexity and can difficult securing traceability, chain of custody, and transparency. The authors propose that assuring chain of custody and traceability via blockchain allows organizations to demonstrate product provenance, integrity, and compliance. This work proposes that to effect true traceability the more complete approach is to connect both the supply chain actors (SCAs) and products identifications using digital certificates. A blockchain is used to manage the traceability of products and validation of the identities. Importing, verifying, and storing the certificates uses an off-chain data storage solution for products certificates. To create, validate the certificates, and setup the chain of trust, a public key infrastructure (PKI) was designed as part of the proposal. The results were architectural artifacts, including an Ethereum smart contract and a PKI-based certificate authentication system.
Gamification in Education
Authors: Millan-Tudela Luis A. , Marco-Lajara Bartolomé , Sánchez-García Eduardo , Martínez-Falcó Javier
Published: September 2023

The use of gamification in education has been proved to enhance students' attention and learning compared to traditional methodologies. In this chapter, a generic game theory equation is developed and assessed to be applied in different economic and management-related education sessions. Additionally, the main potential digital sources to apply it are exposed. Finally, three examples of gamification dynamics in the scope of those topics are proposed. Consequently, this research opens the door to future developments where the equation is modified to be applied in other areas of knowledge in the context of education.
Accidents in Mass Transit Systems
Authors: Santos-Reyes Jaime , Moran-Ramirez Rosario
Published: September 2023

The chapter presents the results of a spatiotemporal analysis of accident occurrence of the trolleybus mass transit system in Mexico City. Chi-square analysis for goodness of fit method was employed to assess the relationship between the temporal variables and the accident occurrence. The ArcGis software was used for the analysis of the spatial visualization. The employed data were for 2017. The main conclusion were a) accidents do not have a uniform distribution weekly and hourly (All lines and Line A), on weekdays and the seasons of the year for Lines B and C, and crashes occurring hourly for the case of lines D-G; b) there was not a relationship between weekdays and hourly accident occurrence when considering the seven lines altogether and Line A; c) the most-affected boroughs were those related to Cuauhtémoc (27%), Coyocan (21.6%), and GAM (20.5%); they accounted for 69.1% of the accidents; and d) the peaks of trolleybus accident occurrence depend on the lines, that is, Line F (one peak of hours), Lines B-E (two), and Lines A and G (three).
Comprehensive Study on Rubber Particle Size and Replacement Ratio on Fresh and Hardened Properties of Rubberized Concrete: A Review
Authors: Sanjaya B. G. V. , Appuhamy J. M. R. S. , Bandara W. M. K. R. T. W. , Venkatesan S. , Gravina R. J.
Published: September 2023

The black pollution caused by the accumulation of Waste Tire Rubber (WTR) has engendered significant environmental and social consequences throughout the world by emphasizing the requirement of introducing a new approach to recycling WTR effectively. The recent research findings towards the utilization of End-of-Life Tires (ELT) to replace the Natural Aggregate (NA) in concrete have facilitated a promising way to handle the WTR while reducing the consumption of natural raw materials in the construction industry. However, the weak Interfacial Transition Zone (ITZ) between rubber aggregate and cement paste reduces the properties of Rubberized Concrete (RuC) and hinders its commercial usage. Among the many factors, the rubber particle size, shape, and Replacement Ratio (RR) significantly influence the performance of RuC. This paper reviews previous research findings relevant to the effect of the rubber particle size, shape, and percentage replaced in the concrete mix to pinpoint the further research gaps to be investigated. Overall, the previous findings indicate that the tire aggregate inclusion at a low level of replacement in the form of crumb rubber resulted in improved ductility and toughness with marginal impacts on workability, strength, and other mechanical properties of concrete compared to the control mix without WTR.
Estimating Remaining Fatigue Life of Critical Members of Steel Railway Bridges using Fatigue Crack Growth Model
Authors: Viththagan V. , Wimalasiri R. J. , Karunananda P. A. K.
Published: September 2023

Fatigue failure of steel structures is one of the most urgent study areas due to the inherent catastrophic nature of the failure. Engineers have made a substantial contribution to the understanding of the fatigue phenomenon through several approaches. Heavy cyclic loads imposed on steel railway bridges have the potential to cause cracks in structurally important members. Initiated cracks propagate during its service and lead to a complete structural failure. Since it is not practical to continuously monitor the structural health of bridges, an accurate life prediction approach is necessary to predict failure. This study proposes the fracture mechanics approach for fatigue life prediction of the critical members of bridges. Standard compact tension C(T) specimens were prepared with a pre-crack to test the fatigue crack growth rate under different stress levels. The crack growth rate da/dN was calculated by plotting the crack length (a) vs the number of cycles (N). According to ASTM E647-15, the stress intensity factor range (ΔK) for the C(T) specimen was determined. Under the conditions of constant amplitude loading, a modified version of the Paris law was used to construct an empirical relationship between da/dN and ΔK. The results of the vibration analysis were used to validate the finite element model of a case study railway bridge in Sri Lanka. The Finite Element (FE) method was used to assess the life of the most critical bridge member, and its estimated remaining fatigue life is 14.5 years.
Exploring Flood Susceptibility Mapping Using ArcGIS Techniques Integrated with Analytical Hierarchy Process under Multi-Criteria Decision Analysis in Kanakarayan Aru River Basin, Sri Lanka
Authors: Rajagopalasingam V. , Mikunthan T. , Sivakumar S. S.
Published: September 2023

Floods are one of the natural disasters causing economic, social, and environmental damage around the world, including in Sri Lanka. Flood susceptibility mapping is essential for flood prevention and mitigation measures. This study aimed to develop and validate a flood susceptibility map for the Kanakarayan Aru River Basin in Sri Lanka. Primary data were collected from water professionals and experts from Provincial Irrigation-Northern Province, Provincial Irrigation-Eastern Province, Disaster Management Centre, and Irrigation Department to decide the significance of flood causative factors. Secondary data of rainfall, digital elevation model, and GIS-based thematic data layers were collected from different agencies. GIS-based spatial multi-criteria decision analysis and analytical hierarchy process method were used for the study. A total of eight flood causative factors, i.e., elevation, slope, precipitation, land use and land cover, river proximity, drainage network density, topographic wetness index, and soil types were identified. Results show that the three mostrelevant factors of flood risk were precipitation (33%), drainage density network (17%), and surface slope (11%). The very high, high, and moderate flood risks occupy 12.5%, 23.4%, and 27.1% of the river basin areas, respectively. The validation process is executed based on the map's comparison of the historical flood locations of the different flood-susceptible zones and it provides a significant accuracy.
Review on the Estimation of Static Deformability Modulus of Rocks and their adoptability in Different Rock Masses
Authors:  Samarawickrama M. N. C. , Puswewala U. G. A. , Thilakasiri H. S. , Udamulla K. M. L. A.
Published: September 2023

The aim of this study is to review the different mechanisms employed in the estimation of static rock mass deformability modulus (𝐸𝑚) in rock engineering applications and to investigate the adoptability of the identified mechanisms in different rock masses. The paper discusses different evaluation criteria through experimental, empirical and other means, with their merits and demerits, including influential factors. It is known that deformability modulus of intact rock depends on the imposed stress, strain rate and the confining stress on the rock sample as well as the rock texture and structure. The results generated for 𝐸𝑚 by different in-situ tests are different and an appropriate in-situ test based on the rock mass conditions should be employed to obtain reasonable results. Empirical criteria are found to produce results of reasonable precision if appropriately adopted for specific rock mass conditions, while the back analysis method is widely adopted as an insitu estimation measure for the design of rock-sockets and tunnel support. It has also been reported that substantial reduction in 𝐸𝑚 occurs due to schistosity and larger test volumes, while it is sensitive to stress and discontinuity conditions. In this work, specific recommendations are made on the estimation of 𝐸𝑚 for different types of rock masses based on the findings and reviews reported in the literature.
The dual role of striatal interneurons: circuit modulation and trophic support for the basal ganglia
Authors: Wegman Elliot , Wosiski-Kuhn Marlena , Luo Yu
Published: September 2023

Striatal interneurons play a key role in modulating striatal-dependent behaviors, including motor activity and reward and emotional processing. Interneurons not only provide modulation to the basal ganglia circuitry under homeostasis but are also involved in changes to plasticity and adaptation during disease conditions such as Parkinson’s or Huntington’s disease. This review aims to summarize recent findings regarding the role of striatal cholinergic and GABAergic interneurons in providing circuit modulation to the basal ganglia in both homeostatic and disease conditions. In addition to direct circuit modulation, striatal interneurons have also been shown to provide trophic support to maintain neuron populations in adulthood. We discuss this interesting and novel role of striatal interneurons, with a focus on the maintenance of adult dopaminergic neurons from interneuron-derived sonic-hedgehog.
Enhancement of endogenous midbrain neurogenesis by microneurotrophin BNN-20 after neural progenitor grafting in a mouse model of nigral degeneration
Authors: Mourtzi Theodora , Antoniou Nasia , Dimitriou Christina , Gkaravelas Panagiotis , Athanasopoulou Georgia , Kostantzo Panagiota Nti , Stathi Olga , Theodorou Efthymia , Anesti Maria , Matsas Rebecca , Angelatou Fevronia , Kouroupi Georgia , Kazanis Ilias
Published: September 2023

JOURNAL/nrgr/04.03/01300535-202406000-00036/inline-graphic1/v/2023-10-30T152229Z/r/image-tiff

We have previously shown the neuroprotective and pro-neurogenic activity of microneurotrophin BNN-20 in the substantia nigra of the “weaver” mouse, a model of progressive nigrostriatal degeneration. Here, we extended our investigation in two clinically-relevant ways. First, we assessed the effects of BNN-20 on human induced pluripotent stem cell-derived neural progenitor cells and neurons derived from healthy and parkinsonian donors. Second, we assessed if BNN-20 can boost the outcome of mouse neural progenitor cell intranigral transplantations in weaver mice, at late stages of degeneration. We found that BNN-20 has limited direct effects on cultured human induced pluripotent stem cell-derived neural progenitor cells, marginally enhancing their differentiation towards neurons and partially reversing the pathological phenotype of dopaminergic neurons generated from parkinsonian donors. In agreement, we found no effects of BNN-20 on the mouse neural progenitor cells grafted in the substantia nigra of weaver mice. However, the graft strongly induced an endogenous neurogenic response throughout the midbrain, which was significantly enhanced by the administration of microneurotrophin BNN-20. Our results provide straightforward evidence of the existence of an endogenous midbrain neurogenic system that can be specifically strengthened by BNN-20. Interestingly, the lack of major similar activity on cultured human induced pluripotent stem cell-derived neural progenitors and their progeny reveals the in vivo specificity of the aforementioned pro-neurogenic effect.
Exercise-with-melatonin therapy improves sleep disorder and motor dysfunction in a rat model of ischemic stroke
Authors: Zhao Haitao , Zhang Tong , Zhang Haojie , Wang Yunlei , Cheng Lingna
Published: September 2023

JOURNAL/nrgr/04.03/01300535-202406000-00038/inline-graphic1/v/2023-10-30T152229Z/r/image-tiff

Exercise-with-melatonin therapy has complementary and synergistic effects on spinal cord injury and Alzheimer’s disease, but its effect on stroke is still poorly understood. In this study, we established a rat model of ischemic stroke by occluding the middle cerebral artery for 60 minutes. We treated the rats with exercise and melatonin therapy for 7 consecutive days. Results showed that exercise-with-melatonin therapy significantly prolonged sleep duration in the model rats, increased delta power values, and regularized delta power rhythm. Additionally, exercise-with-melatonin therapy improved coordination, endurance, and grip strength, as well as learning and memory abilities. At the same time, it led to higher hippocampal CA1 neuron activity and postsynaptic density thickness and lower expression of glutamate receptor 2 than did exercise or melatonin therapy alone. These findings suggest that exercise-with-melatonin therapy can alleviate sleep disorder and motor dysfunction by increasing glutamate receptor 2 protein expression and regulating hippocampal CA1 synaptic plasticity.
Hemorrhagic transformation in patients with large-artery atherosclerotic stroke is associated with the gut microbiota and lipopolysaccharide
Authors: Huang Qin , Wei Minping , Feng Xianjing , Luo Yunfang , Liu Yunhai , Xia Jian
Published: September 2023

JOURNAL/nrgr/04.03/01300535-202407000-00032/figure1/v/2023-11-20T171125Z/r/image-tiff

Hemorrhagic transformation is a major complication of large-artery atherosclerotic stroke (a major ischemic stroke subtype) that worsens outcomes and increases mortality. Disruption of the gut microbiota is an important feature of stroke, and some specific bacteria and bacterial metabolites may contribute to hemorrhagic transformation pathogenesis. We aimed to investigate the relationship between the gut microbiota and hemorrhagic transformation in large-artery atherosclerotic stroke. An observational retrospective study was conducted. From May 2020 to September 2021, blood and fecal samples were obtained upon admission from 32 patients with first-ever acute ischemic stroke and not undergoing intravenous thrombolysis or endovascular thrombectomy, as well as 16 healthy controls. Patients with stroke who developed hemorrhagic transformation (n = 15) were compared to those who did not develop hemorrhagic transformation (n = 17) and with healthy controls. The gut microbiota was assessed through 16S ribosomal ribonucleic acid sequencing. We also examined key components of the lipopolysaccharide pathway: lipopolysaccharide, lipopolysaccharide-binding protein, and soluble CD14. We observed that bacterial diversity was decreased in both the hemorrhagic transformation and non-hemorrhagic transformation group compared with the healthy controls. The patients with ischemic stroke who developed hemorrhagic transformation exhibited altered gut microbiota composition, in particular an increase in the relative abundance and diversity of members belonging to the Enterobacteriaceae family. Plasma lipopolysaccharide and lipopolysaccharide-binding protein levels were higher in the hemorrhagic transformation group compared with the non-hemorrhagic transformation group. lipopolysaccharide, lipopolysaccharide-binding protein, and soluble CD14 concentrations were associated with increased abundance of Enterobacteriaceae. Next, the role of the gut microbiota in hemorrhagic transformation was evaluated using an experimental stroke rat model. In this model, transplantation of the gut microbiota from hemorrhagic transformation rats into the recipient rats triggered higher plasma levels of lipopolysaccharide, lipopolysaccharide-binding protein, and soluble CD14. Taken together, our findings demonstrate a noticeable change in the gut microbiota and lipopolysaccharide-related inflammatory response in stroke patients with hemorrhagic transformation. This suggests that maintaining a balanced gut microbiota may be an important factor in preventing hemorrhagic transformation after stroke.
Targeting tau in Alzheimer's disease: from mechanisms to clinical therapy
Authors: Ye Jinwang , Wan Huali , Chen Sihua , Liu Gong-Ping
Published: September 2023

Alzheimer's disease is the most prevalent neurodegenerative disease affecting older adults. Primary features of Alzheimer's disease include extracellular aggregation of amyloid-β plaques and the accumulation of neurofibrillary tangles, formed by tau protein, in the cells. While there are amyloid-β-targeting therapies for the treatment of Alzheimer's disease, these therapies are costly and exhibit potential negative side effects. Mounting evidence suggests significant involvement of tau protein in Alzheimer's disease-related neurodegeneration. As an important microtubule-associated protein, tau plays an important role in maintaining the stability of neuronal microtubules and promoting axonal growth. In fact, clinical studies have shown that abnormal phosphorylation of tau protein occurs before accumulation of amyloid-β in the brain. Various therapeutic strategies targeting tau protein have begun to emerge, and are considered possible methods to prevent and treat Alzheimer's disease. Specifically, abnormalities in post-translational modifications of the tau protein, including aberrant phosphorylation, ubiquitination, small ubiquitin-like modifier (SUMO)ylation, acetylation, and truncation, contribute to its microtubule dissociation, misfolding, and subcellular missorting. This causes mitochondrial damage, synaptic impairments, gliosis, and neuroinflammation, eventually leading to neurodegeneration and cognitive deficits. This review summarizes the recent findings on the underlying mechanisms of tau protein in the onset and progression of Alzheimer's disease and discusses tau-targeted treatment of Alzheimer's disease.
Genetic pathways in cerebral palsy: a review of the implications for precision diagnosis and understanding disease mechanisms
Authors: Xu Yiran , Li Yifei , Richard Seidu A. , Sun Yanyan , Zhu Changlian
Published: September 2023

Cerebral palsy is a diagnostic term utilized to describe a group of permanent disorders affecting movement and posture. Patients with cerebral palsy are often only capable of limited activity, resulting from non-progressive disturbances in the fetal or neonatal brain. These disturbances severely impact the child's daily life and impose a substantial economic burden on the family. Although cerebral palsy encompasses various brain injuries leading to similar clinical outcomes, the understanding of its etiological pathways remains incomplete owing to its complexity and heterogeneity. This review aims to summarize the current knowledge on the genetic factors influencing cerebral palsy development. It is now widely acknowledged that genetic mutations and alterations play a pivotal role in cerebral palsy development, which can be further influenced by environmental factors. Despite continuous research endeavors, the underlying factors contributing to cerebral palsy remain are still elusive. However, significant progress has been made in genetic research that has markedly enhanced our comprehension of the genetic factors underlying cerebral palsy development. Moreover, these genetic factors have been categorized based on the identified gene mutations in patients through clinical genotyping, including thrombosis, angiogenesis, mitochondrial and oxidative phosphorylation function, neuronal migration, and cellular autophagy. Furthermore, exploring targeted genotypes holds potential for precision treatment. In conclusion, advancements in genetic research have substantially improved our understanding of the genetic causes underlying cerebral palsy. These breakthroughs have the potential to pave the way for new treatments and therapies, consequently shaping the future of cerebral palsy research and its clinical management. The investigation of cerebral palsy genetics holds the potential to significantly advance treatments and management strategies. By elucidating the underlying cellular mechanisms, we can develop targeted interventions to optimize outcomes. A continued collaboration between researchers and clinicians is imperative to comprehensively unravel the intricate genetic etiology of cerebral palsy.
Testing modalities for ALK-driven lung cancer: A narrative review
Authors: Nathany Shrinidhi , Sharma Mansi , Batra Ullas
Published: September 2023

Anaplastic lymphoma kinase (ALK) rearranged non-small-cell lung cancer (NSCLC) comprises a distinct molecular entity with a reported global prevalence of 5–7%. The development and rapid approvals of small molecule ALK tyrosine kinase inhibitors (TKIs) have led to the development of diagnostic strategies with robust methodology and superior attributes. Owing to myriad alterations which can be present in the ALK gene in NSCLC, it is important to understand the principal attributes as well as limitations of each to aid in optimal therapeutic decision making. To prepare this review, we used the keywords, “ALK detection,” “ALK NGS,” “ALK TKI,” and “EML4 (echinoderm microtubule-associated protein-like 4)-ALK,” to search within scientific databases like Scopus, PubMed, and Embase. We chose 55 articles that we identified from this search. Detection of ALK is an essential frontline diagnostic test as per all international and national recommendations. The various modalities available include immunohistochemistry, fluorescence in situ hybridization, reverse transcriptase polymerase chain reaction, and DNA/RNA-based next-generation sequencing. Each has its own advantages and limitations with respect to test metrics like sensitivity and specificity, as well as ease of use, availability, and cost. This is a detailed review of these various techniques and their attributes.