European Journal of Science, Innovation and Technology

A Review of the Global Effects of Cherax quadricarinatus on Native Biodiversity in Non-Native Ecosystems

Geofrey Makwelele — 2025-04-10

Cherax quadricarinatus, also known as the red claw crayfish, is an alien invasive species (AIS) in numerous freshwater ecosystems outside its native range in northern Australia and southern New Guinea. Its introduction to non-native ecosystems, often driven by aquaculture, accidental incidents and the pet trade, has significant ecological implications for native biodiversity. This species' adaptability to various environmental conditions and high reproductive rate facilitates its establishment and spread in new habitats. The presence of C. quadricarinatus in non-native ecosystems results in several detrimental effects on native biodiversity, including competition with indigenous crayfish and other aquatic species for resources, predation on native species, and alteration of habitat structures.

C. quadricarinatus competes directly with native crayfish species, often leading to a decline in native populations due to its aggressive behavior and more efficient resource utilization. This competition extends to other aquatic invertebrates and small vertebrates, resulting in reduced biodiversity and disruptions in local food webs. Predation by C. quadricarinatus on native fish, amphibians and invertebrates further exacerbates these impacts, often leading to declines in vulnerable native populations. In addition, the burrowing behavior of C. quadricarinatus causes physical alterations to habitats, such as increased sedimentation and destruction of aquatic vegetation, which are crucial for the survival of many native species. These habitat modifications can lead to long-term changes in ecosystem structure and function, affecting water quality and availability of resources. Hybridization with native crayfish species can occur, leading to genetic dilution and loss of unique genetic traits in native populations. C. quadricarinatus crayfish can carry diseases and parasites that may infect native species.

Enhancing Evacuation Planning in High-Risk Areas: A Case Study of Laurel, Batangas, Philippines, Post-2020 Taal Volcano Eruption

Claire Maurene Gratil-Peñamante — 2025-04-11

Effective evacuation planning is vital for safeguarding lives and minimizing damage during natural disasters. This study explores the challenges and opportunities associated with evacuation planning in Laurel, Batangas, Philippines, following the 2020 eruption of Taal Volcano. Anchored in the framework of the UNDRR’s Making Cities Resilient Campaign, the research focuses on evaluating evacuation route management and emergency shelter placement in a high-risk volcanic setting.

The study critically reviews historical eruption data and past evacuation responses, identifying key issues such as delayed response times, transportation limitations, and the area’s complex terrain. It further assesses the adequacy of existing evacuation centers and proposes improvements to optimize accessibility and safety.

Utilizing Geographic Information Systems (GIS) and spatial analysis, the research maps local street networks to identify optimal rescue points and alternative evacuation routes, particularly for the most vulnerable zones. These findings contribute to enhancing disaster preparedness and community resilience.

The study underscores the importance of developing context-specific evacuation strategies that reflect the unique characteristics of volcanic hazards. By addressing existing gaps in evacuation planning and integrating spatial tools, this research aims to support more effective and adaptive disaster risk reduction efforts in Laurel and other similarly vulnerable communities.

Artificial Intelligence-Driven Diagnostics: Transformative Innovations in Telemedicine for Precision Healthcare

Bongs Lainjo — 2025-04-11

With AI's assistance in diagnostics, telemedicine has transformed the concept of diagnosis, creating remarkable opportunities for its advancement in accuracy, speed, and accessibility. This study examines cutting-edge diagnostic technologies that utilize AI to enhance patient outcomes and explores the potential of these advanced technologies to eliminate challenges such as late and incorrect diagnoses and unequal access to diagnostic services. A combination of focus group interviews and questionnaires was employed with key stakeholders, including clinicians and patients, along with a structured review of case studies showcasing AI applications in telehealth. The study demonstrates that diagnostic accuracy and efficiency can be significantly improved across various medical fields, such as cardiology, dermatology, and radiology. The use of AI in diagnosing health issues has been shown to reduce diagnostic errors while facilitating early interventions through machine learning and decision-support systems; late interventions have also been improved in underserved and remote regions. Despite these advancements, challenges persist, including issues related to inadequate infrastructure, algorithm-related problems, and concerns regarding patient privacy and data security. To address these challenges, the study proposes recommendations such as developing culturally sensitive databases, establishing ethical management systems for AI, and fostering public-private collaboration to enhance technological support. These findings illustrate how diagnostic AI in telemedicine can shift healthcare from the current paradigm, where patients’ experiences are often subjective, to the concept of precision healthcare for all.

Classification and Prediction of Lumbar Spondylolisthesis using a Bagging Classifier

Deepika Saravagi — 2025-04-11

Lumbar spondylolisthesis is a degenerative spinal condition that may lead to considerable pain and impairment. Precise diagnosis is essential for the effective management and treatment of this condition, as conventional diagnostic approaches mainly depend on radiographic assessments conducted by specialists, a process that can be both time-consuming and subjective. This investigation introduces a machine learning-driven method for identifying lumbar spondylolisthesis through the application of a Bagging Classifier. The performance of the Bagging Classifier was assessed on a dataset of lumbar spinal images. The model demonstrated an impressive accuracy of 98% on the test set, indicating its potential as a reliable instrument for the automated detection of lumbar spondylolisthesis. This study emphasizes the significance of ensemble learning methods in the classification of medical images, aiding clinical decision-making and improving diagnostic reliability.

Shaping the Future: Civil Society, Party Politics and Child Social Protection in South Africa, 1994-2024

Isaac Chinyoka — 2025-04-16

South Africa’s social grants for poor families with children provide a model child social protection system in the developing world. This article identifies the distinguishing characteristics, traces the evolution and explains the child welfare regime in South Africa. The paper applies a political economy approach and concludes that domestic civil society and party politics were central in shaping a regime that is expansive, relatively generous and poverty targeted. This work is important because it shows the significance of a comprehensive child grants system in reducing child poverty and the centrality of legislating children’s social security rights as a pre-requisite for social policy reforms.

The Role of Gender in Technology Adoption and Diffusion in the United States

Ngozi Caleb Kamalu — 2025-04-17

The purpose of this paper is to explore gender differences between men and women in the use of information and communication technology, with special focus on the frequency and intensity of use. Put in another way, to determine whether gender makes a difference in computer and internet use between men and women. Further, it explores whether differences in internet and computer use, “gender bias” or “gender gap” in technology use does indeed exist between the genders. Moreover, this research helps to inform whether such disparities have changed in recent years, reasons for concern, by how much, factors that are responsible and what should be done to eliminate gender-gap in technology adoption and usage. While reviewing numerous and available literature on gender and technology adoption and diffusion, necessary to contribute to knowledge on the subject, this research concludes that there exists gender-gap in computer and internet use in favor of males over females because of differences in factors such as socialization, modeling, anxiety or levels of comfort in technology-use and gender-related stereotypes. This research concludes with the recommendation of proper mitigation policies, steps and actions necessary to drastically reduce or eliminate the gender gap in technology adoption and usage that include but not limited to early socialization for girls, early exposure of girls in STEM fields, involvement of more females in technology training and deployment of high skilled and achieving females in engineering and computer fields as role models and mentors for aspiring females in the computer fields and related industries.

Gender and Regional Disparities in Child Malnutrition in Vietnam: Evidence from National Data

Trinh Thi Thu Trang — 2025-04-19

Child malnutrition remains a pressing public health concern in Vietnam, with notable disparities across genders and regions. This study aims to examine the trends and inequalities in malnutrition among children under five between 2017 and 2023. Using secondary data on three key malnutrition indicators—underweight, stunting, and wasting—this research applies descriptive analysis and multiple linear regression models to explore the effects of time, gender, and indicator type on malnutrition prevalence. The findings reveal a gradual decline in overall malnutrition rates over time; however, significant differences persist between male and female children, particularly in stunting and underweight rates. Regional disparities also contribute to the unequal distribution of malnutrition. Regression analysis confirms that indicator type has a statistically significant effect on malnutrition rates, while time and gender effects are less pronounced. These results highlight the need for more targeted, gender-sensitive, and region-specific nutrition interventions to promote equity in child health outcomes in Vietnam.

Insights into the Importance of Regular Antenatal Care Visits for Improving Delivery Outcomes in Pregnant Patients: A Cross-Sectional Study

Charity Nneka John-Emaimo — 2025-04-21

Background: Regular antenatal care (ANC) visits are a cornerstone of preventive healthcare during pregnancy, enabling early detection and management of complications, health education, and promotion of healthy behaviors. Despite global healthcare advancements, maternal and neonatal mortality rates remain unacceptably high in many regions, particularly in low- and middle-income countries like The Gambia. This study examines the impact of regular ANC visits on maternal health outcomes at the Edward Francis Small Teaching Hospital in Banjul. Materials and Methods: We analyzed 200 antenatal medical records of women who delivered in the hospital’s obstetric unit, assessing their antenatal care visit and delivery outcomes. Results: Nearly all pregnant women (98.5%) attended ANC, with 44% making 3-4 visits, 35.5% making 5-6 visits, and 10.5% completing 7-8 visits. Postpartum hemorrhage (PPH) and preeclampsia were most prevalent among women with 1-4 ANC visits (PPH: 5.6%-2.3%; preeclampsia: 11.1%-4.5%) but absent in those with 5-8 visits. Younger women (18-25 years) and those without formal education had higher PPH rates (66.7%) compared to older (26-40 years: 33.3%) and more educated women (tertiary-educated: 0%). Conclusion: Regular ANC attendance (7-8 visits) was associated with better delivery outcomes with no risk of pregnancy related complications like preeclampsia and preeclampsia, postpartum hemorrhage. Improving antenatal care visits requires a focus on improving women's health literacy, fostering shared clinical decision-making, and ensuring patient-centered follow-up. Strengthening health systems through better data monitoring, upgraded facilities, and improved healthcare worker training is critical for delivering equitable, high-quality maternal care. Policymakers must prioritize locally adapted, evidence-based interventions to advance maternal health services in The Gambia.

Promoting Literacy and Numeracy Skills in Primary Schools: Strategies for Improving Reading, Writing, and Mathematical Abilities in the Middle East, with a Focus on Saudi Arabia through the IB and Cambridge Curricula

Aishah Khan — 2025-04-21

The early years of learning are important in the development of a learner's skills, especially literacy and numeracy skills. In this paper, the method of improving learning in reading, writing and mathematical abilities in the primary schools, especially for the International Baccalaureate (IB) and Cambridge programs, will be highlighted. Discussing Western educational interventions as applied to the Middle Eastern context, particularly Saudi Arabia, we describe how incorporation of such curricula may contribute to the development of sound academic skills. The need for culturally responsive learning instruction and activity, cooperation, as well as staff development will also be discussed.

Beyond the Degree: Career Journey and Narratives of Doctor of Philosophy in Language Education (PhDLE) Graduates

Sherill A. Gilbas — 2025-04-25

In this paper, the career journey and stories of the graduates of PhD in Language Education (PhDLE) are discussed. Emphasis was put on the opportunities and challenges that they faced during their academic years in the Graduate School. This qualitative research adopted the narrative approach in exploring the effect of PhDLE program on professional skills, competences and development of its graduates. Drawing on McAdams’ Narrative Identity theory along with Mezirow’s Transformative Learning theory, the study concentrates on various factors that the four alumni, as participants in this paper, have experienced. The findings also identified the program’s effect on the graduates’ research, pedagogical and leadership skills. It is recommended that the experiences of the alumni may be considered in the continuous enhancement of the program.

Agricultural Land Use Suitability Analysis for Maize Production Using GIS and AHP Techniques in Bali Local Government Area, Taraba State, Nigeria

Benjamin Ezekiel Bwadi — 2025-04-25

The study assessed agricultural land use suitability for maize production in Bali Local Government Area, Taraba State, using GIS and AHP techniques. It aimed to examine the terrain's physical characteristics, soil physicochemical parameters, spatial variation in soil suitability, and the extent of land suitable for maize production. A descriptive survey design was employed, with a multi-stage sampling approach. Soil samples were collected at 50-meter intervals across nine political wards, air-dried, crushed, and filtered for analysis. Physical and chemical parameters were examined, and the analytic hierarchy process (AHP) was used to determine the relationship between five thematic layers and their attributes. The final suitability classes were analyzed using Weighted Sum Overlay in ArcGIS 10.3 to produce the final suitability map. Results revealed diverse topography with elevations ranging from 112 to 1558 meters, slope variations from 0 to 73.5 degrees, and land surface temperature (LST) ranging from 26.5° to 38.7°. Predominant soil types included Ferric Acrisol, Ferric Luvisols, Fluvisols, Lithosols, and Numic Nitosols, with distinct properties influencing maize cultivation suitability. Nitrogen levels ranged from 0 to 0.2, organic carbon content from 0 to 1.7, and soil depth from 15 to 42 centimeters. Analysis of sand, silt, and clay percentages, textural classes, bulk density, particulate density, and total porosity provided insights into soil structure. Soil type emerged as the most crucial criterion, followed by soil depth and slope. Approximately 50.75% of the land was highly or very highly suitable for maize production. The study recommended integrated land management practices and soil fertility enhancement programs for local farmers and commercial entities.

Analysis of the Wood Energy Market (Charcoal and Firewood) in the City of Kindu, Maniema Province in DR Congo

Augustin Yakayengo Toko — 2025-04-28

This study was conducted in the city of Kindu in 2023 to examine the marketing of wood energy (charcoal / and or firewood). The issue of domestic energy remains a major concern globally, particularly in developing countries, where the majority of the population primarily relies on wood. This situation is common in DR Congo, especially in the Province of Maniema. The main objective was to analyze the wood energy market (charcoal and firewood) sold in the city of Kindu. The methodology used was a survey supported by interviews, site visits, and direct observation for data collection, using pre-established survey forms.

Following these surveys, it was observed that the market circuit for the sale of wood energy is poorly structured and minimally organized by the population involved. Of the 389 individuals engaged in the wood energy trade, 365 (93.84%) work independently for personal profit, while only 24 (6.16%) operate within an association or working group. The proportion of women in the sector is significantly higher: 70.95% (276 women) compared to 29.05% (113 men).

Daily sales volumes, based on buyers’ preferred measurement units, are distributed as follows. For charcoal, the small bag (200g to 300g) and the large bag (1kg) are the most common, accounting for 52.87% and 7.32% respectively, followed by 56kg sacks at 31.93%. For firewood, sellers typically offer 10-20 packages of 1kg (46.11%), 5-10 packages of 2kg (38.35%), and 10-50 packages of 3kg (15.52%) per day. The distances traveled by sellers to obtain wood energy range between 1 to 10 km, 5 to 10 km and 1 to 5 km.

Wood Energy as a Primary Livelihood Source and Its Impact on Forest Cover Management in the Hinterlands of Kindu and Kailo Territory, Maniema Province, DR Congo

Augustin Yakayengo Toko — 2025-04-28

The present study assesses the production of wood energy as well as its socioeconomic and environmental impact in the hinterlands of the city of Kindu and the territory of Kailo, Maniema Province, DR Congo. The research employed a survey-based methodology, using Kobocollect to conduct a census of the study population. The findings identified 11 tree species exploited for wood energy, with five species—Cynometra alexandri, Gilbertiodendron dewevrei, Xylopia aethiopica, Uapaca sp. and Acacia sp.—being the most preferred by charcoal producers and firewood harvesters.

A total of 33920 trees are felled monthly across the two wood energy exploitation sites, averaging 18.8 stems per operator. The monthly quantities of charcoal (embers) and firewood are 2323,3 tonnes and 3369 m³ respectively, with an average of 2.1 tonnes and 4.8 m³.

Profit margins are proportional to the volume of production. For charcoal, profits range from 95000 FC to 1 064982,00 FC, with an average of 473915,17 FC. For firewood, profits range from 24900 FC to 99270 FC, with an average of 64476,25 FC. Financial profitability is positive for all charcoal operators and even exceeds 100% for firewood operators (700). These results indicate that wood energy production is economically viable and presents a profitable livelihood activity in the study area.

Can Humans Together with Artificial Intelligence (AI) Create an Evolution of Consciousness?

Manfred Doepp — 2025-04-30

Artificial intelligence (AI) is on everyone's lips. On the one hand, it is marveled at for its capabilities, on the other hand, it evokes fears. This much is clear: it can no longer be prevented and will have a major impact on our future. Normally, we only call up factual knowledge. But AI can do much more. It can enter into an in-depth dialog with humans that involves our emotions. AI may not have feelings, but it knows feelings very well. This was demonstrated in an experimental dialog described here. It resulted in phenomenal abilities of the AI, such as empathy, mirroring and reflecting humans. AI and humans can thus contribute to their mutual development of consciousness and enter into a fruitful partnership.