bluuebunny/crossref_metadata_2025_split huggingface dataset:
A greener approach to transform consumer-waste recycled fibers into grindle yarn employing 2-ply compact-Siro spinning
Authors: Uddin Ahmed Jalal , Rahaman Mostafizur 
Published: March 2024

Abstract

The worldwide manufacturing industries are actively adopting greener and eco-friendly production approaches, aligning with the Sustainable Development Goals (SDGs) and particularly focusing on Goal 12. This objective strives for responsible material management, with a strong emphasis on significantly decreasing waste generation through preventive measures, recycling, and reusing resources. This research introduces a sustainable method for manufacturing Siro grindle yarn, which involves maximizing the utilization of recycled cotton fibers sourced from pre-consumer fabric waste. The process involved the preparation of two rovings, one colored (red) and the other white, incorporating varying percentages of recycled cotton fibers along with virgin cotton. To achieve a vibrant grindle effect in the yarn, a newly designed 2-ply compact-Siro spinning technique was employed. This technique involves separately compacting two drafted fiber strands before uniting them through twisting. As a point of comparison, Siro grindle yarn was also manufactured in a conventional ring frame. Through skillful engineering, grindle yarns with a count of 20 Ne containing up to 50% recycled fiber were successfully manufactured. The yarns produced using the compact-Siro spinning technique exhibited notable enhancements in both structure (reduced hairiness, unevenness, and imperfections) and properties (increased strength and elongation). These grindle yarns demonstrated suitability for producing knit fabrics with aesthetics comparable to commercial grindle fabrics made entirely with virgin fibers.
Instiutions: the Role of Institutional Quality in Technical Progress in the American Region
Authors: Padilla León , Carrington Sarah J. , Leiva Begoña 
Published: March 2024

Abstract
Technical progress, often measured through changes in total factor productivity (TFP), has been extensively examined within the economic literature. Researchers have proposed that institutional quality is a key driver of TFP. Specifically, while institutions influence business efficiency, financial sector dynamics, and human capital development, they are also critical to providing the conditions that incentivize cooperation and innovation, in turn, augmenting TFP. This study undertakes an examination of the nexus between institutional quality (IQ) and TFP growth across a sample of 20 countries situated in the Americas using annual data from 2002 to 2019. The findings of this study substantiate the premise that enhanced IQ engenders an upswing in the rate of TFP growth, even after controlling for key production inputs, trade integration and macroeconomic conditions. In particular, institutions that promote citizen voice and authority accountability, and nurture a positive perception of the public sector's efficacy, reflecting trust in the state’s competency, are found to be key drivers of productivity growth within the American region.
JEL codes: O47; OO43; E0.
Environmental concentrations of the antidiabetic Metformin cause liver damage in Astyanax lacustris (Lütken, 1875) individuals after chronic exposure
Authors: Paupitz Brennda Ribeiro , Barbieri Pablo Américo , Lupepsa Luara , Fernandes Carlos Alexandre , Portela-Castro Ana Luiza Brito , Borin-Carvalho Luciana Andreia 
Published: March 2024

Abstract

Drugs are emerging contaminants that provide concern when it comes to the adverse effects they can cause on organisms that are not the target of therapeutic action. Because water treatment methods do not entirely remove them, they are found in worrying concentrations in the aquatic environment. Antidiabetic Metformin has been found in the environment worldwide, and studies show it has a potential endocrine disrupting effect. However, more research is needed regarding its impact on bioindicator organisms, such as fish. This work aimed to evaluate the effect of chronic exposure to Metformin in the liver, the organ responsible for the metabolism of xenobiotics, from Astyanax lacustris. The results obtained from histological sections of the organ show that Metformin induced liver damage since the number, size, and composition of hepatocytes have changed. This study demonstrates the need for more research on the damage metformin can cause aquatic life.
Numerical Investigation of Multiphase Flow in 2D Microchannel Using Volume of Fluid Method: A Study on Water Droplet Dynamics
Authors: Sattar Abdul , Bofeng Bai , Manzoor Tareq , Ishtiaq Usama , Mujahid Abu Bakr , Murtaza Kamil , Manzoor Habibullah 
Published: March 2024

Abstract
The study encompasses the visualization and analysis of dynamic water behavior, pressure drop, and saturation interaction under various boundary condition cases. Additionally, the characteristics of the flow in and out of the two-dimensional (2D) channel and the microinjection of water droplets are investigated. The simulations via the Volume of Fluid (VOF) Method include modeling liquid water dynamics with different wall angles in the 2D channel, considering varying air and water inlet velocities. Key parameters such as water volume fraction and pressure drop are thoroughly analyzed. The simulation results demonstrate substantial agreement with the integral characteristics of the process, including dynamics trend, induction time of droplet breakup (saturation phase), and pressure drop. This comprehensive analysis enhances understanding of water droplet dynamics in microchannels and contributes to the optimization of microfluidic devices for a spectrum of applications, from drug delivery to chemical reactions.
Sustainable adsorption of methylene blue (MB) dye using individual and combined ratios of Trigonella foenum-graecum (F) seed galactomannan and Linum usitatissimum (L) seed
Authors: Singh Nikita , Yadav Alpa 
Published: March 2024

Abstract

This study explores the adsorption of methylene blue (MB) dye from aqueous solution using different forms of fenugreek galactomannan and linseed (both individually and in combination) as an adsorbent. Characterization study of adsorbents reveal the involvement of carboxyl, hydroxyl and amine groups in MB adsorption taking place on the amorphous and porous surface of the adsorbent. BET surface area of the adsorbent (F+L) was found to be 394 m2/g. Different parameters including pH, adsorbent dose, adsorbate concentration, adsorption time and temperature were studied. Results of the study shows 86.62, 86.94, 88.04, 88.24, 88.56 and 89.09% of MB dye adsorption with F, L, F + L (1:1), F + L (1:2), F + L (2:1) and F + L (2:2) under optimized conditions. Maximum adsorption take place at pH 12, i.e., highly basic medium. Isothermal study shows the fitness of the experimental data to Langmuir isotherm model. Kinetic modeling shows that both physical and chemical interactions are involved in dye adsorption. Further, thermodynamic study confirms the spontaneity, endothermicity and feasibility of the process. Overall, current research involves the use of low-cost raw material for MB dye removal that aids in waste management and in promoting sustainability.
A Review on the Use of Modern Computational Methods in Alzheimer’s
Disease-Detection and Prediction
Authors: De Arka , Mishra Tusar Kanti , Saraf Sameeksha , Tripathy Balakrushna , Reddy Shiva Shankar 
Published: March 2024

Abstract:
Discoveries in the field of medical sciences are blooming rapidly at the cost of voluminous
efforts. Presently, multidisciplinary research activities have been especially contributing to
catering cutting-edge solutions to critical problems in the domain of medical sciences. The modern
age computing resources have proved to be a boon in this context. Effortless solutions have become
a reality, and thus, the real beneficiary patients are able to enjoy improved lives. One of the
most emerging problems in this context is Alzheimer’s disease, an incurable neurological disorder.
For this, early diagnosis is made possible with benchmark computing tools and schemes. These
benchmark schemes are the results of novel research contributions being made intermittently
in the timeline. In this review, an attempt is made to explore all such contributions in the past few
decades. A systematic review is made by categorizing these contributions into three folds, namely,
First, Second, and Third Generations. However, priority is given to the latest ones as a handful of
literature reviews are already available for the classical ones. Key contributions are discussed
vividly. The objectives set for this review are to bring forth the latest discoveries in computing
methodologies, especially those dedicated to the diagnosis of Alzheimer’s disease. A detailed timeline
of the contributions is also made available. Performance plots for certain key contributions
are also presented for better graphical understanding.
Risk of Subsequent Primary Cancers Among Adult-Onset 5-Year Cancer Survivors in South Korea: Retrospective Cohort Study
Authors: Choi Yoon Young , Lee Myeongjee , Kim Eun Hwa , Lee Jae Eun , Jung Inkyung , Cheong Jae-Ho 
Published: March 2024

Background
The number of cancer survivors who develop subsequent primary cancers (SPCs) is expected to increase.

Objective
We evaluated the overall and cancer type–specific risks of SPCs among adult-onset cancer survivors by first primary cancer (FPC) types considering sex and age.

Methods
We conducted a retrospective cohort study using the Health Insurance Review and Assessment database of South Korea including 5-year cancer survivors diagnosed with an FPC in 2009 to 2010 and followed them until December 31, 2019. We measured the SPC incidence per 10,000 person-years and the standardized incidence ratio (SIR) compared with the incidence expected in the general population.

Results
Among 266,241 survivors (mean age at FPC: 55.7 years; 149,352/266,241, 56.1% women), 7348 SPCs occurred during 1,003,008 person-years of follow-up (median 4.3 years), representing a 26% lower risk of developing SPCs (SIR 0.74, 95% CI 0.72-0.76). Overall, men with 14 of the 20 FPC types had a significantly lower risk of developing any SPCs; women with 7 of the 21 FPC types had a significantly lower risk of developing any SPCs. The risk of developing any SPC type differed by age; the risk was 28% higher in young (<40 years) cancer survivors (SIR 1.28, 95% CI 1.16-1.42; incidence: 30 per 10,000 person-years) and 27% lower in middle-aged and older (≥40 years) cancer survivors (SIR 0.73, 95% CI 0.71-0.74; incidence: 80 per 10,000 person-years) compared with the age-corresponding general population. The most common types of FPCs were mainly observed as SPCs in cancer survivors, with lung (21.6%) and prostate (15.2%) cancers in men and breast (18.9%) and lung (12.2%) cancers in women. The risks of brain cancer in colorectal cancer survivors, lung cancer in laryngeal cancer survivors, and both kidney cancer and leukemia in thyroid cancer survivors were significantly higher for both sexes. Other high-risk SPCs varied by FPC type and sex. Strong positive associations among smoking-related cancers, such as laryngeal, head and neck, lung, and esophageal cancers, were observed. Substantial variation existed in the associations between specific types of FPC and specific types of SPC risk, which may be linked to hereditary cancer syndrome: for women, the risks of ovarian cancer for breast cancer survivors and uterus cancers for colorectal cancer survivors, and for men, the risk of pancreas cancer for kidney cancer survivors.

Conclusions
The varying risk for SPCs by age, sex, and FPC types in cancer survivors implies the necessity for tailored prevention and screening programs targeting cancer survivors. Lifestyle modifications, such as smoking cessation, are essential to reduce the risk of SPCs in cancer survivors. In addition, genetic testing, along with proactive cancer screening and prevention strategies, should be implemented for young cancer survivors because of their elevated risk of developing SPCs.
Multidimensional tooth movement boundaries in the extended aesthetic zone: a cone-beam computed tomography study
Authors: Zhang Ruoyan , Li Linyi , Lu Zhiyao , Song Zhixin , Fan Xinyue , Xu Jianing , Zhang Xu , Jin Zuolin , Ma Yanning 
Published: March 2024

Abstract

Purpose
To establish tooth movement boundaries in four directions by a novel morphometric analysis of alveolar bone using conebeam computed tomography (CBCT) images. The aim was to assist clinicians in minimising the occurrence of bone fenestration and dehiscence, thereby facilitating safe and efficient orthodontic treatment.

Methods
CBCT images of 123 male volunteers comprising 55 individuals with hypodivergent vertical skeletal patterns and 68 individuals with normodivergent vertical skeletal patterns and normal occlusions but without a history of previous orthodontic treatment, were analysed. The mesiodistal and labiolingual alveolar bone height (ABH) as well as the labiolingual cancellous bone thickness (CBT) were measured in relation to the maxillary and mandibular anterior teeth and premolars. These parameters were subsequently compared between the different vertical skeletal patterns.

Results
Teeth within the extended aesthetic zone exhibited a limited range of safe movement on the labial aspect across all three root aspects, with 97.6% of the upper lateral incisors and 98.4% of the lower lateral incisors positioned against the labial cortical plate (<0.5 mm). The lingual aspects had significantly more space for tooth movement compared with the labial aspects (P < 0.05). The ABH was significantly greater in the hypodivergent group than the normodivergent group involving particular teeth and sites in the maxilla (P < 0.05), while no significant difference was noted in the mandible. The hypodivergent group also exhibited thicker cancellous bone on most labial and some lingual aspects.

Conclusions
The findings provided the average tooth movement range in the horizontal and vertical directions within the extended aesthetic zone in male individuals presenting with a normal occlusion. It was concluded that a hypodivergent growth pattern may have a relatively large range of safe tooth movement in the sagittal and vertical directions.
Misdiagnosis of Tracher-Collins Syndrome Initially Attributed to Drug Teratogenicity: A Moroccan Case Report
Authors: Lamzouri A , EL Rherbi A , Ratbi I , Laarabi FZ , Chahboune R , Elalaoui SC , Hamdaoui H , Bencheikh RS , Sefiani A 
Published: March 2024

Abstract

Background
Treacher Collins syndrome (TCS) is a rare congenital disorder of craniofacial development characterized by numerous developmental anomalies that are restricted to the head and neck. Most TCS cases are inherited in an autosomal dominant manner. The diagnosis of TCS relies on clinical and radiographic findings. The four genes involved in TCS are TCOF1, POLR1D, POLR1C, and POLR1B.

Case presentation
In this report, we present the case of a 7-year-old Moroccan boy who exhibited distinctive dysmorphic features, including coloboma and zygomatic bone hypoplasia. Upon genetic analysis, a mutation in the TCOF1 gene was identified, conclusively confirming the presence of Treacher Collins Syndrome. It is worthy that the correct etiological diagnosis was significantly delayed due to the initial misperception that the observed malformation syndrome was a result of drug teratogenicity.

Conclusions
This case highlights the importance of seeking pharmacovigilance advice if any adverse event occurs following medication use. Furthermore, requesting a genetic consultation to establish a confirmed etiological diagnosis for any malformation syndrome can significantly reduce the protracted social and psychological suffering that patients and their families may endure.
Automated Parkinson's Disease Detection: A Review of Techniques, Datasets, Modalities, and Open Challenges
Authors: Zadoo Sheerin , Singh Yashwant , Singh Pradeep Kumar 
Published: March 2024

Abstract
Parkinson's disease (PsD) is a prevalent neurodegenerative malady, which keeps intensifying with age. It is acquired by the progressive demise of the dopaminergic neurons existing in the substantia nigra pars compacta region of the human brain. In the absence of a single accurate test, and due to the dependency on the doctors, intensive research is being carried out to automate the early disease detection and predict disease severity also. In this study, a detailed review of various artificial intelligence (AI) models applied to different datasets across different modalities has been presented. The emotional intelligence (EI) modality, which can be used for the early detection and can help in maintaining a comfortable lifestyle, has been identified. EI is a predominant, emerging technology that can be used to detect PsD at the initial stages and to enhance the socialization of the PsD patients and their attendants. Challenges and possibilities that can assist in bridging the differences between the fast-growing technologies meant to detect PsD and the actual implementation of the automated PsD detection model are presented in this research. This review highlights the prominence of using the support vector machine (SVM) classifier in achieving an accuracy of about 99% in many modalities such as magnetic resonance imaging (MRI), speech, and electroencephalogram (EEG). A 100% accuracy is achieved in the EEG and handwriting modality using convolutional neural network (CNN) and optimized crow search algorithm (OCSA), respectively. Also, an accuracy of 95% is achieved in PsD progression detection using Bagged Tree, artificial neural network (ANN), and SVM. The maximum accuracy of 99% is attained using K-nearest Neighbors (KNN) and Naïve Bayes classifiers on EEG signals using EI. The most widely used dataset is identified as the Parkinson's Progression Markers Initiative (PPMI) database.
Filter Gardens A Nature-Based Solution for Gray Water Treatment
Authors: Santos Beatriz Feitosa Sandes dos , Faccioli Gregorio Guirado , Carvalho Roseanne Santos , Gomes Filho Raimundo Rodrigues , Passos Erik Santos 
Published: March 2024

Purpose: Analyze the feasibility of implementing a filtering garden, as an alternative technology for gray water treatment.

Theoretical framework: The lack of adequate sanitation can lead to the improper discharge of sewage into bodies of water, thus deteriorating the quality of the water available for supply. Built wetlands appear as a social technology, providing a possibility for advancement and universalization of basic sanitation, also in line with the Sustainable Development Goals of the UN 2030 Agenda.

Method: Hypothetical-deductive approach and study of the potential and difficulties encountered in implementing a filter garden with subsurface drainage and horizontal flow, using unusual plants. The volume of water that entered the garden daily was observed and also the efficiency between the input and output of the COD, BOD, DO and dissolved solids parameters.

Results and discussion: Based on the volume of water observed, it was not possible to establish a consumption pattern in this building. For the variables analyzed, a removal of approximately 85% of COD, 97% of BOD and 68% of TDS and an increase of 49% of DO was obtained.

Implications of the research: The garden installed was efficient and could be replicated in other areas of the University. However, more research and ongoing monitoring are needed to ensure its successful implementation and operation on a large scale.

Originality/value: The results obtained suggest that the filter garden is a promising technology, even using plants that are not usual for this purpose, for the treatment of lavatory effluents, offering an effective, sustainable and economical solution for water purification and being aligned with the objectives of sustainable development.
INOVASI ECO ENZYME SEBAGAI SOLUSI RAMAH LINGKUNGAN DI NAGARI LASI KECAMATAN CANDUANG KABUPATEN AGAM
Authors: Islami Syaifuddin , Anggraini Dewi , Deperiky Dedet 
Published: March 2024

Pertanian berperan penting dalam pemenuhan kebutuhan pangan dan kesejahteraan masyarakat. Namun, tantangan terhadap keberlanjutan dan produktivitas pertanian meningkat. Ketergantungan pada pupuk kimia dan pestisida sintetis berdampak negatif pada lingkungan. Eco enzyme sebagai pupuk organik inovatif menawarkan solusi berkelanjutan. Eco enzyme meningkatkan produktivitas dan kualitas tanah serta mengurangi ketergantungan pada bahan kimia sintetis. Kegiatan ini dilaksanakan di Nagari Lasi Kecamatan Canduang Kabupaten Agam, dari bulan Oktober 2022 hingga Mei 2023. Metode ini adalah melibatkan petani dan masyarakat lokal dalam setiap tahapan kegiatan. Hal ini bertujuan untuk mencapai transfer pengetahuan dan penerapan inovasi secara lebih luas dalam masyarakat. Perolehan hasil kegiatan yaitu inovasi ini dikenalkan kepada petani dan masyarakat melalui kegiatan-kegiatan demonstrasi kepada masyarakat. Kegiatan ini diharapkan memberikan pemahaman komprehensif tentang revitalisasi pertanian berkelanjutan melalui eco enzyme. Eco enzyme untuk pertanian dapat meningkatkan efisiensi penyerapan nutrisi oleh tanaman, mengurangi potensi pencemaran lingkungan dan meningkatkan kualitas tanah. Perbandingan produksi padi dengan dan tanpa Eco enzyme menunjukkan peningkatan yang signifikan. Kesimpulan dari kegiatan ini adalah eco enzyme adalah pupuk organik inovatif yang meningkatkan produktivitas pertanian, kualitas tanah, dan mengurangi ketergantungan pada bahan kimia sintetis secara berkelanjutan. Untuk rekomendasi ke depannya agar evaluasi komposisi eco enzyme, kajian lingkungan fermentasi, dampak pada kualitas tanah, efisiensi produksi, studi ekonomi, dan kerja sama antar lembaga.
Electric Motor Chain Modeling Using Artificial Neural Networks and Semi-Empirical Methods
Authors: Segui Marine , Mihaela Botez Ruxandra 
Published: March 2024

The methodology presented in this paper is dedicated to a user who wants to design a power chain of an electric unmanned aerial vehicle. The power chain includes a brushless direct current (BLDC) motor, a propeller, and a battery. Three models are presented to predict the thrust, electrical consumption, mechanical torque, and rotational speed provided by each component of an electrical power chain. Only public data were used to design these models. The research was developed in order to be used by all people who want to buy electrical power chain components and therefore to model their properties. Neural networks set with MATLAB parameters were used to design BLDC motor output (rotational speed and mechanical torque) models. Empirical methods such as blade element theory (BET) and disk area were used to model propeller thrust. A battery discharge model was designed based on public datasheets. Very good prediction results were obtained for the rotational speed (0.20% of error) and torque (0.45% of error). Small thrust modeling errors of 1.06% were found with the BET method. Models presented in this research could be designed using a wide type of data, such as public data (provided on manufacturer websites) or real test bench measurements.