bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of friction stir-based linear continuous joining of aluminium alloy to structural polymer
Authors: Khadka Prabilson , Varglund Sean , Akinwamide Samuel , Vilaça Pedro 
Published: August 2023

Abstract
Dissimilar continuous joining of lightweight metal alloys to structural polymer is a major manufacturing challenge, demanding feasible and reliable solutions. Through-slot extrusion joining (TSEJ) is a friction stir-based processing technique investigated in the manufacturing of continuous linear joints between aluminium alloy AA5754 overlapping structural polymer polyether ether ketone (PEEK). An intermediate rigid and thin titanium extrusion die protects locally the polymer from thermal degradation and promotes the formation along the joint path of a continuous double hook-like feature of extruded aluminium into the polymer component, providing macro-mechanical interlocking.
A set of four tools with different probe geometries at three positions relative to the extrusion die were investigated for process stability, tensile-shear strength, and microstructure. Four tensile-shear specimens are extracted from each joint, and the cross-section from the best TSEJ condition is chosen for microstructural analysis via optical microscopy and scanning electron microscope. Three distinct failure modes were identified. The best condition provided an average tensile-shear load of 110 kN/m. For the best joint condition, 84 % of the test population presents an extension at fracture load over 1.9 mm, mostly concentrated at the joint thermomechanical affected zone. The tool position with bias toward the flow side of the extrusion slot shows to improve the strength of joints. The microstructural analysis along the interface of AA5754 to PEEK shows micro-mechanical interlocking, intercalated layers of these materials and adhesion as joining mechanisms.
Lean Manufacturing is a Prerequisite for Automation, A Quantified Study
Authors: Urmee Sharmin Akter , Hossain Md. Mosharraf 
Published: August 2023

Abstract
Lean manufacturing has become a well-known term for the past few years due to its capability to reduce waste and make a system more efficient. Most firms are shifting towards Industry 4.0 to cope with personalized customer demands, which can only be achieved with automation. Previous studies showed a conceptual framework for the integration of lean tools into automation but lacked systematic and quantified study. This study aims to find out the quantified effects of applying lean tools before and after automation. A case study was done in a leather industry with a specific production line that is completely labor dependent. The production line's assembly line data have been used to create the first simulation model (using ARENA). The second simulation model have been created considering automating the existing production line without any improvement by lean tools. Lean wastages are identified in the existing production line. Major wastage was a higher number of defects from certain workstations. The third simulation model have been created with an improvement using one of the lean tools-Inline Quality Check (IQC). The improvement lowers the number of defective items in the existing production line. Lastly, this improved labor-intensive production line is simulated by considering automation to find a comparison with the second simulation. The comparison study showed that productivity decreases (with higher input) more quickly in automated lines if lean tools are not applied before automation.
Cross-Lingual Depression Detection for Twitter Users: A Comparative Sentiment Analysis of English and Arabic Tweets
Authors: Helmy Abdelmoniem , Nassar Radwa , Ramdan Nagy 
Published: August 2023

Abstract

Depression, a common mental health issue, significantly disrupting an individual's daily functioning and increasing premature Depression, a common mental health issue, significantly disrupting an individual's daily functioning and increasing premature mortality risk. The ubiquitous use of social media platforms for expressing sentiments and sharing daily activities provides a fertile ground for early detection of depression. This paper makes significant contributions in utilizing online platforms for depression detection. Firstly, we introduce five machine-learning models to detect depression in Arabic and English text from Twitter. For Arabic text, our optimal model achieved a high accuracy with an F1-score of 96.6% for binary classification of depressed and non-depressed tweets. For English text, excluding negations, the model accomplished an F1-score of 92% for binary classification and 88% for multi-classification (depressed, indifferent, happy). When considering negations, the model demonstrated a slightly lower performance with an 87% and 85% F1-score for binary and multi-classification respectively. Secondly, we present three unique corpora: one manually annotated Arabic corpus, and two automatically annotated English corpora—with and without negation. These corpora encompass a broad spectrum of emotional sentiments, enhancing the depth of our analysis. Lastly, the paper presents a novel web application for depression detection, implementing our refined models. This application enables the identification of depression symptoms in tweets and prediction of an individual's depression trends, supporting both English and Arabic languages. This research represents a significant stride forward in mental health detection leveraging the widespread use of social media.
Association of Maternal Pre-Pregnancy or First Trimester Body Mass Index with Neurodevelopmental Outcome in Extremely Low Gestational Age Neonates
Authors: Chawla Sanjay , Laptook Abbot , Smith Emily , Tan Sylvia , Natarajan Girija , Wyckoff Myra , Greenberg Rachel , Ambalavanan Namasivayam , Bell Edward , Meurs Krisa Van , Hintz Susan , Vohr Betty 
Published: August 2023

Abstract
Objective: To compare the rates of death or survival with severe neurodevelopmental impairment (sNDI) at 2 years among extremely preterm infants in relation to pre-pregnancy or first trimester maternal body mass index (BMI).
Methods: This retrospective cohort study included extremely preterm infants (gestational age 220/7-266/7 weeks). The study was conducted at National Institute of Child Health and Human Development Neonatal Research Network sites. The primary outcome was death or sNDI at 2 years.
Results:
Data on the primary outcome were available for 1,208 children. Death or sNDI was not different among the three groups: 54.9% in normal, 56.1% in overweight, and 53.4% in obese group (p=0.39). There was no significant difference in mortality, sNDI, moderate/severe cerebral palsy, Bayley Scales of Infant Development (BSID)-III cognitive composite score <70, BSID-III language composite score <70 in adjusted models.
Conclusion:
Neurodevelopmental outcome was not significantly associated with maternal pre-pregnancy BMI among extreme preterm infants.
Investigating Virtual Interactions in Teamwork
Authors: safardoust atiyeh , Ramezanian Mohammad Rahim , Pourqasem Mohsen , Safardoust Asiyeh 
Published: August 2023

Abstract
Objective: This study aimed to identify the indicators of team virtual interactions or virtuality and the dimensions of teamwork and to examine the relationships between them. In this regard, work teams with different levels of virtual interactions on home appliance companies were examined.
Method: In the present study, 29 teams were randomly selected. To test the research hypotheses, structural equation modeling method was applied in the Smart pls software.
Results: Our findings demonstrated that the extent of virtual interactions of team members has a significant effect on some aspects of teamwork. Accordingly, the more virtual interactions of the teams were linked to the higher negative relationship between conflict and trust and the less positive relationship between trust and cooperation. On the other hand, virtual interactions have little effect on the positive relationship between trust and job satisfaction and organizational commitment.
Conclusions: Virtual interactions have an effect on different dimensions of teamwork and the relationship between these dimensions can be influenced.
CCR3 contributes to neuroinflammation and cognitive impairment induced by prolonged underwater exercise
Authors: Zhao Houyu , Liang Kun , Yu Zeyuan , Wen Yukun , Yu Xuhua , Xin Jiayun , Zhang Tingting , Tian Jianquan , Fang Yiqun 
Published: August 2023

Abstract
Underwater operations are widely used in diverse fields such as marine exploration, underwater construction and infrastructure maintenance, and military missions. Previous research has emphasized the significance of maintaining cognitive function during these tasks. However, the impact of underwater operations on cognitive function and the underlying mechanisms remain unclear. Hence, this study aimed to investigate the effects of underwater operations on cognitive function and explore the potential molecular mechanisms involved. We accomplished this first by assessing underwater operators’ stress response, anxiety, and cognitive function before and after a single underwater operation of two different durations and found that 30 min underwater operation improved cognitive function while 3 h underwater operation induced significant cognitive decline. Then, an animal model of swimming in a hyperbaric environment at 2.0ATA (atmospheres absolute) for varying durations was applied to simulate underwater operations. Behavioral tests, histological examinations, biochemical assays were conducted, and results indicated that the effect of a single underwater exercise on cognitive function was time-dependent and prolonged underwater exercise caused significant cognitive impairment. Furthermore, RNA-sequencing was conducted for the normal control group and the most significantly impaired group, leading to the focus on neuroinflammation and the identification of C-C chemokine receptor type 3(CCR3) as a potential target for further investigation. Finally, knockdown experiment was performed using an adeno-associated virus (AAV) vector containing shRNA (CCR3)-EGFP injected to the rats’ hippocampus to explore the involvement of CCR3 in cognitive impairment induced by prolonged underwater exercise. Results revealed that CCR3 knockdown significantly alleviated neuroinflammation and cognitive impairment. Moreover, prolonged underwater exercise activated microglia and promotes their polarization towards the pro-inflammatory phenotype. Conversely, CCR3 knockdown switched the activated microglia to the anti-inflammatory phenotype. Taken together, these results highlight the time-dependent effect of a single underwater operation on cognitive function and shed insight on alleviating CCR3-mediated neuroinflammation as potential intervention targets to protect the brain during underwater operations.
Effect of different planting depths on the emergence and growth of lentil
Authors: Biabani Abbas , Azarnia Mohsen 
Published: August 2023

Abstract
The most important principles of crops, the depth and the optimum planting date for optimum use of water resources and radiation, therefore the aim of this study was to determine the proper planting depth and date on lentil (cultivar Kimia). The experiment was conducted with two factors; planting date (first November and first December) as the main factor, and 15 planting depth (from sowing the surface (zero) to 14 cm as a subplot, with three replications in a split-plot of randomized complete block design. It was done in Gonbad Kavous University Greenhouse outdoor in 2014-2015- Iran. Traits such as D05, D10, D50, D90, D95, EU, R50, emergence rate, emergence percentage, seed vigor, number of primary branches, leaf area, and seedling dry weight were measured. By increasing the depth of planting, all traits except D05, D10, D50, D90, and D95 decreased significantly. Decrease of characteristics was lower in the first planting date in comparison with the second planting date. The highest emergence rate (2.16 seedlings per day), emergence percentage (92.59 percent), seed vigor (145.2), number of branches (2.80), seedling dry weight (237.8 mg seedling) and leaf area (26.44 cm2 per seedling) were obtained from two centimeters depth in first planting. The results can be concluded that the optimum planting date for achieving the most growth of lentil in Gonbad Kavous of the climatic region, was the first planting date (November); and planting depth 2–7 cm.
Reliving positive and negative interpersonal events activates a common set of neural networks for emotional processing
Authors: Chien Ling-Yao , Lee Hsin-Ju , Lin Fa-Hsuan , Kuo Wen-Jui 
Published: August 2023

Abstract
In this study, we asked the participants to recall both positive and negative interpersonal events, as well as a relatively neutral one, during fMRI, and compared their evoked brain activities. Our results delineated a neural system that exhibited differential response patterns within the same set of networks for positive emotions elicited by a joyful event with a good friend and negative emotions elicited by the breakup event with their ex-partner. The findings corroborated the constructed theories of emotion, which propose that emotions are constructed through a set of processes, including categorization, abstraction, and interpretation, by simulating interoceptive representations. In society, some individuals are more vulnerable to social rejection, and their psychological difficulties are multifaceted. Our study sheds light on the developmental course of these difficulties and paves the way for further evaluation.
Study on Influencing Factors of Tourist Flow in Scenic Spots Based on Big Data
Authors: Fu Li , Yao Yi , Liu Lina , Chen Ran 
Published: August 2023

Abstract
Tourism in China is a thriving industry. For the past few years, the growth of rural tourism was an important emphasis for many areas, which has had a positive impact on rural economies. Chinese people's attention to tourism cultures has shifted dramatically in the period of economic worldwide and the quick propagation of network data. Currently, popular tourism activities are now more attractive. Studying the allocation of tourism activities in terms of avoiding overpopulation and wasteful use of assets in tourist hotspots is a popular subject in the area of tourism. With the use of tourist activity information, this article expands a big data platform focused on spatial and temporal distribution (STD) features and presents a data mining technique founded on revamped genetic-coalesced convolutional neural network with fine-tuned long short-term memory (RG-CCNN-FLSTM) technique to forecast tourist activity in STD aspect. The distribution of tourist traffic can be successfully regulated; the goal of equitable distribution of tourism assets accomplished, and the establishment of intellectual tourism should be further boosted by providing the prediction results back to scenic spot workers in real-time. Using the simulation results, we may conclude that data mining is highly adaptable and accurate. The proposed technique here can lessen the negative effects induced by the unequal distribution of tourism activity and conceptual direction for a better-functioning tourism economy, according to this research. The findings of this article are presented in graphical forms by employing the Origin tool.
Molar ratio precursor investigation: a simple route to fabricate unfiltered carbon dot-based electroluminescent devices
Authors: Trapani Danilo , Saiano Filippo , Boninelli Simona , Crupi Isodiana , Macaluso Roberto , Mosca Mauro 
Published: August 2023

Abstract
In this paper we report a rapid, low cost and easy way to produce solid-state luminescent carbon-dots (CDs) as color converters for light-emitting diodes (LEDs). CD precursor (urea and citric acid) molar ratio in aqueous solution is varied with the aim to find out the best conditions for an efficient color conversion and reducing photoluminescence quenching without any additional treatments, and to produce color conversion LEDs in a simple and green way.
Evaluation of Total Phenolic, Flavonoid Contents and Antioxidant Activities of Seed Extracted from Coriander (Coriandrum Sativum L) and Black cumin (Nigella Sativa) Spices
Authors: Tibebe Dessie , Belete Abebaw , Kassa Yezbie , Mulugeta Marye , Moges Zerubabel , Yenealem Dereje , Fentie Tarekegn , Amare Agmas 
Published: August 2023

Abstract

Black cumin (Nigella sativa), and Coriander (Coriandrum sativum L.) are common culinary spices that are used singly or combined in the diet of many populations of Ethiopia and there is a long-held belief of their health-enhancing properties. The present study was designed to investigate the antioxidant properties, phenolic and flavonoid contents of aqueous methanolic extracts from Nigella sativa and Coriandrum sativum L. seed samples. The contents of polyphenols and flavonoids were evaluated by colorimetric method and antioxidant activity was determined based on the ability to scavenge free radicals by using DPPH assay. An aqueous methanol extract of Coriandrum sativum L. resulted in the highest phenolic content from West Dembia (1.799 ± 0.0011 mg GAE/g), followed by Nigella sativa from East and West Dembia (1.737 ± 0.0014 & 1.734 ± 0.0013 mg gallic acid equivalent per gram (mg GAE/g) respectively) and Coriandrum sativum L. from West Dembia (1.678 ± 0.0018 mg GAE/g) measured by the Folin–Ciocalteu reagent method. The greatest flavonoid content was observed with extracts of Coriandrum sativum L. (1.114 ± 0.0005 mg quercetin equivalents per gram samples (mg QE/g)) from East Dembia district followed by Nigella sativa (1.002 ± 0.0007 (mg QE/g) as measured by an aluminum chloride colorimetric method, while the least was recorded for Coriandrum sativum L. (0.926 ± 0.0013 mg QE/g) and Nigella sativa (0.764 ± 0.0010 mg QE/g) from West Dembia district. Among the two selected spice extracts Nigella sativa from East Dembia district displayed the highest DPPH radical scavenging activity with an IC50 value 432 mg ascorbic acid equivalent per gram sample (AAE/g), while Nigella sativa & Coriandrum sativum L. from West Dembia and Coriandrum sativum L. (East Dembia) showed lower antioxidant activities having 372, 320 and 366 mg AAE/g of sample respectively. These results confirmed that Nigella sativa and Coriandrum sativum L. extracts possess appreciable natural antioxidant potentials, thereby providing good justification for their increased domestication and combined food consumption.
Blood pressure measurement knowledge and counselling among hospital pharmacists – an interventional study
Authors: Aje Akinniyi Akinbiyi , Adeyemo Jumoke Oyeladun 
Published: August 2023

Abstract
Background
Pharmacists occupy a vantage position to educate patients with hypertension on self-monitoring of blood pressure (BP). An update on their knowledge and counselling on BP measurement is needful to ascertain proper information dissemination to patients.
Methods
An interventional study was carried out among hospital pharmacists using a semi-structured questionnaire for data collection. Sequel to preintervention assessment of pharmacists’ knowledge and counselling on BP measurement, an educational intervention was carried out by to address the gaps observed. Knowledge and counselling were then reassessed one-month postintervention to find out the impact of the intervention. Data was summarized with descriptive and inferential statistics with significance level set at p < 0.05.
Results
One hundred and forty-four pharmacists completed the study. Preintervention knowledge and counselling on BP measurement among the pharmacists was poor. Pharmacists’ knowledge on BP measurement increased significantly from 12.63 ± 4.12 preintervention to 23.64 ± 1.93 postintervention (p < 0.001); while their counselling on BP measurement also increased significantly from 1.31 ± 1.71 preintervention to 11.01 ± 1.43 postintervention (p < 0.001). The knowledge category of the pharmacists’ improved as majority who were categorized as having either “poor” (67, 46.5%) or “fair” (68, 47.2%) knowledge preintervention advanced to “excellent” (99, 68.7%) knowledge postintervention. Similarly, the pharmacists’ counselling category was upgraded from the majority categorized as poor (141, 97.9%) preintervention to excellent (87, 60.4%) postintervention. Prior to the educational intervention, only 62 (43.1%) pharmacists knew that BP measurement had to be carried out in both arms for a first-time patient. Also, when asked the question “What BP reading will be recorded for a patient whose BP readings when taken thrice were 149/82 mmHg, 141/78 mmHg, and 139/78 mmHg?” only 38 (26.4%) provided the right answer. Similarly, majority of the pharmacists (51, 35.4%) could only state one out of five precautions during blood pressure measurement. In this study, pharmacists’ gender, additional educational qualification, and work experience did not significantly influence their knowledge and counselling on BP measurement.
Conclusions
The educational intervention significantly improved pharmacists’ knowledge and counselling on BP measurement.
Evaluating The Effectiveness Of Graph Convolutional Network For Detection Of Polypharmacy Side Effects
Authors: IBRAHIM Abdullahi Abdu , Mohammed Tareq Abed , DARA Omer 
Published: August 2023

Abstract
Polypharmacy is frequently used to treat numerous illnesses; however, it might have unintended consequences. Recent research using graph convolutional networks (GCNs) has demonstrated promising results in the difficult problem of polypharmacy side effect detection. Using accuracy (ACC), area under the receiver operating characteristic curve (AUC), and F1-score, this study presents a GCN-based model for detecting polypharmacy side effects. The model draws on pharmaceutical data from electronic health records to generate a medication network graph to learn the intricate interrelationships between medications and estimate the risk of adverse effects. The experimental results demonstrate that the proposed GCN-based model outperforms conventional machine learning techniques with an ACC of 91%, an AUC of 0.88, and an F1-score of 0.83. The findings of this article suggest that GCNs are a useful method for monitoring patients on several medications for adverse reactions with total accuracy of 98.47%. Additional study is required to refine the model and collect more data for use in actual clinical settings.
GEOTAIL observations of magnetic reconnection environment around the dayside magnetopause under steady southward interplanetary magnetic field conditions
Authors: Kondoh Koji , Nitta Shinya 
Published: August 2023

Abstract
The magnetic reconnection environment around the dayside geomagnetopause under steady southward interplanetary magnetic field conditions is investigated using the in-situ observation by GEOTAIL satellite. We focus on the degrees of asymmetry in the plasma density, plasma temperature and the magnetic field strength between the both sides of the magnetopause, that is, the ratio of the value in the magnetosphere to that in the magnetosheath in order to build much more realistic initial condition in numerical simulation.
GEOTAIL satellite repeatedly across the magnetopause during a single pass due to the oscillating of the magnetopause. The degrees of asymmetry varies even during a single pass. We suggest these variations in the degree of asymmetry is caused by the dawn-dusk asymmetry of magnetic field strength due to the Parker spiral of the interplanetary magnetic field. The degree of asymmetry in the magnetic field strength is less than 4 and more than 0.5. The smaller degrees (<1.0) are observed in the dusk side. In the numerical simulation of the asymmetric magnetic reconnection in the dayside magnetopause, we should set the constant temperature ratio ~ 20 in the initial condition.