bluuebunny/crossref_metadata_2025 huggingface dataset:
The ripple effect of strain in times of change: how manager emotional exhaustion affects team psychological safety and readiness to change
Authors: Groulx Patrick , Maisonneuve Francis , Harvey Jean-François , Johnson Kevin J.
Published: March 2024

Introduction

Managers assume a pivotal role during periods of organizational change, yet there exists a notable gap in our understanding of how their emotional exhaustion may impact their capacity to generate readiness to change within their teams. Grounded in the conservation of resources theory (COR), this study explores the crossover effect of managers’ emotional exhaustion on team readiness to change. We expect this to occur through higher levels of laissez-faire leadership, which impacts the teams’ psychological safety.

Methodology

Data was gathered within a Canadian governmental organization undergoing two significant changes—cultural change and digitalization—with a specific focus on leadership as a pivotal factor in preparing teams for change. Employing surveys from 372 team members and 62 managers affected by this change, we conducted path analysis to empirically test the proposed model across 74 teams and their respective managers.

Results

Managers’ emotional exhaustion has a negative indirect effect on team readiness to change. The double mediation pathway implies a positive relationship on laissez-faire leadership, which hinders psychological safety. In turn, psychological safety hampers team readiness to change.

Conclusion

Managers must invest significant resources to fulfill their roles and responsibilities during strategic change. Those who feel exhausted during change may look for ways to protect some of their resources by reducing the time and energy they invest leading their team. This self-preserving resource strategy has detrimental consequences on teams’ effectiveness during change due to an indirect crossover effect that affects the levels of psychological safety on the team.
The effect of anxiety on sleep disorders in medical students: a moderated mediation model
Authors: Yu Chuang , Liu Zhiyi , Su Tiehong , Li Zhongyu , Jiang Zinan , Zhong Wen , Xiao Zhongju
Published: March 2024

The relationship between anxiety and sleep disorders is a key research topic in the academic community. However, evidence on the mechanism through which anxiety influences sleep disorders remains limited. The purpose of this study was to investigate the roles of flourishing and neuroticism in the mechanism through which anxiety influences sleep disorders in medical students. We constructed a moderated mediation model and tested the mediating role of flourishing and the moderating role of neuroticism in medical college students. The results showed that: (1) anxiety was significantly and positively related to sleep disorders and significantly and negatively related to flourishing; flourishing was significantly and negatively related to sleep disorders; neuroticism was significantly and positively related to sleep disorders; (2) flourishing had a mediation effect on the relationship between anxiety and sleep disorders; (3) neuroticism moderated the process through which flourishing mediated the effect of anxiety on sleep disorders. Our research expands the literature on the mechanism underlying the effects of anxiety on sleep disorders and provides insights into the potential prevention and intervention of sleep and emotional problems in medical students.
Using staged teaching and assessment approaches to facilitate inter-university collaboration and problem-based learning
Authors: Dawson Henry , Davis Gayle , Ross Kirstin , Miller Marie Vaganay , Tomlinson Alastair
Published: March 2024

This article describes the segmented module design and problem-based learning approaches employed to enable parts of a higher education environmental health module (course) to be shared between universities in Wales, Northern Ireland, and Australia. The module requires students to identify the needs and assets of a community then design community-based interventions to address problems and undertake an evaluation of those interventions. Accreditation body and the degree program learning outcome requirements in the UK and Australia were found to hold many comparable knowledge, skills, and graduate attribute criteria, eliminating a potential barrier for international learning and teaching collaboration between higher education institutions. Instead, barriers to collaboration were associated with institutional issues and practicalities such as timetabling and assessment requirements. Taking a segmented approach to module design allowed staged and varied levels of collaboration between participating institutions, all delivering modules (courses) with similar learning outcomes. This provided a more sustainable environment to facilitate shared learning and teaching and fostered closer relations between programs, within these constraining factors. Students using problem-based learning and its group-working component exhibited the development of leadership, communication, and independent learning skills.
What Can Tree Swallows Teach Us About Biology?
Authors: Miller Colleen R. , Houtz Jennifer L. , Mejia Nicole , Morris Natalie J. , Pipkin Monique A. , Shankar Anusha , Uehling Jennifer J. , Williamson Jessie L. , Vitousek Maren N.
Published: March 2024

Tree swallows are North American birds that can help us understand more about biology. We already know a lot about tree swallows because they are easy to work with. These birds are popular for scientists to study. We know a lot about bird health, migration, and nesting because of tree swallows. However, tree swallows are declining because of climate change, insect loss, and habitat destruction. You can help by becoming a community scientist! Tree swallows are fascinating birds that everyone can help conserve. And along the way, we can learn more about our world.
How Will Climate Change Affect Pikas’ Favorite Snacks?
Authors: Monk Emily , Weatherill Karli , Ray Chris , Whipple Ashley , Varner Johanna
Published: March 2024

Many animals are herbivores, which means they get all their nutrients from eating plants. American pikas are cute rabbit relatives that eat plants in the mountains. But alpine winters are harsh, so pikas spend their entire summer gathering and storing plants to eat under the winter snow. Just like people, pikas in Colorado have a favorite food: a plant called alpine avens. This plant species is a special pika snack because it contains natural preservatives called phenolics, which keep the food fresh all winter. We studied how climate change is affecting this important feature of the pika’s favorite meal. Alpine avens contains more phenolics now than it did 30 years ago, so they preserve better in storage. But there is a catch: these preservatives can be hard to digest. Studies like this help us start to understand the many complicated ways that climate change affects herbivores like pikas.
Comparison of computed tomography perfusion and magnetic resonance dynamic susceptibility contrast perfusion-weighted imaging in canine brain
Authors: Lee Sangmin , Park Soomin , Hong Sungwha , Kim Soyeon , Yoon Junghee , Choi Jihye
Published: March 2024

Brain perfusion allows for the evaluation of cerebral hemodynamics, particularly in brain infarcts and tumors. Computed tomography (CT) perfusion (CTP) provides reliable data; however, it has a limited scan field of view and radiation exposure. Magnetic resonance (MR) perfusion provides detailed imaging of small structures and a wide scan field of view. However, no study has compared CTP and MR perfusion and assessed the correlation between the perfusion parameters measured using CTP and MR perfusion. The aim of the present study was to assess the correlation and agreement of the cerebral perfusion derived from dynamic susceptibility contrast (DSC)-MRI and CTP in dogs. In this crossover design study, the cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time, and time to peak were measured in the temporal cerebral cortex, caudate nucleus, thalamus, piriform lobe, and hippocampus using CTP and DSC-MRI in six healthy beagle dogs and a dog with a pituitary tumor. On the color map of healthy beagles, blood vessels and the perivascular brain parenchyma appeared as red-green, indicating high perfusion, and the areas distant from the vessels appeared as green-blue, indicating low perfusion levels in CTP and DSC-MRI. CTP parameters were highest in the piriform lobe (CBF = 121.11 ± 12.78 mL/100 g/min and CBV = 8.70 ± 2.04 mL/100 g) and lowest in the thalamus (CBF = 63.75 ± 25.24 mL/100 g/min and CBV = 4.02 ± 0.55 mL/100 g). DSC-MRI parameters were also highest in the piriform lobe (CBF = 102.31 ± 14.73 mL/100 g/min and CBV = 3.17 ± 1.23 mL/100 g) and lowest in the thalamus (CBF = 37.73 ± 25.11 mL/100 g/min and CBV = 0.81 ± 0.44 mL/100 g) although there was no statistical correlation in the quantitative perfusion parameters between CTP and DSC-MRI. In a dog with a pituitary tumor, the color map of the tumor appeared as a red scale, indicating high perfusion and higher CBF and CBV on CTP (149 mL/100 g and 20 mL/100 g/min) and on DSC-MRI (116.3 mL/100 g and 15.32 mL/100 g/min) compared to those measured in healthy dogs. These findings indicate that DSC-MRI and CTP maps exhibit comparability and interchangeability in the assessment of canine brain perfusion.
Progressive Multiple Alignment of Graphs
Authors: González Laffitte Marcos E. , Stadler Peter F.
Published: March 2024

The comparison of multiple (labeled) graphs with unrelated vertex sets is an important task in diverse areas of applications. Conceptually, it is often closely related to multiple sequence alignments since one aims to determine a correspondence, or more precisely, a multipartite matching between the vertex sets. There, the goal is to match vertices that are similar in terms of labels and local neighborhoods. Alignments of sequences and ordered forests, however, have a second aspect that does not seem to be considered for graph comparison, namely the idea that an alignment is a superobject from which the constituent input objects can be recovered faithfully as well-defined projections. Progressive alignment algorithms are based on the idea of computing multiple alignments as a pairwise alignment of the alignments of two disjoint subsets of the input objects. Our formal framework guarantees that alignments have compositional properties that make alignments of alignments well-defined. The various similarity-based graph matching constructions do not share this property and solve substantially different optimization problems. We demonstrate that optimal multiple graph alignments can be approximated well by means of progressive alignment schemes. The solution of the pairwise alignment problem is reduced formally to computing maximal common induced subgraphs. Similar to the ambiguities arising from consecutive indels, pairwise alignments of graph alignments require the consideration of ambiguous edges that may appear between alignment columns with complementary gap patterns. We report a simple reference implementation in Python/NetworkX intended to serve as starting point for further developments. The computational feasibility of our approach is demonstrated on test sets of small graphs that mimimc in particular applications to molecular graphs.
High-Precision Detection for Sandalwood Trees via Improved YOLOv5s and StyleGAN
Authors: Zhang Yu , Niu Jiajun , Huang Zezhong , Pan Chunlei , Xue Yueju , Tan Fengxiao
Published: March 2024

An algorithm model based on computer vision is one of the critical technologies that are imperative for agriculture and forestry planting. In this paper, a vision algorithm model based on StyleGAN and improved YOLOv5s is proposed to detect sandalwood trees from unmanned aerial vehicle remote sensing data, and this model has excellent adaptability to complex environments. To enhance feature expression ability, a CA (coordinate attention) module with dimensional information is introduced, which can both capture target channel information and keep correlation information between long-range pixels. To improve the training speed and test accuracy, SIOU (structural similarity intersection over union) is proposed to replace the traditional loss function, whose direction matching degree between the prediction box and the real box is fully considered. To achieve the generalization ability of the model, StyleGAN is introduced to augment the remote sensing data of sandalwood trees and to improve the sample balance of different flight heights. The experimental results show that the average accuracy of sandalwood tree detection increased from 93% to 95.2% through YOLOv5s model improvement; then, on that basis, the accuracy increased by another 0.4% via data generation from the StyleGAN algorithm model, finally reaching 95.6%. Compared with the mainstream lightweight models YOLOv5-mobilenet, YOLOv5-ghost, YOLOXs, and YOLOv4-tiny, the accuracy of this method is 2.3%, 2.9%, 3.6%, and 6.6% higher, respectively. The size of the training sandalwood tree model is 14.5 Mb, and the detection time is 17.6 ms. Thus, the algorithm demonstrates the advantages of having high detection accuracy, a compact model size, and a rapid processing speed, making it suitable for integration into edge computing devices for on-site real-time monitoring.
Evaluating Tomato Performance: A Novel Approach of Combining Full and Deficit Irrigation with Saline Water
Authors: Alghamdi Abdulaziz G. , Alshami Akram K. , El-Shafei Ahmed , Al-Omran Abdulrasoul M. , Alkhasha Arafat , Aly Anwar A. , Alharbi Abdulaziz R.
Published: March 2024

The tomato is a vital component of agriculture and is the second-most important vegetable globally. Maintaining a high tomato production requires both water quality and quantity. Water-scarce regions like Saudi Arabia still lack an understanding of the impact of deficit irrigation and the use of a blend of saline and freshwater, especially their nuanced impact across growth stages. The purpose of this study was to evaluate the effects of six different irrigation amounts: full irrigation with 100% ETc (FI), regulated deficit irrigation with 60% ETc (DI), and deficit irrigation with 60% ETc, except for the initial (DI-int), development (DI-dev), mid-season (DI-mid), and late-season (DI-lat) stages. This was performed with three different water qualities: fresh (FW), saline (SW), and fresh-saline blend (1:1) (MW) water. FW and MW enhanced the growth, physiology, morphology, yield, and quality, while SW had the lowest values. DI reduced these parameters and lowered yields by 13.7%, significantly improving water use efficiency (WUE) by 44% and fruit quality. DI-mid or DI-lat slightly improved yields while remarkably decreasing WUE and fruit quality. DI outperforms deficit irrigation in all growth stages except one, and countries with limited freshwater resources can benefit from a mix of fresh and saline water with a 60% ETc deficit irrigation, resulting in greater water savings.
ENVISPRAY: A Methodology to Evaluate PAE (Pesticide Application Equipment) According to the Environmental Risk
Authors: Collantes Rubén , Salcedo Ramon , Armengol Enric , Schlosser Jose F. , Gil Emilio
Published: March 2024

Pesticide application equipment (PAE) is the last part of the chain during the plant protection process. The use-phase of plant protection products (PPP) has been addressed in two EU Directives: 128/2009/EC and 127/2009/EC. This last one covers all the mandatory technical requirements to be fulfilled by new sprayers prior to their placement in the market. The objective of this research was to develop a potential decision support system (DSS) to evaluate and quantify the degree of implementation of all the required characteristics of new sprayers, including not only the mandatory requirements but also specifications widely described in the corresponding harmonized standard ISO 16119. It includes 10 independent elements of the sprayer, including a list of technical specifications listed in the applied standards ISO 16119 and ISO 16122. The relative influence of every one of the different elements has been quantified based on previous research. The algorithm enables the establishment of an objective relative classification of the sprayers to differentiate among different machines, mainly based on their quantified environmental contamination risk. The DSS can also discriminate among sprayers that should not reach the market due to their non-compliance with any of the mandatory requirements.
Beyond Fixed Dates and Coarse Resolution: Developing a Dynamic Dry Season Crop Calendar for Paddy in Indonesia from 2001 to 2021
Authors: Irawan Amalia Nafisah Rahmani , Komori Daisuke
Published: March 2024

There is valuable information that can be obtained beyond using a fixed crop calendar with coarse spatial resolution. Knowing the dynamics of the timing and location in which a particular crop is planted and harvested, with an annual temporal resolution and a fine spatial resolution, is crucial not only for monitoring crop conditions and production but also for understanding crop management under changing climates. In this study, the Normalized Difference Vegetation Index (NDVI) was utilized to develop a historical crop calendar for paddy in Indonesia with a 1 km resolution from 2001 to 2021. The result of this study is the first dynamic crop calendar that includes information about the planting, peak, and harvesting dates, as crop growth indicators, derived from the analysis of NDVI value fluctuations. Additionally, this dataset also includes the total number of cropping seasons each year. In Indonesia, there are intensive agricultural activities, including two dry cropping seasons that occur after the wet cropping season. However, this dataset is limited only to crops grown during the dry seasons, which typically begin in February and June. This dataset offers significant information at a finer spatiotemporal resolution to enable studies on agricultural fields undergoing climate change, although it is more country–specific than the other established dataset. The annual crop calendar dataset from 2001 to 2021 underscores the significance of examining the variability in cropping seasons over the years. This exploration aims to deepen our comprehension of the interplay between cropping seasons, climatic indicators, and even the social factors influencing farmers’ decisions. Furthermore, presented at a 1 km resolution, this dynamic crop calendar underscores the need for a more precise representation of diverse cropping intensities and seasons, particularly within small and fragmented agricultural areas.
Research on Indoor Environment Prediction of Pig House Based on OTDBO–TCN–GRU Algorithm
Authors: Guo Zhaodong , Yin Zhe , Lyu Yangcheng , Wang Yuzhi , Chen Sen , Li Yaoyu , Zhang Wuping , Gao Pengfei
Published: March 2024

Temperature and humidity, along with concentrations of ammonia and hydrogen sulfide, are critical environmental factors that significantly influence the growth and health of pigs within porcine habitats. The ability to accurately predict these environmental variables in pig houses is pivotal, as it provides crucial decision-making support for the precise and targeted regulation of the internal environmental conditions. This approach ensures an optimal living environment, essential for the well-being and healthy development of the pigs. The existing methodologies for forecasting environmental factors in pig houses are currently hampered by issues of low predictive accuracy and significant fluctuations in environmental conditions. To address these challenges in this study, a hybrid model incorporating the improved dung beetle algorithm (DBO), temporal convolutional networks (TCNs), and gated recurrent units (GRUs) is proposed for the prediction and optimization of environmental factors in pig barns. The model enhances the global search capability of DBO by introducing the Osprey Eagle optimization algorithm (OOA). The hybrid model uses the optimization capability of DBO to initially fit the time-series data of environmental factors, and subsequently combines the long-term dependence capture capability of TCNs and the non-linear sequence processing capability of GRUs to accurately predict the residuals of the DBO fit. In the prediction of ammonia concentration, the OTDBO–TCN–GRU model shows excellent performance with mean absolute error (MAE), mean square error (MSE), and coefficient of determination (R2) of 0.0474, 0.0039, and 0.9871, respectively. Compared with the DBO–TCN–GRU model, OTDBO–TCN–GRU achieves significant reductions of 37.2% and 66.7% in MAE and MSE, respectively, while the R2 value is improved by 2.5%. Compared with the OOA model, the OTDBO–TCN–GRU achieved 48.7% and 74.2% reductions in the MAE and MSE metrics, respectively, while the R2 value improved by 3.6%. In addition, the improved OTDBO–TCN–GRU model has a prediction error of less than 0.3 mg/m3 for environmental gases compared with other algorithms, and has less influence on sudden environmental changes, which shows the robustness and adaptability of the model for environmental prediction. Therefore, the OTDBO–TCN–GRU model, as proposed in this study, optimizes the predictive performance of environmental factor time series and offers substantial decision support for environmental control in pig houses.
An Overview of Antibiotic Therapy for Early- and Late-Onset Neonatal Sepsis: Current Strategies and Future Prospects
Authors: Boscarino Giovanni , Romano Rossana , Iotti Carlotta , Tegoni Francesca , Perrone Serafina , Esposito Susanna
Published: March 2024

Neonatal sepsis is a clinical syndrome mainly associated with a bacterial infection leading to severe clinical manifestations that could be associated with fatal sequalae. According to the time of onset, neonatal sepsis is categorized as early- (EOS) or late-onset sepsis (LOS). Despite blood culture being the gold standard for diagnosis, it has several limitations, and early diagnosis is not immediate. Consequently, most infants who start empirical antimicrobial therapy do not have an underlying infection. Despite stewardship programs partially reduced this negative trend, in neonatology, antibiotic overuse still persists, and it is associated with several relevant problems, the first of which is the increase in antimicrobial resistance (AMR). Starting with these considerations, we performed a narrative review to summarize the main findings and the future prospects regarding antibiotics use to treat neonatal sepsis. Because of the impact on morbidity and mortality that EOS and LOS entail, it is essential to start an effective and prompt treatment as soon as possible. The use of targeted antibiotics is peremptory as soon as the pathogen in the culture is detected. Although prompt therapy is essential, it should be better assessed whether, when and how to treat neonates with antibiotics, even those at higher risk. Considering that we are certainly in the worrying era defined as the “post-antibiotic era”, it is still essential and urgent to define novel strategies for the development of antibacterial compounds with new targets or mechanisms of action. A future strategy could also be to perform well-designed studies to develop innovative algorithms for improving the etiological diagnosis of infection, allowing for more personalized use of the antibiotics to treat EOS and LOS.
Comparative Analysis of Commonly Used Machine Learning Approaches for Li-Ion Battery Performance Prediction and Management in Electric Vehicles
Authors: Oyucu Saadin , Doğan Ferdi , Aksöz Ahmet , Biçer Emre
Published: March 2024

The significant role of Li-ion batteries (LIBs) in electric vehicles (EVs) emphasizes their advantages in terms of energy density, being lightweight, and being environmentally sustainable. Despite their obstacles, such as costs, safety concerns, and recycling challenges, LIBs are crucial in terms of the popularity of EVs. The accurate prediction and management of LIBs in EVs are essential, and machine learning-based methods have been explored in order to estimate parameters such as the state of charge (SoC), the state of health (SoH), and the state of power (SoP). Various machine learning techniques, including support vector machines, decision trees, and deep learning, have been employed for predicting LIB states. This study proposes a methodology for comparative analysis, focusing on classical and deep learning approaches, and discusses enhancements to the LSTM (long short-term memory) and Bi-LSTM (bidirectional long short-term memory) methods. Evaluation metrics such as MSE, MAE, RMSE, and R-squared are applied to assess the proposed methods’ performances. The study aims to contribute to technological advancements in the electric vehicle industry by predicting the performance of LIBs. The structure of the rest of the study is outlined, covering materials and methods, LIB data preparation, analysis, the proposal of machine learning models, evaluations, and concluding remarks, with recommendations for future studies.
Influence of Air Drying, Freeze Drying and Oven Drying on the Biflavone Content in Yellow Ginkgo (Ginkgo biloba L.) Leaves
Authors: Jurčević Šangut Iva , Pavličević Lana , Šamec Dunja
Published: March 2024

Drying herbs is a crucial method for stabilizing and preserving their essential properties and bioactive compounds. Although freeze drying is the preferred method for most herbs, it is expensive due to high energy consumption and operating costs. Biflavonoids are dimeric flavonoids that have recently been recognized as potential molecules possessing biological activities, such as antiviral and antimicrobial activity, and as effective molecules for the treatment of neurodegenerative and metabolic diseases and for cancer therapies. In this study, we performed a comparative analysis of freeze drying, air drying and oven drying to evaluate their effects on biflavonoid content in yellow ginkgo leaves (Ginkgo biloba L.). After drying, we performed spectrophotometric analysis to determine the browning index, pigments, phenolic compounds and antioxidant activity, while HPLC-DAD was used for the identification and quantification of individual biflavones (amentoflavone, bilobetin, ginkgetin, isoginkgetin and sciadopitysin). The most abundant biflavonoids were isoginkgetin and bilobetin, the amounts of which exceeded 1000 µg/g dw in all leaf samples. They were followed by ginkgetin and sciadopitysin, the amounts of which were about 30% lower. The drying method did not influence biflavone content or the total carotenoids, total polyphenols and total flavonoids. Consequently, our study suggests that all three methods may be used for the preparation of yellow ginkgo leaves as a source of biflavones and other bioactive compounds.
Dhad—A Children’s Handwritten Arabic Characters Dataset for Automated Recognition
Authors: AlMuhaideb Sarab , Altwaijry Najwa , AlGhamdy Ahad D. , AlKhulaiwi Daad , AlHassan Raghad , AlOmran Haya , AlSalem Aliyah M.
Published: March 2024

This study delves into the intricate realm of recognizing handwritten Arabic characters, specifically targeting children’s script. Given the inherent complexities of the Arabic script, encompassing semi-cursive styles, distinct character forms based on position, and the inclusion of diacritical marks, the domain demands specialized attention. While prior research has largely concentrated on adult handwriting, the spotlight here is on children’s handwritten Arabic characters, an area marked by its distinct challenges, such as variations in writing quality and increased distortions. To this end, we introduce a novel dataset, “Dhad”, refined for enhanced quality and quantity. Our investigation employs a tri-fold experimental approach, encompassing the exploration of pre-trained deep learning models (i.e., MobileNet, ResNet50, and DenseNet121), custom-designed Convolutional Neural Network (CNN) architecture, and traditional classifiers (i.e., Support Vector Machine (SVM), Random Forest (RF), and Multilayer Perceptron (MLP)), leveraging deep visual features. The results illuminate the efficacy of fine-tuned pre-existing models, the potential of custom CNN designs, and the intricacies associated with disjointed classification paradigms. The pre-trained model MobileNet achieved the best test accuracy of 93.59% on the Dhad dataset. Additionally, as a conceptual proposal, we introduce the idea of a computer application designed specifically for children aged 7–12, aimed at improving Arabic handwriting skills. Our concluding reflections emphasize the need for nuanced dataset curation, advanced model architectures, and cohesive training strategies to navigate the multifaceted challenges of Arabic character recognition.
Finite Element Simulation and Experimental Verification of Circular Tube Nosing through Conical Dies
Authors: Shewakh Walid M. , Hassab-Allah Ibrahim M.
Published: March 2024

The process of tube nosing is a delicate art that involves forming the end of a tubular part without causing any collapse, buckling, or wrinkling. A recent study has delved into the different modes of failure that can occur during this process and has determined the limits of tube nosing through the use of plasticity and thin/thick-walled tube theories. A finite element simulation was developed to replicate the cold-nosing process using conical dies to validate these theories. The results were compared to experimental outcomes for mild steel, hard steel, and annealed aluminium tubes to ensure accuracy. Through this analysis, we identified and confirmed the modes of failure that can restrict the plastic deformation for the tube nosing process. The outcomes were compared to analytical expressions and showed excellent agreement with the experiments, proving that these expressions provide a reliable reference guide for predicting the limits of the tube-nosing process. The FE simulation method also accurately models critical buckling stresses, nosing loads, and failure modes.
Nutritional and Physico-Chemical Characteristics of Innovative Bars Enriched with Aronia melanocarpa By-Product Powder
Authors: Bratosin Bogdan Constantin , Martău Gheorghe-Adrian , Ciont Călina , Ranga Floricuța , Simon Elemér , Szabo Katalin , Darjan Sorina , Teleky Bernadette-Emőke , Vodnar Dan Cristian
Published: March 2024

In a quest to meet the rising demand for nutrient-rich products, this study delves into the realm of innovative bars enriched with Aronia melanocarpa by-product powder. By repurposing waste material from fruit pressing, the research unveils a sustainable approach to enhancing the health profile of food products. Two variants of bars were used: one as a control and the other enriched with freeze-dried aronia by-product powder. Both bars had similar nutrient content, containing approximately 10% fibre, 12.20% protein, 20.51% fat, and 429–430 kcal calories. The investigation showcases a remarkable 61% increase in antioxidant activity in bars enriched with freeze-dried aronia powder compared to traditional bars. In vitro digestion tests demonstrated enhanced nutrient release in aronia powder-enriched bars. Moreover, a 70-day storage analysis demonstrated the microbiological stability of the bars, which is essential for their commercial viability (final total viable cell count 4.41 log10 CFU/g). Also, total fungi-yeast and moulds increased to 4.17 ± 0.131 log10 CFU/g for aronia bars and to 3.91 ± 0.107 log10 CFU/g for control bars after 70 days of storage. This collaborative research effort not only sheds light on the nutritional and physico–chemical characteristics of the innovative bars but also propels the development of functional food products with heightened antioxidant content and bioactive compounds.
The Impact of Effective Mass on the Strength of Side and Turning Kick in Taekwon-Do Male Practitioners
Authors: Góra Tomasz , Mosler Dariusz , Podstawski Robert , Wąsik Jacek
Published: March 2024

Background: One of the elements of improving the striking power of combat sports athletes is the ability to use their body mass in an efficient manner; this can improve movement technique and thus increase combat effectiveness. Therefore, the aim of this study was to gain knowledge about the influence of the effective mass obtained on the strength of turning and side kicks in the context of lateralization. Material and methods: The study involved four adult taekwon-do ITF (International Taekwon-do Federation) competitors. Acceleration and force data were obtained by mounting a wireless IMU sensor manufactured by Noraxon, which was synchronized with a force plate. Results: The median force pressure values amounted to 2661.53 N for the turning kick and 4596.15 N for the side kick, with foot acceleration of 150.56 m/s2 and 74.34 m/s2, respectively. The calculated median effective mass for the turning kick was 20.12%, and for the side kick, it was 73.09% of the total body mass. The conducted analysis indicates a lack of statistically significant differences between the right and left leg in the obtained kinetic variable values (p > 0.05). Conclusions: Our research suggests that the side kick achieves, on average, higher force values than the turning kick. The noted correlation between the three variables informs us that the greater the effective mass, the greater the force pressure and the smaller the foot acceleration, which is consistent with other studies. The lack of lateralization in the limbs performing the kicks is consistent with another study.
Unraveling Spatial–Temporal Patterns and Heterogeneity of On-Ramp Vehicle Merging Behavior: Evidence from the exiD Dataset
Authors: Wang Yiqi , Li Yang , Li Ruijie , Wu Shubo , Li Linbo
Published: March 2024

Understanding the spatiotemporal characteristics of merging behavior is crucial for the advancement of autonomous driving technology. This study aims to analyze on-ramp vehicle merging patterns, and investigate how various factors, such as merging scenarios and vehicle types, influence driving behavior. Initially, a framework based on a high-definition (HD) map is developed to extract trajectory information in a meticulous manner. Subsequently, eight distinct merging patterns are identified, with a thorough examination of their behavioral characteristics from both temporal and spatial perspectives. Merging behaviors are examined temporally, encompassing the sequence of events from approaching the on-ramp to completing the merge. This study specifically analyzes the target lane’s spatial characteristics, evaluates the merging distance (ratio), investigates merging speed distributions, compares merging patterns and identifies high-risk situations. Utilizing the latest aerial dataset, exiD, which provides HD map data, the study presents novel findings. Specifically, it uncovers patterns where the following vehicle in the target lane chooses to accelerate and overtake rather than cutting in front of the merging vehicle, resulting in Time-to-Collision (TTC) values of less than 2.5 s, indicating a significantly higher risk. Moreover, the study finds that differences in merging speed, distance, and duration can be disregarded in patterns where vehicles are present both ahead and behind, or solely ahead, suggesting these patterns could be integrated for simulation to streamline analysis and model development. Additionally, the practice of truck platooning has a significant impact on vehicle merging behavior. Overall, this study enhances the understanding of merging behavior, facilitating autonomous vehicles’ ability to comprehend and adapt to merging scenarios. Furthermore, this research is significant in improving driving safety, optimizing traffic management, and enabling the effective integration of autonomous driving systems with human drivers.
Long-Term Effects in Structures: Background and Recent Developments
Authors: Harapin Alen , Jurišić Marino , Bebek Neda , Sunara Marina
Published: March 2024

This article addresses the often overlooked but critical long-term factors of creep, shrinkage, ageing and corrosion in civil engineering structures. The paper emphasizes their substantial impact on structural mechanical resistance and safety, drawing attention to key examples like the Civic Tower in Pavia, the Koror-Babeldaob Bridge and dams in the USA. By exploring the challenges faced in modern engineering, the article sheds light on the need to consider these effects. Various models for predicting creep and shrinkage in concrete structures are introduced as potential solutions. In conclusion, the paper highlights the necessity for engineers to navigate the intricacies of material behaviour for successful construction amidst evolving challenges.
Research on Multi-UAV Task Assignment Based on a Multi-Objective, Improved Brainstorming Optimization Algorithm
Authors: Wang Xiaofang , Yin Shi , Luo Lianyong , Qiao Xin
Published: March 2024

In response to the practice of rescue channel blocking and a shortage of emergency materials in the event of sudden significant disasters, a multi-UAV collaborative distribution scheme was designed based on the demand for rapid and accurate distribution of materials. This paper constructed a multi-UAV collaborative task assignment and routing problem with simultaneous delivery and pick-up and time windows (MVTARPSDPTW), considering the factors of UAV load, energy consumption, cargo quality, and volume to minimize the total cost of UAV distribution and the full penalty of the task, as well as optimizing the balance of UAV efficiency. This paper proposes a multi-objective, improved brainstorming optimization algorithm based on Pareto dominance (MIBSO) to solve the MVTARPSDPTW problem. With DTLZ4, DTLZ5, and DTLZ6 benchmarks, this work tests the algorithm performance according to the characteristic attributes of the model sought, selecting the four indicators of GD, the Spacing metric, HV, and IGD, concerning convergence, solution distribution, and comprehensive performance. Case validation is based on a COVID-19 scenario in Changchun, China, and the results show that the model algorithm designed in this paper has good performance and feasibility in convergence and distribution of reconciliation. Finally, the multi-UAV emergency material distribution solution provides practical, theoretical support for rescue tasks in sudden significant disasters.
The Distribution and Accessibility of Elements of Tourism in Historic and Cultural Cities
Authors: Hsu Wei-Ling , Chang Yi-Jheng , Mou Lin , Huang Juan-Wen , Liu Hsin-Lung
Published: March 2024

Historic urban areas are the foundations of urban development. Due to rapid urbanization, the sustainable development of historic urban areas has become challenging for many cities. Elements of tourism and tourism service facilities play an important role in the sustainable development of historic areas. This study analyzed policies related to tourism in Panguifang and Meixian districts in Meizhou, Guangdong, China. Kernel density estimation was used to study the clustering characteristics of tourism elements through point of interest (POI) data, while space syntax was used to study the accessibility of roads. In addition, the Pearson correlation coefficient and regression were used to analyze the correlation between the elements and accessibility. The results show the following: (1) the overall number of tourism elements was high on the western side of the districts and low on the eastern one, and the elements were predominantly distributed along the main transportation arteries; (2) according to the integration degree and depth value, the western side was easier to access than the eastern one; and (3) the depth value of the area negatively correlated with kernel density, while the degree of integration positively correlated with it. Based on the results, the study put forward measures for optimizing the elements of tourism in Meizhou’s historic urban area to improve cultural tourism and emphasize the importance of the elements.
Development of a Smartphone-Based System for Intrinsically Photosensitive Retinal Ganglion Cells Targeted Chromatic Pupillometry
Authors: Sousa Ana Isabel , Marques-Neves Carlos , Vieira Pedro Manuel
Published: March 2024

Chromatic Pupillometry, used to assess Pupil Light Reflex (PLR) to a coloured light stimulus, has regained interest since the discovery of melanopsin in the intrinsically photosensitive Retinal Ganglion Cells (ipRGCs). This technique has shown the potential to be used as a screening tool for neuro-ophthalmological diseases; however, most of the pupillometers available are expensive and not portable, making it harder for them to be used as a widespread screening tool. In this study, we developed a smartphone-based system for chromatic pupillometry that allows targeted stimulation of the ipRGCs. Using a smartphone, this system is portable and accessible and takes advantage of the location of the ipRGCs in the perifovea. The system incorporates a 3D-printed support for the smartphone and an illumination system. Preliminary tests were carried out on a single individual and then validated on eleven healthy individuals with two different LED intensities. The average Post-Illumination Pupil Light Response 6 s after the stimuli offsets (PIPR-6s) showed a difference between the blue and the red stimuli of 9.5% for both intensities, which aligns with the studies using full-field stimulators. The results validated this system for a targeted stimulation of the ipRGCs for chromatic pupillometry, with the potential to be a portable and accessible screening tool for neuro-ophthalmological diseases.
Analysis of Intracranial Aneurysm Haemodynamics Altered by Wall Movement
Authors: Goetz Aurèle , Jeken-Rico Pablo , Chau Yves , Sédat Jacques , Larcher Aurélien , Hachem Elie
Published: March 2024

Computational fluid dynamics is intensively used to deepen our understanding of aneurysm growth and rupture in an attempt to support physicians during therapy planning. Numerous studies assumed fully rigid vessel walls in their simulations, whose sole haemodynamics may fail to provide a satisfactory criterion for rupture risk assessment. Moreover, direct in vivo observations of intracranial aneurysm pulsation were recently reported, encouraging the development of fluid–structure interaction for their modelling and for new assessments. In this work, we describe a new fluid–structure interaction functional setting for the careful evaluation of different aneurysm shapes. The configurations consist of three real aneurysm domes positioned on a toroidal channel. All geometric features, employed meshes, flow quantities, comparisons with the rigid wall model and corresponding plots are provided for the sake of reproducibility. The results emphasise the alteration of flow patterns and haemodynamic descriptors when wall deformations were taken into account compared with a standard rigid wall approach, thereby underlining the impact of fluid–structure interaction modelling.
Exosomes as Promising Therapeutic Tools for Regenerative Endodontic Therapy
Authors: Kong Qingyue , Wang Yujie , Jiang Nan , Wang Yifan , Wang Rui , Hu Xiaohan , Mao Jing , Shi Xin
Published: March 2024

Pulpitis is a common and frequent disease in dental clinics. Although vital pulp therapy and root canal treatment can stop the progression of inflammation, they do not allow for genuine structural regeneration and functional reconstruction of the pulp–dentin complex. In recent years, with the development of tissue engineering and regenerative medicine, research on stem cell-based regenerative endodontic therapy (RET) has achieved satisfactory preliminary results, significantly enhancing its clinical translational prospects. As one of the crucial paracrine effectors, the roles and functions of exosomes in pulp–dentin complex regeneration have gained considerable attention. Due to their advantages of cost-effectiveness, extensive sources, favorable biocompatibility, and high safety, exosomes are considered promising therapeutic tools to promote dental pulp regeneration. Accordingly, in this article, we first focus on the biological properties of exosomes, including their biogenesis, uptake, isolation, and characterization. Then, from the perspectives of cell proliferation, migration, odontogenesis, angiogenesis, and neurogenesis, we aim to reveal the roles and mechanisms of exosomes involved in regenerative endodontics. Lastly, immense efforts are made to illustrate the clinical strategies and influencing factors of exosomes applied in dental pulp regeneration, such as types of parental cells, culture conditions of parent cells, exosome concentrations, and scaffold materials, in an attempt to lay a solid foundation for exploring and facilitating the therapeutic strategy of exosome-based regenerative endodontic procedures.
Simulation Analysis of Frog-Inspired Take-Off Performance Based on Different Structural Models
Authors: Wang Shuqi , Fan Jizhuang , Liu Yubin
Published: March 2024

The frog-inspired jumping robot is an interesting topic in the field of biomechanics and bionics. However, due to the frog’s explosive movement and large range of joint motion, it is very difficult to make their structure completely bionic. To obtain the optimal jumping motion model, the musculoskeletal structure, jumping movement mechanism, and characteristics of frogs are first systematically analyzed, and the corresponding structural and kinematic parameters are obtained. Based on biological characteristics, a model of the articular bone structure is created, which can fully describe the features of frog movement. According to the various factors affecting the frog’s jumping movement, mass and constraints are added, and the complex biological joint structure is simplified into four different jumping structure models. The jumping ground reaction force, velocity, and displacement of the center of mass, joint torque, and other motion information of these four models are obtained through ADAMS simulation to reveal the jumping movement mechanism and the influencing factors of frogs. Finally, various motion features are analyzed and compared to determine the optimal structural model of the comprehensive index, which provides a theoretical basis for the design of the frog-inspired jumping robot.
Exploring the Impact of Leader Bottom-Line Mentality on Subordinate Learning from Work Failures: A Social Information Processing Perspective
Authors: Shi Yunsheng , Gao Lei , Yu Haibo , Song Shanghao
Published: March 2024

Learning from work failures is not only beneficial for individual development but also crucial for improving organizational performance and achieving sustainable development. We hypothesize that leader bottom-line mentality, which is commonly used by leaders to prevent profit and performance losses, may reduce subordinates learning from work failures. Drawing on social information processing theory, this paper examines how and when leader bottom-line mentality negatively affects subordinates learning from work failures. We tested our hypotheses through a three-wave survey of 245 employees from several high-tech companies in China. For data analysis, we used SPSS 26.0 and Mplus 8.0 to test the theoretical model and research hypotheses. The results indicated that leader bottom-line mentality has a negative indirect effect on subordinates learning from work failures through the mediating role of subordinates’ psychological availability. In addition, subordinate self-compassion can mitigate this negative mediating mechanism. The present study has several theoretical and practical implications for the current literature.