bluuebunny/crossref_metadata_2025 huggingface dataset:
Autonomy and identity: the role of two developmental tasks on adolescent's wellbeing
Authors: Ruiz Wawie D. G. , Yabut Homer J.
Published: April 2024

Developmental tasks theory suggests that the wellbeing of adolescents can be better understood by considering their developmental tasks, rather than just viewing it as a specific age. This concept has significantly influenced contemporary studies on the transition to adulthood. Study explains that psychosocial developmental tasks involve shifts in an individual's psychological state and social relationships, potentially disrupting their previous equilibrium. Authors stress the importance of forming personal identity and fostering a healthy sense of independence, especially concerning identity and autonomy tasks, as crucial elements for adolescent wellbeing analysis. In line with this, the study focuses on the concurrent and predictive relationship between identity process of commitment, emotional autonomy, and psychological wellbeing among adolescents. Four hundred fifty-four (454) participants with an age ranged from 15 to 19 years (m = 17.96) completed surveys measuring emotional autonomy, identity commitment, and psychological wellbeing. The findings revealed that both emotional autonomy and identity commitment predicted psychological wellbeing, but in different ways. The study revealed that emotional autonomy is inversely associated with psychological wellbeing in middle and late adolescents, indicating that their ability to establish independence from their parents or relinquish unrealistic parental expectations may be linked to a decline in their mental health. The results also indicated that identity commitment is moderately and positively related to psychological wellbeing, suggesting that when adolescents have a clear sense of their identity, they may experience greater wellbeing. This finding underscores the importance of encouraging adolescents to explore their values, interests, and goals, as well as providing them with support and guidance throughout the process. Additionally, the findings of the study revealed that emotional autonomy has a negative influence on psychological wellbeing when identity commitment is low or average. Specifically, when individuals have a low level of identity commitment, emotional autonomy significantly predicts lower psychological wellbeing. Similarly, when identity commitment is at an average level, emotional autonomy also has a detrimental effect on psychological wellbeing. Lastly, the study revealed that when individuals have a high level of identity commitment, emotional autonomy does not have a significant impact on psychological wellbeing. In simpler terms, when individuals possess a strong sense of commitment to their identity, their level of emotional autonomy does not play a significant role in influencing their psychological wellbeing.
Prevalence and related factors of sleep quality among Chinese undergraduates in Jiangsu Province: multiple models' analysis
Authors: Hu Bin , Shen Wen , Wang Yun , Wu Qi , Li Jiali , Xu Xiaozhou , Han Yaohui , Xiao Lishun , Yin Dehui
Published: April 2024

Background and aims

In China, a significant number of undergraduates are experiencing poor sleep quality. This study was designed to investigate the prevalence of poor sleep quality and identify associated factors among undergraduates in Jiangsu Province, China.

Methods

A total of 8,457 participants were collected in 2022 using whole-group convenience sampling. The factors studied included basic demographics, family and social support, personal lifestyles, physical and mental health, mobile phone addiction index (MPAI), and the Connor-Davidson resilience scale (CD-RISC). The Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality. Four models, including weighted multiple linear regression, binary logistic regression, weighted linear mixed model, and logistic regression with random effects, were applied to identify associated factors for sleep quality.

Results

Of the 8,457 participants analyzed, 26.64% (2,253) were classified into the poor sleep quality group with a PSQI score >7. No significant relationship was found between sleep quality and gender, native place, economic level of family, physical exercise, dormitory light, dormitory hygiene, and amativeness matter. Risk factors for sleep quality identified by the four models included lower CD-RISC, higher MPAI, fourth grade or above, smoking, drinking, greater academic pressure, greater employment pressure, roommate sleeping late, noisy dormitory, poorer physical health status, poorer mental health status, and psychological counseling.

Conclusions

These findings provide valuable insights for university administrators, enabling them to better understand the risk factors associated with poor sleep quality in undergraduates. By identifying these factors, administrators can provide targeted intervention measures and counseling programs to improve students' sleep quality.
Mental health among adolescents exposed to social inequality in Latin America and the Caribbean: a scoping review
Authors: Sánchez-Castro Johanna Carolina , Pilz González Laura , Arias-Murcia Saidy Eliana , Mahecha-Bermeo Viviana Andrea , Stock Christiane , Heinrichs Katherina
Published: April 2024

Background and objective

Adolescents from Latin America and the Caribbean grow up in a context of social inequality, which diminishes their well-being and leads to impaired emotional-cognitive development. To understand the problem, it is important to synthesize the available research about it. This study aims to explore the knowledge about adolescents’ mental health in Latin America and the Caribbean exposed to social inequality.

Methods

A systematic scoping review was conducted encompassing a search in five databases (Medline, CINAHL, PsycINFO, Scopus, and LILACS) in June 2022. Articles of various typologies were included without time limit. After two rounds of screening, relevant data were manually extracted and synthesized into self-constructed themes using thematic analysis.

Results

Out of 8,825 retrieved records, 42 papers were included in the final review, with a predominance of quantitative approaches. The synthesis revealed two main analytical themes: (a) defining social inequality, wherein intersecting inequalities produce discrimination and determine conditions for social vulnerability; (b) social inequality and mental health, which highlights the association between socio-structural difficulties and emotional problems, amplifying vulnerability to mental ill health and poor mental health care.

Conclusion

The scientific evidence reveals that social inequality is related to impaired well-being and mental ill health on the one hand and a lack of access to mental health care on the other hand.
Artificial intelligence in the healthcare sector: comparison of deep learning networks using chest X-ray images
Authors: Yenikaya M. Akif , Kerse Gökhan , Oktaysoy Onur
Published: April 2024

Purpose

Artificial intelligence has led to significant developments in the healthcare sector, as in other sectors and fields. In light of its significance, the present study delves into exploring deep learning, a branch of artificial intelligence.

Methods

In the study, deep learning networks ResNet101, AlexNet, GoogLeNet, and Xception were considered, and it was aimed to determine the success of these networks in disease diagnosis. For this purpose, a dataset of 1,680 chest X-ray images was utilized, consisting of cases of COVID-19, viral pneumonia, and individuals without these diseases. These images were obtained by employing a rotation method to generate replicated data, wherein a split of 70 and 30% was adopted for training and validation, respectively.

Results

The analysis findings revealed that the deep learning networks were successful in classifying COVID-19, Viral Pneumonia, and Normal (disease-free) images. Moreover, an examination of the success levels revealed that the ResNet101 deep learning network was more successful than the others with a 96.32% success rate.

Conclusion

In the study, it was seen that deep learning can be used in disease diagnosis and can help experts in the relevant field, ultimately contributing to healthcare organizations and the practices of country managers.
“Better than my professor?” How to develop artificial intelligence tools for higher education
Authors: Triberti Stefano , Di Fuccio Raffaele , Scuotto Chiara , Marsico Emanuele , Limone Pierpaolo
Published: April 2024

Artificial Intelligence (AI) tools are currently designed and tested in many fields to improve humans’ ability to make decisions. One of these fields is higher education. For example, AI-based chatbots (“conversational pedagogical agents”) could engage in conversations with students in order to provide timely feedback and responses to questions while the learning process is taking place and to collect data to personalize the delivery of course materials. However, many existent tools are able to perform tasks that human professionals (educators, tutors, professors) could perform, just in a timelier manner. While discussing the possible implementation of AI-based tools in our university’s educational programs, we reviewed the current literature and identified a number of capabilities that future AI solutions may feature, in order to improve higher education processes, with a focus on distance higher education. Specifically, we suggest that innovative tools could influence the methodologies by which students approach learning; facilitate connections and information attainment beyond course materials; support the communication with the professor; and, draw from motivation theories to foster learning engagement, in a personalized manner. Future research should explore high-level opportunities represented by AI for higher education, including their effects on learning outcomes and the quality of the learning experience as a whole.
Adopting sea water reverse osmosis desalination technologies for sustainable development: lessons learnt from Algiers Science and Technology for membranes 2023 workshop
Authors: Ouali S. , Doucoure A.
Published: April 2024

The city of Algiers hosted the workshop on Science and Technology for Membranes from 30th May to 1st June 2023—STM 2023, held in Algeria. The main topics focused on Reverse Osmosis (RO) desalination technologies, decentralized autonomous systems, wastewater recycling for circularity, and the effects of green membrane processes on socio-economic growth. This review examines the influence of global trends and instabilities (i.e., climate change, disrupted supply chain platforms, natural disasters) on the steady supply of freshwater. The implementation of RO desalination solutions and their sustainability are assessed based on resiliency factors, which is helpful to screen water treatment alternatives based on technological benefits, ecological safety and environmental protection. Key takeaways from this study call for rolling out local membrane production capabilities, promoting the benefits of autonomous decentralized treatment systems, prioritizing innovative solutions to reduce greenhouse gas emissions, and for developing RO-specific equipment recycling infrastructures. Implementing these new tactics can lead to mitigate water scarcity and enable a sustainable deployment of desalination membrane technologies in Algeria and its region.
A sub-band division algorithm for ultra-wide bandwidth pulsar signals based on RFSoC
Authors: Du Xu , Zhang Hai-Long , Guo Shao-Cong , Zhang Ya-Zhou , Li Jian , Wang Jie , Ye Xin-Chen , Wu Han , Zhang Ting
Published: April 2024

In order to realize the real-time processing and analysis of astronomical ultra-wide bandwidth signals, this study proposes a sub-band division algorithm based on RFSoC. The algorithm uses Kaiser window to design FIR prototype low-pass filter, adopts critical sampling polyphase filter bank to decompose ultra-wide bandwidth signal into several sub-bands, and encapsulates each sub-band into VDIF data frame and sends it to GPU server. The algorithm is implemented on RFSoC platform, and its effectiveness is verified by simulation and actual observation. The experimental results show that the algorithm can divide the astronomical ultra-wide bandwidth signal into multiple sub-bands in real time, packetize and transmit them to GPU. This research provides reproducible design and project for ultra-wide bandwidth signal sub-band division with low spectrum leakage and aliasing, high data accuracy, and fast processing speed.
The Canadian Cow-Calf Surveillance Network – productivity and health summary 2018 to 2022
Authors: Waldner Cheryl , Windeyer M. Claire , Rousseau Marjolaine , Campbell John
Published: April 2024

Cow-calf surveillance data provide critical information about changing herd demographics, productivity, health, and management as well as the opportunity to investigate the impact of differing management practices. A national cow-calf network was established to collect baseline information on herd health, production performance measures, and management. Questionnaires were used to collect information on herd attributes as well as data for the calving season, breeding, pregnancy testing, and weaning for herds from across Canada. From 2018 to 2022, a total of 565 calving record questionnaires, representing 110,658 calving female records from 171 herds were returned, along with 543 herd breeding to weaning questionnaires. Suggested benchmark values based on the 25th percentiles from Western and Eastern Canada were determined to be <5% for non-pregnancy, <2% for calf death from birth to 24 h, and < 2% for calf death from 24 h to weaning. Herds from Eastern Canada were more likely to report any assistance at calving (p < 0.001) than herds from Western Canada. Participating herds from the east had longer breeding (p < 0.001) and calving (p < 0.001) seasons than those from the west and were also more likely to use artificial insemination or embryo transfer (p < 0.001). Timing of calving season and use of large pastures for calving were not associated with mortality at birth. Herds that started calving before April were more likely to have calves die before 30 d than those that started calving later; however, this difference was not observed between 30 d and weaning. Herds that started to calve earlier were also more likely to report treating more calves for bovine respiratory disease, diarrhea, and navel or joint infections as well as to calf deaths from respiratory disease. Calves from herds in the east were more likely to be treated or die from diarrhea than from the west. Females from herds that started calving later were less likely to be pregnant. The unique longitudinal productivity and health data resulting from this network established a national baseline to address region-specific needs for knowledge translation and solutions to enhance productivity and support sustainability.
The Cut-Cell Method for the Conjugate Heat Transfer Topology Optimization of Turbulent Flows Using the “Think Discrete–Do Continuous” Adjoint
Authors: Galanos Nikolaos , Papoutsis-Kiachagias Evangelos M. , Giannakoglou Kyriakos C.
Published: April 2024

This paper presents a topology optimization (TopO) method for conjugate heat transfer (CHT), with turbulent flows. Topological changes are controlled by an artificial material distribution field (design variables), defined at the cells of a background grid and used to distinguish a fluid from a solid material. To effectively solve the CHT problem, it is crucial to impose exact boundary conditions at the computed fluid–solid interface (FSI); this is the purpose of introducing the cut-cell method. On the grid, including also cut cells, the incompressible Navier–Stokes equations, coupled with the Spalart–Allmaras turbulence model with wall functions, and the temperature equation are solved. The continuous adjoint method computes the derivatives of the objective function(s) and constraints with respect to the material distribution field, starting from the computation of derivatives with respect to the positions of nodes on the FSI and then applying the chain rule of differentiation. In this work, the continuous adjoint PDEs are discretized using schemes that are consistent with the primal discretization, and this will be referred to as the “Think Discrete–Do Continuous” (TDDC) adjoint. The accuracy of the gradient computed by the TDDC adjoint is verified and the proposed method is assessed in the optimization of two 2D cases, both in turbulent flow conditions. The performance of the TopO designs is investigated in terms of the number of required refinement steps per optimization cycle, the Reynolds number of the flow, and the maximum allowed power dissipation. To illustrate the benefits of the proposed method, the first case is also optimized using a density-based TopO that imposes Brinkman penalization terms in solid areas, and comparisons are made.
Implementing Industry 4.0: An In-Depth Case Study Integrating Digitalisation and Modelling for Decision Support System Applications
Authors: Ranade Akshay , Gómez Javier , de Juan Andrew , Chicaiza William D. , Ahern Michael , Escaño Juan M. , Hryshchenko Andriy , Casey Olan , Cloonan Aidan , O’Sullivan Dominic , Bruton Ken , McGibney Alan
Published: April 2024

The scientific community has shown considerable interest in Industry 4.0 due to its capacity to revolutionise the manufacturing sector through digitalisation and data-driven decision-making. However, the actual implementation of Industry 4.0 within complex industrial settings presents obstacles that are typically beyond the scope of mainstream research articles. In this paper, a comprehensive case-study detailing our collaborative partnership with a leading medical device manufacturer is presented. The study traces its evolution from a state of limited digitalisation to the development of a digital intelligence platform that leverages data and machine learning models to enhance operations across a wide range of critical machines and assets. The main business objective was to enhance the energy efficiency of the manufacturing process, thereby improving its sustainability measures while also saving costs. The project encompasses energy modelling and analytics, Fault Detection and Diagnostics (FDD), renewable energy integration and advanced visualisation tools. Together, these components enable informed decision making in the context of energy efficiency.
Machine Learning Classifier for Supporting Generator’s Impedance-Based Relay Protection Functions
Authors: Sarajcev Petar , Lovric Dino
Published: April 2024

Transient stability of the electric power system still heavily rests on a timely and correct operation of the relay protection of individual power generators. Power swings and generator pole slips, following network short-circuit events, can initiate false relay activations, with negative repercussions for the overall system stability. This paper will examine the generator’s underimpedance (21G) and out-of-step (78) protection functions and will propose a machine learning based classifier for supporting and reinforcing their decision-making logic. The classifier, based on a support vector machine, will aid in blocking the underimpedance protection during stable generator swings. It will also enable faster tripping of the out-of-step protection for unstable generator swings. Both protection functions will feature polygonal protection characteristics. Their implementation will be based on European practice and IEC standards. Classifier will be trained and tested on the data derived from simulations of the IEEE New England 10-generator benchmark power system.
Urinary Biomarkers for Cell Cycle Arrest TIMP-2 and IGFBP7 for Prediction of Graft Function Recovery after Kidney Transplantation
Authors: Gäckler Anja , Ertasoglu Onurcan , Rohn Hana , Friebus-Kardash Justa , Ickerott Philipp-Christopher , Witzke Oliver , Kribben Andreas , Vogt Bruno , Dahdal Suzan , Arampatzis Spyridon , Eisenberger Ute
Published: April 2024

TIMP-2 and IGFBP7 have been identified and validated for the early detection of renal injury in critically ill patients, but data on recovery of allograft function after kidney transplantation (KTx) are scarce. In a prospective observational multicenter cohort study of renal transplant recipients, urinary [TIMP-2] × [IGFBP7] was evaluated daily from day 1 to 7 after KTx. Different stages of early graft function were defined: immediate graft function (IGF) (decrease ≥ 10% in serum creatinine (s-crea) within 24 h post KTx); slow graft function (SGF) (decrease in s-crea < 10% within 24 h post KTx); and delayed graft function (DGF) (any dialysis needed within the first week after KTx). A total of 186 patients were analyzed. [TIMP-2] × [IGFBP7] was significantly elevated as early as day 1 in patients with DGF compared to SGF and IGF. ROC analysis of [TIMP-2] × [IGFBP7] at day 1 post-transplant for event “Non-DGF” revealed a cut-off value of 0.9 (ng/mL)2/1000 with a sensitivity of 87% and a specificity of 71%. The positive predictive value for non-DGF was 93%. [TIMP-2] × [IGFBP7] measured at day 1 after KTx can predict early recovery of transplant function and is therefore a valuable biomarker for clinical decision making.
Regulation of Molecular Biomarkers Associated with the Progression of Prostate Cancer
Authors: Martin-Caraballo Miguel
Published: April 2024

Androgen receptor signaling regulates the normal and pathological growth of the prostate. In particular, the growth and survival of prostate cancer cells is initially dependent on androgen receptor signaling. Exposure to androgen deprivation therapy leads to the development of castration-resistant prostate cancer. There is a multitude of molecular and cellular changes that occur in prostate tumor cells, including the expression of neuroendocrine features and various biomarkers, which promotes the switch of cancer cells to androgen-independent growth. These biomarkers include transcription factors (TP53, REST, BRN2, INSM1, c-Myc), signaling molecules (PTEN, Aurora kinases, retinoblastoma tumor suppressor, calcium-binding proteins), and receptors (glucocorticoid, androgen receptor-variant 7), among others. It is believed that genetic modifications, therapeutic treatments, and changes in the tumor microenvironment are contributing factors to the progression of prostate cancers with significant heterogeneity in their phenotypic characteristics. However, it is not well understood how these phenotypic characteristics and molecular modifications arise under specific treatment conditions. In this work, we summarize some of the most important molecular changes associated with the progression of prostate cancers and we describe some of the factors involved in these cellular processes.
L-Asparaginase Conjugates from the Hyperthermophilic Archaea Thermococcus sibiricus with Improved Biocatalytic Properties
Authors: Dobryakova Natalia V. , Dumina Maria V. , Zhgun Alexander A. , Pokrovskaya Marina V. , Aleksandrova Svetlana S. , Zhdanov Dmitry D. , Kudryashova Elena V.
Published: April 2024

This study investigated the effect of polycationic and uncharged polymers (and oligomers) on the catalytic parameters and thermostability of L-asparaginase from Thermococcus sibiricus (TsA). This enzyme has potential applications in the food industry to decrease the formation of carcinogenic acrylamide during the processing of carbohydrate-containing products. Conjugation with the polyamines polyethylenimine and spermine (PEI and Spm) or polyethylene glycol (PEG) did not significantly affect the secondary structure of the enzyme. PEG contributes to the stabilization of the dimeric form of TsA, as shown by HPLC. Furthermore, neither polyamines nor PEG significantly affected the binding of the L-Asn substrate to TsA. The conjugates showed greater maximum activity at pH 7.5 and 85 °C, 10–50% more than for native TsA. The pH optima for both TsA-PEI and TsA-Spm conjugates were shifted to lower pH ranges from pH 10 (for the native enzyme) to pH 8.0. Additionally, the TsA-Spm conjugate exhibited the highest activity at pH 6.5–9.0 among all the samples. Furthermore, the temperature optimum for activity at pH 7.5 shifted from 90–95 °C to 80–85 °C for the conjugates. The thermal inactivation mechanism of TsA-PEG appeared to change, and no aggregation was observed in contrast to that of the native enzyme. This was visually confirmed and supported by the analysis of the CD spectra, which remained almost unchanged after heating the conjugate solution. These results suggest that TsA-PEG may be a more stable form of TsA, making it a potentially more suitable option for industrial use.
CdSe/ZnS Quantum Dots’ Impact on In Vitro Actin Dynamics
Authors: Chand Abhishu , Le Nhi , Kim Kyoungtae
Published: April 2024

Quantum dots (QDs) are a novel type of nanomaterial that has unique optical and physical characteristics. As such, QDs are highly desired because of their potential to be used in both biomedical and industrial applications. However, the mass adoption of QDs usage has raised concerns among the scientific community regarding QDs’ toxicity. Although many papers have reported the negative impact of QDs on a cellular level, the exact mechanism of the QDs’ toxicity is still unclear. In this investigation, we study the adverse effects of QDs by focusing on one of the most important cellular processes: actin polymerization and depolymerization. Our results showed that QDs act in a biphasic manner where lower concentrations of QDs stimulate the polymerization of actin, while high concentrations of QDs inhibit actin polymerization. Furthermore, we found that QDs can bind to filamentous actin (F-actin) and cause bundling of the filament while also promoting actin depolymerization. Through this study, we found a novel mechanism in which QDs negatively influence cellular processes and exert toxicity.
Defining the Most Potent Osteoinductive Culture Conditions for MC3T3-E1 Cells Reveals No Implication of Oxidative Stress or Energy Metabolism
Authors: Semicheva Alexandra , Ersoy Ufuk , Vasilaki Aphrodite , Myrtziou Ioanna , Kanakis Ioannis
Published: April 2024

The MC3T3-E1 preosteoblastic cell line is widely utilised as a reliable in vitro system to assess bone formation. However, the experimental growth conditions for these cells hugely diverge, and, particularly, the osteogenic medium (OSM)’s composition varies in research studies. Therefore, we aimed to define the ideal culture conditions for MC3T3-E1 subclone 4 cells with regard to their mineralization capacity and explore if oxidative stress or the cellular metabolism processes are implicated. Cells were treated with nine different combinations of long-lasting ascorbate (Asc) and β-glycerophosphate (βGP), and osteogenesis/calcification was evaluated at three different time-points by qPCR, Western blotting, and bone nodule staining. Key molecules of the oxidative and metabolic pathways were also assessed. It was found that sufficient mineral deposition was achieved only in the 150 μg.mL−1/2 mM Asc/βGP combination on day 21 in OSM, and this was supported by Runx2, Alpl, Bglap, and Col1a1 expression level increases. NOX2 and SOD2 as well as PGC1α and Tfam were also monitored as indicators of redox and metabolic processes, respectively, where no differences were observed. Elevation in OCN protein levels and ALP activity showed that mineralisation comes as a result of these differences. This work defines the most appropriate culture conditions for MC3T3-E1 cells and could be used by other research laboratories in this field.
Recent Advances in 3D Cultures
Authors: Picchio Vittorio , Gaetani Roberto , Chimenti Isotta
Published: April 2024

Methods and protocols for creating complex 3D cell culture systems have been rapidly advancing in the past decade from the perspective of biomaterials [...]
Phytocannabinoids: Exploring Pharmacological Profiles and Their Impact on Therapeutical Use
Authors: Blebea Nicoleta Mirela , Pricopie Andreea Iulia , Vlad Robert-Alexandru , Hancu Gabriel
Published: April 2024

Phytocannabinoids, a diverse group of naturally occurring compounds extracted from the Cannabis plant, have attracted interest due to their potential pharmacological effects and medicinal uses. This comprehensive review presents the intricate pharmacological profiles of phytocannabinoids while exploring the diverse impacts these substances have on biological systems. From the more than one hundred cannabinoids which were identified in the Cannabis plant so far, cannabidiol (CBD) and tetrahydrocannabinol (THC) are two of the most extensively studied phytocannabinoids. CBD is a non-psychoactive compound, which exhibits potential anti-inflammatory, neuroprotective, and anxiolytic properties, making it a promising candidate for a wide array of medical conditions. THC, known for its psychoactive effects, possesses analgesic and antiemetic properties, contributing to its therapeutic potential. In addition to THC and CBD, a wide range of additional phytocannabinoids have shown intriguing pharmacological effects, including cannabichromene (CBC), cannabigerol (CBG), and cannabinol (CBN). The endocannabinoid system, made up of the enzymes involved in the production and breakdown of endocannabinoids, cannabinoid receptors (CB1 and CB2), and endogenous ligands (endocannabinoids), is essential for preserving homeostasis in several physiological processes. Beyond their effects on the endocannabinoid system, phytocannabinoids are studied for their ability to modify ion channels, neurotransmitter receptors, and anti-oxidative pathways. The complex interaction between phytocannabinoids and biological systems offers hope for novel treatment approaches and lays the groundwork for further developments in the field of cannabinoid-based medicine. This review summarizes the state of the field, points out information gaps, and emphasizes the need for more studies to fully realize the therapeutic potential of phytocannabinoids.
Fatigue Behavior and Fracture Surface Analysis of Corroded High-Strength Bridge Cable Wires
Authors: Liu Zhongxiang , Guo Tong , Li Wenjie , Zhang Qinghua , Cheng Bin , Correia José
Published: April 2024

Bridge cable wires suffer from alternating stress and environmental erosion, leading to premature failure prior to its design life. This paper investigates the fatigue and mechanical behaviors of corroded bridge cable wires with a zinc–aluminum (Zn-Al) alloy coating. Based on the salt spray corrosion test and microstructure analysis, the anti-corrosion resistance and corrosion appearance characteristics of the Zn-Al alloy coating and galvanized coating were investigated. The Zn-Al alloy coating was superior in resistance to corrosion fatigue for the improvement in toughness and the generation of anti-corrosion Zn-Al and Fe-Zn-Al phases. Equations of the accelerated corrosion depth of the steel wires had been regressed to roughly estimate the corrosion life of the Zn-Al alloy coating, which can reach 29.1 years with a thickness of 70 μm. The fatigue and mechanical properties of the bare wires after the salt spray test were further studied based on tensile tests and fatigue tests. The fatigue properties of the bridge cable wire would decrease with the corrosion degree due to the deterioration and embrittlement of materials, where ductility characterized by the elongation rate was the most affected. Fracture surfaces of the wires were captured and analyzed based on a method for recognizing graphical contours. Insufficient fatigue life may occur in the steel wires after corrosion and increase with the degree of corrosion. The pit depth logarithmically weakened the fatigue life of steel wires for the weakening of fatigue toughness and the bearing area. The flat fracture was more common with a single fatigue source, while multiple fatigue sources led to step-like fractures for the generation of multiple dispersed crack propagation regions. Corrosion fatigue was more sensitive to the existence of fatigue sources than the reduction. Multiple initiation sources significantly reduced the fatigue life due to the cracking facilitation of the joint effect of multiple pits. The electrochemical reactions of corrosion can lead to material embrittlement and a reducing effect on the fracture toughness of the steel wires.
Performance Evaluation of Calcined Phosphogypsum Reinforced with Basalt Fiber and Calcium Carbonate Whiskers: A Study on Individual and Mixed Tests
Authors: Jiang Yong , Huo Jichuan , Lei Yonglin , Jia Lujun
Published: April 2024

In an effort to appropriately address the insufficient mechanical properties of calcined phosphogypsum, this research intends to explore how to utilize basalt fiber and calcium carbonate whiskers as reinforcing agents. The study delves deep into their impacts on the flexural and compressive strength, toughness, water resistance, and tensile strength of calcined phosphogypsum. In the individual tests, basalt fibers with different lengths (3 mm, 6 mm, 9 mm, and 18 mm) were added at dosages of 0%, 0.5%, 1.0%, and 1.5%, respectively. As clearly demonstrated by the research findings, basalt fiber effectively reinforces the flexural and compressive strength, toughness, and tensile strength of calcined phosphogypsum, though compromising water resistance. Among the various fiber lengths, the 6 mm fibers impose the most advantageous influence on the performance of calcined phosphogypsum. Afterwards, a test was conducted to explore how cross−scale fibers affect the properties of calcined phosphogypsum by mixing 6 mm basalt fibers and calcium carbonate whiskers. As illustrated by the experimental findings, calcium carbonate whisker refines the pores, thereby elevating the flexural strength and toughness of calcined phosphogypsum. Furthermore, it compensates for the water resistance limitations associated with the sole utilization of basalt fiber while further augmenting the tensile strength and strain capacity. Nonetheless, it is particularly noteworthy that heightening the dosage of both calcium carbonate whiskers and basalt fibers concurrently gives rise to augmented porosity of phosphogypsum and lowered compressive strength.
Microstructure and Chlorine Ion Corrosion Performance in Bronze Earring Relics
Authors: Song Zhiqiang , Tegus Ojiyed
Published: April 2024

Chlorine ions play an important role in the corrosion of bronzeware. This study employs techniques such as XRD, OM, SEM, EBSD, and electrochemical testing to analyze the microstructure, crystal structure, chemical composition, and corrosion performance of bronze earrings unearthed at the Xindianzi site in Inner Mongolia. The results indicate the presence of work-hardened structures, including twinning and equiaxed crystals, on the earrings’ surface. With an increase in chloride ion concentration in NaCl solutions from 10−3 mol/L to 1 mol/L, the corrosion current density of the bronze earrings increased from 2.372 × 10−7 A/cm2 to 9.051 × 10−7 A/cm2, demonstrating that the alloy’s corrosion rate escalates with chloride ion concentration. A 3-day immersion test in 0.5% NaCl solution showed the formation of a passivation layer of metal oxides on the earrings’ surface. These findings underscore the significance of the impact chloride ions have on the corrosion of copper alloys, suggesting that activating the alloy’s reactive responses can accelerate the corrosion process and provide essential insights into the corrosion mechanisms of bronze artifacts in chloride-containing environments.
Sorption Processes of Selected PAHs on Selected Fire-Resistant Materials Used in Special Firefighter Clothing
Authors: Rabajczyk Anna , Gniazdowska Justyna , Stojek Piotr , Bąk Łukasz
Published: April 2024

Fires constitute a significant threat due to the pollutants emitted and the destruction they cause. People who take part in firefighting operations must be equipped with appropriate tools, including special clothing that will allow them to work and guarantee safety. One of the threats is represented by compounds from the PAH (Polycyclic Aromatic Hydrocarbons) group, which are characterized by high toxicity and carcinogenicity. Therefore, it is important that the materials used constitute a barrier to contamination. Various materials from which individual elements of special firefighter’s clothing are made were tested. Additionally, the effect of height on the possibility of sorption of PAH compounds on a given type of material was analyzed. Based on the obtained analysis results, it was found that both the type of material and the zone in which the clothing items are used are important in the sorption processes of pollutants. For example, PAHs with high molecular weight are most likely to settle on rubber, i.e., the material from which shoes are made, with the exception of Chrysene, whose presence was found primarily in aramid fibers, i.e., the material from which trousers and jackets are made. However, among PAHs with low molecular weight, compounds such as Methylnaphthalene,1- and Fluorene were sorbed on the rubber surface in large quantities. The only compound that is present in comparable amounts in all materials is Acenaphthylene. Data in this area may be important for taking further actions related to the modification of materials used in special fire brigade clothing and in their cleaning processes.
Efficient Image Retrieval Using Hierarchical K-Means Clustering
Authors: Park Dayoung , Hwang Youngbae
Published: April 2024

The objective of content-based image retrieval (CBIR) is to locate samples from a database that are akin to a query, relying on the content embedded within the images. A contemporary strategy involves calculating the similarity between compact vectors by encoding both the query and the database images as global descriptors. In this work, we propose an image retrieval method by using hierarchical K-means clustering to efficiently organize the image descriptors within the database, which aims to optimize the subsequent retrieval process. Then, we compute the similarity between the descriptor set within the leaf nodes and the query descriptor to rank them accordingly. Three tree search algorithms are presented to enable a trade-off between search accuracy and speed that allows for substantial gains at the expense of a slightly reduced retrieval accuracy. Our proposed method demonstrates enhancement in image retrieval speed when applied to the CLIP-based model, UNICOM, designed for category-level retrieval, as well as the CNN-based R-GeM model, tailored for particular object retrieval by validating its effectiveness across various domains and backbones. We achieve an 18-times speed improvement while preserving over 99% accuracy when applied to the In-Shop dataset, the largest dataset in the experiments.
Cramér–Rao Lower Bound for Magnetic Field Localization around Elementary Structures
Authors: Dammann Armin , Siebler Benjamin , Sand Stephan
Published: April 2024

The determination of a mobile terminal’s position with high accuracy and ubiquitous coverage is still challenging. Global satellite navigation systems (GNSSs) provide sufficient accuracy in areas with a clear view to the sky. For GNSS-denied environments like indoors, complementary positioning technologies are required. A promising approach is to use the Earth’s magnetic field for positioning. In open areas, the Earth’s magnetic field is almost homogeneous, which makes it possible to determine the orientation of a mobile device using a compass. In more complex environments like indoors, ferromagnetic materials cause distortions of the Earth’s magnetic field. A compass usually fails in such areas. However, these magnetic distortions are location dependent and therefore can be used for positioning. In this paper, we investigate the influence of elementary structures, in particular a sphere and a cylinder, on the achievable accuracy of magnetic positioning methods. In a first step, we analytically calculate the magnetic field around a sphere and a cylinder in an outer homogeneous magnetic field. Assuming a noisy magnetic field sensor, we investigate the achievable positioning accuracy when observing these resulting fields. For our analysis, we calculate the Cramér–Rao lower bound, which is a fundamental lower bound on the variance of an unbiased estimator. The results of our investigations show the dependency of the positioning error variance on the magnetic sensor properties, in particular the sensor noise variance and the material properties, i.e., the relative permeability of the sphere with respect to the cylinder and the location of the sensor relative to the sphere with respect to the cylinder. The insights provided in this work make it possible to evaluate experimental results from a theoretical perspective.
Observer-Based Adaptive Sliding Mode Compensation Position-Tracking Control for Drilling Tool Attitude Adjustment
Authors: Gu Jinheng , Wang Xunqi , Yan Haifeng , Tan Chao , Si Lei , Wang Zhongbin
Published: April 2024

This study develops an adaptive sliding mode control approach for a drilling tool attitude adjustment system, aiming at solving the problems of model uncertainties and insufficient ability of disturbance suppression during the regulation behavior. To further improve the performance of the position-tracking loop in terms of response time, tracking accuracy, and robustness, a state observer based on an improved radial basis function is designed to approximate the model uncertainties, a valve dead-zone compensate controller is used to reduce control deviation, an adaptive sliding mode controller is designed to improve the position-tracking precision and attenuate sliding mode chattering. Finally, simulation and experimental results are carried out to verify the observability of the model uncertainties and position-tracking errors of the drilling tool attitude adjustment system, which can effectively improve the position-tracking performance and robustness of the drilling tool attitude adjustment system.
XMEA: A New Hybrid Diamond Multielectrode Array for the In Situ Assessment of the Radiation Dose Enhancement by Nanoparticles
Authors: Nicolucci Patricia , Gambaro Guilherme , Araujo Silva Kyssylla Monnyelle , Souza Lima Iara , Baffa Oswaldo , Pasquarelli Alberto
Published: April 2024

This work presents a novel multielectrode array (MEA) to quantitatively assess the dose enhancement factor (DEF) produced in a medium by embedded nanoparticles. The MEA has 16 nanocrystalline diamond electrodes (in a cell-culture well), and a single-crystal diamond divided into four quadrants for X-ray dosimetry. DEF was assessed in water solutions with up to a 1000 µg/mL concentration of silver, platinum, and gold nanoparticles. The X-ray detectors showed a linear response to radiation dose (r2 ≥ 0.9999). Overall, platinum and gold nanoparticles produced a dose enhancement in the medium (maximum of 1.9 and 3.1, respectively), while silver nanoparticles produced a shielding effect (maximum of 37%), lowering the dose in the medium. This work shows that the novel MEA can be a useful tool in the quantitative assessment of radiation dose enhancement due to nanoparticles. Together with its suitability for cells’ exocytosis studies, it proves to be a highly versatile device for several applications.
Reduction in the Sensor Effect on Acoustic Emission Data to Create a Generalizable Library by Data Merging
Authors: Chen Xi , Godin Nathalie , Doitrand Aurélien , Fusco Claudio
Published: April 2024

The aim of this paper is to discuss the effect of the sensor on the acoustic emission (AE) signature and to develop a methodology to reduce the sensor effect. Pencil leads are broken on PMMA plates at different source–sensor distances, and the resulting waves are detected with different sensors. Several transducers, commonly used for acoustic emission measurements, are compared with regard to their ability to reproduce the characteristic shapes of plate waves. Their consequences for AE descriptors are discussed. Their different responses show why similar test specimens and test conditions can yield disparate results. This sensor effect will furthermore make the classification of different AE sources more difficult. In this context, a specific procedure is proposed to reduce the sensor effect and to propose an efficient selection of descriptors for data merging. Principal Component Analysis has demonstrated that using the Z-score normalized descriptor data in conjunction with the Krustal–Wallis test and identifying the outliers can help reduce the sensor effect. This procedure leads to the selection of a common descriptor set with the same distribution for all sensors. These descriptors can be merged to create a library. This result opens up new outlooks for the generalization of acoustic emission signature libraries. This aspect is a key point for the development of a database for machine learning.
A Comprehensive Review of Behavior Change Techniques in Wearables and IoT: Implications for Health and Well-Being
Authors: Del-Valle-Soto Carolina , López-Pimentel Juan Carlos , Vázquez-Castillo Javier , Nolazco-Flores Juan Arturo , Velázquez Ramiro , Varela-Aldás José , Visconti Paolo
Published: April 2024

This research paper delves into the effectiveness and impact of behavior change techniques fostered by information technologies, particularly wearables and Internet of Things (IoT) devices, within the realms of engineering and computer science. By conducting a comprehensive review of the relevant literature sourced from the Scopus database, this study aims to elucidate the mechanisms and strategies employed by these technologies to facilitate behavior change and their potential benefits to individuals and society. Through statistical measurements and related works, our work explores the trends over a span of two decades, from 2000 to 2023, to understand the evolving landscape of behavior change techniques in wearable and IoT technologies. A specific focus is placed on a case study examining the application of behavior change techniques (BCTs) for monitoring vital signs using wearables, underscoring the relevance and urgency of further investigation in this critical intersection of technology and human behavior. The findings shed light on the promising role of wearables and IoT devices for promoting positive behavior modifications and improving individuals’ overall well-being and highlighting the need for continued research and development in this area to harness the full potential of technology for societal benefit.
Study on Dynamic Damage of Crash Barrier under Impact Load of High-Speed Train
Authors: Qian Kun , Wang Guanhan , Ma Hongsheng , Zeng Hailing
Published: April 2024

The derailment of a high-speed train in a tunnel will cause a very serious accident, but there are few research articles on anti-collision facilities in tunnels. In order to promote the sustainable development of high-speed trains and reduce the severity of accidents caused by derailment in tunnels of high-speed trains, this paper puts forward a crash barrier scheme in tunnels through the method of numerical simulation; the coupling finite element model of train–crash barrier–tunnel is established by using ABAQUS. The changes in lateral velocity and lateral displacement after the train hits the crash barrier without embedding steel bars are explored. We also explore the influence of different reinforcement amounts on the changes in the lateral speed and lateral displacement of trains under the condition of embedding steel bars. The results show that with the increase in stirrups and vertical reinforcement, the anti-impact and sustainable operation capability of the crash barrier are greater. It can also be seen from the lateral displacement of the train that the train shows the reverse movement trend, and the crash barrier plays a good role in intercepting the train. These research results can provide a reference for the sustainable development of transportation infrastructure construction.