bluuebunny/crossref_metadata_2025 huggingface dataset:
Myocardial Injury after Non-Cardiac Surgery in Patients Who Underwent Open Repair for Abdominal Aortic Aneurysm: A Retrospective Study
Authors: Bae Myung Il , Kim Tae-Hoon , Yoon Hei Jin , Song Suk-Won , Min Narhyun , Lee Jongyun , Ham Sung Yeon
Published: February 2024

Background: Myocardial injury after non-cardiac surgery (MINS) has been known to be associated with mortality in various surgical patients; however, its prognostic role in abdominal aortic aneurysm (AAA) open repair remains underexplored. This study aimed to investigate the role of MINS as a predictor of mortality in patients who underwent AAA open repair. Methods: This retrospective study investigated 352 patients who underwent open repair for non-ruptured AAA. The predictors of 30-day and 1-year mortalities were investigated using logistic regression analysis. Results: MINS was diagnosed in 41% of the patients after AAA open repair in this study. MINS was an independent risk factor of 30-day mortality (odds ratio [OR]: 10.440, 95% confidence interval [CI]: 1.278–85.274, p = 0.029) and 1-year mortality (OR: 5.189, 95% CI: 1.357–19.844, p = 0.016). Kaplan–Meier survival curves demonstrated significantly lower overall survival rates in patients with MINS compared to those without MINS (p = 0.003). Conclusion: This study revealed that MINS is a common complication after AAA open repair and is an independent risk factor of 30-day and 1-year mortalities. Patients with MINS have lower overall survival rates than those without MINS.
Experiential Transformation in Privacy Behavior: A New Framework for Privacy Behavior Enhancement
Authors: Paspatis Ioannis , Tsohou Aggeliki
Published: February 2024

Multiple studies have demonstrated that the conventional method of learning is suboptimal when our goal is to enhance individuals’ genuine privacy behavior. This study introduces a framework for transforming privacy behavior, with the objective of enhancing individuals’ privacy practices to a higher level of confidentiality. We performed an experiment on a limited number of people to validate the efficacy of our suggested transformation framework. This framework combined determining aspects of privacy behavior with experiential behavior modification methodologies such as neutral stimuli (e.g., cognitive behavioral transformation—CBTx), practical assessments and motivational interviews from other disciplines. While these methods have proven effective in fields like psychology and sociology, they have not yet been applied to the realm of Information Computer and Technology (ICT). In this study, we have effectively demonstrated the efficacy of the proposed framework through a five-phase experiment. The suggested framework has the potential to be advantageous for educational institutions, including both public and private schools as well as universities, to construct new frameworks or develop new methodologies regarding individuals’ privacy behavior transformation to a more protective one. Furthermore, our framework offers a conducive environment for further investigation into privacy behavior transformation methodologies.
Self-Unfolding Properties of Smart Grid-Reinforced Membrane Origami
Authors: Hu Haotian , Xia Zhenmeng , Tao Qiang , Ye Zixin , Yuan Kaifeng , Song Leying
Published: February 2024

Origami-based membrane structures have shown great potential to revolutionize the construction of deployable and lightweight space structures in the future. However, the efficient unfolding mechanism puts forward major challenges to the practical realization of space-deployable structures. Here, a smart grid-reinforced membrane origami (SGRMO) is presented. The unfolding action hinges upon the application of forces facilitated by shape memory polymer composites (SMPCs). Subsequent locking action ensues through the restoration of the initial rigidity, accomplished via cooling mechanisms. This novel structure achieves the required lightweight and functionality by employing the grid design concept and effectively reduces the decline in unfolding extent caused by irreversible plastic deformation at the crease. Its recovery properties, including unfolding angle, distance, and surface precision, are experimentally and analytically investigated under different conditions. The results indicate that the structure can be reliably unfolded into the predefined shapes. In the case of Miura-SGRMO, the optimal surface precision is attained when the angle-ψ registers at 30°. The results of this study are expected to serve as the design of ultra-large flexible solar arrays and deployable antenna structures.
Delving into the Role of Receptor-like Tyrosine Kinase (RYK) in Cancer: In Silico Insights into Its Diagnostic and Prognostic Utility
Authors: Zapata-García Jessica Alejandra , Jave-Suárez Luis Felipe , Aguilar-Lemarroy Adriana
Published: February 2024

The RYK gene encodes a receptor-like tyrosine kinase crucial for several biological processes, including development, tissue homeostasis, and cancer. This study utilized data from the Cancer Genome Atlas Project (TCGA) to evaluate RYK expression at both mRNA and protein levels in various cancers, determine its prognostic significance, and explore its involvement in cancer-related signaling pathways. Elevated levels of RYK mRNA were identified in cholangiocarcinoma (CHOL), pancreatic adenocarcinoma (PAAD), glioblastoma multiforme (GBM), lung squamous cell carcinoma (LUSC), brain lower grade glioma (LGG), head and neck squamous cell carcinoma (HNSC), liver hepatocellular carcinoma (LICH), esophageal carcinoma (ESCA), and colon adenocarcinoma (COAD), while RYK protein levels were observed to be increased in colon adenocarcinoma (COAD), GBM, LICH, cervical and endocervical adenocarcinoma (CESC), and breast invasive carcinoma (BRCA). Additionally, RYK overexpression correlated with poorer prognosis in several cancers, including PAAD, LICH, BRCA, ESCA, COAD, and CESC. Furthermore, RYK showed a positive correlation with the upregulation of multiple receptors and coreceptors in the WNT signaling pathway in various types of cancer. In terms of cancer-related signaling pathways, RYK was found to potentially interact with DNA damage, TSC/mTOR, PI3K/AKT, EMT, RTK, RAS/MAPK, ER hormone, AR hormone, and the cell cycle. This study provides new and previously unreported insights into the role of RYK in cancer biology.
Experimental and Numerical Studies on the Ultimate Bending Strength of Welded Plated Grillage with Combined Openings
Authors: Chen Chen , Zhou Hong , Lv Zhengda , Li Ziqiu
Published: February 2024

Plated grillage with combined openings was susceptible to complex failure behaviors as the main load-bearing structure of the superstructure on passenger ships subjected to deck loads. Additionally, the deformation and stresses generated during the welding of the plated grillage complicated the prediction of its failure behavior. In this case, a new partitioned inherent strain method and nonlinear finite element method were used to simulate the welding and loading process, and experiments were designed and carried out to make comparisons, unveiling the influence regulations between the failure behavior of the structure and the loading condition, the initial welding state. This research on the failure mode analysis of plated grillages could provide references for the optimization of the structural form of plated grillages and the cargo loading scheme on the deck of a real ship.
Distributed Swarm Trajectory Planning for Autonomous Surface Vehicles in Complex Sea Environments
Authors: Wang Anqing , Li Longwei , Wang Haoliang , Han Bing , Peng Zhouhua
Published: February 2024

In this paper, a swarm trajectory-planning method is proposed for multiple autonomous surface vehicles (ASVs) in an unknown and obstacle-rich environment. Specifically, based on the point cloud information of the surrounding environment obtained from local sensors, a kinodynamic path-searching method is used to generate a series of waypoints in the discretized control space at first. Next, after fitting B-spline curves to the obtained waypoints, a nonlinear optimization problem is formulated to optimize the B-spline curves based on gradient-based local planning. Finally, a numerical optimization method is used to solve the optimization problems in real time to obtain collision-free, smooth and dynamically feasible trajectories relying on a shared network. The simulation results demonstrate the effectiveness and efficiency of the proposed swarm trajectory-planning method for a network of ASVs.
Financial Literacy of Entrepreneurs and Companies’ Performance
Authors: Culebro-Martínez Román , Moreno-García Elena , Hernández-Mejía Sergio
Published: February 2024

Financial literacy is the ability of people to process economic information to make better financial decisions. Therefore, the financial literacy of entrepreneurs could affect the management of their companies and their results. The aim of this research is to determine if there is a significant relationship between companies’ performance and financial knowledge, financial behavior, and financial attitude of micro, small, and medium-sized entrepreneurs. The incidence of the variables age, size, and sector of the companies, as well as the entrepreneur’s age, gender, and educational level on companies’ performance, is also analyzed. Data from 206 entrepreneurs from Veracruz, Mexico, were analyzed using a logistic regression model. The results show that the financial behavior of the entrepreneurs has a positive and highly significant effect on companies’ performance, although the entrepreneur´s knowledge and attitude don´t have a significant relationship with companies´ performance. The results also show that companies in the industrial sector led by men are less likely to obtain high performance compared to those in the commerce sector. No incidence was found of the variables age, size of the company, and entrepreneur´s educational level on the performance of their companies.
IFGAN—A Novel Image Fusion Model to Fuse 3D Point Cloud Sensory Data
Authors: Ignatious Henry Alexander , El-Sayed Hesham , Bouktif Salah
Published: February 2024

To enhance the level of autonomy in driving, it is crucial to ensure optimal execution of critical maneuvers in all situations. However, numerous accidents involving autonomous vehicles (AVs) developed by major automobile manufacturers in recent years have been attributed to poor decision making caused by insufficient perception of environmental information. AVs employ diverse sensors in today’s technology-driven settings to gather this information. However, due to technical and natural factors, the data collected by these sensors may be incomplete or ambiguous, leading to misinterpretation by AVs and resulting in fatal accidents. Furthermore, environmental information obtained from multiple sources in the vehicular environment often exhibits multimodal characteristics. To address this limitation, effective preprocessing of raw sensory data becomes essential, involving two crucial tasks: data cleaning and data fusion. In this context, we propose a comprehensive data fusion engine that categorizes various sensory data formats and appropriately merges them to enhance accuracy. Specifically, we suggest a general framework to combine audio, visual, and textual data, building upon our previous research on an innovative hybrid image fusion model that fused multispectral image data. However, this previous model faced challenges when fusing 3D point cloud data and handling large volumes of sensory data. To overcome these challenges, our study introduces a novel image fusion model called Image Fusion Generative Adversarial Network (IFGAN), which incorporates a multi-scale attention mechanism into both the generator and discriminator of a Generative Adversarial Network (GAN). The primary objective of image fusion is to merge complementary data from various perspectives of the same scene to enhance the clarity and detail of the final image. The multi-scale attention mechanism serves two purposes: the first, capturing comprehensive spatial information to enable the generator to focus on foreground and background target information in the sensory data, and the second, constraining the discriminator to concentrate on attention regions rather than the entire input image. Furthermore, the proposed model integrates the color information retention concept from the previously proposed image fusion model. Furthermore, we propose simple and efficient models for extracting salient image features. We evaluate the proposed models using various standard metrics and compare them with existing popular models. The results demonstrate that our proposed image fusion model outperforms the other models in terms of performance.
Potential for Agricultural Expansion in Degraded Pasture Lands in Brazil Based on Geospatial Databases
Authors: Bolfe Édson Luis , Victoria Daniel de Castro , Sano Edson Eyji , Bayma Gustavo , Massruhá Silvia Maria Fonseca Silveira , de Oliveira Aryeverton Fortes
Published: February 2024

Important public and private initiatives to map agricultural lands and natural resources have been carried out in Brazil to support land use planning. Some studies indicate that Brazil still has up to 109.7 million hectares of cultivated pastures with some level of degradation, representing around 60% of the total pasturelands, estimated at 177 million hectares. This study aimed to gather, process, and analyze publicly available databases to generate quantitative and spatial information about the potential of Brazilian degraded pastures for agricultural expansion. We considered data related to the natural agricultural potential, restrictions imposed by special areas (indigenous lands and Afro-Brazilian “quilombola” settlements), areas with high biodiversity conservation priorities, infrastructure such as distance between major highways and availability of warehouses, current agricultural areas, and the information made available by Agricultural Climate Risk Zoning. The results indicated the existence of approximately 28 million hectares of planted pastures with intermediate and severe levels of degradation that show high potential for agricultural crops. These areas could increase the planted areas with grains in Brazil by approximately 35% in relation to the total area used in the 2022/23 crop season.
Kazakhstani Gansu Dungan as a Contact Language: An Analysis of Russian Influence
Authors: Honkasalo Sami
Published: February 2024

This paper discusses extensive language contact and its results in Kazakhstani Gansu Dungan, a divergent variety of Mandarin Chinese. Based primarily on recorded conversational source materials, this study offers a contact linguistic overview of the language, introducing both phonological and morphosyntactic contact phenomena. It is shown that Kazakhstani Gansu Dungan is currently under extensive Russian influence. The influence permeates all layers of the language and exceeds lexical borrowing mentioned in earlier Dungan studies. For instance, clause combining and complex clauses in Dungan have shifted to the direction of a Russian model, which makes the language stand out among other Sinitic varieties. This study demonstrates that, in addition to introducing new structures, extensive Russian influence on Dungan also reinforces earlier development that has led the language further away from the Sinitic prototype. In all, Kazakhstani Gansu Dungan forms its own kind of divergent Russianized Sinitic variety and thus offers a contribution to both researching language contact in the Russophone world and to understanding the typological diversity of Sinitic languages.
Integrating Artificial Intelligence for Drug Discovery in the Context of Revolutionizing Drug Delivery
Authors: Visan Anita Ioana , Negut Irina
Published: February 2024

Drug development is expensive, time-consuming, and has a high failure rate. In recent years, artificial intelligence (AI) has emerged as a transformative tool in drug discovery, offering innovative solutions to complex challenges in the pharmaceutical industry. This manuscript covers the multifaceted role of AI in drug discovery, encompassing AI-assisted drug delivery design, the discovery of new drugs, and the development of novel AI techniques. We explore various AI methodologies, including machine learning and deep learning, and their applications in target identification, virtual screening, and drug design. This paper also discusses the historical development of AI in medicine, emphasizing its profound impact on healthcare. Furthermore, it addresses AI’s role in the repositioning of existing drugs and the identification of drug combinations, underscoring its potential in revolutionizing drug delivery systems. The manuscript provides a comprehensive overview of the AI programs and platforms currently used in drug discovery, illustrating the technological advancements and future directions of this field. This study not only presents the current state of AI in drug discovery but also anticipates its future trajectory, highlighting the challenges and opportunities that lie ahead.
The Appropriateness of Medical Devices Is Strongly Influenced by Sex and Gender
Authors: Campesi Ilaria , Franconi Flavia , Serra Pier Andrea
Published: February 2024

Until now, research has been performed mainly in men, with a low recruitment of women; consequentially, biological, physiological, and physio-pathological mechanisms are less understood in women. Obviously, without data obtained on women, it is impossible to apply the results of research appropriately to women. This issue also applies to medical devices (MDs), and numerous problems linked to scarce pre-market research and clinical trials on MDs were evidenced after their introduction to the market. Globally, some MDs are less efficient in women than in men and sometimes MDs are less safe for women than men, although recently there has been a small but significant decrease in the sex and gender gap. As an example, cardiac resynchronization defibrillators seem to produce more beneficial effects in women than in men. It is also important to remember that MDs can impact the health of healthcare providers and this could occur in a sex- and gender-dependent manner. Recently, MDs’ complexity is rising, and to ensure their appropriate use they must have a sex–gender-sensitive approach. Unfortunately, the majority of physicians, healthcare providers, and developers of MDs still believe that the human population is only constituted by men. Therefore, to overcome the gender gap, a real collaboration between the inventors of MDs, health researchers, and health providers should be established to test MDs in female and male tissues, animals, and women.
Classification of Progressive Wear on a Multi-Directional Pin-on-Disc Tribometer Simulating Conditions in Human Joints-UHMWPE against CoCrMo Using Acoustic Emission and Machine Learning
Authors: Deshpande Pushkar , Wasmer Kilian , Imwinkelried Thomas , Heuberger Roman , Dreyer Michael , Weisse Bernhard , Crockett Rowena , Pandiyan Vigneashwara
Published: February 2024

Human joint prostheses experience wear failure due to the complex interactions between Ultra-High-Molecular-Weight Polyethylene (UHMWPE) and Cobalt-Chromium-Molybdenum (CoCrMo). This study uses the wear classification to investigate the gradual and progressive abrasive wear mechanisms in UHMWPE. Pin-on-disc tests were conducted under simulated in vivo conditions, monitoring wear using Acoustic Emission (AE). Two Machine Learning (ML) frameworks were employed for wear classification: manual feature extraction with ML classifiers and a contrastive learning-based Convolutional Neural Network (CNN) with ML classifiers. The CNN-based feature extraction approach achieved superior classification performance (94% to 96%) compared to manual feature extraction (81% to 89%). The ML techniques enable accurate wear classification, aiding in understanding surface states and early failure detection. Real-time monitoring using AE sensors shows promise for interventions and improving prosthetic joint design.
Study of the Dynamic Properties of the Miniature Electro-Hydrostatic Actuator
Authors: An Yiqiang , Mao Jiazhe , Tong Chengwei , Zhou Xiaoyun , Ruan Jian , Li Sheng
Published: February 2024

The electro-hydrostatic actuator (EHA) is a new type of high-performance servo actuator that originated in the field of aerospace, and it is gradually becoming a common basic component for various types of large equipment. A miniature EHA, mainly composed of a micro two-dimensional (2D) piston pump and a brushless DC motor, is designed in this article by simplifying the system structure. This paper analyzes the structure and working principle of this EHA and establishes the mathematical models of the brushless DC motor, micro two-dimensional pump, and hydraulic cylinder. Field-oriented control (FOC) is used to drive the brushless DC motor, and the models of the controller are established in Simulink. Furthermore, the models of the mechanical and hydraulic systems of the miniature EHA are established in AMESim. In addition to this, a prototype of this miniature EHA was fabricated in this paper and an experimental platform was built for experiments. In the joint simulation environment, the rise time of the EHA system at 6000 r/min is 0.158 s and the frequency response amplitude attenuation to −3 dB has a bandwidth of 20 Hz. On the other hand, the constructed miniature EHA prototype was dynamically characterized to obtain a rise time of 0.242 s at 6000 r/min and a bandwidth of 13 Hz. In this paper, the feasibility of the design scheme of the miniature EHA system is verified, and its excellent dynamic properties are verified with simulation and experiment.
A Deep-LSTM-Based Fault Detection Method for Railway Vehicle Suspensions
Authors: Chen Yuejian , Liu Xuemei , Fan Wenkun , Duan Ningyuan , Zhou Kai
Published: February 2024

The timely detection of faults that occur in industrial machines and components can avoid possible catastrophic machine failure, prevent large financial losses, and ensure the safety of machine operators. A solution to tackle the fault detection problem is to start with modeling the condition monitoring signals and then examine any deviation of real-time monitored data from the baseline model. The newly developed deep long short-term memory (LSTM) neural network has a high nonlinear flexibility and can simultaneously store long- and short-term memories. Thus, deep LSTM is a good option for representing underlying data-generating processes. This paper presents a deep-LSTM-based fault detection method. A goodness-of-fit criterion is innovatively used to quantify the deviation between the baseline model and the newly monitored vibrations as opposed to the mean squared value of the LSTM residual used in many reported works. A railway suspension fault detection case is studied. Benchmark studies have shown that the deep-LSTM-based fault detection method performs better than the vanilla-LSTM-based and linear-autoregression-model-based methods. Using the goodness-of-fit criterion, railway suspension faults can be better detected than when using the mean squared value of the LSTM residual.
More Capable, Less Benevolent: Trust Perceptions of AI Systems across Societal Contexts
Authors: Novozhilova Ekaterina , Mays Kate , Paik Sejin , Katz James E.
Published: February 2024

Modern AI applications have caused broad societal implications across key public domains. While previous research primarily focuses on individual user perspectives regarding AI systems, this study expands our understanding to encompass general public perceptions. Through a survey (N = 1506), we examined public trust across various tasks within education, healthcare, and creative arts domains. The results show that participants vary in their trust across domains. Notably, AI systems’ abilities were evaluated higher than their benevolence across all domains. Demographic traits had less influence on trust in AI abilities and benevolence compared to technology-related factors. Specifically, participants with greater technological competence, AI familiarity, and knowledge viewed AI as more capable in all domains. These participants also perceived greater systems’ benevolence in healthcare and creative arts but not in education. We discuss the importance of considering public trust and its determinants in AI adoption.
Assessment of the Overall Lifetime Performance Index of Weibull Products in Multiple Production Lines
Authors: Wu Shu-Fei , Chiang Kuan-Yi
Published: February 2024

Process capability indices have been extensively employed to assess process performance in order to drive ongoing enhancements in quality and productivity, where the larger, the better for these lifetime performance indices. For multiple production lines, an overall lifetime performance index is proposed and the relationship between the overall lifetime performance index and the individual lifetime performance index is displayed. For products with lifetimes following the Weibull distribution for the ith production line, the maximum likelihood estimator and asymptotic distribution for the individual lifetime performance index were investigated so that the maximum likelihood estimator and asymptotic distribution for the overall lifetime performance index were also derived. Based on the pre-assigned target value of the overall lifetime performance index, the target value of an individual lifetime performance index could be determined. To test whether the overall lifetime performance index reached the target value was equivalent to testing whether the individual lifetime performance index reached the corresponding target value. The testing procedure based on the maximum likelihood estimator is given in this paper and the analysis of test power is displayed by figures. Finally, one practical example is given to illustrate the use of this testing algorithmic procedure to determine whether the overall production process was capable.
Adaptation of the Scaling Factor Based on the Success Rate in Differential Evolution
Authors: Stanovov Vladimir , Semenkin Eugene
Published: February 2024

Differential evolution is a popular heuristic black-box numerical optimization algorithm which is often used due to its simplicity and efficiency. Parameter adaptation is one of the main directions of study regarding the differential evolution algorithm. The main reason for this is that differential evolution is highly sensitive to the scaling factor and crossover rate parameters. In this study, a novel adaptation technique is proposed which uses the success rate to replace the popular success history-based adaptation for scaling factor tuning. In particular, the scaling factor is sampled with a Cauchy distribution, whose location parameter is set as an nth order root of the current success rate, i.e., the ratio of improved solutions to the current population size. The proposed technique is universal and can be applied to any differential evolution variant. Here it is tested with several state-of-the-art variants of differential evolution, and on two benchmark sets, CEC 2017 and CEC 2022. The performed experiments, which include modifications of algorithms developed by other authors, show that in many cases using the success rate to determine the scaling factor can be beneficial, especially with relatively small computational resource.
Summary-Sentence Level Hierarchical Supervision for Re-Ranking Model of Two-Stage Abstractive Summarization Framework
Authors: Yoo Eunseok , Kim Gyunyeop , Kang Sangwoo
Published: February 2024

Fine-tuning a pre-trained sequence-to-sequence-based language model has significantly advanced the field of abstractive summarization. However, the early models of abstractive summarization were limited by the gap between training and inference, and they did not fully utilize the potential of the language model. Recent studies have introduced a two-stage framework that allows the second-stage model to re-rank the candidate summary generated by the first-stage model, to resolve these limitations. In this study, we point out that the supervision method performed in the existing re-ranking model of the two-stage abstractive summarization framework cannot learn detailed and complex information of the data. In addition, we present the problem of positional bias in the existing encoder–decoder-based re-ranking model. To address these two limitations, this study proposes a hierarchical supervision method that jointly performs summary and sentence-level supervision. For sentence-level supervision, we designed two sentence-level loss functions: intra- and inter-intra-sentence ranking losses. Compared to the existing abstractive summarization model, the proposed method exhibited a performance improvement for both the CNN/DM and XSum datasets. The proposed model outperformed the baseline model under a few-shot setting.
Brexpiprazole Attenuates Aggression, Suicidality and Substance Use in Borderline Personality Disorder: A Case Series
Authors: Francis Benedict , Ganasan Vijay A/L , Sulaiman Abdul Rasyid Bin
Published: February 2024

Background: Borderline personality disorder (BPD) is a heterogeneous and highly comorbid disorder. Suicidality, aggression and substance abuse are common presentations of BPD. Our case series is the first to highlight the role of brexpiprazole in improving these symptoms in patients with BPD. Case presentation: We describe three cases demonstrating the role of brexpiprazole in improving BPD’s prominent features and comorbidities. All cases improved when brexpiprazole was added to their treatment regime. Case 1: A 26-year-old woman who was diagnosed with BPD and cyclothymia, presented to the psychiatric emergency unit with impulsive suicidal behaviour. Case 2: A 43-year-old woman suffering from BPD sought help due to her violent behaviour and emotional dysregulation. Case 3: A 22-year-old woman with underlying attention deficit and hyperactivity disorder, polysubstance use disorder and BPD presented with dysregulated emotions. Conclusions: Our case series provides anecdotal evidence of the potential role of brexpiprazole in attenuating suicidality, aggression and substance abuse in patients with BPD. We postulate that brexpiprazole’s high affinity for the 5HT1A/5HT2A receptors, coupled with its low intrinsic effect on the D2/D3 receptor system, is fundamental in its actions to stabilise the aberrant dopaminergic and serotonergic signalling in BPD. Future research should focus on well-designed clinical trials investigating the efficacy of brexpiprazole in patients with BPD.
Heat Dissipation of Open-Cell-Type Aluminum Foams Manufactured by Replication-Casting Process
Authors: Kim Jongmin , Ha Taekyu , Lee Youngki , Kang Byungil , Kim Youngjig
Published: February 2024

Open-cell-type aluminum foam demonstrates excellent heat dissipation owing to interconnected pores. In this study, open-cell-type aluminum foams with various pore sizes and porosities were fabricated using the replication-casting process, which is a relatively simple process. The porosity of the manufactured foams ranged from approximately 55% to 62%. To assess the heat dissipation of the manufactured foams, an air-cooling system was designed. The device could pass a controlled amount of air through the connected pores, simultaneously measuring pressure drop ∆P and temperature changes. It was confirmed that the open-cell-type aluminum foams exhibited a very high cooling rate in the initial cooling phase, and the thermal behavior is influenced by structural characteristics. At a porosity of 62%, the initial maximum cooling rate was measured to be 1.41 ℃/s for a pore size of 0.7~1.0 mm, and it was observed to significantly increase to 3.82 ℃/s for a pore size of 2.8~3.4 mm. Furthermore, for the same pore size, an increase in porosity resulted in an increase in the initial cooling rate. Lager pore sizes and higher porosities led to lower pressure drop ∆P and improved airflow, enhancing the cooling efficiency of open-cell-type aluminum foams.
Foam Pressure Mapping with Optimized Electrodes
Authors: Sundet Jake , Merrell Jake , Tree Maxwell , Christensen Trevor , Schultz Stephen
Published: February 2024

Nano-composite piezo-responsive foam (NCPF) is an inexpensive foam that can be used to measure a static load while still providing a comfortable interface. The purpose of this study was to create a modularized foam-based pressure measurement system. A measurement system was developed that uses an interdigitated electrode applied to the NCPF. Applied pressure changes the impedance of the NCPF, which, in turn, is converted into a voltage using a voltage divider. A modular measurement system is described that uses an ATtiny 1627 microcontroller to measure the pressure at nine electrodes. The nine electrode modules are controlled by an ESP32 microcontroller that aggregates the data and wirelessly transmits the data to a tablet. The modular system was demonstrated with 1008 individual electrodes. The characterization of the electrode combined with the NCPF is presented, along with optimization of the electrode geometry.
Komagataella phaffii as a Platform for Heterologous Expression of Enzymes Used for Industry
Authors: Khlebodarova Tamara M. , Bogacheva Natalia V. , Zadorozhny Andrey V. , Bryanskaya Alla V. , Vasilieva Asya R. , Chesnokov Danil O. , Pavlova Elena I. , Peltek Sergey E.
Published: February 2024

In the 1980s, Escherichia coli was the preferred host for heterologous protein expression owing to its capacity for rapid growth in complex media; well-studied genetics; rapid and direct transformation with foreign DNA; and easily scalable fermentation. Despite the relative ease of use of E. coli for achieving the high expression of many recombinant proteins, for some proteins, e.g., membrane proteins or proteins of eukaryotic origin, this approach can be rather ineffective. Another microorganism long-used and popular as an expression system is baker’s yeast, Saccharomyces cerevisiae. In spite of a number of obvious advantages of these yeasts as host cells, there are some limitations on their use as expression systems, for example, inefficient secretion, misfolding, hyperglycosylation, and aberrant proteolytic processing of proteins. Over the past decade, nontraditional yeast species have been adapted to the role of alternative hosts for the production of recombinant proteins, e.g., Komagataella phaffii, Yarrowia lipolytica, and Schizosaccharomyces pombe. These yeast species’ several physiological characteristics (that are different from those of S. cerevisiae), such as faster growth on cheap carbon sources and higher secretion capacity, make them practical alternative hosts for biotechnological purposes. Currently, the K. phaffii-based expression system is one of the most popular for the production of heterologous proteins. Along with the low secretion of endogenous proteins, K. phaffii efficiently produces and secretes heterologous proteins in high yields, thereby reducing the cost of purifying the latter. This review will discuss practical approaches and technological solutions for the efficient expression of recombinant proteins in K. phaffii, mainly based on the example of enzymes used for the feed industry.
Syringaldehyde Exhibits Antibacterial and Antioxidant Activities against Mycobacterium marinum Infection
Authors: Wen Da , Meng Chaoqun , Feng Yazhi , Shen Lin , Liu Yiyao , Sun Wei , Chen Guangxin , Wu Changxin
Published: February 2024

Tuberculosis (TB) is caused by infection with Mycobacterium tuberculosis (Mtb), which has a unique resistance to many antimicrobial agents. TB has emerged as a significant worldwide health issue because of the rise of multidrug-resistant strains causing drug-resistant TB (DR-TB). As a result, the development of new drugs or effective strategies is crucial for patients with TB. Mycobacterium marinum (Mm) and Mtb are both species of mycobacteria. In zebrafish, Mm proliferates and forms chronic granulomatous infections, which are similar to Mtb infections in lung tissue. Syringaldehyde (SA) is a member of the phenolic aldehyde family found in various plants. Here, we investigated its antioxidative and antibacterial properties in Mm-infected cells and zebrafish. Our results demonstrated that SA inhibits Mm-infected pulmonary epithelial cells and inhibits the proliferation of Mm in Mm-infected zebrafish, suggesting that SA provides an antibacterial effect during Mm infection. Further study demonstrated that supplementation with SA inhibits the production of malondialdehyde (MDA) and reactive oxygen species (ROS) and increases the levels of reduced glutathione (GSH) in Mm-infection-induced macrophages. SA inhibits the levels of MDA in Mm-infected zebrafish, suggesting that SA exerts antioxidative effects in vivo. Additionally, we found that SA promotes the expression of NRF2/HO-1/NQO-1 and the activation of the AMPK-α1/AKT/GSK-3β signaling pathway. In summary, our data demonstrated that SA exerts antioxidative and antibacterial effects during Mm infection both in vivo and in vitro and that the antioxidative effects of SA may be due to the regulation of NRF2/HO-1/NQO-1 and the AMPK-α1/AKT/GSK-3β signaling pathway.
Sulphuric Acid Digestion of Anatase Concentrate
Authors: da Silva Carolina Nogueira , Nazareth Liliani Pacheco Tavares , de Freitas Mônica Elizetti , Ladeira Ana Claudia Queiroz
Published: February 2024

The processing of anatase ores by sulphuric acid digestion is well known for its low titanium dissolution yields, which makes the process economically and technically unfeasible. Anatase is considered much less reactive than other forms of titanium such as ilmenite and rutile. Generally, to enhance its dissolution, thermal processes along with acid and/or alkaline leaching processes are necessary. Studies of direct sulphuric acid digestion are few and the reported yields of titanium dissolution are <48%. This study investigated the main parameters of sulphuric digestion of anatase such as temperature, anatase:acid ratio, and time of reaction. Dissolution of titanium of around 86% were obtained at relatively mild conditions such as, temperature at 220 °C, grain size of 62 µm, an anatase:sulphuric acid ratio of 1:2, and 4 h of reaction. A comprehensive characterization of the resulting material indicated a content of 56.5% of TiO2 and 15% iron oxide—the main impurity. It also contained silica, aluminum, phosphorus, calcium, and rare earth elements (REE) in concentrations that varied from 1.61% to 6.01%.
Advances for Triangular and Sandwich-Shaped All-Metal Aromatics
Authors: Wang Miaomiao , Wang Yanlan
Published: February 2024

Much experimental work has been contributed to all-metal σ, π and δ-aromaticity among transition metals, semimetallics and other metals in the past two decades. Before our focused investigations on the properties of triangular and sandwich-shaped all-metal aromatics, A. I. Boldyrev presented general discussions on the concepts of all-metal σ-aromaticity and σ-antiaromaticity for metallo-clusters. Schleyer illustrated that Nucleus-Independent Chemical Shifts (NICS) were among the most authoritative criteria for aromaticity. Ugalde discussed the earlier developments of all-metal aromatic compounds with all possible shapes. Besides the theoretical predictions, many stable all-metal aromatic trinuclear clusters have been isolated as the metallic analogues of either the σ-aromatic molecule’s [H3]+ ion or the π-aromatic molecule’s [C3H3]+ ion. Different from Hoffman’s opinion on all-metal aromaticity, triangular all-metal aromatics were found to hold great potential in applications in coordination chemistry, catalysis, and material science. Triangular all-metal aromatics, which were theoretically proved to conform to the Hückel (4n + 2) rule and possess the smallest aromatic ring, could also play roles as stable ligands during the formation of all-metal sandwiches. The triangular and sandwich-shaped all-metal aromatics have not yet been specifically summarized despite their diversity of existence, puissant developments and various interesting applications. These findings are different from the public opinion that all-metal aromatics would be limited to further applications due to their overstated difficulties in synthesis and uncertain stabilities. Our review will specifically focus on the summarization of theoretical predictions, feasible syntheses and isolations, and multiple applications of triangular and sandwich shaped all-metal aromatics. The appropriateness and necessities of this review will emphasize and disseminate their importance and applications forcefully and in a timely manner.
Functional Relevance of Extracellular Vesicle-Derived Long Non-Coding and Circular RNAs in Cancer Angiogenesis
Authors: Peña-Flores José A. , Muela-Campos Daniela , Guzmán-Medrano Rebeca , Enríquez-Espinoza Diego , González-Alvarado Karla
Published: February 2024

Extracellular vesicles (EVs) are defined as subcellular structures limited by a bilayer lipid membrane that function as important intercellular communication by transporting active biomolecules, such as proteins, amino acids, metabolites, and nucleic acids, including long non-coding RNAs (lncRNAs). These cargos can effectively be delivered to target cells and induce a highly variable response. LncRNAs are functional RNAs composed of at least 200 nucleotides that do not code for proteins. Nowadays, lncRNAs and circRNAs are known to play crucial roles in many biological processes, including a plethora of diseases including cancer. Growing evidence shows an active presence of lnc- and circRNAs in EVs, generating downstream responses that ultimately affect cancer progression by many mechanisms, including angiogenesis. Moreover, many studies have revealed that some tumor cells promote angiogenesis by secreting EVs, which endothelial cells can take up to induce new vessel formation. In this review, we aim to summarize the bioactive roles of EVs with lnc- and circRNAs as cargo and their effect on cancer angiogenesis. Also, we discuss future clinical strategies for cancer treatment based on current knowledge of circ- and lncRNA-EVs.
Point-of-Care Arterio-Venous Fistula Ultrasound in the Outpatient Hemodialysis Unit—A Survey on the Nurses’ Perspective
Authors: Grosu Iulia , Stirbu Oana , Schiller Adalbert , Gadalean Florica , Bob Flaviu
Published: February 2024

The preservation of complication-free arterio-venous fistulas (AVF) for long-term hemodialysis (HD) use is associated with better overall patient outcomes, which is why this is a current goal in any HD center. Point-of-care ultrasound (POCUS) for in-center AVF assessment has proven its benefits in the identification of vascular access (VA) complications and as an additional tool to avoid blind cannulation. The current study aims to assess the change in the HD nurses’ perceptions regarding AVF POCUS use in the HD center. The nursing staff anonymously answered a Likert scale questionnaire with five questions related to various aspects of AVF POCUS utility shortly after the technique had been implemented and at a 5-year follow-up. The results showed an overall positive attitude toward this method, both at implementation and at follow-up, with no statistically significant score changes for four out of the five items assessed. However, we found a statistically significant reduction in the nurses’ cannulation confidence scores at the 5-year follow-up (p < 0.01). Overall, AVF POCUS implementation is regarded as a useful tool, with major benefits both for the patient and for the medical team. The current study results aim to support the introduction of AVF POCUS assessment as a standard practice from the nursing staff’s viewpoint. This study was not registered.
Umbrella Review: Stress Levels, Sources of Stress, and Coping Mechanisms among Student Nurses
Authors: Labrague Leodoro J.
Published: February 2024

Prelicensure nursing students face significant stress from their education and clinical placements, highlighting the crucial need for the development of effective coping mechanisms with which to manage both academic and clinical responsibilities, ultimately enhancing the wellbeing and academic performance of these students. This umbrella review aims to evaluate and synthesize existing review articles that examine stress levels and coping mechanisms among student nurses during their education and training. Five databases (PsycINFO, PubMed, CINAHL, Scopus and Web of Science) were searched for review articles published from 2010 onwards. This review includes twelve articles, encompassing 189 studies. The review findings demonstrate that student nurses experience moderate-to-high levels of stress during their nurse education. Major sources of stress include academic demands, patient care responsibilities, and interactions with nursing staff and faculty. Commonly utilized coping skills involve problem-solving behaviors, transference, and maintaining an optimistic outlook. Given the adverse consequences of stress, nurse educators play a critical role in the development of strategies with which to reduce stress and enhance coping skills among student nurses. This study was not registered.
Bacteriophage Challenges in Industrial Processes: A Historical Unveiling and Future Outlook
Authors: Kamiński Bartosz , Paczesny Jan
Published: February 2024

Humans have used fermentation processes since the Neolithic period, mainly to produce beverages. The turning point occurred in the 1850s, when Louis Pasteur discovered that fermentation resulted from the metabolism of living microorganisms. This discovery led to the fast development of fermented food production. The importance of industrial processes based on fermentation significantly increased. Many branches of industry rely on the metabolisms of bacteria, for example, the dairy industry (cheese, milk, yogurts), pharmaceutical processes (insulin, vaccines, antibiotics), or the production of chemicals (acetone, butanol, acetic acid). These are the mass production processes involving a large financial outlay. That is why it is essential to minimize threats to production. One major threat affecting bacteria-based processes is bacteriophage infections, causing substantial economic losses. The first reported phage infections appeared in the 1930s, and companies still struggle to fight against phages. This review shows the cases of phage infections in industry and the most common methods used to prevent phage infections.