bluuebunny/crossref_metadata_2025 huggingface dataset:
Cross-Sectional Shape Optimization of Cylindrical Elastomer Spring for Sensitive Cargo Container
Authors: Kim Kyung-Sik , Kim Chul-Su
Published: February 2023

High-value sensitive cargoes are often damaged by low-frequency vibration and shock of containers during land and rail transport processes or mixed transport processes. Therefore, a dedicated cylindrical elastomer spring that absorbs vibration transmitted into the container has been developed. This study developed an optimal shape using a polyurethane material instead of the existing rubber spring. Elastomer spring requires an optimal design that satisfies the design target stiffness and strength by nonlinear finite element analysis. In order to develop an elastomer spring for a cargo container, the material constant was obtained by a hyperelastic behavior test of natural rubber, and based on this, the necessary optimal material constant of the new spring was predicted. In addition, nonlinear structural analysis was performed using ABAQUS to obtain the optimal shape of the spring, and optimal design was performed with I-SIGHT software. As a result of the sum of squared difference minimization with the comparison algorithm, it was found that the polyurethane material constant C10, C20, and C30 with the same characteristics as natural rubber was obtained. In addition, analysis using three optimization algorithms, Hooke–Jeeves algorithm, multi-island genetic algorithm, and optimal Latin hypercube, yielded a maximum principal strain of 0.244 of the spring obtained through the optimal cross-sectional shape design. It was found that this value was about 39% lower than the natural rubber spring in use. As a result of the compression load-displacement test of the actually developed product, it was confirmed that the correlation coefficient between the predicted value and the measured value was 0.928.
Radiometric Normalization Using a Pseudo−Invariant Polygon Features−Based Algorithm with Contemporaneous Sentinel−2A and Landsat−8 OLI Imagery
Authors: Chen Lei , Ma Ying , Lian Yi , Zhang Hu , Yu Yanmiao , Lin Yanzhen
Published: February 2023

As sensor parameters and atmospheric conditions create uncertainties for at−sensor radiation detection, radiometric consistency among satellite images is difficult to achieve. Relative radiometric normalization is a method that can improve multi−image consistency with accurate pseudo−invariant features (PIFs), especially over large areas or long time series satellite images. Although there are algorithms that manually or automatically select PIFs, the spatial mismatch of satellite images can affect PIF extraction, particularly with artificial pixels. To alleviate this problem, we proposed to use Landsat−8 OLI as the reference image and Sentinel−2A as the subject image, to apply pseudo−invariant features−based algorithms with polygon features through the single−band and multiple−band regression. Compared to pseudo−invariant point features, hyperspectral library, and histogram matching approaches, the results demonstrate the superiority of the proposed algorithms with correlation coefficients of 0.9948 and 0.9945, and an RMSE of 0.0097 and 0.0095 with multiple− and single−band regression, respectively. We also found more accurate linear fitting and better shape matching through band scattering and reflectance frequency analysis. The proposed algorithms are a significant improvement in radiometric normalization, within artificial pixels, achieving spectral signature consistency.
A Hybrid Heuristic Algorithm for Energy Management in Electricity Market with Demand Response and Distributed Generators
Authors: Albogamy Fahad R.
Published: February 2023

Optimal energy management trends are indispensable in improving the power grid’s reliability. However, power usage scheduling for energy management (EM) poses several challenges on a practical and technical level. This paper develops an energy consumption scheduler (ECS) to solve the power usage scheduling problem for optimal EM and overcome the major challenge in demand response (DR) implementation. This work aims to solve the power usage scheduling problem for EM to optimize utility bill, peak energy demand, and pollution emission while considering the varying pricing signal, distributed generators (DGs), household load, energy storage batteries, users, and EUC constraints. The ECS is based on a stochastic algorithm (genetic wind-driven optimization (GWDO) algorithm) because generation, DGs, demand, and energy price are stochastic and uncertain. The ECS based on the GWDO algorithm determines the optimal operation schedule of household appliances and batteries charge/discharge for a day time horizon. The developed model is analyzed by conducting simulations for two cases: home is not equipped with DGs, and home is equipped DGs in terms of utility bill, peak energy demand, and pollution emission. The simulation results validated the proposed model’s applicability to EM problems.
An Efficient Feature Augmentation and LSTM-Based Method to Predict Maritime Traffic Conditions
Authors: Lee Eunkyu , Khan Junaid , Son Woo-Ju , Kim Kyungsup
Published: February 2023

The recent emergence of futuristic ships is the result of advances in information and communication technology, big data, and artificial intelligence. They are generally autonomous, which has the potential to significantly improve safety and drastically reduce operating costs. However, the commercialization of Maritime Autonomous Surface Ships requires the development of appropriate technologies, including intelligent navigation systems, which involves the identification of the current maritime traffic conditions and the prediction of future maritime traffic conditions. This study aims to develop an algorithm that predicts future maritime traffic conditions using historical data, with the goal of enhancing the performance of autonomous ships. Using several datasets, we trained and validated an artificial intelligence model using long short-term memory and evaluated the performance by considering several features such as the maritime traffic volume, maritime traffic congestion fluctuation range, fluctuation rate, etc. The algorithm was able to identify features for predicting maritime traffic conditions. The obtained results indicated that the highest performance of the model with a valid loss of 0.0835 was observed under the scenario with all trends and predictions. The maximum values for 3, 6, 12, and 24 days and the congestion of the gate lines around the analysis point showed a significant effect on performance. The results of this study can be used to improve the performance of situation recognition systems in autonomous ships and can be applied to maritime traffic condition recognition technology for coastal ships that navigate more complex sea routes compared to ships navigating the ocean.
Periodic Solutions of Quasi-Monotone Semilinear Multidimensional Hyperbolic Systems
Authors: Mascia Corrado
Published: February 2023

This paper deals with the Cauchy problem for a class of first-order semilinear hyperbolic equations of the form ∂tfi+∑j=1dλij∂xjfi=Qi(f). where fi=fi(x,t) (i=1,⋯,n) and x=(x1,⋯,xd)∈IRd (n≥2,d≥1). Under assumption of the existence of a conserved quantity ∑iαifi for some α1,⋯,αn>0, of (strong) quasimonotonicity and an additional assumption on the speed vectors Λi=(λi1,⋯,λid)∈IRd—namely, span{Λj−Λk:j=1,⋯,n}=IRd for any k—it is proved that the set of constant steady state {f¯∈IRn:Q(f¯)=0} is asymptotically stable with respect to periodic perturbations, i.e., any initial data given by an periodic L1–perturbations of a constant steady state f¯ leads to a solution converging to another constant steady state g¯ (uniquely determined by the initial condition) as t→+∞.
Effect of Zr4+ on Lithium-Ion Conductivity of Garnet-Type Li5+xLa3(Nb2−xZrx)O12 Solid Electrolytes
Authors: Reis Shirley , Grosso Robson , Kosctiuk Juliane , Franchetti Marianne , Oliveira Francisca , Souza Adler , Gonin Cyrille , Freitas Heverson , Monteiro Robson , Parreira Luanna , Berton Marcos
Published: February 2023

Garnet-type structured electrolytes are considered a key technology for the next generation of lithium-ion batteries such as all-solid-state batteries. Cubic Garnet-type solid oxides with composition Li5+xLa3(Nb2−xZrx)O12 (x between 0 and 1.5) were synthesized by solid-state reaction and sintered by spark plasma sintering. Powder characterization indicates the formation of solid solution with high chemical homogeneity and spherical particles. High relative densities (>96%) were obtained by spark plasma sintering at 950 °C for 10 min and pressure application of 50 MPa. Although the formation of secondary phase La2Zr2O7 was identified by the X-ray diffraction patterns of Zr-doped pellets, it has been eliminated for x = 0.75 and 1 by conventional heat treatment at 850 °C for 1 h. High ionic conductivity values were attained for x ≥ 0.75, reaching a maximum value in the order of 10−4 S.cm−1 at 25 °C with activation energy of 0.38 eV. The results indicated that Zr4+ promoted significant increasing of the lithium-ion conductivity by lowering the activation energy.
“What Can ChatGPT Do?” Analyzing Early Reactions to the Innovative AI Chatbot on Twitter
Authors: Taecharungroj Viriya
Published: February 2023

In this study, the author collected tweets about ChatGPT, an innovative AI chatbot, in the first month after its launch. A total of 233,914 English tweets were analyzed using the latent Dirichlet allocation (LDA) topic modeling algorithm to answer the question “what can ChatGPT do?”. The results revealed three general topics: news, technology, and reactions. The author also identified five functional domains: creative writing, essay writing, prompt writing, code writing, and answering questions. The analysis also found that ChatGPT has the potential to impact technologies and humans in both positive and negative ways. In conclusion, the author outlines four key issues that need to be addressed as a result of this AI advancement: the evolution of jobs, a new technological landscape, the quest for artificial general intelligence, and the progress-ethics conundrum.
A Novel and Noninvasive Risk Assessment Score and Its Child-to-Adult Trajectories to Screen Subclinical Renal Damage in Middle Age
Authors: Chen Chen , Liu Guanzhi , Chu Chao , Zheng Wenling , Ma Qiong , Liao Yueyuan , Yan Yu , Sun Yue , Wang Dan , Mu Jianjun
Published: February 2023

This study aimed to develop a noninvasive, economical and effective subclinical renal damage (SRD) risk assessment tool to identify high-risk asymptomatic people from a large-scale population and improve current clinical SRD screening strategies. Based on the Hanzhong Adolescent Hypertension Cohort, SRD-associated variables were identified and the SRD risk assessment score model was established and further validated with machine learning algorithms. Longitudinal follow-up data were used to identify child-to-adult SRD risk score trajectories and to investigate the relationship between different trajectory groups and the incidence of SRD in middle age. Systolic blood pressure, diastolic blood pressure and body mass index were identified as SRD-associated variables. Based on these three variables, an SRD risk assessment score was developed, with excellent classification ability (AUC value of ROC curve: 0.778 for SRD estimation, 0.729 for 4-year SRD risk prediction), calibration (Hosmer—Lemeshow goodness-of-fit test p = 0.62 for SRD estimation, p = 0.34 for 4-year SRD risk prediction) and more potential clinical benefits. In addition, three child-to-adult SRD risk assessment score trajectories were identified: increasing, increasing-stable and stable. Further difference analysis and logistic regression analysis showed that these SRD risk assessment score trajectories were highly associated with the incidence of SRD in middle age. In brief, we constructed a novel and noninvasive SRD risk assessment tool with excellent performance to help identify high-risk asymptomatic people from a large-scale population and assist in SRD screening.
Infections of Tumor Prostheses: An Updated Review on Risk Factors, Microbiology, Diagnosis, and Treatment Strategies
Authors: Tsantes Andreas G. , Altsitzioglou Pavlos , Papadopoulos Dimitrios V. , Lorenzo Drago , Romanò Carlo Luca , Benzakour Thami , Tsukamoto Shinji , Errani Costantino , Angelini Andrea , Mavrogenis Andreas F.
Published: February 2023

Several causes contribute to the high infection rate in tumor prostheses, including extensive tissue dissection and patients’ immunosuppression due to the neoplastic disease. Most of these infections develop within the first 2 years following surgery with 70% of them occurring during the first year, while they are often associated with a low pathogen burden. The pathogenesis of infections in tumor prostheses is linked to bacteria developing in biofilms. Approximately half of them are caused by Staphylococcus spp., followed by Streptococcus spp., Enterococcus spp., and Enterobacteriaceae spp., while multiple pathogens may be isolated in up to 25% of the cases, with coagulase-negative Staphylococci (CoNS) and Enterococccus spp. being the most frequent pair. Although early detection and timely management are essential for complete resolution of these challenging infections, prompt diagnosis is problematic due to the highly varying clinical symptoms and the lack of specific preoperative and intraoperative diagnostic tests. Surgical management with one- or two-stage revision surgery is the mainstay for successful eradication of these infections. The recent advances in laboratory diagnostics and the development of biofilm-resistant prostheses over the past years have been areas of great interest, as research is now focused on prevention strategies. The aim of this study is to review and consolidate the current knowledge regarding the epidemiology, risk factors, microbiology, and diagnosis of infections of tumor prostheses, and to review the current concepts for their treatment and outcomes.
Exploring Genetic Interactions with Telomere Protection Gene pot1 in Fission Yeast
Authors: Ueno Masaru
Published: February 2023

The regulation of telomere length has a significant impact on cancer risk and aging in humans. Circular chromosomes are found in humans and are often unstable during mitosis, resulting in genome instability. Some types of cancer have a high frequency of a circular chromosome. Fission yeast is a good model for studying the formation and stability of circular chromosomes as deletion of pot1 (encoding a telomere protection protein) results in rapid telomere degradation and chromosome fusion. Pot1 binds to single-stranded telomere DNA and is conserved from fission yeast to humans. Loss of pot1 leads to viable strains in which all three fission yeast chromosomes become circular. In this review, I will introduce pot1 genetic interactions as these inform on processes such as the degradation of uncapped telomeres, chromosome fusion, and maintenance of circular chromosomes. Therefore, exploring genes that genetically interact with pot1 contributes to finding new genes and/or new functions of genes related to the maintenance of telomeres and/or circular chromosomes.
The Current Therapeutic Role of Chromatin Remodeling for the Prognosis and Treatment of Heart Failure
Authors: Kraus Lindsay , Beavens Brianna
Published: February 2023

Cardiovascular diseases are a major cause of death globally, with no cure to date. Many interventions have been studied and suggested, of which epigenetics and chromatin remodeling have been the most promising. Over the last decade, major advancements have been made in the field of chromatin remodeling, particularly for the treatment of heart failure, because of innovations in bioinformatics and gene therapy. Specifically, understanding changes to the chromatin architecture have been shown to alter cardiac disease progression via variations in genomic sequencing, targeting cardiac genes, using RNA molecules, and utilizing chromatin remodeler complexes. By understanding these chromatin remodeling mechanisms in an injured heart, treatments for heart failure have been suggested through individualized pharmaceutical interventions as well as biomarkers for major disease states. By understanding the current roles of chromatin remodeling in heart failure, a potential therapeutic approach may be discovered in the future.
An Improved Grey Wolf Optimizer and Its Application in Robot Path Planning
Authors: Ou Yun , Yin Pengfei , Mo Liping
Published: February 2023

This paper discusses a hybrid grey wolf optimizer utilizing a clone selection algorithm (pGWO-CSA) to overcome the disadvantages of a standard grey wolf optimizer (GWO), such as slow convergence speed, low accuracy in the single-peak function, and easily falling into local optimum in the multi-peak function and complex problems. The modifications of the proposed pGWO-CSA could be classified into the following three aspects. Firstly, a nonlinear function is used instead of a linear function for adjusting the iterative attenuation of the convergence factor to balance exploitation and exploration automatically. Then, an optimal α wolf is designed which will not be affected by the wolves β and δ with poor fitness in the position updating strategy; the second-best β wolf is designed, which will be affected by the low fitness value of the δ wolf. Finally, the cloning and super-mutation of the clonal selection algorithm (CSA) are introduced into GWO to enhance the ability to jump out of the local optimum. In the experimental part, 15 benchmark functions are selected to perform the function optimization tasks to reveal the performance of pGWO-CSA further. Due to the statistical analysis of the obtained experimental data, the pGWO-CSA is superior to these classical swarm intelligence algorithms, GWO, and related variants. Furthermore, in order to verify the applicability of the algorithm, it was applied to the robot path-planning problem and obtained excellent results.
The Effect of the Motivational Climate on Satisfaction with Physical Education in Secondary School Education: Mediation of Teacher Strategies in Maintaining Discipline
Authors: Bracho-Amador Clara Marina , Granero-Gallegos Antonio , Baena-Extremera Antonio , López-García Ginés David
Published: February 2023

The objective of this study was to analyze the mediating role of strategies to maintain classroom discipline between the motivational climate generated by the teacher and the students’ satisfaction with physical education classes. The research design was observational, descriptive, cross-sectional, and non-randomized. In total, 2147 secondary school physical education students participated (Mage = 15.05; SD = 1.45) (male = 1050; female = 1097). A structural equation model was calculated with latent variables controlled by the teacher’s sex and time of service and using the scales of the motivational climate, the teacher’s strategies for maintaining classroom discipline, and the students’ satisfaction with physical education classes. The results from the model highlight the importance of intrinsic strategies in maintaining discipline; these act as a mediator between the motivational climate towards learning and the students’ satisfaction with physical education classes. In addition, the findings reveal the influence of a performance-oriented climate in predicting boredom in a class when the teacher shows an indifference towards maintaining discipline.
The Double-Sided Effect of Empowering Leadership on Constructive Voice Behavior: Focusing on the Mediating Effects of Task Significance and Task Overload
Authors: Tian Xueqin , Chae Heesun
Published: February 2023

Focusing on job characteristics, this study examined the double-sided effect of empowering leadership on constructive voice behavior. We obtained and analyzed a total of 294 questionnaire responses from pairs of subordinates and supervisors in various industries in Korea. The results supported our hypotheses that task significance and task overload partially mediate the relationship between empowering leadership and constructive voice behavior. Specifically, we found that empowering leadership can promote constructive voice behavior by inducing a recognition of task significance and can suppress constructive voice behavior by causing task overload. These results confirm that empowering leadership indirectly influences constructive voice behavior through job characteristics. These findings have important theoretical and practical implications and highlight directions for future research.
In-Plane Shear Behavior of Unreinforced Masonry Wall Strengthened with Bamboo Fiber Textile-Reinforced Geopolymer Mortar
Authors: Libre Jr. Roneh Glenn D. , Leaño Jr. Julius L. , Lopez Luis Felipe , Cacanando Carlo Joseph D. , Promentilla Michael Angelo B. , Guades Ernesto J. , Garciano Lessandro Estelito O. , Ongpeng Jason Maximino C.
Published: February 2023

Old structures that are made of adobe or brick walls are usually unreinforced and not designed for lateral forces. In-plane loads applied to unreinforced masonry walls (URM) are the usual cause of damage and failure of old buildings. In this research, small unreinforced brick masonry wallettes, 350 mm × 350 mm and 50 mm in thickness, are strengthened using bamboo fiber textile and plastered to the face of the walls using short bamboo fiber-reinforced geopolymer mortar. The wallettes are subjected to diagonal shear tests as described by ASTM E519 to investigate the in-plane shear performance of the strengthening method. The performances of 5 wallettes strengthened on one-side with mortar only, 5 wallettes on both-sides with mortar only, 5 wallettes with textile plastered on one-side only, and another 5 wallettes with textile plastered on both-sides, are compared to 5 control specimens without any strengthening. It is observed that the wallettes strengthened on one side and both sides with textile yield an increase in shear of about 24% and 35% in average, respectively. Failure modes show that the usual failure for URM is running bond failure and for strengthened URM is columnar failure. The implications of the results can be used in developing textile-reinforced geopolymer mortar systems to strengthen URM walls.
Impact of Geometric and Electronic Factors on Selective Hydro-Deoxygenation of Guaiacol by Surface-Rich Metal/Silica Catalysts
Authors: Kretzschmar Nils , Busse Oliver , Seifert Markus
Published: February 2023

The selective production of hydrocarbons for the chemical industry from biogenic feedstock is a significant challenge when ensuring hydrocarbon and fuel supply, despite the heterogeneity of this feed. In this study, guaiacol, as a surrogate for complex lignin-based biomass resources, is converted by an inert silica carrier material with different d-metal impregnation (Mo, W, Re, Fe, Co, Ni, Cu, Pd, Ag) to reveal the reasons for different product selectivity to hydrogenated and deoxygenated hydrocarbon products. Hydrogen at 15 bar (gauge) and guaiacol are converted on metal/silica catalysts between 250 °C and 400 °C, while the physicochemical catalyst properties are characterized before and after catalytic tests. Volcano plots for the conversion, hydrogenation and deoxygenation products versus the d-band energy, surface atom distance and fouling properties reveal three groups of metals: (i) those that are less active and show high coking (Ag, α-Fe); (ii) those that show high activity for hydrogenation (β-Co, Ni, Pd) and, therefore, preferably yielded cyclohexane, cyclohexanol and 2-methoxycyclohexanol; (iii) those that preferably promote deoxygenation (Mo, W, Re, Cu) and, therefore, promoted the formation of phenol, benzene, anisole and catechol. The results are summarized in a pseudo van Krevelen diagram and interpreted as a complex interdependency from Sabatier’s principle of geometric correspondence of hexagonal metal surface for hydrogenation, electronic correspondence for the activation of hydrogen and electronic correspondence by oxophilicity for deoxygenation from the d-band center model.
Theoretical Study of Excited-State Dynamics of Hypercoordinated Carbon Molecule
Authors: Nag Probal , Vennapusa Sivaranjana Reddy
Published: February 2023

Structural and dynamical aspects of vibronically coupled S1 (dipole-allowed, “bright”) and S2 (dipole-forbidden, “dark”) states of hypercoordinated carbon molecule, 1,8-dimethoxy-9-dimethoxymethylanthracene monocation, are investigated. Potential energy surfaces are modeled within the linear vibronic coupling scheme. Quantum dynamics simulation show that the nuclear wavepacket initiated on the “bright” S1 state would move to “dark” S2 within a few femtoseconds via an accessible conical intersection. A dynamical equilibrium of wavepacket exchange between S1 and S2 is observed after 50 fs of propagation time. The activity of vibrational motions associated with the hypercoordinated carbon and C−H vibrations is analyzed using the reduced nuclear densities. Our findings illustrate that the excited-state nonadiabatic behavior has to be taken into account while analyzing the optical properties of this hypercoordinated carbon molecule.
Trends in Molecularly Imprinted Polymers (MIPs)-Based Plasmonic Sensors
Authors: Alberti Giancarla , Zanoni Camilla , Spina Stefano , Magnaghi Lisa , Biesuz Raffaela
Published: February 2023

In recent years, plasmonic sensors have been used in various fields ranging from environmental monitoring, pharmaceutical analysis, medical diagnosis, and food quality assessment to forensics. A significant amount of information on plasmonic sensors and their applications already exists and there is a continuing development of reliable, selective, sensitive, and low-cost sensors. Combining molecularly imprinting technology with plasmonic sensors is an increasingly timely and important challenge to obtain portable, easy-to-use, particularly selective devices helpful in detecting analytes at the trace level. This review proposes an overview of the applications of molecularly imprinted plasmonic chemosensors and biosensors, critically discussing the performances, pros, and cons of the more recently developed devices.
The Effectiveness of the Schroth Best Practice Program and Chêneau-Type Brace Treatment in Adolescent Idiopathic Scoliosis: Long-Term Follow-Up Evaluation Results
Authors: Kuru Çolak Tuğba , Akçay Burçin , Apti Adnan , Çolak İlker
Published: February 2023

Background: Although the number of studies showing the efficacy of conservative treatment in adolescent idiopathic scoliosis has increased, studies with long-term follow-up are very limited. The aim of this study was to present the long-term effects of a conservative management method including exercise and brace in adolescent idiopathic scoliosis patients. Methods: This retrospective cohort study included patients with idiopathic scoliosis who presented at our department and were followed up for at least 2 years after completing the treatment. The main outcome measurements were the Cobb angle and angle of trunk rotation (ATR). Results: The cohort participants were 90.4% female, with a mean age of 11 years and the maximum Cobb angle was mean 32.1°. The mean post-treatment follow-up period was 27.8 months (range 24–71 months). The improvements after treatment in mean maximum Cobb angle (p < 0.001) and ATR (p = 0.001) were statistically significant. At the end of treatment, the maximum Cobb angle was improved in 88.1% of the patients and worsened in 11.9% compared to baseline. In the long-term follow-up evaluations, 83.3% of the curvatures remained stable. Conclusions: The results of this study showed that moderate idiopathic scoliosis in growing adolescents can be successfully halted with appropriate conservative treatment and that long-term improvement is largely maintained.
Total Anomalous Pulmonary Venous Return in the Time of SARS-CoV-2—Case Report
Authors: Luca Alina-Costina , Curpăn Alexandrina-Ștefania , Manea Raluca-Stefania , Butnariu Lacramioara Ionela , Țarcă Elena , Starcea Iuliana Magdalena , Roșu Solange Tamara , Mîndru Dana Elena , Macsim Elena , Adumitrăchioaiei Heidrun , Pădureț Ioana Alexandra
Published: February 2023

The management of children with complex and life-threatening heart malformations became a clinical conundrum during the SARS-CoV-2 pandemic. The pathophysiological features of the new coronavirus infection have raised major dilemmas regarding the postoperative evolution of an infected patient, and the epidemiological limitations have tightened the criteria for selecting cases. We present the case of a newborn diagnosed with total anomalous pulmonary venous return (TAPVR) who underwent surgical repair of the defect with favorable outcome, despite a prior diagnosis of SARS-CoV-2 infection. We discuss the medical and surgical management of TAPVR, highlighting possible management difficulties brought by the SARS-CoV-2 pandemic.
Genome-Wide Identification and Expression Analysis of Calmodulin-Like Gene Family in Paspalums vaginatium Revealed Their Role in Response to Salt and Cold Stress
Authors: Yang Meizhen , Chen Jingjin , Liu Tingting , Xiang Leilei , Zhou Biao-Feng
Published: February 2023

The calmodulin-like (CML) family is an important calcium (Ca2+) sensor in plants and plays a pivotal role in the response to abiotic and biotic stresses. As one of the most salt-tolerant grass species, Paspalums vaginatum is resistant to multiple abiotic stresses, such as salt, cold, and drought. However, investigations of PvCML proteins in P. vaginatum have been limited. Based on the recently published P. vaginatum genome, we identified forty-nine PvCMLs and performed a comprehensive bioinformatics analysis of PvCMLs. The main results showed that the PvCMLs were unevenly distributed on all chromosomes and that the expansion of PvCMLs was shaped by tandem and segmental duplications. In addition, cis-acting element analysis, expression profiles, and qRT–PCR analysis revealed that PvCMLs were involved in the response to salt and cold stress. Most interestingly, we found evidence of a tandem gene cluster that independently evolved in P. vaginatum and may participate in cold resistance. In summary, our work provides important insight into how grass species are resistant to abiotic stresses such as salt and cold and could be the basis of further gene function research on CMLs in P. vaginatum.
Cost Savings of Expedited Care with Upfront Next-Generation Sequencing Testing versus Single-Gene Testing among Patients with Metastatic Non-Small Cell Lung Cancer Based on Current Canadian Practices
Authors: Sheffield Brandon S. , Eaton Kiefer , Emond Bruno , Lafeuille Marie-Hélène , Hilts Annalise , Lefebvre Patrick , Morrison Laura , Stevens Andrea L. , Ewara Emmanuel M. , Cheema Parneet
Published: February 2023

This study assessed the total costs of testing, including the estimated costs of delaying care, associated with next-generation sequencing (NGS) versus single-gene testing strategies among patients with newly diagnosed metastatic non-small cell lung cancer (mNSCLC) from a Canadian public payer perspective. A decision tree model considered testing for genomic alterations using tissue biopsy NGS or single-gene strategies following Canadian guideline recommendations. Inputs included prevalence of mNSCLC, the proportion that tested positive for each genomic alteration, rebiopsy rates, time to test results, testing/medical costs, and costs of delaying care based on literature, public data, and expert opinion. Among 1,000,000 hypothetical publicly insured adult Canadians (382 with mNSCLC), the proportion of patients that tested positive for a genomic alteration with an approved targeted therapy was 38.0% for NGS and 26.1% for single-gene strategies. The estimated mean time to appropriate targeted therapy initiation was 5.1 weeks for NGS and 9.2 weeks for single-gene strategies. Based on literature, each week of delayed care cost CAD 406, translating to total mean per-patient costs of CAD 3480 for NGS and CAD 5632 for single-gene strategies. NGS testing with mNSCLC in current Canadian practice resulted in more patients with an identified mutation, shorter time to appropriate targeted therapy initiation, and lower total testing costs compared to single-gene strategies.
Immunotherapy for Metastatic Non-Small Cell Lung Cancer: Therapeutic Advances and Biomarkers
Authors: Russano Marco , La Cava Giulia , Cortellini Alessio , Citarella Fabrizio , Galletti Alessandro , Di Fazio Giuseppina Rita , Santo Valentina , Brunetti Leonardo , Vendittelli Alessia , Fioroni Iacopo , Pantano Francesco , Tonini Giuseppe , Vincenzi Bruno
Published: February 2023

Immunotherapy has revolutionized the treatment paradigm of non-small cell lung cancer and improved patients’ prognosis. Immune checkpoint inhibitors have quickly become standard frontline treatment for metastatic non-oncogene addicted disease, either as a single agent or in combination strategies. However, only a few patients have long-term benefits, and most of them do not respond or develop progressive disease during treatment. Thus, the identification of reliable predictive and prognostic biomarkers remains crucial for patient selection and guiding therapeutic choices. In this review, we provide an overview of the current strategies, highlighting the main clinical challenges and novel potential biomarkers.
Tumors of the Digestive System: Comprehensive Review of Ancillary Testing and Biomarkers in the Era of Precision Medicine
Authors: Molnar Attila , Monroe Hunter , Basri Aydin Hasan , Arslan Mustafa Erdem , Lightle Andrea , Lee Hwajeong , El Jabbour Tony
Published: February 2023

Immunotherapy has remained at the vanguard of promising cancer therapeutic regimens due to its exceptionally high specificity for tumor cells and potential for significantly improved treatment-associated quality of life compared to other therapeutic approaches such as surgery and chemoradiation. This is especially true in the digestive system, where high rates of mutation give rise to a host of targetable tumor-specific antigens. Many patients, however, do not exhibit measurable improvements under immunotherapy due to intrinsic or acquired resistance, making predictive biomarkers necessary to determine which patients will benefit from this line of treatment. Many of these biomarkers are assessed empirically by pathologists according to nuanced scoring criteria and algorithms. This review serves to inform clinicians and pathologists of extant and promising upcoming biomarkers predictive of immunotherapeutic efficacy among digestive system malignancies and the ancillary testing required for interpretation by pathologists according to tumor site of origin.
Violaceous Lesions on the Leg: What Else Apart from Kaposi Sarcoma? Differential Diagnosis with a Narrative Review of the Literature
Authors: Pileri Alessandro , Orioni Gionathan , Zengarini Corrado , Grandi Vieri , Piraccini Bianca Maria , Gaspari Valeria
Published: February 2023

With this work, we aimed to review the principal benign and malignant tumors (including vascular, keratinocytic/epidermal, melanocytic, hematopoietic, and lymphoid origin), primarily affecting the leg’s skin. The lesions’ location can also help focus on a spectrum of differential diagnoses in clinical practice. All the diseases present the same clinical presentation characterized by erythematous to violaceous nodules. Despite the same clinical presentation, each disease’s prognostic outcome and therapeutic management can be somewhat different. Since clinical diagnosis may sometimes be challenging, histology and immunohistochemistry play a fundamental role in recognizing and staging these types of lesions. Molecular studies can help to determine the exact nature of lesions with no specific characteristics. Kaposi’s sarcoma is an angioproliferative neoplasm that typically occurs in the lower limbs and can enter into differential diagnosis with several other rarer skin diseases. The principal differential diagnosis concerns primary cutaneous lymphomas, of which mycosis fungoides represent the most frequent primary cutaneous T-cell lymphoma. Other rare forms include primary cutaneous B-cell lymphomas, which can be divided into indolent and aggressive forms, such as the primary cutaneous diffuse large B-cell lymphoma, leg type, and lymphomatoid papulomatosis (LyP). In the case of indolent lesions, skin-directed therapies, limited-field radiotherapy, and surgical approaches can be good options. At the same time, different management, with systemic chemotherapy and allogenic bone marrow transplant, is required with aggressive neoplasms, such as blastic plasmacytoid dendritic cell neoplasia or advanced mycosis fungoides. The dermatologist’s role can be crucial in recognizing such diseases and avoiding misdiagnosis, giving the pathologist the correct clinical information for an accurate diagnosis, and starting the suitable therapy.
Machine Learning Augmented Interpretation of Chest X-rays: A Systematic Review
Authors: Ahmad Hassan K. , Milne Michael R. , Buchlak Quinlan D. , Ektas Nalan , Sanderson Georgina , Chamtie Hadi , Karunasena Sajith , Chiang Jason , Holt Xavier , Tang Cyril H. M. , Seah Jarrel C. Y. , Bottrell Georgina , Esmaili Nazanin , Brotchie Peter , Jones Catherine
Published: February 2023

Limitations of the chest X-ray (CXR) have resulted in attempts to create machine learning systems to assist clinicians and improve interpretation accuracy. An understanding of the capabilities and limitations of modern machine learning systems is necessary for clinicians as these tools begin to permeate practice. This systematic review aimed to provide an overview of machine learning applications designed to facilitate CXR interpretation. A systematic search strategy was executed to identify research into machine learning algorithms capable of detecting >2 radiographic findings on CXRs published between January 2020 and September 2022. Model details and study characteristics, including risk of bias and quality, were summarized. Initially, 2248 articles were retrieved, with 46 included in the final review. Published models demonstrated strong standalone performance and were typically as accurate, or more accurate, than radiologists or non-radiologist clinicians. Multiple studies demonstrated an improvement in the clinical finding classification performance of clinicians when models acted as a diagnostic assistance device. Device performance was compared with that of clinicians in 30% of studies, while effects on clinical perception and diagnosis were evaluated in 19%. Only one study was prospectively run. On average, 128,662 images were used to train and validate models. Most classified less than eight clinical findings, while the three most comprehensive models classified 54, 72, and 124 findings. This review suggests that machine learning devices designed to facilitate CXR interpretation perform strongly, improve the detection performance of clinicians, and improve the efficiency of radiology workflow. Several limitations were identified, and clinician involvement and expertise will be key to driving the safe implementation of quality CXR machine learning systems.
Association of Tumor Volumetry with Postoperative Outcomes for Cervical Paraganglioma
Authors: Hoffmann-Wieker Carola Marie , Rebelo Artur , Moll Martin , Ronellenfitsch Ulrich , Rengier Fabian , Erhart Philipp , Böckler Dittmar , Ukkat Jörg
Published: February 2023

Objectives: To analyze the association of tumor volume with outcome after surgery for cervical paraganglioma. Materials and Methods: This retrospective study included consecutive patients undergoing surgery for cervical paraganglioma from 2009–2020. Outcomes were 30-day morbidity, mortality, cranial nerve injury, and stroke. Preoperative CT/MRI was used for tumor volumetry. An association between the volume and the outcomes was explored in univariate and multivariable analyses. A receiver operating characteristic (ROC) curve was plotted, and the area under the curve (AUC) was calculated. The study was conducted and reported according to the STROBE statement. Results: Volumetry was successful in 37/47 (78.8%) of included patients. A 30-day morbidity occurred in 13/47 (27.6%) patients with no mortality. Fifteen cranial nerve lesions occurred in eleven patients. The mean tumor volume was 6.92 cm3 in patients without and 15.89 cm3 in patients with complications (p = 0.035) and 7.64 cm3 in patients without and 16.28 cm3 in patients with cranial nerve injury (p = 0.05). Neither the volume nor Shamblin grade was significantly associated with complications on multivariable analysis. The AUC was 0.691, indicating a poor to fair performance of volumetry in predicting postoperative complications. Conclusions: Surgery for cervical paraganglioma bears a relevant morbidity with a particular risk of cranial nerve lesions. Tumor volume is associated with morbidity, and MRI/CT volumetry can be used for risk stratification.
Considering Both GLS and MD for a Prognostic Value in Non-ST-Segment Elevated Acute Coronary Artery Syndrome
Authors: Ionac Ioana , Lazăr Mihai-Andrei , Șoșdean Raluca , Văcărescu Cristina , Simonescu Marius , Luca Constantin-Tudor , Mornoș Cristian
Published: February 2023

Global longitudinal strain (GLS) and mechanical dispersion (MD), as determined by 2D speckle tracking echocardiography, have been demonstrated to be reliable indicators of prognosis in a variety of cardiovascular illnesses. There are not many papers that discuss the prognostic significance of GLS and MD in a population with non-ST-segment elevated acute coronary syndrome (NSTE-ACS). Our study objective was to examine the predictive utility of the novel GLS/MD two-dimensional strain index in NSTE-ACS patients. Before discharge and four to six weeks later, echocardiography was performed on 310 consecutive hospitalized patients with NSTE-ACS and effective percutaneous coronary intervention (PCI). Cardiac mortality, malignant ventricular arrhythmia, or readmission owing to heart failure or reinfarction were the major end points. A total of 109 patients (35.16%) experienced cardiac incidents during the follow-up period (34.7 ± 8 months). The GLS/MD index at discharge was determined to be the greatest independent predictor of composite result by receiver operating characteristic analysis. The ideal cut-off value was −0.229. GLS/MD was determined to be the top independent predictor of cardiac events by multivariate Cox regression analysis. Patients with an initial GLS/MD > −0.229 that deteriorated after four to six weeks had the worst prognosis for a composite outcome, readmission, and cardiac death according to a Kaplan–Meier analysis (all p < 0.001). In conclusion, the GLS/MD ratio is a strong indicator of clinical fate in NSTE-ACS patients, especially if it is accompanied by deterioration.
Routing Strategies for Isochronal-Evolution Random Matching Network
Authors: Lun Weicheng , Li Qun , Zhu Zhi , Zhang Can
Published: February 2023

In order to abstract away a network model from some real-world networks, such as navigation satellite networks and mobile call networks, we proposed an Isochronal-Evolution Random Matching Network (IERMN) model. An IERMN is a dynamic network that evolves isochronally and has a collection of edges that are pairwise disjoint at any point in time. We then investigated the traffic dynamics in IERMNs whose main research topic is packet transmission. When a vertex of an IERMN plans a path for a packet, it is permitted to delay the sending of the packet to make the path shorter. We designed a routing decision-making algorithm for vertices based on replanning. Since the IERMN has a specific topology, we developed two suitable routing strategies: the Least Delay Path with Minimum Hop (LDPMH) routing strategy and the Least Hop Path with Minimum Delay (LHPMD) routing strategy. An LDPMH is planned by a binary search tree and an LHPMD is planned by an ordered tree. The simulation results show that the LHPMD routing strategy outperformed the LDPMH routing strategy in terms of the critical packet generation rate, number of delivered packets, packet delivery ratio, and average posterior path lengths.
Improved Link Entropy with Dynamic Community Number Detection for Quantifying Significance of Edges in Complex Social Networks
Authors: Lubashevskiy Vasily , Ozaydin Seval Yurtcicek , Ozaydin Fatih
Published: February 2023

Discovering communities in complex networks is essential in performing analyses, such as dynamics of political fragmentation and echo chambers in social networks. In this work, we study the problem of quantifying the significance of edges in a complex network, and propose a significantly improved version of the Link Entropy method. Using Louvain, Leiden and Walktrap methods, our proposal detects the number of communities in each iteration on discovering the communities. Running experiments on various benchmark networks, we show that our proposed method outperforms the Link Entropy method in quantifying edge significance. Considering also the computational complexities and possible defects, we conclude that Leiden or Louvain algorithms are the best choice for community number detection in quantifying edge significance. We also discuss designing a new algorithm for not only discovering the number of communities, but also computing the community membership uncertainties.
Slack Resources and Export Intensity: New Empirical Evidence from Vietnam
Authors: Dinh Thi Thanh Binh , Tu Thuy Anh , Chu Thi Mai Phuong
Published: February 2023

The paper explored the effects of financial and human resource slacks on firms’ export intensity. Using longitudinal data of Vietnamese firms with a random effect model, the study found that financial slack had an inverted-U shaped effect; meanwhile, human resource slack had no consistently significant effect on firms’ export intensity. The empirical findings could have managerial practice implications at the firm level. Too few—or too many—slack resources are bad for export intensity. Therefore, firm managers need to consider the necessary level of redundancy for slack resources to avoid prodigality while doing business. This study contributed new insights to international business and slack literatures. First, our findings contributed to the international business literature. In classic internalization studies, it has generally been believed that firms with access to greater resources are more likely to exploit foreign markets. However, our research showed that, when there were too many slack resources, business activities in firms’ foreign markets, such as exports, could be reduced due to complacency among firm managers. Second, the research results contributed to literature on slack resources, providing a new insight on their effects on firms’ export intensity. Aside from linear or U-shaped effects, slack resources could have inverse U-shaped relationships with firms’ export intensity.
Implementation of the Critical Thinking Blended Apprenticeship Curricula and Findings per Discipline: Foreign Language Teaching
Authors: Ivancu Ovidiu , Kriaučiūnienė Roma , Poštič Svetozar
Published: February 2023

Critical thinking is a central element in higher education, designed to respond to authentic challenges that our society currently faces: the emergence and spread of fake news, disinformation, and manipulation. There is a consensus regarding CT’s importance and role in higher education. Nevertheless, CT skills are often implicitly mentioned and only occasionally included in university curricula explicitly. The present paper aims at analysing how CT can be measured and tested in higher education, and it proposes specific tasks designed to increase the use of CT within the theoretical framework defined by Peter Facione and Paul Elder. Updated course descriptions were tested, and students’ feedback was analysed and discussed. CT was measured by pre-questionnaires, mid-questionnaires, and post-questionnaires to establish the effectiveness of coherently implementing CT into the course descriptions. The survey includes answers to open questions to determine the suitability of the tasks proposed. The present research is part of the international Erasmus project “Critical Thinking for Successful Jobs”.