bluuebunny/crossref_metadata_2025 huggingface dataset:
WITHDRAWN: The role of students’ higher-order thinking skills in the relationship between academic achievements and machine learning using generative AI chatbots
Authors: Pellas Nikolaos
Published: July 2024

Students' perspectives on using generative artificial intelligence (AI) chatbots and machine learning are crucial in shaping the design, development, and implementation of their learning projects across various disciplines. Cognitive thinking, a key aspect of AI-related machine learning, aims to replicate human intelligence and behavior. However, the relation between cognitive thinking and knowledge acquisition is not always clear. Therefore, it is essential for students to engage in higher-order thinking, which allows them to critically analyze diverse viewpoints, assess their relevance, and understand the complex relationship between cognitive thinking and knowledge acquisition. This empirical study investigates the role of higher-order thinking skills, such as problem-solving, critical thinking, and creativity, in the relationship between academic achievements and attitudes toward machine learning technologies using generative AI chatbots. Four hundred sixteen undergraduate students (n = 416) from diverse academic backgrounds voluntarily took part in a project, in which they designed and developed generative AI chatbots in media and information literacy courses. The findings indicate that creativity mediated the relationship between academic achievements and attitudes toward machine learning, but its moderating impact was not significant. Problem-solving and critical thinking did not show significant mediating effects on attitudes toward machine learning, while they showed significant moderating effects in the connection between academic performance and attitudes toward machine learning. This study contributes by elucidating the interrelationships between students’ higher-order thinking skills, academic performance, and attitudes on the use of AI and machine learning technologies. By highlighting the mediating role of creativity and the moderating effects of problem-solving and critical thinking, this study offers a deeper understanding of how these skills shape students' perceptions of AI. The findings have significant implications for educational practices, suggesting that fostering higher-order thinking skills is crucial in preparing students to embrace AI and machine learning technologies.
A Dosimetric Comparison of Stereotactic Body Radiation Therapy for Lung Tumors: Plans of Gamma Knife, and Volumetric Modulated Arc Therapy, Dynamic Multileaf Collimator Plans based on Linear Accelerator
Authors: Duan Wenyue , Wu Huajian , Zhu Yanmei , Zhao Genghao , Zhang Chuanhao , Jiang Jianing , Fan Zhijun , Wang Zhe , Wang Ruoyu
Published: July 2024

Objective This study evaluates dosimetric differences in Stereotactic Body Radiation Therapy (SBRT) for lung tumors using plans of Gamma Knife, and Volumetric Modulated Arc Therapy (VMAT), Dynamic Multileaf Collimator (DMLC) plans based on Linear Accelerator, aiming to inform the reader of appropriate treatment strategy selection.
Methods Ten patients with 23 lung tumor lesions treated with SBRT at Zhongshan Hospital of Dalian University were analyzed. Plans of Gamma Knife, and VMAT, DMLC plans based on Linear Accelerator were created for each lesion, totaling 18 plans per type. Lesions were treated with 30-50 Gy in 5-10 fractions. Dosimetric parameters, including gradient index (GI), heterogeneity index (HI), conformity index (CI), and doses to the plan target volumes (PTVs), the gross tumor volumes (GTVs) and organs at risk (OARs) were compared.
Results Plans of Gamma Knife showed superior HI and GI, higher PTV and GTV doses, and reduced doses to the ipsilateral and contralateral lungs, esophagus, spinal cord, and heart compared to VMAT and DMLC plans (p< 0.05). However, Plans of Gamma Knife required longer delivery times. When comparing VMAT and DMLC plans，VMAT plans had shorter delivery times than DMLC plans, but required more monitor units (MUs). Additionally, DMLC plans delivered a lower mean dose to the ipsilateral lung compared to VMAT plans.
Conclusions Gamma Knife SBRT plans achieves steeper dose falloff and minimizes radiation to normal lung tissue compared to VMAT and DMLC plans, but with longer delivery times. VMAT and DMLC plans displayed similar dose distributions for lung SBRT.
Strategic Joining and Optimal Pricing in the Hybrid Cloud System with Risk-sensitive Service Requests
Authors: Zhao Yiqian , Zhu Sheng , Wang Jinting
Published: July 2024

We investigate a hybrid cloud system consisting of a private cloud and a public cloud along with highly and lowly risk-sensitive customers (denoted by H-and L-customers, respectively). Customers arrive in the system according to a Poisson process, and upon arrival, they decide to join a private cloud, or to join a hybrid cloud, or refuse to join any cloud based on a reward-cost structure. Specifically, for H-customers, if their expected benefit of joining a private cloud is negative, they will abandon the hybrid cloud system. For L-customers, they will compare the expected benefits of joining each of two clouds and then choose the cloud with higher benefit. Based on customers' strategic behavior, we explore the optimal decision-making problem in the hybrid cloud system. In virtue of a queueing-game approach, we analyze the equilibrium joining strategies of two types of customers. Moreover, taking into account various cooperation scenarios between customers, the optimal joining strategies of customers in different cases are derived. It is found that to maximize the utility for all customers, low risk-sensitive customers should be encouraged to join the public cloud. Furthermore, we investigate the optimal pricing issue for cloud services with subsidiary and discuss the revenue-maximization pricing of these two cloud resources numerically.
Medical Educator’s Attitudes and Experiences of Teaching Clinical Skills Online to Undergraduate Medical Students: Learning from COVID 19 and Future Implications
Authors: Qi Ziqiao , Aziz Wajeeha , Butler Ceri
Published: July 2024

Background: Traditional hands-on instruction of clinical skills in undergraduate medical education faced a paradigm shift with the emergence of COVID-19. Online teaching through virtual learning environments swiftly replaced traditional methods, necessitating an urgent reassessment of clinical skills education. Despite this, a knowledge gap persists regarding the effective delivery and integration of online clinical skills teaching within established medical curricula. This study investigated UK based medical educators and their experiences teaching clinical skills in an online environment enforced by social distancing. From these results we aimed to better understand how aspects of online teaching can be strategically employed within the current landscape of medical education to optimize practical skills acquisition.Methods: A cross-sectional study design employing a survey with closed and open-ended questions was utilized. The survey was hosted through the online survey platform EU Qualtrics and approved by the Education Leads Advisory Group of the Medical Schools Council for further distribution to medical educators. The results were analysed by frequency of answers with accompanying thematic analysis.Results: This study gathered responses from 22 medical educators of various seniority across 11 UK universities. Educators had low levels of knowledge regarding pre-COVID-19 online teaching. During the pandemic, sessions were often conducted remotely, with F2F teaching resuming under strict measures. Educators believed that online teaching, particularly for non-practical skills, offered engagement and flexibility. While the majority preferred a blended approach, there was hesitation in completely replacing F2F teaching. Educators expressed a strong belief in F2F as the most effective means of skills teaching, emphasizing the importance of supervision and hands-on practice. Despite uncertainties, educators acknowledged the benefits of online learning, emphasizing the need for proper resources and training for successful integration into clinical skills teaching.Conclusion: While there is preference for online teaching in non-practical skills, educators continued to express reservations about fully replacing F2F clinical skills teaching due to technological challenges and limited digital fluency. The overall preference among educators leaned towards a blended approaching utilising both modalities, harnessing benefits of online teaching such as flexibility while retaining the advantages of traditional methods.
A Summer Course in Cancer for High School Students – An Update on Lessons Taught and Lessons Learned
Authors: Solone Xzaviar K. , Chitre Siddhi , Font Laura Falceto , Pereira Kimberly N. Espinoza , Stofer Kathryn , Siemann Dietmar W
Published: July 2024

Background: Previous graduate students and postdoctoral associates from the University of Florida Health Cancer Center, in partnership with the University of Florida Student Science Training Program, implemented a cooperative learning curriculum, providing high school students with a broad overview of cancer topics over six weeks over the summer. However, the ongoing shift in education and training delivery initially necessitated by the COVID-19 pandemic has given rise to many discussions surrounding student autonomy and satisfaction. Furthermore, adapting hybrid and distance learning styles has notably influenced student-led collaboration and critical thinking skills. Here, we report on an update of experiences gleaned from the modified curriculum of this course to accommodate hybrid and cooperative teaching.
Methods: This pre-post longitudinal observational study evaluated modifications to a cancer biology and therapeutics course. Student performance was assessed using surveys administered before and after the course to determine effectiveness.
Results: Student performance tracked over a 7-year period indicated improved cumulative grade averages after modifying the previous curriculum. Post-assessment analysis revealed significant improvements in student benchmark understanding, notably in their ability to define cancer in one sentence (p = 0.0407), identify cancer therapies (p = 0.0040), and recognize cancer hallmarks (p < 0.0001). An increased trend in median response to the likelihood of pursuing cancer research (p = 0.8793) and the possibility of pursuing cancer research (p = 0.4874) were also observed, although not statistically significant. Moreover, feedback from participating students indicated that “the educational activities at the end of class (e.g., escape room, case studies)” and “learning about cancer and getting to work in groups…” the curriculum fostered a positive educational learning environment.
Conclusion: Students generally held a positive perception of the course. Post-assessment analysis revealed decreasing trends in students' perception of course difficulty compared to their expectations in the pre-assessment. Constructive feedback centered around fostering collaborative environments, with an observed increase in learner autonomy towards the end of the course, as evidenced by students' growing comfort in leading group case studies and conducting research on topics. We hope that future course directors engage actively and incorporate practical clinical examples for students, especially when introducing or discussing complex issues like cancer.
Cooperative supporting effect of intermediate bridge and inner dump on slope in adjacent open-pit mining area
Authors: Wang Dong , Liang Zuchao , Li Guanghe , Xv Yongchao , Wang Jingwei , Zhao Lichun , Li Yunguang
Published: July 2024

To solve the problem of dynamic demolition of intermediate bridges, study on the calculation method of slope stability under the synergistic support effect of the intermediate bridge and the inner dump. On the basis of constructing the mechanical model of the intermediate bridge and the inner dump, using Mohr-Coulomb shear strength theory and soil pressure theory, the mathematical expressions of the variation of the supporting effect and the three-dimensional mechanical effect of the internal dump during the demolition of the intermediate bridge are derived, and the quantitative relationship between the dumping height and the demolition length of the intermediate bridge is obtained. Based on the idea of equivalence, a two-dimensional equivalent method for synergistic mechanical effect of inner dump is proposed, the influence of the height of the inner discharge pressure on the equivalent physical and mechanical parameters is revealed theoretically. The method is applied to Zahannaoer open-pit coal mine, the intermediate bridge demolition project was designed in stages and the slope stability of each stage was analyzed and verified. The results can lay a theoretical and application foundation for dynamic demolition design and engineering implementation of intermediate bridge in open-pit coal mine.
Effect of surfactant compounding on emulsion stability and acid-base resistance using optical tweezers
Authors: Shang Xiaoxiao , Jin Huaizhou , Tian Zhen , Ma Qifei , Wang Weihonng , Jin Shangzhong
Published: July 2024

In industries, emulsions must adapt to various acid-base environments, making it crucial to study their properties and acid-base resistance. We prepared an oil-in-water (O/W) emulsion by adding oleic acid and polyether amine D-230 to water, with tetradecane as the oil phase. The stability of the emulsion was assessed by measuring the interaction forces between droplets using optical tweezers. Our results demonstrated that the amphoteric surfactant could significantly improve the stability of the emulsion. The results show that in the presence of amphoteric surfactant, the maximum repulsion force between droplets can reach 18.9 pN and ζ- potential is -65.16 mV, while in the absence of surfactant, the maximum repulsion is only 1.2 pN and ζ- potential is -25.54 mV. Further stabilization was achieved with the addition of 10 mmol/L anionic surfactant sodium dodecyl sulfate (SDS) or 1 mmol/L cationic surfactant cetyltrimethyl ammonium bromide (CTAB). With SDS, the maximum repulsive force was 40.8 pN and ζ- potential was 132.44 mV at the drop distance of 1.93 µm. With CTAB, the maximum repulsive force of 48.2 pN and ζ- potential of + 42.28 mV were measured at the drop distance of 3.12 µm, indicating that adding surfactants can effectively improve the stability of the emulsion. At the same pH value, the combined emulsion can measure the interaction force at a longer drop distance than the emulsion containing only amphoteric surfactants. When pH = 8, the interaction force of 1 mmol/L CTAB and 10 mmol/L SDS can be measured at the drop distance of 2.51 µm and 2.78 µm, respectively. Only the emulsion containing amphoteric surfactant can be measured at the drop distance of 2.26 µm, and the results show that it can enhance the acid-base resistance of the emulsion. These emulsions can be used to make good anticorrosive coatings and improve various properties of the original coatings.
Development and Validation of Deep Learning Model for Intravascular Ultrasound Image Segmentation
Authors: Kim Hyeonmin , Lee June-Goo , Jeong Gyu-Jun , Lee Geunyoung , Min Hyunseok , Cho Hyungjoo , Min Daegyu , Lee Seung-Whan , Cho Jun Hwan , Cho Sungsoo , Kang Soo-Jin
Published: July 2024

Aims. This study was conducted to develop and validate a deep learning model for delineating intravascular ultrasound (IVUS) images of coronary arteries.
Materials and Methods. Using atotal of 1240 40-MHz IVUS pullbacks with 191,407 frames, the model for lumen and external elastic membrane (EEM) segmentation was developed. Both frame- and vessel-level performances and clinical impact of the model on 3-year cardiovascular events were evaluated in the independent data sets.
Results. In the test set, the Dice similarity coefficients (DSC) were 0.966 ± 0.025 and 0.982 ± 0.017 for the lumen and EEM, respectively. Even at sites of extensive attenuation, the frame-level performance was excellent (DSCs > 0.96 for the lumen and EEM). The model (vs. the expert) showed a better temporal consistency for contouring the EEM. The agreement between the model- vs. the expert-derived cross-sectional and volumetric measurements was good in the independent retrospective cohort (all, intra-class coefficients > 0.94). The model-derived PAV>52.5% (area under curve 0.70, sensitivity 71% and specificity 67%) and plaque burden at the MLA site (area under curve 0.72, sensitivity 72% and specificity 66%) best predicted 3-year cardiac death and nonculprit-related target vessel revascularization, respectively. In the stented segment, the DSCs > 0.96 for contouring lumen and EEM were achieved by fine-tuning. Applied to the 60-MHz IVUS images, the DSCs were > 0.97. In the external cohort with 45-MHz IVUS, the DSCs were > 0.96.
Conclusion. The deep learning model accurately delineated vascular geometry, which may be cost-saving and support clinical decision-making.
Empagliflozin enhances cisplatin activity in chemo-resistant EJ138 bladder cancer cells: The importance of anti-diabetic medications in cancer treatment
Authors: Shariati Saeedeh , Mohtadi Shokooh , Molavinia Shahrzad , Salehcheh Maryam , Dayer Dian , Farzaneh Maryam
Published: July 2024

Background
Anti-diabetic medications has been found to reduce chemotherapy resistance. This study sought to investigate the role of Empagliflozin (Empa) as an anti-diabetic medication in reversing Cisplatin (Cis) resistance in EJ138 bladder cancer (BC) cells.
Materials and Methods
The EJ138 cell line was cultured and divided into four groups: control, Cis-treated, Empa-treated, and Cis + Empa-treated groups. The effects of Cis and/or Empa on cell viability were determined using the MTT technique. The level of ROS produced by cells was evaluated using the green fluorescent dye dichloro-dihydro fluorescein (DCF). The expression of proteins involved in glucose transport, proliferation, apoptosis, cell cycle control, and invasion was evaluated by Western blotting. The Data were analyzed using GraphPad prism software and a One-way ANOVA test. All experiments were repeated three times. Data were presented as Mean ± SEM. The significant difference between groups was calculated based on P < 0.05.
Results
IC50 was calculated equal to 16 mM for Cis and 72 µg/ml for Empa. Treatment with Cis caused a significant increase in SGLT2 expression (p < 0.001). Conversely, the group treated with 72 µg/ml Empa showed a significant decrease in SGLT2 compared with the control group (P < 0.001). ROS generation was significantly elevated after treatment with Cis, Empa, and their combination (P < 0.001). Treatment with Cis and/or Empa downregulated AKT, PI3K, mTOR, Bax, MMP-2, and MMP-9 expression (P < 0.001). However, Bcl2, P21, and P53 expression showed a significant increase following Cis and/or Empa treatment (P < 0.001). Protein expression differed significantly across the Cis-treated group and all other groups.
Conclusion
Empa exhibits beneficial anti-cancer activity against EJ138 cells. Empa boosts the anti-cancer activity of Cis in EJ138 BC cancer cells through SGLT2 inhibition.
Evaluation of polyclonal antibodies raised in rabbit against Dengue NS1 antigen
Authors: Abraham Philip Raj , Devaraju Panneer , Bharath L. , Prasad Eiriene , Dhotre Akash , Kumar Ashwani
Published: July 2024

The vector-borne disease, dengue is caused by the dengue virus (DENV) and the illness spread by Aedes mosquitoes like AedesaegyptiandAedesalbopictus.In the absence of antiviral drugs and vaccines, dengue prevention is centred on mosquito vector control. Current methods of dengue detection suffer from limitations. The non-structural protein-1 (NS1) antigen in secretory form is being employed as a diagnostic marker to identify dengue infection andAedes vector infections. This method involves the use of commercial dengue NS1 ELISA kits. In the present study, we have evaluated Rabbit Polyclonal Antibodies raised against the Dengue NS1 antigen (RPAD). The RPAD were tested against commercial recombinant dengue virus-2 NS1 antigen (rDNS1Ag) by standardized ELISA and Western Blotting. Further, the sensitivity of RPAD was checked against the NS1 antigens of different serotypes of DENV. The specificity of RPAD towards the NS1 antigens of other flavivirus was also tested.We found that the RPAD is specific and sensitive for detecting rDNS1Ag of all serotypes and it can be explored to detect DENV infection in the mosquito vectors collected from the field during the dengue outbreaks.
Root windows – a tool to study relationships between rhizosphere processes, soil-microbial communities, and plant performance under field conditions?
Authors: Neumann Günter , Sommermann Loreen , Behr Jan Helge , Moradtalab Narges , Windisch Saskia , Chowdhury Soumitra Paul , Rothballer Michael , Babin Doreen , Smalla Kornelia , Maccario Lorrie , Ludewig Uwe , Geistlinger Jörg , Grosch Rita
Published: July 2024

Background and Aims:
Root observation windows (RW) installed in the field provide a tool for non-destructive monitoring of root development and rhizosphere processes. However, the highly invasive installation process, requiring cutting of soil profiles, may affect plant development and finally the outcome of the experiments. This study systematically compares plant development with and without RW installation.
Methods
Using the location of a long-term field experiment, the responses of winter wheat to different intensities of tillage, N-fertilization, and use of fungicides were compared for plants grown along root windows and in undisturbed control plots. The sampling was performed during vegetative growth, six weeks after RW-installation with comparisons of shoot and root biomass, root length, mineral nutritional status, expression of stress-related genes, and the composition of microbial communities reflecting the conditions in the rhizosphere (RH).
Results
The presence of RW did not affect most of the parameters analyzed. As an exception, a range of mineral nutrients (K, Mg, Ca, Cu, Mn) was increased in RW plants most probably due to RW location in the border rows of the experimental plots with reduced inter-plant competition for nutrient uptake. By contrast, N-fertilization intensity and fungicide use affected plant biomass, root growth, and fungal communities. Tillage intensity mainly affected the composition of RH-microbial communities and the expression of stress-related genes in the leaf tissue.
Conclusion
The results suggest only a limited influence on plant performance six weeks after RW installation with plant responses and experimental results comparable to undisturbed controls.
Study of a novol cyclic loading-unloading constitutive model of rock based on a developed discrete element program
Authors: Chen Yu , Deng Zinuo , Huang Linchong , Wang Yixian , Lin Hang , Sun Wei
Published: July 2024

This study has developed a novel discrete element computation program that enhances the efficiency of model generation by improving internal algorithms and offers high editability. Although existing constitutive models in commercial software are able to simulate rock material, they exhibit noticeable limitations in capturing the cyclic loading-unloading mechanical characteristics of materials. In this research, a cyclic loading-unloading constitutive model that considers damage was developed for rock materials. The numerical outcomes were compared and analyzed with experimental data. Research on three different types of rock demonstrates a high degree of concordance between numerical simulation results and laboratory experiments. The developed constitutive models effectively capture the plastic failure process of rock material under cyclic loading, with stress-strain curves exhibiting hysteresis loops. Compared to traditional discrete element software employing parallel bonding models, this program provides more accurate results, making it more suitable for simulating cyclic loading-unloading performance.
Chlamydia psittaci inhibits the production of reactive oxygen species in human neutrophils by inhibiting NADPH oxidase through the p38/ERK signaling pathway
Authors: Yu maoying , Tang Yuanyuan , Li Weiwei , He zhangping , Liu Jie , Yang Hongyu , Guo Ningyuan , Wang Chuan , Wu Yimou
Published: July 2024

Chlamydia psittaci (C. psittaci) is an obligate intracellular bacterium that replicates in neutrophils, a significant producer of reactive oxygen species(ROS). However, the effect of ROS on C. psittaci infection and whether C. psittaci regulates ROS production in neutrophils is unclear. When C. psittaci infects neutrophils, it can induce the production of a small amount of ROS, affect the assembly of NADPH oxidase through p38/ERK signaling pathways, and actively block the ROS produced by PMA-stimulated neutrophils. Importantly, this study may provide new insights into the molecular pathogenesis and immune escape of C. psittaci.
Lutein protection against doxorubicin-induced liver damage in male Wistar rat is associated with inhibition of oxido-inflammatory stress and modulation of Beclin-1/mTOR activities
Authors: Asiwe Jerome Ndudi , Yovwi Godwin D. , Alawode Mercy Oluwalani , Isola Theodora , Umukoro Emuesiri Kohworho , Igbokwe Vincent Ugochukwu , Asiwe Nicholas
Published: July 2024

A wide range of clinical applications are reported for doxorubicin (DOX), yet both people and research animals experience substantial tissue damage. However, the protective mechanism of lutein, a natural carotenoid against doxorubicin associated liver toxicity has not been fully studied. Therefore, the aim of this study is to investigate the protective mechanism of lutein in doxorubicin-induced liver damage. Twenty male Wistar rats were randomly assigned to four groups and treated as follows: Group 1 was administered 10 ml/kg body weight of distilled water intraperitoneally for a duration of 28 days. Group 2 was administered Doxorubicin (15 mg/kg body weight) intraperitoneally for three days in a row. Group 3 was administered intraperitoneal injections of Lutein (40 mg/kg body weight) daily for 28 days, and Group 4 was administered intraperitoneal injections of Lutein (40 mg/kg body weight) daily for 25 days and three days in a row of injections of Doxorubicin (15 mg/kg body weight). Our results showed that lutein reduced levels of AST, ALT, ALP, LDH, MDA, nitrite, beclin-1, caspase-3, IL-6 as well as TNF-α against the increase caused by doxorubicin. GSH, SOD, GST, catalase, mTOR as well as Bcl-2 were markedly increased by lutein against the harmful effect of doxorubicin. Moreso, lutein restored normal histoarchitecture as well as reduced fibrosis. In conclusion, Lutein protection against doxorubicin-induced liver damage in male Wistar rat is associated with inhibition of oxidative stress, pro-inflammatory reactions and modulation of Beclin-1/mTOR activities
Application of modified acetylene carbon black with different particle sizes in sodium-ion batteries
Authors: Zheng Weiyue , Tang Yi , Yang Kejia , Li Jiali , Qi Linhao , Yue Chenxi , Chen HuaYu , Chen Jian
Published: July 2024

Currently, the anode of sodium-ion battery is mainly made of carbon material, and the carbon black made of acetylene has the advantages of low cost, high purity and simple process, etc. The particle size of carbon black has a great influence on the storage capacity of sodium ions, in this study, carbon black particles with different particle sizes were prepared by chemical vapour deposition method by changing the temperature and gas flow rate, and the effects of the temperature and the gas flow rate on the size of the carbon black were investigated, and the effect of the particle size of carbon black on the performance of the battery was studied. The effect of temperature and gas flow rate on the particle size of carbon black was investigated, and then the effect of the particle size of carbon black on the battery performance was studied. The larger the gas flow rate of acetylene, the smaller the particle size of carbon black generated. The carbon black CB-3 generated by holding at 900 ℃ and an acetylene flow rate of 300 mL/min for 30 min kept the capacity of 112.36 mAh/g after 180 cycles, and the specific capacity of the first discharge was 414.66 mAh/g, and the reversible specific capacity at 2 A/g still had 92.12 mA/g. This work helps to provide new ideas for research in enhancing the electrochemical performance of sodium-ion battery materials.
Vessel Trajectory Prediction at Inner Harbor based on Deep Learning using AIS Data
Authors: Shin Gilho , Yang Hyun
Published: July 2024

This study proposes a novel approach for predicting vessel trajectories in the inner harbor of Busan Port using Automatic Identification System (AIS) data and deep learning techniques. Linear interpolation was applied to address unequal time intervals and limited data. Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Bidirectional Long Short-Term Memory (Bi-LSTM), Gated Recurrent Unit (GRU), and Bidirectional Gated Recurrent Unit (Bi-GRU) models were trained and evaluated, with LSTM achieving the best performance. The study also identified the critical prediction area for Vessel Traffic Service Operator (VTSO). The proposed method can contribute to enhancing safety and efficiency of vessel traffic management in complex port environments.
Efficient Multi-Agent Reinforcement Learning HVAC Power Consumption Optimization
Authors: Miao Chenyang , Cui Yunduan , Li Huiyun , Wu Xinyu
Published: July 2024

Intelligent and energy-efficient heating, ventilation, and air conditioning (HVAC) system plays an important role in reducing energy consumption and protecting our environment. In this work, we focus on exploring suitable power optimization strategies using reinforcement learning (RL) without relying on human prior knowledge. A novel RL approach, multi-stabilization network(MADDPG-MSN) is proposed to tackle the sample-efficiency issue of current RL-based approaches for HVAC systems. Employing the multi-stabilization network trick, MADDPG-MSN efficiently learns to balance temperature control and power consumption with a limited number of interactions. Evaluated by the simulated data center scenario, it reduced 28% powerusage without compromising temperature control capability compared with the traditional model-predictive controller. In the real-world air conditioner testing, it demonstrated superior control performances than the built-in controller with 35% less power consumption and 21% smaller standard deviation of the indoor temperature after 72 hours’ learning. These results demonstrate the superior effectiveness and practicality of MADDPG-MSN in HVAC power consumption optimization, expanding the potential of RL as an emerging direction to more energy-saving systems.
Prediction ability in bilingual individuals: An eye tracking study with younger and older adults
Authors: Ribu Ingeborg Sophie , Simonsen Hanne Gram , Norvik Monica , Lehtonen Minna , Murstad Jeanett , Theimann Ane , Nygreen Thomas , Goral Mira
Published: July 2024

Studies with monolingual speakers show that people predict upcoming linguistic elements during sentence processing. Linguistic prediction behavior has been found to be less consistent in studies with bilingual individuals performing in their non-native language and in neurotypical older monolingual adults. The present study utilized an eye-tracking paradigm to investigate whether bilingual younger and older neurotypical individuals predict upcoming nouns in sentences that include constraining verbs, and if they do so both in their first language (L1) and in their second language (L2). Data was analyzed from 44 Norwegian-English proficient bilingual adults (27 younger and 17 older adults) who completed the eye-tracking experiment in each of the two languages, as well as cognitive and linguistic tests. The results demonstrated similar prediction abilities in L1 and L2 for both the younger and older participants. Older adults were slower than younger adults, although they did look to the target images only at the end of the predictive window. Participants' working memory span, language proficiency, and the cognate status of the stimuli did not explain prediction performance. The study adds to the relatively sparse existing data on prediction abilities in bilingual people and in older individuals.
Is The Serum Creatinine / Alanine Transaminase Ratio A Predictor Of Mortality In Elderly Patients With Acute Ischemic Stroke?
Authors: Yılmaz Özgür , Yılmaz Ayşe , Soylu Veysel Garani , Taşkın Öztürk , Demir Ufuk , Kurada Gizem , Tanyıldızı Büşra , Doğanay Zahide
Published: July 2024

Background
This study by aiming to investigate the relationship of serum creatinine/alanine transaminase ratio(sCr/Alt) with mortality of patients aged 85 and over treated for acute ischemic stroke
Methods
Medical records of patients aged 85 and over treated for acute ischemic stroke between January-2017 and October-2021 were evaluated. A total of 189 patients over the age of 85 with a diagnosis of cerebrovascular disease were included in the study.
Results
When we evaluated the 28-day mortality prediction performance of the variables, ALT(p < 0.001), serum creatinine(p < 0.001), serum creatinine/alanine transaminase(p < 0.001) were significantly higher in the mortal cases than in the other patients. We evaluated the 28-day mortality prediction performances of the variables, the sCr/Alt ratio was found to have 85.4% sensitivity and 84.8% specificity.
Conclusion
sCr/Alt value is a more valuable marker compared to NIHSS, APACHE II and SAPS II values which are mortality markers in advanced elderly patients with acute ischemic stroke in intensive care.
Hidden Dynamics of a Self-excited SD Oscillator
Authors: Bandi Dinesh , TAMADAPU GANESH
Published: July 2024

The present study explores the nonlinear dynamics of a self-excited smooth and discontinuous (SD) oscillator with geometric nonlinearity at the switching surface. Using a novel framework called hidden dynamics, introduced by Jeffrey, the research addresses the challenge posed by dry friction oscillators where the static friction coefficient is greater than the kinetic friction coefficient, which is ignored in Filippov’s theory. By modelling the belt friction in the SD oscillator as Coulomb friction, we investigate the consequences of the discontinuity in the friction model. The sliding regions were determined analytically and validated through numerical simulations. The system's behaviour is analyzed through the examination of bifurcation diagrams and phase portraits, and a comparison is conducted with Filippov’s theory. Some interesting bifurcation phenomena are highlighted, including a novel phenomenon involving the collision and merging of two degenerate boundaries and the bifurcation of a sliding homoclinic orbit to a saddle. Furthermore, the system's response to harmonic excitation is analyzed, wherein the oscillator displays stick-slip limit cycles, pure slip limit cycles and the emergence of chaotic solutions through periodic doubling bifurcation.
The influence of body posture on facial expression perception in Autism
Authors: Finn Abigail , Shah Punit , Rosa Stephan de la , Teufel Christoph , Hagen Elisabeth von dem
Published: July 2024

Facial expression perception is influenced by body posture, with perception biased toward the body emotion. Previous research has suggested that the magnitude of this biasing influence of body posture is driven by individual differences in the precision of facial expression representations underlying discrimination abilities, where lower precision leads to a greater influence of body posture. It is unclear however whether similar mechanisms might drive the influence of contextual cues in Autism, which is often characterised by reduced facial expression discrimination abilities. Here, we addressed this question by using online psychophysical methods to determine the precision of isolated face and body expression representations, as well as the influence of body posture on facial expression perception, in autistic and non-autistic adults. Both groups showed a strong influence of body context on facial expression perception, but this influence was larger in the autistic group, mirroring their lower overall precision of facial expression representations relative to non-autistic individuals. Crucially, the magnitude of the biasing influence of body posture in both groups was related to the precision of individuals’ facial expression representations. The results suggest that similar principles govern the integration of facial expression and body posture information in both autistic and non-autistic individuals.
Apparent Diffusion Coefficient as a Prognostic Indicator in Definitive Radiotherapy for Gleason Score 7 Prostate Cancer: A Retrospective Analysis
Authors: Onal Cem , Elmali Aysenur , Erbay Gurcan , Demirhan Birhan , Guler Ozan Cem
Published: July 2024

Objective
To investigate the utility of diffusion-weighted magnetic resonance imaging (DW-MRI) in evaluating Gleason score (GS) 7 tumors before definitive radiotherapy (RT) and to explore its association with clinicopathological factors and treatment outcomes.
Methods
Clinical data of 266 prostate cancer (PCa) patients with biopsy-confirmed GS 7 who underwent RT were retrospectively analyzed. Pre-treatment DW-MRI was utilized to measure apparent diffusion coefficient (ADC) values of primary tumors. Treatment outcomes, including biochemical disease-free survival (bDFS) and prostate cancer-specific survival (PCSS), were assessed. Statistical analyses were conducted to determine the correlation between tumor ADC values, clinicopathological factors, and treatment outcomes.
Results
Tumors with a GS of 3 + 4 had significantly higher ADC values than those with a GS of 4 + 3 (0.746 ± 0.150 vs. 0.702 ± 0.157 × 10˗³ mm²/sec; p < 0.001). Median follow-up time was 8.6 years, and the 7-year rates for bDFS and PCSS were 89.1% and 95.3%, respectively. Lower tumor ADC values were significantly correlated with higher GS and increased risk of disease progression. A primary tumor ADC cutoff value of 0.682 × 10˗³ mm²/sec was identified for predicting disease progression. Patients with higher ADC values exhibited significantly better 7-year bDFS rates (92.8% vs. 83.2%; p = 0.02). However, GS 4 + 3 tumors independently predicted poorer bDFS and PCSS outcomes. In the multivariable analysis, only GS 4 + 3 tumor was predictive for worse bDFS and PCSS.
Conclusions
Tumor ADC values are a reliable biomarker for differentiating between GS 3 + 4 and 4 + 3 tumors in the GS 7 category. Tumors exhibiting lower ADC values have been associated to higher risk factors and an increased likelihood of disease progression, particularly in GS 3 + 4 tumors where GS upgrading could happen.
Assessing the stability and adaptability of corn hybrid yield with the Bayesian AMMI model
Authors: Silva Eliam Vitor Pereira da , Davide Livia Maria Chamma , Gianlup Camila , de Oliveira Wanderley Jorge Soares , de Oliveira Luciano Antonio , Silva Alessandra Querino da , Silva Carlos Pereira da , Mendes Cristian Tiago Erazo , Khan Shahid
Published: July 2024

The objective of this work was to evaluate the stability and adaptability of commercial and experimental corn hybrids tested in three locations in Mato Grosso do Sul (MS) in the 2021 and 2022 agricultural years. We identified superior genotypes that can be recommended broadly and/or restrictedly to optimize productivity. The randomized complete block design (RCBD) was used to evaluate the grain yield per plot (ton/ha) with the additive main effects model and multiplicative interaction via Bayesian inference (BAMMI). It was observed from the results that the genotype by environment interaction (G x E) did not behave in a complex way and that the genotypes, in general, do not have significant contributions to the interaction. Furthermore, it was found that stable and productive hybrids can be selected regardless of genetic structure. The G26 genotype, which is the simple commercial hybrid B2702, stood out as one of the best cultivars. However, it was observed that there are experimental hybrids as good as B2702, such as G9, which is a double hybrid. This result is relevant since double hybrid cultivation is more viable in low investment contexts, as occurs in family farming. Finally, the BAMMI model proved to be a versatile tool with flexibility to overcome the limitations inherent to classical and frequentist analyses of linear-bilinear models.
Knowledge Representation Learning Based on Neighborhood Semantics
Authors: Fu Zijian , Li Dun
Published: July 2024

Knowledge representation is a key technology for knowledge acquisition, application and construction of knowledge graphs. Aiming at the problem of insufficient information utilization in current knowledge representation learning models, a knowledge representation learning model based on neighborhood semantics is proposed. This model focuses on generating hybrid neighborhood representations that blend entity neighborhood details. In addition, it combines entity semantic category information with mixed neighborhood as a unit to extend the entity's semantic category to neighborhood semantic categories. Comparative experiments show that our model outperforms other models in terms of metrics, such as MR, HITS@K in the link prediction, and Micro-ACC and Macro-ACC for triplet classification.
A study on the molecular mechanism of Baicalin in improving Myocardial Fibrosis based on network pharmacology and experimental verification
Authors: Zhang Minghao , Wu Liujun , Shen Yanduo , Zhang Jiale , Xie Bingheng , Wu Xingfei , Wei Danan
Published: July 2024

This study aimed to evaluate the pharmacological mechanism of baicalin intervention on myocardial fibrosis through network pharmacological analysis, molecular docking, and experimental verification.The chemical components and targets of all the drugs in the Baicalin were obtained through Target Prediction databases. The targets of Myocardial fibrosis(MF)were screened through the GeneCards and OMIM databases. The obtained targets were imported into Cytoscape 3.9 software to construct the active ingredient target network and were imported into the String database to construct PPI network, and the in Cytoscape 3.9 was used for network topology analysis. Gene Ontology (GO) enrichment analysis and Kyoto gene and genomic (KEGG) enrichment analysis were performed on the potential targets of Wuling decoction for MF using the David database.The results were imported into bioinformatics platform to obtain GO and KEGG network relationship maps. The molecular docking software AutoDock Vina was used to dock the core targets with the active ingredients. A MF rat model was established and animals were divided into the control, MF model, a captopril group (9 mg/kg), and low-, middle-, and high-dose baicalin groups (50, 100, 200 mg/kg). Compared with the rats in the MF model group, rats in each administration group demonstrated restoration of ST segment amplitude and T wave on electrocardiograms. Moreover, HWI and LVWI exhibited significant decreases. The levels of CK, LDH, NT-proBNP, Col I and Col III in myocardial tissue also showed significant decreases. Additionally,the degree of myocardial fibrosis was reduced; there were also significant decreases observed in the expression levels of PTGS2 and TNF-α in myocardial tissue, where as an increase was noted in the expression level of IL2. Baicalin has been shown to enhance myocardial fibrosis and cardiac function in a rat model of myocardial fibrosis. The mechanism underlying this effect appears to be associated with the down-regulation of PTGS2 and TNF-αexpression levels, as well as the up-regulation of IL2 expression levels.
Bioinformatics analysis and Late Blight resistance identification of zinc finger protein gene StZFP16
Authors: He Miaomiao , Zhu Di , Zhou Yun , Yang Shenglong , Sun Haihong , Wang Jian
Published: July 2024

Late blight is the most notorious oomycete disease in potato production. Qingshu 9 has been the leading potato cultivar Qingshu 9 in China, which showed excellent field performance against late blight in different regions and multiple years. Based on the transcriptome data of the interaction between Qingshu9 and late blight in the early stage of the research group, zinc finger protein genes plays a critical role in interaction between late blight and Qingshu9. In this study, a novel gene, StZFP16 was cloned from Qingshu 9. The total length of StZFP16 is 1107 bp, and it encodes 369 amino acid polypeptides. The StZFP16 was induced by SA and MeJA to express. An overexpression vector of StZFP16 was constructed and transiently transformed into the model plant Nicotiana benthamiana. And the results showed that StZFP16 gene enhances plant resistance to late blight by mediating H2O2 content, antioxidant enzyme activity and the expression of related defense genes. These results indicated that StZFP16 enhanced potato resistance to P. infestans, providing a vital theoretical basis for analyzing the functional diversity of zinc finger protein family genes and the effective utilization of Qingshu 9 in disease resistance breeding.
Towards LLMCI - Multimodal AI for LLM-Vision UI Operation
Authors: Barham Husam , Fasha Mohammed
Published: July 2024

Human-computer interaction (HCI) has evolved significantly, yet it still largely depends on visual communication through screens and manual input devices. While this paradigm is likely to remain dominant for the foreseeable future, this research suggests that existing user interfaces (UI) can also be leveraged by Large Language Models (LLMs) to interact with computers. By integrating vision models into a multimodal framework, LLMs can gain the ability to understand and operate UI elements, enabling them to retrieve information, run functions, and perform various tasks just like humans. The framework utilizes a vision model to communicate UI components and information to the LLM, which then leverages its language understanding capabilities to retrieve information, and operate keyboard and mouse inputs.This paper introduces a new element to Human-Computer Interaction (HCI), called LLM-Computer Interaction (LLMCI), which combines Large Language Models (LLMs) with computer vision via intelligent agents. These agents process user text commands and use visual perception to recognize visual and textual elements of computer interfaces. This allows the Multimodal AI to independently perform complex tasks and navigate applications in a way that resembles human behavior. We present a proof-of-concept framework that illustrates how the agent uses LLMs and computer vision to handle interface elements, complete tasks, and support users according to their instructions. This strategy closely imitates human interactions and suggests a path forward for enhancing HCI practices.