bluuebunny/crossref_metadata_2025 huggingface dataset:
Applied Machine Learning for the Imputation of Missing Core Petrophysical Property Data in Clastic and Carbonate Reservoirs
Authors: Abdulkhaleq Hussein B. , Al-Mudhafar Watheq J. , Wood David A. , Sausan Sarah
Published: April 2024

Estimating missing petrophysical data, particularly in permeability/porosity core-analysis measurements is a challenge. The data gaps substantially increase uncertainty in multivariate statistical analysis degrading the accuracy of geomodeling. Data imputation algorithms can be used to estimate such missing values but their performance and reliability vary in providing usable estimates. This study comprehensively compares seven imputation techniques for predicting missing core-measured horizontal and vertical permeability and porosity data in two wells drilled in the North Rumaila oil field a southern Iraqi field; one in the clastic Zubair Formation, and one in the carbonate Yamama Formation. Relative bias (RB) and robustness to outliers were used to assess and compare the estimates of each imputation technique. The results are presented in terms of outlier percentages and displayed using several statistical plots to compare the imputed and original data points. The results reveal that the MICE-CART data imputation method outperforms the other methods with the clastic and carbonate datasets studied. It generates low RB values, and realistic variable density distributions and demonstrates robustness to outliers. The novel workflow (combining relative bias, outlier robustness, and comparison of depth, variable distribution, and box plots) is suitable for application in both clastic and carbonate reservoir formations. It is effective at revealing the relative strengths and weaknesses of specific data imputation methods.
Challenges and Recent Advances in Modeling and Simulation of Geothermal Systems
Authors: Temizel Cenk , Odi Uchenna , Cetin Coskun , Pamukcu Yusuf , Yegin Cengiz
Published: April 2024

The use of geothermal resources for electricity generation began in Larderello, Italy, in 1904 with an experimental generator producing 10 kilowatts of electricity (kWe) (Keller & Valduga, 1946). This initial effort led to the establishment of the first commercial unit generating 250 kWe from the geothermal fluids of two wells at 200-250 °C in 1913 (Lund, 2005). For decades, Italy was the only producer of geothermal electricity on an industrial scale until 1958 when New Zealand introduced an 11.2 Megawatts electric (MWe) facility at Wairakei (Stimac et al., 2015), which was also the first to use the "wet" steam (or flash steam) as opposed to dry steam, marking a significant expansion in geothermal energy (Lund, 2005).

After the end of World War II, the geothermal power industry saw a growth rate of 6.2%, and geothermal power plants spread globally during the 1960s. For example, Mexico, the United States, and Russia (the former Soviet Union or USSR) have adopted these energy solutions. In particular, Russia pioneered the world's first binary-cycle power plant in Kamchatka in 1967. Then, other countries including Japan, Iceland, and China joined the league of geothermal power producers by 1970 (Lund, 2005; Pambudi & Ulfa, 2024).

Initially, the geothermal sector mainly relied on steam from high-temperature sources above 150 °C. However, technological advancements allowed for the utilization of lower temperature resources at 90 °C. This was made possible thanks to using organic working fluids instead of water in the organic Rankine cycle process to improve efficiency. These are often integrated into district heating projects, expanding the range and effectiveness of energy applications. However, the optimal and flexible design of such systems under uncertainties of the future energy markets remains challenging (Wieland et al., 2023).
Hydrogen Storage in Saline Aquifers: Experimental Observations of Viscous-Dominated Flow
Authors: Zhou J. D. , Kovscek A. R.
Published: April 2024

Hydrogen (H2) storage in the subsurface is a potential long-term energy storage solution for renewable energy; however, hydrogen flow in the subsurface is not well understood and studied in the context of conventional reservoir engineering. A quantitative understanding of the similarities and dissimilarities between the transport behavior of H2, CO2, and CH4 is necessary to assess the feasibility of underground hydrogen storage (UHS) as well as guide the design and optimization of the storage site. A multi-phase flow experimental setup is introduced to examine the behavior of H2 transport in a brine-saturated core under different flow rates and flow regimes. Analog fluids of nitrogen (N2) and viscosified brine were used in lieu of H2 to obtain capillary number (NCa) and viscosity ratios similar to H2/brine flow at reservoir conditions. X-ray computed tomography (CT) was used to image the flow during gas injection and compute average gas saturation across the core sample. The small NCa experiment showed behavior consistent with capillary fingering and stable displacement based on the piston-like gas saturation curve. The high NCa experiment showed a mixture of viscous fingering and capillary fingering tendencies, necessitating the need for a liquid-liquid pairing study that allows for distinct viscous fingering behavior.
Fractal Approach for Naturally Fractured Reservoirs Characterization Using Reservoir Simulation
Authors: Silva-Escalante C. F. , Camacho-Velazquez R. G.
Published: April 2024

Fractals are present in the naturally fractured reservoirs, that implies a pressure response is affected by a power law behavior in the fracture properties showing characteristics in their pressure drop performance deviating the typical and idealized Warren and Root (1963) approach for reservoir characterization.

The work’s objective is to characterize fractal naturally fractured reservoirs for obtaining the fractal parameters and reservoir properties from a pressure drawdown coupling a black-oil reservoir simulator with a power-law based (fractal) distribution of permeability and porosity of natural fractures over the simulation grid plane, thus, analyzing the resulting pressures and production scenarios corresponding to the fractal behavior in naturally fractured reservoirs. The proposed methodology results in an alternative for fractal reservoir characterization applying reservoir simulation modelling.

A double-porosity model is constructed to match the pressure behavior with two field cases with fractal behavior identified from pressure drop performance, and noncommon flow regimes resulted because the fractal flow dimension differs from the Euclidian one, which is a fractal special case where the fractal dimension, dmf, is equal to the Euclidean dimension, d=1, 2 or 3. By a pressure history matching, the characterization of the fractal parameters is reached for both field cases as dmf = 1.386 and the connectivity index, θ = 0.17, and dmf = 1.162 & θ = 0.167, respectively. The rest of reservoir unknown parameters were obtained, and a sensitivity analysis of the fractal parameters shows the impact in the pressure responses and the underestimation in the production rate performance compared with the Euclidian 2D flow.
ESG Consciousness in Mutual Fund Advisory: Examining Attitudes, Intentions, and Moderating role of Fund Fundamentals and Herding Bias
Authors: Tiwari Kamesh , Sharma Meghna , Deka Jimnee
Published: April 2024

This study explores the relationship between mutual fund advisors' ESG consciousness, their attitude towards ESG funds, and their intention to advise ESG funds, while also considering the moderating influence of fund fundamentals and herding bias. Data was collected from 234 Indian financial advisors in the mutual fund domain using a Likert scale questionnaire. Amos based Structural Equation Modeling (SEM) was employed for data analysis. The results indicate a significant connection wherein advisors with heightened ESG consciousness tend to hold more positive attitudes toward ESG funds, which, in turn, positively predict their intention to provide advisory services related to ESG funds. Furthermore, fund fundamentals, encompassing financial and non-financial attributes of ESG funds, play a crucial moderating role, particularly when advisors perceive these fundamentals as robust and positive. Notably, herding bias among advisors also positively moderates the relationship, indicating that advisors with a greater inclination to follow industry trends and peer behavior are more influenced by their positive attitudes, resulting in a stronger intention to recommend ESG funds. These findings have implications for investors and advisors alike, shedding light on the dynamics of ESG-conscious investing in emerging markets and its potential impact on financial decisions.
Research on information security of urban traffic control system based on tripartite evolutionary game
Authors: Li Kailong , Pan Ke , Wang Li , Zhang Feng , Xiu Weijie , Li Min , Zhang Lili
Published: April 2024

In recent years, emerging technologies such as smart cities, Urban Traffic brains, and car networking are vigorously promoting the intelligent development of urban traffic signals, which means that the Urban Traffic Control (UTC) system will interact with more and more network and physical terminals, which will lead to more malicious attacks and information destruction. It will be a great threat to the personal and property safety of participants in urban traffic. In response to this severe demand, this paper studied the network topology of UTC system and based on the tripartite evolutionary game theory (TEG), A Signal control security game model involving attackers, Upper Computer (UC) and Traffic Signal Machine (TSM) is designed, and the evolutionary stability of strategy selection of each participant is analyzed. This paper discusses the comprehensive judgment principle of each element on attack cost and defense cost, compares the influence of tripartite strategy selection, and further analyzes the stability of equilibrium point in tripartite evolutionary information security game system with Lyapunov's first method. Finally, by using real data and MATLAB simulation analysis, the impact of key parameters such as attack cost, defense cost and detection rate on information security game participants is verified, making theoretical contributions to enhancing the security of urban traffic signal control system.
Analysis of effects of Correlated Color Temperature (CCT) on the
performance of Visible Light Communication (VLC) Link.
Authors: Paliwal Rajat , Patel Piyush , Atieh Ahmad
Published: April 2024

CA system model for the Line-of-Sight (LoS) Lambertian radiation pattern has been designed with commercially used high power white phosphorous converted white light emitting diode (PLED) of CCTs 2200K, 3000K and 5700 K and three photodiodes of quite different specifications. This system has been successfully tested for the maximum data rate of 300 Mbps and 170 Mbps for RC constant and electron life time 0.5 ns and 1 ns, respectively. The CCTs 2200k and 3000k irrespective of any particular detector have provided maximum data rates. One CCT 5700K with detector model of S5107 or S7686 for the values 0.5 ns and 1 ns has provided slight lower data rate of 200 Mbps or 150 Mbps, respectively with required BER of 10-6 for stable communication. This CCT 5700 K performance with another detector S5973/-01 has been noticed altogether different and could not sustained the VLC link and signals were not detected by the detector. It is thus concluded that both the CCTs 2200K and 3000K have performed satisfactorily with all the three detectors but one CCT 5700K with combination of detector S5973/-01 found completely mismatched as this could not even establish the link. This CCT 5700 K despite of having higher brightness and transmit power due to lower responsivity of the detector as compared with the other two CCTs supported slight lower data rates. All the three detectors have varied responsivity and other specifications which have affected performance of VLC link. For CCT 5700 K both the detectors, S5107 and S7686 have almost equal responsivity support but the detector S5973/-01 provided slight lesser as compared to other detectors. This exhibited that all the three detectors have varied performance for CCT 5700 K due to dominating in blue wavelength beside other limitations of responsivity and photo sensing area of the detectors.
The Social Art of Wealth Creation: Unpacking Alternative Philosophy for Inclusive Socio- economic Development in South Africa
Authors: Kajiita Robert Mutemi , Kang'ethe Simon Murote
Published: April 2024

Generally, economic investment models are primarily premised on maximising profit and accumulating wealth, a development paradigm that benefits a few. This paper focuses on social entrepreneurship as an emerging socio-economic paradigm in South Africa. The objective of the paper was to demonstrate the philosophical nuances within social entrepreneurship as an alternative socio-economic paradigm in South Africa. Through a qualitative research approach, in-depth interviews were conducted with selected social enterprises in South Africa. The data was analysed thematically. The study established that social entrepreneurship is premised on people-centredness; cultural-embedded socio-economic investments; empowerment and socio-economic emancipatory; and innovativeness. These principles advance the social investment paradigm in social enterprises by reconceptualising and contextualising wealth creation and its concomitant social impact on communities. These findings imply that social services practitioners must undergo a paradigm shift in designing and implementing inclusive and equitable-orientated socio-economic models and approaches to development.
Predictive Modeling of Adaptive Behavior Trajectories in Autism: Insights from a Clinical Cohort Study
Authors: Brandes-Aitken Annie , Lazerwitz Maia , Eash Ally , Hattangadi Neil , Mukherjee Pratik , Marco Elysa , Shapiro Kevin
Published: April 2024

Research aimed at understanding how baseline clinical and demographic characteristics influence outcomes over time is critically important to inform individualized therapeutic programs for children with neurodevelopmental differences. This study characterizes adaptive behavior trajectories in children receiving medical and behavioral therapy within a network of care centers with a shared data-gathering mechanism for intake and longitudinal assessments. We then take the further step of utilizing intake data to develop machine-learning models which predict differences in those trajectories. Specifically, we evaluated data from 1,225 autistic children, aged 20–90 months, using latent class growth mixture modeling (LCGMM) with scores on the Vineland Adaptive Behavior Scales, 3rd Edition, as the primary outcome measure. The LCGMM analysis revealed two distinct clusters of adaptive behavior trajectories. The “Improved” group (\(\ge\)66% of the sample) exhibited greater developmental change in adaptive behavior, while the “Stable” group (\(\le\)33% of the sample) showed little change over time relative to age-matched normative data. For a subset of 729 children, we used machine learning algorithms to forecast adaptive behavior trajectories using clinical and sociodemographic data collected at the initial assessment, comparing elastic net GLM, support vector machine, and random forest. The best-performing random forest model predicted adaptive behavior trajectory with an accuracy rate of 77%. The strongest predictors in our model were socioeconomic status, history of developmental regression, child temperament, paternal age at the time of the child’s birth, baseline autism symptom severity, parent concerns about development, presence of ADHD symptoms, and parent concerns about mood. Notably, the inclusion of cumulative hours of applied behavioral analysis and developmental therapies in the machine learning models did not yield significant changes in performance metrics, indicating that increased therapy hours did not predict greater improvement. These findings extend our understanding of adaptive behavior development in autistic children and underscore the value of gathering comprehensive patient information at intake to tailor clinical care.
Efficacy of monotherapy or combination therapy against bloodstream infection caused by carbapenem-resistant Klebsiella pneumoniae
Authors: Jiang Lushun , Fang Jiaheng , Zhang Kanghui , Shen Jiaying , Guo Wenhui , Xu Liqian , Yu Wei
Published: April 2024

Objectives: The aim of this study was to summarize available dataon monotherapy or combination therapy for bloodstream infection (BSI) caused by carbapenem-resistant Klebsiella pneumoniae (CRKP).
Methods: A systematic review and meta-analysis was conducted to compare monotherapy with combination therapy in patients with BSI-CRKP. Mortality was the primary outcome.
Results: A total of 1675 patients in 13 studies were included. The pooled risk ratio (RR) of mortality were 0.79 (95%CI: 0.60-1.05) between combination therapy and monotherapy. However, no significant difference in mortality was observed. The RR of polymyxins-based and tigecycline-based combination therapy were 0.72 (95%CI: 0.47-1.12) and 0.67 (95%CI: 0.42-1.09), respectively. Similarly, the difference is statistically insignificant. Further analysis showed the lower mortality associated with polymyxins+tigecycline-based combination therapies than that with tigecycline combined with other antibiotics (RR=0.66, 95%CI: 0.52-0.83, P=0.00).
Conclusions: Combination therapy against BSI-CRKP has survival benefit, especially for polymyxins+tigecycline-containing therapies.
Unraveling Hematopoietic Stem Cell Expansion: A Microfluidic 3D Co-culture Approach on Demineralized Bone Matrix
Authors: kojabad Amir Asri , Atashbar Maryam , Atashi Amir , soleimani masoud
Published: April 2024

Background
Hematopoietic stem cell transplantation (HSCT) is a well-established therapy for various hematological malignancies. Umbilical cord blood (UCB) HSCs offer an alternative source but are limited by a small number of CD34 + cells, delaying hematopoietic and immunologic recovery. Recent evidence underscores the importance of closely recapitulating the bone marrow niche for ex vivo stem cell expansion..
Methods
We describe a novel 3D microfluidic chip for dynamic co-culture of MSCs and HSCs within a demineralized bone matrix (DBM) scaffold. Co-culture was conducted in both dynamic and static 3D conditions without exogenous cytokines for seven days.
Results
Scanning electron microscopy images revealed that CD34 + CD38- cells primarily lodged beneath the MSCs layer rather than on its surface. MSCs repopulated the DBM scaffold and sustained HSC expansion for seven days. The proportion of CD34 + cells increased significantly (1.35-fold), with CD34 + CD38- cells nearly doubling in the microfluidic 3D co-culture compared to the control group. Microfluidic conditions promoted CXCR4 transcription (4.7-fold), colony-forming potency (3.6-fold), and osteogenic properties of DBM (9.4-fold) compared to the control group.
Conclusion
Indirect and direct crosstalk among HSCs, MSCs, and extracellular matrix (ECM) proteins can enhance UCB HSC expansion potency in an engineered bone marrow chip. Our microfluidic-based chip represents a significant step toward overcoming current limitations in UCB HSC numbers.
Investigations for increasing the 3D-forming potential of high-density fiberboards
Authors: Krüger Robert , Buchelt Beate , Herold Jan , Wagenführ André
Published: April 2024

The trend in modern interior design leans towards curved and shaped surfaces. This cannot be achieved with flat materials without additional effort. Materials from renewable resources, such as wood-based materials, are material- and energy-intensively processed to enable larger deformations. Therefore, this study deals with methods to increase the deformation potential of adhesive-free high-density fiberboards. One method is plasticizing in a saturated steam atmosphere, which is well known from the bending of solid wood. The second is the application of a special kerf pattern that geometrically increases the deformability. The combination of both methods was also investigated. Uniaxial tensile tests were performed to evaluate the deformation potential of the methods used. The strain along and transverse to the tensile direction as well as the modulus of elasticity and Poisson's ratio were determined as results. All the methods investigated lead to an increase in the maximum strain along the tensile load; steaming by a factor of 2, kerf patterning by a factor of 4 and the combination by a factor of 10 as compared to solid fiberboard. The application of the kerf pattern causes an auxetic material behavior with a negative Poisson's ratio. The combination of both methods reduces the modulus of elasticity by a factor of more than 100. Overall, the investigated methods are suitable for increasing the deformation potential of fiberboards with regard to the forming of 3D-shaped surfaces.
Chemical and Microbial Safety Criteria for Egyptian Ras Cheeses
Authors: Awad Sameh , Elsaadany Khaled , Ibrahim Amel
Published: April 2024

Up until now, most of the Ras cheese has been produced by small dairy sectors in Egypt using raw milk. This research aimed to determine the pathogens, and undesirable microorganisms in traditional Egyptian Ras cheese using classical methods and real-time PCR. Forty samples of Ras cheese were analysed for chemical and microbiological properties. The results revealed a wider range in the chemical composition of the collected samples. Most of the Ras cheese samples were within the Egyptian Standard for chemical compositions. There were only two samples of Ras cheese that had more moisture than the Egyptian Standard recommended.. The results of the microbiological analysis of the Ras cheese reveal that the coliform count ranged between 1 and 5.20 log CFU/g, with an average of 1.70 log CFU/g. Anaerobic spore-forming bacteria (Clostridium perfringens) were found in 29 out of 40 Ras cheese samples. All Egyptian cheese samples contained more yeast and mold than the Egyptian Standard recommends. All cheese samples were free of Listeria monocytogenes and Salmonella spp. The real-time PCR showed that 5% of samples were positive for methicillin-resistant Staphylococcus aureus, and all the analysed samples were free of E. coli O157:H7. According to this study's findings, most Ras cheese samples contained higher levels of Staphylococcus aureus, molds, and yeasts than what Egyptian standards recommended. The results of this study should be used to develop specific procedures for risk management along the milk production chain.
Exploring the Dynamics of Women's Field Hockey Performance: A Comparative Analysis of the Impact of Opponent Quality between Olympic Games and Chinese National Games
Authors: Huo Kelin , Yang Xudong , Zhang Ziyu , Li Baitu , Zhou Changjing
Published: April 2024

This study analyzed the performance of the Chinese women’s national field hockey team during the 2020 Tokyo Olympics and 2021 National Games to assess the impact of opposition quality on performance. Game statistics were collected using notational analysis software for 76 Olympic and 40 National Games matches. Non-parametric Mann-Whitney U tests were used to compare tournaments. No significant differences existed for 35 out of 38 metrics, except Offense in 25-Yd Area (P = 0.013), Handball Style (P = 0.000) and Entry into Arc - Right Lane (P = 0.017). When exclusively considering Chinese national team’s observations, superior National Games performance did emerge for Shot (P = 0.046), Goal from Short Corner (P = 0.044), Into the Arc (P = 0.046), Entry into Arc - Q3 (P = 0.009), Dribble into the Arc (P = 0.046), Handball Style into Arc (P = 0.041), Forehand Shot (P = 0.033), and Small Skill Shot (P = 0.014). The study underscores the influence of opposition quality on team performance, with a need for targeted improvements in arc penetration efficacy, conversion rates of shots to goals, and adaptation of tactical approaches against stronger defenses. The research points towards the need for strategic high-performance programs, improved domestic league quality, and a structured youth development system to elevate the overall standard of Chinese field hockey to achieve global competitiveness.
Quantifying trade-offs between therapeutic efficacy and resistance dissemination for enrofloxacin dose regimens in cattle
Authors: Deb Liton Chandra , Timsina Archana , Lenhart Suzanne , Foster Derek , Lanzas Cristina
Published: April 2024

The use of antimicrobial drugs in food-producing animals increases the selection pressure on pathogenic and commensal bacteria to become resistant. This study aims to evaluate the existence of trade-offs between treatment effectiveness, cost, and the dissemination of resistance in gut commensal bacteria. We developed a within-host ordinary differential equation model to track the dynamics of antimicrobial drug concentrations and bacterial populations in the site of infection (lung) and the gut. The model was parameterized to represent enrofloxacin treatment for bovine respiratory disease (BRD) caused by Pastereulla multocida in cattle. Three approved enrofloxacin dosing regimens were compared for their effects on resistance on P. multocida and commensal E. coli: 12.5 mg/kg and 7.5 mg/kg as a single dose, and 5 mg/kg as three doses. Additionally, we explored non-approved regimes. Our results indicated that both 12.5 mg/kg and 7.5 mg/kg as a single dose scenario increased the most the treatment costs and prevalence of P. multocida resistance in the lungs, while 5 mg/kg as three doses increased resistance in commensal E. coli bacteria in the gut the most out of the approved scenarios. A proposed scenario (7.5 mg/kg, two doses 24 hours apart) showed low economic costs, minimal P. multocida, and moderate effects on resistant E. coli. Overall, the scenarios that decrease P. multocida, including resistant P. multocida did not coincide with the scenarios that decrease resistant E. coli the most, suggesting a trade-off between both outcomes. The sensitivity analysis indicates that bacterial populations were the most sensitive to drug conversion factors into plasma (𝛽), elimination of the drug from the colon (𝜗), fifty percent sensitive bacteria (P. multocida) killing effect (Ls50), fifty percent of bacteria (E. coli) above ECOFF killing effect (Cr50), and net drug transfer rate in the lung (𝛾) parameters.
A conditional latent autoregressive recurrent model for generation and forecasting of beam dynamics in particle accelerators
Authors: Rautela Mahindra , Williams Alan , Scheinker Alexander
Published: April 2024

Particle accelerators are complex systems that focus, guide, and accelerate intense charged particle beams to high energy. Beam diagnostics present a challenging problem due to limited non-destructive measurements, computationally demanding simulations, and inherent uncertainties in the system. We propose a two-step unsupervised deep learning framework named as Conditional Latent Autoregressive Recurrent Model (CLARM) for learning the spatiotemporal dynamics of charged particles in accelerators. CLARM consists of a Conditional Variational Autoencoder (CVAE) transforming six-dimensional phase space into a lower-dimensional latent distribution and a Long Short-Term Memory (LSTM) network capturing temporal dynamics in an autoregressive manner. The CLARM can generate projections at various accelerator modules by sampling and decoding the latent space representation. The model also forecasts future states (downstream locations) of charged particles from past states (upstream locations). The results demonstrate that the generative and forecasting ability of the proposed approach is promising when tested against a variety of evaluation metrics.
Perioperative Complications and Outcomes of 12 Patients Bridged to Heart Transplantation by Extracorporeal Membrane Oxygenation
Authors: Fang Xing , Yan Jueyue , Xu Zhipeng , Zhang Jingchen , Li Tong
Published: April 2024

Background: Cardiogenic shock (CS) is characterized by end-organ hypoperfusion resulting from low cardiac output. Venous-artery extracorporeal membrane oxygenation (VA-ECMO), is widely used in patients presenting with refractory cardiogenic shock. The decision to use VA-ECMO as a bridge to heart transplantation has become widely accepted as a short-term option. However, complications can develop within weeks, which makes it unsuitable for bridging to transplantation and even affects the prognosis.
Methods：Data were collected from 12 patients who received extracorporeal membrane oxygenation (ECMO) as a bridge to heart transplantation between October 2020 and October 2021. General perioperative characteristics, ECMO-related complications, and posttransplantation survival were summarized.
Results：The 12 patients were male, with an average age of 45.33 years and an average BMI of 22.87 kg/m2. The main primary diseases were myocardial infarction (7 cases), dilated cardiomyopathy (4 cases), and fulminant myocarditis (1 case); the average ECMO maintenance time before transplantation was 14.25 days, the longest preoperative maintenance time was 37 days, the overall ECMO perioperative survival rate was 75.00%, and the 30-day survival rate was 91.67%. The main complications in the perioperative period are gastrointestinal bleeding, distal limb ischemia of the perfusion tube and distal limb ischemia requiring fasciotomy during ECMO maintenance, bleeding after transplantation in the operative area requiring reoperation for bleeding, and poor healing at the ECMO cannulation insertion site.
Conclusion：ECMO as a bridge to heart transplantation is a feasible treatment option for patients with end-stage heart failure and refractory cardiogenic shock. We should be aware of the complications related to ECMO management.
Findings of tobacco ringspot virus in ornamentals in the Netherlands from 1997 to 2020 indicate a need for evaluation of its EU-quarantine status
Authors: Schoen Ruben , de Krom Christel , Westenberg Marcel , Botermans Marleen , Bruggen Anne Sophie van , Meekes Ellis , Didden Leonie , Hooftman Rien , Roenhorst Annelien
Published: April 2024

Occasional findings of Tobacco ringspot virus (TRSV) in the Netherlands since 1997, were reason for large-scale surveys for TRSV in vegetatively propagated ornamental plants and for its vector, Xiphinema americanum sensu lato. In total, TRSV was identified in ten ornamental species, comprising over 30 cultivars, while X. americanum s.l. was not found. In addition, TRSV was identified in four ornamental species originating from outside the Netherlands. This report describes a newly designed and validated real time RT-PCR and gives an overview of TRSV findings and interceptions, including phylogenetic analyses of (nearly) complete genome sequences from available isolates and NCBI GenBank accessions in relation to their metadata of host and origin. Overall, the results suggest that TRSV entered the Netherlands on multiple occasions and was further spread by vegetative propagation. Furthermore, TRSV seems to be more widespread in the European Union (EU) than previously assumed, indicating that the current regulatory measures do not fully safeguard the absence of TRSV. Alternative strategies to protect the crops at risk are discussed, and reconsideration of the regulatory status of TRSV in the EU is recommended.
Preoperative Prediction of Rectal Cancer Staging Combining MRI Deep Transfer Learning, Radiomics Features, and Clinical Factors: Accurate Differentiation from Stage T2 to T3
Authors: Fan Lifang , Wu Huazhang , Wu Yimin , Wu Shujian , Zhao Jinsong , Zhu Xiangming
Published: April 2024

Background This study evaluates the efficacy of integrating MRI deep transfer learning, radiomic signatures, and clinical variables to accurately preoperatively differentiate between stage T2 and T3 rectal cancer.
Methods We included 361 patients with pathologically confirmed stage T2 or T3 rectal cancer, divided into a training set (252 patients) and a test set (109 patients) at a 7:3 ratio. The study utilized features derived from deep transfer learning and radiomics, with Spearman rank correlation and the Least Absolute Shrinkage and Selection Operator (LASSO) regression techniques to reduce feature redundancy. Predictive models were developed using Logistic Regression (LR), Random Forest (RF), Decision Tree (DT), and Support Vector Machine (SVM), selecting the best-performing model for a comprehensive predictive framework incorporating clinical data.
Results After removing redundant features, 24 key features were identified. In the training set, the area under the curve (AUC)values for LR, RF, DT, and SVM were 0.867, 0.834, 0.900, and 0.944, respectively; in the test set, they were 0.847, 0.803, 0.842, and 0.910, respectively. The combined model, using SVM and clinical variables, achieved AUCs of 0.946 in the training group and 0.920 in the validation group.
Conclusion The study confirms the utility of a combined model of MRI deep transfer learning, radiomic features, and clinical factors for preoperative classification of stage T2 vs. T3 rectal cancer, offering significant technological support for precise diagnosis and potential clinical application.
Dependency-aware Online Task Offloading based on Deep Reinforcement Learning for IoV
Authors: Liu Chunhong , Wang HuaiChen , Zhao Mengdi , Liu Jialei , Zhao XiaoYan , Yuan Peiyan
Published: April 2024

The integration of artificial intelligence with vehicle wireless communicationtechnology willing meet the intelligent communication needs of the Internetof Vehicles (IoV), supporting more sophisticated vehicle applications. However,making real-time dependency-aware task offloading decisions is difficult due tothe high mobility of vehicles and the dynamic nature of the network environment.This leads to additional application computation time and energy consumption,increasing the risk of offloading failures for computationally intensive andlatency-sensitive applications. In this paper, an offloading strategy for vehicleapplications that jointly considers latency and energy consumption in the basestation cooperative computing model is proposed. Firstly, we establish a collaborativeoffloading model involving multiple vehicles, multiple base stations,and multiple edge servers. Transferring vehicular applications to the applicationqueue of edge servers and prioritizing them based on their completion deadlines.Secondly, each vehicular application is modeled as a directed acyclic graph(DAG) task with data dependency relationships. Subsequently, we propose atask offloading method based on task dependency awareness in deep reinforcementlearning (DAG-DQN). Tasks are assigned to edge servers at different base stations, and edge servers collaborate to process tasks, minimizing vehicle applicationcompletion time and reducing edge server energy consumption. Finally,simulation results show that compared with the heuristic method, our proposedDAG-DQN method reduces task completion time by 16%, reduces system energyconsumption by 19%, and improves decision-making efficiency by 70%.
Changing Patterns of Severe Acute Malnutrition and Associated Socio-Demographic Factors Among Under-Five Children in Maharashtra
Authors: Tonpe Mayura , Mankar Dhananjay
Published: April 2024

Background:
Malnutrition poses a significant health concern, particularly among children under the age of five, on a global scale. Among the various forms of malnutrition, Severe Acute Malnutrition (SAM) stands out as one of the most devastating conditions, contributing to an 11-fold greater risk of mortality and morbidity in affected children than in well-nourished children.
Despite being regarded as one of India's most economically developed states, Maharashtra continues to experience a persistently high prevalence of SAM. Recognizing this, there is a necessity to delve into the evolving trends of SAM in Maharashtra and explore the factors influencing its prevalence.
Materials and Methods:
In this study, the focus was on children aged 6 to 59 months who were residents of the state of Maharashtra. The information was obtained from the National Family Health Survey-4 (NFHS-4, 2015-16) and NFHS-5 (2019-21) databases. Bivariate analysis was conducted to determine the association between socio-demographic variables and SAM between NFHS-4 and NFHS-5 in Maharashtra. The multivariable binary logistic regression analysis was used to study the significant factors associated with the rising trend in SAM between the two survey periods.
Results:
The analysis showed that the SAM prevalence in Maharashtra has increased from 9.4% to 10.9% since NFHS-4. Bivariate analysis revealed that factors such as the wealth index, total number of children, media exposure of mothers, birth order, birthplace, and birth weight of the child were significant factors during NFHS-4, whereas, during NFHS-5, birth order and child age were the only factors that were found to be significant. The multivariable logistic regression model showed that maternal education and birth weight were the only factors that had a consistently significant association with SAM between the two survey periods (p<0.05).
Conclusion:
This study showed that despite the nutrition-sensitive policies and efforts of the Maharashtra government, the level of SAM among children is increasing. The observations from the study underscore the necessity of implementing nutrition-specific measures that target the underlying social issues in the state. Addressing these social determinants is crucial to overcoming the challenges associated with SAM effectively.
Identification and expression characterization of a WRKY transcription factor affecting squalene synthesis in Camellia oleifera
Authors: Du Qinhui , Ge Luyao , Zeng YanLing , Li Aori , Zhu Ziyan , Tan Xiaofeng
Published: April 2024

WRKY-like transcriptional regulators are widely involved in physiological processes such as growth and development, metabolic regulation and environmental response. In this study, we obtained six CoWRKY transcription factors by yeast one-hybrid screening library with reference to the Camellia oleifera genome sequence, using squalene synthase gene (CoSQS) as bait. AOS (Antibody Optimization System) analysis showed that CoWRKY15 had the highest interactions with a confidence level of 0.9026. Bioinformatics analysis showed that CoWRKY15 encodes 346 amino acid residues, was a basic hydrophilic protein, did not contain a transmembrane region, contained one WRKY conserved structural domain and one C2H2 zinc finger structural domain. and belonged to class 2 of the WRKY gene family, and had the closest genetic distance of 0.5564 to the homologous protein of Panax quinquefolius PqWRKY1. The results of prokaryotic expression showed that the CoWRK15 protein with a size of 38.3 kD was successfully induced by adding a final concentration of 0.5 mM ITPG for 4 h at 37℃. The results of subcellular localization showed that CoWRKY15 functioned in the nucleus. The results of CoWRKY15 promoter analysis showed that 8 out of 14 cis-elements with annotatable functions were related to the light response, indicating that the expression of CoWRKY15 was strongly affected by light. The correlation analysis of CoWRKY15 expression and squalene content in Camellia oleifera seed kernels treated under different light quality conditions showed a significant positive correlation.
An investigation of the agriculture vulnerability and risk from climate change in Liberia: an institutional-socio-economic-technological-system framework approach.
Authors: Masike Sennye , Urich Peter , Li Yinpeng , Mmereki Daniel
Published: April 2024

Climate change presents unprecedented challenges to the agricultural sector particularly in Africa where adaptive capacity and sensitivity are extremely low and high. Adequately addressing climate change risks and impacts in the agricultural sector through mainstreaming in the national development planning process is critical. Therefore, to plan and mainstream climate change into development planning processes, gaining an in-depth characterization of the agricultural sector’s vulnerability to climate change is needed. To this end, we proposed an institutional, social, earth, economic and technical (ISEETS) framework based on the systems approach. Due to limited data, we constructed climate scenarios to present the earth subsector of the ISEETS and provided both theoretical and analytical analyses of the climate change impact on the agricultural sector. Based on the RCP4.5, the results showed that temperature would increase by a range of 1 to 1.25 oC. In terms of precipitation, it would increase by a range of 0.36–1.13%. Analysis of extreme events for precipitation indicated that the country would experience an increase in extreme precipitation of 3–14%, suggesting increased flooding in the country. From the ISEETS perceptive, the sector vulnerability could be amplified by the weak institutional, social, economic, earth, and technology subsectors. The study provided information that could help strengthen all aspects of the ISEETS to reduce vulnerability to climate change.
Tracing N utilization and distribution during development of grape seedlings by applying different forms of 15N labeled fertilizer with fruit tree hole storage brick
Authors: Yao Dongdong , jia Haifeng , Zhang Huanhuan , Li Xujiao , Salah Hossam , Zhao fengyun , Yu SongLin , Yu Kun
Published: April 2024

Background and aims
Application of soil conditioner can promote the NUE in plants by increasing N retention in soil as an effective method to reduce chemical fertilizer consumption and environmental pollution.
Methods
We have prepared fruit tree hole storage brick (FTHSB) suitable for perennial fruit trees using natural nanomaterials, vermiculite and montmorillonite, and organic fertilizers, then recommended a new fertilization strategy combining N fertilizer and FTHSB based on subsurface drip irrigation.
Results
Application of FTHSB significantly increased the amount of dry matter in each organ of grape (Vitis vinifera L.) seedlings, significantly promoted fine root growth of soil layer in the range of 15–30 cm, reduced the leaching loss of 15N to deep soil and significantly improved the use efficiency of 15N. In the treatment without FTHSB, NO3−-N is better than NH4+-N and CO(NH2)2-N in terms of plant growth index of soil layer in the range of 15–30 cm and 15N use efficiency in plants. After the application of FTHSB, CO(NH2)2-N is better than NO3−-N and NH4+-N according to the above indicators.
Conclusions
In general, compared with ammonium and nitrate N FTHSB had the strongest adsorption capacity for amide N, so the N content of the soil in the vicinity of the FTHSB with amide N was also the highest, which improved the dry matter of all organs, the growth of the fine roots and the efficiency of N utilization in the grape seedlings.
Enhanced Anti-Tumor Effects by Combination of Tucatinib and Radiation in HER2-Overexpressing Human Cancer Cell Lines
Authors: Amrell Lukas , Bär Eric , Glasow Annegret , Kortmann Rolf-Dieter , Seidel Clemens , Patties Ina
Published: April 2024

Background
Tucatinib (TUC), a HER2-directed tyrosine kinase inhibitor, is the first targeted drug demonstrating intracranial efficacy and significantly prolonged survival in metastatic HER2-positive breast cancer (BC) patients with brain metastases. Current treatments for brain metastases often include radiotherapy, but little is known about the effects of combination treatment with TUC. Therefore, we examined the combined effects of irradiation and TUC in human HER2-overexpressing BC, non-small cell lung cancer (NSCLC), and colorectal cancer (CRC) cell lines. For the latter two, a standard therapy successfully targeting HER2 is yet to be established.
Methods
Nine HER2-overexpressing (BC: BT474, ZR7530, HCC1954; CRC: LS411N, DLD1, COLO201; NSCLC: DV90, NCI-H1781) and three control cell lines (BC: MCF7, HCC38; NSCLC: NCI-H2030) were examined. Changes in metabolic activity, proliferation, DNA double-strand break (DSB) induction/repair, apoptosis, and clonogenicity after treatment with TUC and/or irradiation (IR) were measured. The relevance of the treatment sequence was analyzed exemplarily.
Results
In BC, combinatorial treatment with TUC and IR significantly decreased metabolic activity, cell proliferation, clonogenicity and enhanced apoptotis compared to IR alone, whereby cell line-specific differences occurred. In the more resistant PI3KCA-mutated HCC1954 cell line, addition of alpelisib (ALP) further decreased clonogenic survival. TUC delayed the repair of IR-induced DNA damage but did not induce DSB itself. Investigation of treatment sequence indicated a benefit of IR before TUC versus IR after TUC. Also in CRC and NSCLC, the combination led to a stronger inhibition of metabolic activity, proliferation, and clonogenic survival (only in NSCLC) than IR alone, whereby about 10-fold higher concentrations of TUC had to be applied than in BC to induce significant changes.
Conclusion
Our data indicate that combination of TUC and IR could be more effective than single treatment strategies for BC. Thereby, treatment sequence seems to be an important factor. The lower sensitivity to TUC in NSCLC and particularly in CRC (compared to BC) implicates, that tumor promotion there might be less HER2-related. Combination with inhibitors of other driver mutations may aid in overcoming partial TUC resistance. These findings are of high relevance to improve long-time prognosis especially in brain-metastasized situations given the intracranial activity of TUC.
Using Machine learning to identify metabolomic signatures of ulcerative colitis with the classification according to disease extent
Authors: Ge Changchang , Lu Yi , Shen Zhaofeng , Lu Yizhou , Liu Xiaojuan , Zhang Mengyuan , Liu Yijing , Shen Hong , Zhu Lei
Published: April 2024

Background: Ulcerative colitis (UC) is a metabolic-related chronic intestinal inflammatory disease. Disease extent is an intrinsic aspect of UC and influences the treatment modality. Identifying serum metabolic profiling of different disease extent may help to elucidate the underlying molecular mechanisms of UC.
Methods: UC patients with different disease extent and healthy controls were included in this study. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) method detected the metabolites, and the orthogonal partial least squares-discriminant analysis (OPLS-DA) were performed to identify metabolites. Lasso regression and support vector machine-recursive feature elimination (SVM-RFE) were used to screen metabolites. Receiver operating characteristic curves (ROC) were plotted to represent the diagnostic value of metabolites.
Results: 93 differential metabolites between the UC and HCs, and57, 66, 44 in E1 and E2, E1 and E3, E2 and E3 groups were confirmed by OPLS-DA in the positive and negative ion mode. KEGG pathway analysis show that Arachidonic acid metabolism, Glycerophospholipid metabolism and Pentose phosphate pathway were the main disturbed metabolic pathway related to UC. Glycerophospholipid metabolism, Sphingolipid metabolism, Pyrimidine metabolism and Linoleic acid metabolism are involved UC site phenotype. Lasso and SVM-RFE screened differential metabolites relating to disease extent, and 8 metabolites were confirmed. The area under the ROC curve of all metabolites predicting the disease extent is greater than 0.7.
Conclusions: There are significant differences in metabolomics among UC patients with different disease extent. Tridecanoic acid may be a potential biomarker for identifying patients with extensive colitis.