Hasil untuk "Analysis"

A. G. W. Biersma, B. van Leer, M. H. Renes et al.

Abstract Background Kidney function is associated with kidney volume. This study aims to explore automated segmentation for measuring total kidney volume (TKV) and to analyse the association between (changes in) TKV and acute kidney injury (AKI) incidence and/or severity in Intensive Care Unit (ICU) patients. Methods Patients were included in this retrospective pilot cohort study when at least two abdominal Computed Tomography (CT) scans were performed during ICU admission. If available, CT scans made before the ICU admission were included as a baseline scan. TKV was measured by automated segmentation of both kidneys using Data Analysis Facilitation Suite (DAFS, Voronoi Analytics Incorporated). All segmentations were visually checked and manually adjusted when necessary. ΔTKV was calculated between baseline CT and CT1 (ΔTKVCT1–baseline) and CT1 and CT2 (ΔTKVCT2–CT1). Primary outcomes were differences in kidney volume before and after manual correction and AKI incidence and severity, per the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines, on the day of scanning. Results Twenty-six patients were included, of whom eighteen developed AKI during ICU admission. Analysis showed no significant differences in volumes before and after manual correction of the automated segmentations. TKV was not associated with AKI incidence or severity. Longitudinal intraindividual changes in TKV were observed. Median ΔTKVCT1–baseline was statistically significantly different for AKI versus non-AKI patients (−22 cm3 (−49–9) versus 42 cm3 (23–43), p = 0.03) and for different KDIGO stages. Conclusion This study demonstrates the possibility of measuring TKV on CT in ICU patients using automated segmentation. Longitudinal intraindividual changes in TKV were observed, however, no clear association between TKV and AKI was found. Clinical trial number Not applicable.

Kyosuke Nagura, Satoko Watanabe, Taro Watanabe et al.

IntroductionOveractive bladder (OAB) drugs are widely prescribed, yet the occurrence of atrial fibrillation (AF) after treatment initiation remains poorly characterized.MethodsWe evaluated reports of AF associated with OAB medications using two spontaneous reporting systems (SRSs): the Japanese Adverse Drug Event Report (JADER) database and the U.S. FDA Adverse Event Reporting System (FAERS). We screened eight agents and assessed signals using three disproportionality metrics: the reporting odds ratio (ROR), proportional reporting ratio (PRR), and Bayesian confidence propagation neural network (BCPNN). For drugs showing signals in both databases, we conducted stratified analyses by sex, age, and number of concomitant medications, and evaluated time-to-onset (TTO) using Weibull modeling.ResultsConsistent AF signals were identified for solifenacin succinate and mirabegron, whereas other agents did not meet the prespecified criteria. Solifenacin met the criteria in women and older adults in both JADER and FAERS. Mirabegron met the criteria across multiple strata in both datasets, indicating cross-stratum reproducibility. TTO was right‐skewed, with most reports occurring within one year of initiation. Exploratory Weibull modeling, based on limited numbers of date‐complete reports, suggested a wear-out pattern for solifenacin in JADER and an early pattern in FAERS, while mirabegron showed a random pattern in JADER and an early pattern in FAERS. These failure‐type patterns should therefore be interpreted cautiously.DiscussionThese findings are hypothesis-generating, given the limitations of SRSs, such as underreporting, missing dates, and unknown exposure—and they reflect reporting patterns rather than causal risk. They outline strata and early treatment periods that may warrant clinical attention and help prioritize pharmacovigilance and targeted hypothesis‐driven evaluation in routine OAB care.

Janine Wesslowski, Sadia Safi, Michelle Rottmann et al.

Upon engagement of one of the nineteen secreted Wnt signaling proteins with one of the ten Frizzled transmembrane Wnt receptors (FZD_1–10), a wide variety of cellular Wnt signaling responses can be elicited, the selectivity of which depends on the following: (1) the specific Wnt-FZD pairing, (2) the participation of Wnt co-receptors and (3) the cellular context. Co-receptors play a pivotal role in guiding the specificity of Wnt signaling, most notably between β-catenin-dependent and -independent pathways, where co-receptors such as LRP5/6 and ROR1/2/PTK7 play major roles, respectively. It remains less understood how specific Wnt/FZD combinations contribute to the selectivity of downstream Wnt signaling, and we lack accurate comparative data on their binding properties under physiological conditions. Here, using fluorescently tagged Wnt3a, Wnt5a and Wnt16 proteins and cell lines expressing HiBiT-tagged Frizzled, we build on our ongoing efforts to provide a complete overview of the biophysical properties of all Wnt/FZD interactions using full-length proteins. Our real-time NanoBRET analysis using living cells expressing low receptor levels provides more accurate quantification of binding and will help us understand how these binary engagements control Wnt signaling outputs. We also provide evidence that LRP6 regulates the binding affinity of Wnt/FZD interactions in the trimeric Wnt-FZD-LRP6 complex.

Gabriel de Sousa Meira, João Victor Ferreira Guedes, Edilson de Souza Bias

The use of geotechnologies in the field of diagnostic engineering has become ever more present in the identification of pathological manifestations in buildings. The implementation of Unmanned Aerial Vehicles (UAVs) and embedded sensors has stimulated the search for new data processing and validation methods, considering the magnitude of the data collected during fieldwork and the absence of specific methodologies for each type of sensor. Regarding data processing, the use of deep learning techniques has become widespread, especially for the automation of processes that involve a great amount of data. However, just as with the increasing use of embedded sensors, deep learning necessitates the development of studies, particularly those focusing on neural networks that better represent the data to be analyzed. It also requires the enhancement of practices to be used in fieldwork, especially regarding data processing. In this context, the objective of this study is to review the existing literature on the use of embedded technologies in UAVs and deep learning for the identification and characterization of pathological manifestations present in building façades in order to develop a robust knowledge base that is capable of contributing to new investigations in this field of research.

Mohammad Mustafizur Rahman, Rashed Abdullah, Arif Ahammad et al.

This paper accentuates the study of LLC resonant converter by a comparative analysis of the properties of LLC resonant and pulse width modulation direct current-direct current converters. Lately, LLC resonant converters have become more appealing and desirable in many applications than other pulse width modulation converters (e.g., Buck, Boost, Cuk) for their soft-switching techniques like zero voltage switching, zero current switching as well as low electromagnetic interference. This paper presents an analysis of efficiency variation, output voltage’s ripple, and various transient performances like percentage overshoot, and the settling time with the variation of load current in a comparative way between LLC resonant converter’s buck, boost operation, and conventional pulse width modulation converter’s buck, boost operation. Feedback proportional-integral-derivative duty cycle controller is used in all converter topologies for some specific analysis. A fixed input voltage of 100 V is selected for simulation and an output voltage of 24 V for buck operation and 120 V for boost operation are chosen. For simulation purposes, MATLAB/SIMULINK software is used.

J. de Curtò, I. de Zarzà, Juan-Carlos Cano et al.

This paper presents a novel approach to enhancing the security and reliability of drone communications through the integration of Quantum Random Number Generators (QRNG) in Frequency Hopping Spread Spectrum (FHSS) systems. We propose a multi-drone framework that leverages QRNG technology to generate truly random frequency hopping sequences, significantly improving resistance against jamming and interception attempts. Our method introduces a concurrent access protocol for multiple drones to share a QRNG device efficiently, incorporating robust error handling and a shared memory system for random number distribution. The implementation includes secure communication protocols, ensuring data integrity and confidentiality through encryption and Hash-based Message Authentication Code (HMAC) verification. We demonstrate the system’s effectiveness through comprehensive simulations and statistical analyses, including spectral density, frequency distribution, and autocorrelation studies of the generated frequency sequences. The results show a significant enhancement in the unpredictability and uniformity of frequency distributions compared to traditional pseudo-random number generator-based approaches. Specifically, the frequency distributions of the drones exhibited a relatively uniform spread across the available spectrum, with minimal discernible patterns in the frequency sequences, indicating high unpredictability. Autocorrelation analyses revealed a sharp peak at zero lag and linear decrease to zero values for other lags, confirming a general absence of periodicity or predictability in the sequences, which enhances resistance to predictive attacks. Spectral analysis confirmed a relatively flat power spectral density across frequencies, characteristic of truly random sequences, thereby minimizing vulnerabilities to spectral-based jamming. Statistical tests, including Chi-squared and Kolmogorov-Smirnov, further confirm the unpredictability of the frequency sequences generated by QRNG, supporting enhanced security measures against predictive attacks. While some short-term correlations were observed, suggesting areas for improvement in QRNG technology, the overall findings confirm the potential of QRNG-based FHSS systems in significantly improving the security and reliability of drone communications. This work contributes to the growing field of quantum-enhanced wireless communications, offering substantial advancements in security and reliability for drone operations. The proposed system has potential applications in military, emergency response, and secure commercial drone operations, where enhanced communication security is paramount.

Abubakar Salihu, Muhammad Mukhtar Aliyu, Nur Fadillah Nurchalis

Artificial intelligence (AI) has a profound influence on various facets of modern-day society, notably within the realm of education. Its application in educational settings is extensive, primarily aimed at improving the methods of instruction and knowledge acquisition. Thus, this research investigates the impact of AI tools (ChatGPT, Google Bard) on the creative writing skills of Nigerian undergraduates using a pretest-posttest quasi-experimental research design. Eighty (80) third-year undergraduates participated in the study. Data were collected using pretest-posttest writing tasks. The writing scripts were graded using creative writing assessment rubrics. Paired sample t-test analysis was conducted to compare the pretest-posttest writing scores using SPSS. The results of the analysis showed a significant improvement in the participants’ overall writing scores after using the AI tools. The results also show significant improvement in all the aspects of creative writing: image, voice, characterization and story. Finally, the study makes some recommendations for practice and further studies.  

Felix Menne, Felix Dörr, Julia Schräder et al.

Abstract Background Psychiatry faces a challenge due to the lack of objective biomarkers, as current assessments are based on subjective evaluations. Automated speech analysis shows promise in detecting symptom severity in depressed patients. This project aimed to identify discriminating speech features between patients with major depressive disorder (MDD) and healthy controls (HCs) by examining associations with symptom severity measures. Methods Forty-four MDD patients from the Psychiatry Department, University Hospital Aachen, Germany and fifty-two HCs were recruited. Participants described positive and negative life events, which were recorded for analysis. The Beck Depression Inventory (BDI-II) and the Hamilton Rating Scale for Depression gauged depression severity. Transcribed audio recordings underwent feature extraction, including acoustics, speech rate, and content. Machine learning models including speech features and neuropsychological assessments, were used to differentiate between the MDD patients and HCs. Results Acoustic variables such as pitch and loudness differed significantly between the MDD patients and HCs (effect sizes 𝜼2 between 0.183 and 0.3, p < 0.001). Furthermore, variables pertaining to temporality, lexical richness, and speech sentiment displayed moderate to high effect sizes (𝜼2 between 0.062 and 0.143, p < 0.02). A support vector machine (SVM) model based on 10 acoustic features showed a high performance (AUC = 0.93) in differentiating between HCs and patients with MDD, comparable to an SVM based on the BDI-II (AUC = 0.99, p = 0.01). Conclusions This study identified robust speech features associated with MDD. A machine learning model based on speech features yielded similar results to an established pen-and-paper depression assessment. In the future, these findings may shape voice-based biomarkers, enhancing clinical diagnosis and MDD monitoring.

Yuehua Yang, Fangkui Wang, Jialin Jiang et al.

Soil drench treatment using <i>Paenibacillus polymyxa</i> strain KN-03 was applied to citrus plants infected with <i>Candidatus</i> Liberibacter asiaticus (<i>C</i>Las). The infection status was assessed using PCR and a real-time quantitative PCR detection system (qPCR). The application of KN-03 resulted in a notable reduction in <i>C</i>Las levels in citrus plants. Specifically, by the 257th day post treatment commencement, following 24 KN-03 applications, the negative rates of <i>C</i>Las in the vein, root tip, and shoot tip were 50%, 0%, and 50%, respectively. After 24 cycles, KN-03 application significantly enhanced plant growth and stimulated reactive oxygen production in citrus leaves compared to control plants. Transcriptome analysis identified specific upregulated pathways. Furthermore, flora analysis revealed an increased abundance of microorganisms possessing potential utilization value, including <i>Burkholderia-Caballeronia-Paraburkholderia</i>, <i>uncultured_bacterium_o_Acidobacteriales</i>, <i>uncultured_bacterium_f_Gemmatimonadaceae</i>, and <i>Rhodanobacter</i>, in the root zone. Moreover, the BugBase analysis indicated that KN-03 treatment increased the abundance of beneficial rhizosphere bacteria associated with biofilm formation, element mobilization, and stress tolerance. These findings support the utility of <i>Paenibacillus polymyxa</i> KN-03 as an effective plant-growth-promoting bacterium for <i>C</i>Las management, with additional benefits for plant growth and soil health, specifically offering detoxification resources for shoot tip grafting.

Jian Yang, Lei Zhang, Jun Zhang et al.

In this study, the mechanical models of a multilayer combined extrusion cylinder and a steel-wire-winding extrusion cylinder were established and compared using a finite element simulation and existing experimental cases. This work provides theoretical support for the selection of an ultrahigh-pressure extrusion cylinder. Comparative analysis of an ultrahigh-pressure extrusion structure was carried out. The mathematical optimization model is established based on the mechanical model, and the ultimate bearing capacities of the schemes are compared. Additionally, the winding mode and the number of core layers of the extrusion cylinder are compared and analyzed, which provides a theoretical basis for the parameter design of the steel-wire-winding ultrahigh-pressure extrusion cylinder. This work holds good theoretical significance and practical value for the promotion and application of ultrahigh-pressure hydrostatic extrusion technology.

Waricha Janjindamai, Anucha Thatrimontrichai, Supaporn Disneevate et al.

Objective: It remains unclear if changes in neonatal care have resulted in better outcomes for extremely preterm infants (EPTs). This study was to evaluate neonatal mortality and morbidity in EPTs. Material and Methods: A retrospective cohort study of EPTs at a gestational age (GA) ≤28 weeks, who were admitted to the neonatal intensive care unit between January 2004 and December 2018. The study was divided into 2 periods, from 2004-2010 and 2011-2018. The likelihood ratio test in Multiple Cox regression models were used to determine adjusted hazard ratios (aHR) for differences in mortality among the two periods. Results: A total of 188 EPTs were enrolled. The overall median (interquartile range), GA and birth weight of the enrolled infants were 26 (25, 27) weeks and 780 (667, 875) g, respectively. The mortality rate was 66/188 (35.1%). The mortality rate between 2004-2010 and 2011-2018 decreased from 44.6% to 32.8%, but was not statistically significant (p-value=0.170). Multiple Cox regression analysis of mortality rate demonstrated statistical significance with infants of 23-24 and 25-26 weeks GA VS 27-28 weeks GA [aHR 3.85, 95% confidence interval (CI) (1.95, 7.58), p-value<0.010] and [aHR 1.92, 95% CI (1.09, 3.35), p-value<0.010], respectively. Pregnancy complications [aHR 2.24, 95% CI (0.96, 5.24), p-value=0.040)] and EPTs intubated VS early CPAP at birth [aHR 2.41, 95% CI (1.36, 4.25), p-value<0.010] were statistically significant. Conclusion: The mortality rate of EPTs decreased with advancing GA. Prenatal care of pregnancy complications and improving care practices might reduce the mortality rate.

A. V. Veretyokhin

The digital advertising development features and prospects in the world and in the Russian Federation in particular have been considered. An approach to defining the advertising concept essence in the digital field has been presented. A summary of the scientific research results has made it possible to identify the industry’s growth constraints and its main development drivers, as well as define the importance and distinguishing features of modern advertising campaigns in the digital space. Based on analysis of current data from relevant organisations for the digital advertising market, an increase in growth rates has been identified overall by region and country, as well as for individual advertising segments.

Sharon Jessica Fandy

Parkinson’s disease (PD) is the most common neurological disease globally, only second to Alzheimer’s disease. One of the emerging treatments for PD is nutraceuticals. Grape seed extract (GSE) has a high concentration of polyphenolic compounds possessing antioxidant and neuroprotective capacity that may be valuable for neurodegenerative diseases. So far, there is no review summarizing the neuroprotective effect of GSE on PD, even though it is crucial to provide an insight into GSE as a potential natural treatment for PD. This systematic review aims to summarize the neuroprotective effect of grape seed extract (GSE) in Parkinson’s Disease in vivo and in vitro and their mechanism. The author performed a literature search using PubMed, Science Direct, Scopus, Sinta, and Garuda databases with keywords comprising “Neuroprotective”, “Grape Seed,” and “Parkinson’s disease.” Out of 1611 studies retrieved, 20 articles fit the inclusion criteria and became the basis for this review. The author analyzed and extracted the records regarding the neuroprotective effect and potential anti-PD properties from the studies. The analysis summarized that GSE could significantly improve the biological hallmarks of PD with numerous mechanisms, including antioxidant, anti-inflammation, protection of dopaminergic neurons, anti-amyloid effect, anti-apoptotic, neurogenesis, and synaptogenesis. Although the precise mechanism underlying PD is still elusive, treatment should target not only a single cause of PD but instead several pathways that could lead to the disease. In conclusion, GSE should be considered a potential nutraceutical in clinical trials to prevent and alleviate Parkinson’s disease by multiple mechanisms.

Risan Putra Anggara, Purnawarman Musa, Sri Lestari et al.

Corona Virus Disease 2019 (Covid-19) has stopped all aspects of human life, including the world of education. The Ministry of Education of the Republic of Indonesia has stopped face-to-face teaching and learning activities in schools, replacing them with online methods. Work from Home (WFH) is an adaptation of activities as applied online methods to anticipate learning activities during the Covid-19 Pandemic. Learning based on digital transformation technology utilizes network technology entirely online. The application of e-learning technology in the teaching and learning process is a choice for various educational institutions. The use of technology can maximize students 'learning time efficiency and increase students' concentration. Learning with the Virtual Reality (VR) method directs students to discoveries, motivates, encourages, and provides more curiosity for students in learning. Besides VR, Augmented Reality (AR) is a learning method for students to interact with virtual objects and real objects. The author proposes e-learning based learning in Natural Sciences (IPA) subjects in grade 3 in Elementary Schools. The research proposal develops lessons using a virtual approach from real events and provides phenomena of natural occurrences. Science lessons in Elementary Schools increase the curiosity of students scientifically. This method will help students develop the ability to ask questions and find answers to natural phenomena. The research stages carried out in application development are analysis, design, implementation, and application testing. The test results by adding e-learning to traditional learning methods impacted students' understanding of the material with an increased level of understanding by 24%.

Jamal Hallajzadeh, Alireza Milajerdi, Željko Reiner et al.

Background: Recently a number of trials investigated the effect of N-acetylcysteine (NAC) administration on inflammatory markers and homocysteine (Hcy). However, their findings are controversial. The aim of this paper is to present a meta-analysis and give a review of all randomized controlled trials (RCTs) in order to determine the effects of NAC on inflammatory markers and Hcy. Methods: An electronic search was conducted using PubMed, Scopus, Cochrane Library, Google scholar and Web of Science databases from inception until April 2019. A study quality assessment was performed using the Jadad scale and heterogeneity between studies was statistically computed using Cochrane’s Q test and I-square (I2). Data were pooled using a random-effects model and weighted mean difference (WMD) was considered as the overall effect size. Results: Out of 1115 potential citations, 10 studies (reported 13 effect sizes for different parameters) met the inclusion criteria and were eligible for this meta-analysis. NAC supplementation resulted in a significant reduction in Hcy levels (WMD: -2.05; 95% CI: -3.73, -0.37). NAC administration did not affect C-reactive protein (CRP) levels (WMD: 0.06; 95% CI: -0.21, 0.34), tumor necrosis factor-α (TNF-α) levels (WMD: 0.07; 95% CI: -0.27, 0.40), and interleukin 6 (IL-6) (WMD: -0.23; 95% CI: -1.23, 0.77). Conclusions: It could be concluded that this meta-analysis of RCTs demonstrated that NAC administration to various patients significantly improved circulating Hcy, but did not affect CRP IL-6 and TNF-α levels.

Lucas Martins Pion, Paolo Alfredini

Considering the demand for mooring larger ships at Brazilian port terminals, both private and public, in a scenario of growing exports, engineering interventions that can provide improvements in the vessel’s maximum allowed dimensions can represent significant profits. Hence, this work presents an approach of Nautical Bottom, defined as the minimum depth in which ships can navigate without significant adverse effects in ship control and maneuverability without physical damage, with the goal of raising the maximum ship draft allowed in nautical spaces with fluid mud beds. Due to its rheological properties, fluid mud, in general, allows for vessels navigate with low or negative under keel clearance, respecting the established Nautical Bottom concepts. In addition, fluid mud layer thickness at port areas can possibly vary according to hydrodynamics and sedimentologic variations. This article presents an analysis of fluid mud thickness variations within the Itajaí Port Complex (Santa Catarina, Brazil) turning basin, where fluid mud layers are up to 2.5 meters thick, by means of analyses of bathymetric surveys and numerical modeling. The Itajaí Port Complex is located at the Itajaí-açu river estuary, which presents high variability of river discharge and suspended sediments. From bathymetric surveys, it is possible to observe fluid mud thickness from 0.5 to 2.5 meters. Numerical simulation results indicate suspended sediment load as a main environmental aspect for fluid mud thickness variations in the study area.

Nina Emsi Pramesti, Ririh Yudhastuti

Fresh milk was one of food ingredients with high nutrition and widely consumed by people with no processed before consumed so it’s easily damaged. This research aims to determine the bacteriological quality of the milk before after distribution, and to analyze an increase of the bacteria Escherichia coli during distribution. The research was an descriptive with observational methods. Subjects were selected by purposive sampling with the number of samples were 4 samples of milk before distribution and 20 samples of milk after distribution of Escherichia coli test. Milk samples were tested before and after the distribution. After distribution during 2 hours, 1 sample was taken every 20 minutes every day during 4 days continuously. Data obtained by interviewing, observing and testing of milk samples to the laboratory. Data were analyzed by descriptive and simple linear regression analysis. The results showed that hygiene and sanitation in the milk process and distributions were not good. The result of laboratory test showed that fresh milk positively contaminated with Escherichia coli was exceeds the standard of microbial contamination in food set by SNI 7389: 2009. The number of Escherichia coli increased during 2 hours for distribution based on a statistical test simple linear regression. Escherichia coli bacterial contamination in milk could be caused from lack of awareness to sanitary hygiene of milk process. Bacteria increased during distribution may be due to lack of good hygiene and sanitation during the distribution process. Therefore it necessary to carry out the processing of milk before the consumption, to monitor the sanitation of the farms by prevent the damage, improve of sanitary and to test the samples of fresh milk regularly for keep a good quality of product.

Jian Zhou, Can-yan Zhu

In the next-generation heterogeneous wireless networks, a mobile terminal with a multi-interface may have network access from different service providers using various technologies. In spite of this heterogeneity, seamless intersystem mobility is a mandatory requirement. One of the major challenges for seamless mobility is the creation of a network selection scheme, which is for users that select an optimal network with best comprehensive performance between different types of networks. However, the optimal network may be not the most reasonable one due to compensation of MADM (Multiple Attribute Decision Making), and the network is called pseudo-optimal network. This paper conducts a performance evaluation of a number of widely used MADM-based methods for network selection that aim to keep the mobile users always best connected anywhere and anytime, where subjective weight and objective weight are all considered. The performance analysis shows that the selection scheme based on MEW (weighted multiplicative method) and combination weight can better avoid accessing pseudo-optimal network for balancing network load and reducing ping-pong effect in comparison with three other MADM solutions.

Roholla Mahdavi

With regard to the ever-increasing need for energy in current societies to satisfy various requirements, scientists and researchers from different countries, such as Iran, have a basic approach in their agenda to achieve renewable energies، The scientists believe that with regard to the limited fossil fuels and their environmental pollutions, renewable and clean energies can be the first alternative to generate energy، Our country, Iran, has numerous capabilities in the field of generating new and renewable energies، This fact emphasizes the need for an optimum model to develop the use of renewable energies، In line with this objective the costfunction is chosenas the objective function، Given the potential and limits ofrenewable energy (resources Limited), Consumptionof electricpowerin each of16regions (apply Limited) confidencelimits  of renewable energy (technical limitations), the model was designed and with use Robust optimization model was solved in LINGO software،The optimum of using renewable energies suggests the 36،71% generation of small hydropower energy, 18،22% wind energy, 17،19% biomass energy, 13،43% geothermal energy, 12،53% tidal energy, and 1% solar energy. 2- Ciaschini, M et al (2011), “The Effects of Environmental Taxation Through a Dynamic CGE Model, Environmental Federalism: The Political Economy of the Design of Local Taxation and Environmental Protection”, Ancona, Italy, December 9-10, 2011   3- Devarajan, S. (1988), “Lecture Notes on Computable General Equilibrium Models”, John F. Kennedy School of Government, Harvard University, Mimeo, Processed. 4- Hosoe.N and et al (2010), “Textbook of Computable General Equilibrium Modelling: Programming and Simulations, Printed and bound in Great Britain by CPI Antony Rowe”, Chippenham and Eastbourne. 5- IEA (2012), World Energy Outlook. 6- Kulmer Y (2011), “Directed Technological Change in a Bottom-Up/Top-Down CGE model: Analysis of Passenger Transport, "Wegener Center for Climate and Global Change”, University of Graz, Austria. 7- Lofgren.H and et.al (2002), “A Standard Computable General Equilibrium (CGE) Model in GAMs”, International Food Policy Research Institute. 8- Orlov. A, Grethe. H and McDonald S, (2011), “Energy Policy and Carbon Emission in Russia: A Short Run CGE Analysis”, Presented at the 14th Annual Conference on Global Economic Analysis”, Venice, Italy.Solaymani. 9- S and Kari. F (2014), “Impacts of Energy Subsidy Reform on the Malaysian Economy and Transportation Sector”, Energy Policy, pp. 115-125. 10- Zhengning Pu and Hayashiyama Y (2012), Energy Resource Tax Effects on China’s Regional Economy by SCGE Model, Environmental Economics, vol. 3, issue 1, pp. 41-52.       bidi13- Stern,  J. (2007), “Gas-OPEC: A Distraction from Important Issues of Russian Gas Supply to Europe”. Oxford Energy Comment.   14- J.F. Nash Jr. (1950), “The Bargaining Problem”, Econometrica, 15(2):155_162. 17- Avrachenkov, K., Elias, J.,  Martignon, F., Neglia, G. and L. Petrosyan (2011), “A Nash bargaining solution for Cooperative Network Formation Games”, Networking 2011, pages 307–318, 2011 16- Shapley ,L. (1953),  “A Value for n-person Games”, In H. Kuhn and A. Tucker, editors, Contribution to the Theory of Games II, page 307. Princeton University Press. 17-  Shapley, L., and Shubik, M. (1969), “On Market Games”, Journal of Economic Theory, 1, 9-25. 19- Maskin, Erik (2003), “Coalitional Bargaining with Externalities, Keynote Lecture for the European Economic Association Conference 2003, Stockholm. 20-OME. “Future Natural Gas Supply Options and Supply Costs for Europe”, Report to Madrid Forum, Observatoire M´editerran´een de l’ Energie, 2004 21- Egging, R. and Gabriel, S. A.(2006), “Examining Market Power in the European Natural Gas Market”, Energy Policy, 34:2762–2778.

WANG Xiao-ya

Electromagnetic interference mechanism of interconnect cables was analyzed, and mathematical model of multi-conductor interconnect crosstalk coupling was established. Capacitance matrix and inductance matrix of mine-used four-core interconnect cables were extracted using the finite element analysis software Ansys. The electromagnetic interference of interconnect cables of electronic equipment was predicted and analyzed applying field-road combined method, and the numerical calculation result was consistent with the theoretical analysis result.