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Composite cis-acting epigenetic switches in eukaryotes:: lessons from Drosophila Fab-7 for the Igf2-H19 imprinted domain

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GENETICA 2003年第2期117卷 199-207页

作者： Brown, JP Singh, PB Cowell, IG Roslin Inst Edinburgh Nucl Programming Lab Div Gene Express & Dev Roslin EH25 9PS Midlothian Scotland

One of the central problems of eukaryotic gene regulation is to understand the mechanism(s) by which the activity of enhancer elements is circumscribed such that they only act upon their cognate promoter sequences. Studies on the bithorax gene complex (BX-C) in Drosophila have highlighted the potential problem of enhancer promiscuity and detailed molecular and genetic analyses are now providing insight into how this gene complex resolves the problem through the activity of boundary/silencer elements that can block the communication between enhancers and promoters. Analysis of the mouse Igf2-H19 imprinted locus also suggests a role for boundary/silencer elements, but in this case these elements are invoked to account for the preferential expression of Igf2 and H19 from the paternally and maternally inherited chromosomes respectively despite the presence of functional downstream enhancers. We discuss recent work that has illuminated both of these systems and consider what parallels exist between them.

关键词： boundary epigenetics parental imprinting Polycomb-group silencer

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Energy-Efficient Optimization Using WSN Framework for Enhanced Smart Agriculture

Energy-Efficient Optimization Using WSN Framework for Enhanc...

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international conference on Communication and Electronics Systems (ICCES)

作者： K. Malarkodi V. Janakiraman D. Sheela Carmel Mary Belinda M J V Balaji R. Rajeswari Saveetha School of Engineering SIMATS Saveetha University Chennai Easwari Engineering College Chennai PERI Institute of Technology Chennai

ISBN: (数字)9798350377972

ISBN: (纸本)9798350377989

Wireless Sensor Networks (WSNs) has revolutionized farming techniques, especially in the field of smart agriculture. this innovative approach enhances both the quantity and quality of crop yields while minimizing labor and resource input. By deploying WSNs across agricultural fields, farmers can automate various monitoring and management tasks, such as operating water pumps and valves. these networks consist of multiple relay sensors and agricultural field sensors that continuously monitor critical parameters like soil moisture, temperature, irrigation status, and pH levels. Each sensor is responsible for data collection, energy management, and ensuring reliable data delivery. Despite the advantages, WSNs face challenges such as high energy consumption, connectivity issues, and latency, all of which can adversely affect crop yields. this paper proposes an IoT-WSN framework designed to mitigate these issues and enhance the functionality of agricultural smart lands. In proposed system, sensors in the agricultural field first gather pertinent data and then select a group of cluster heads through a Multi-Standard Selection these cluster heads are vital for structuring the network and ensuring effective data gathering. Relay sensors are crucial for transmitting data securely from the field to a base station. To optimize this data relay process, utilize a Linear Integer programming Method (LIPM). Our simulations and analytical results demonstrate that this framework effectively prolongs the lifespan of sensors while ensuring that data is transmitted accurately and promptly from agricultural fields to end users. this improvement not only enhances the efficiency of agricultural operations but also contributes to sustainable farming practices by optimizing resource usage and reducing manual intervention.

关键词： Temperature sensors Smart agriculture Integer programming Wireless sensor networks Reliability Relays Intelligent sensors Crop yield Monitoring Farming

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Multi-attention DeepEMD for Few-Shot Learning in Remote Sensing

Multi-attention DeepEMD for Few-Shot Learning in Remote Sens...

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IEEE Joint international Information Technology and Artificial Intelligence conference (ITAIC)

作者： Zhengwu Yuan Wendong Huang College of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (数字)9781728152448

ISBN: (纸本)9781728152455

Currently in the field of remote sensing (RS), scene classification is a crucial research subject. the usual method is to gather plenty of scene classification data manually annotated by experts in the field, and then use the dataset to train a scene classification model. Typically, the better the deep learning model requires more labeled data. therefore, how to obtain a model with good classification performance when there is only a small amount of labeled data, this becomes a well-known few-shot classification problem. In this study, a new few-shot learning scheme is developed for RS scene classification. Our method is based on deepEMD with spatial and channel attention modules(CBAM) to capture subtle but distinguishing features. To get the significant weights of pixels in the EMD formulation, an attention-reference mechanism is designed, which can sufficiently leverage subtle local features and minimize the influence posed by the cluttered background. To avoid overfitting, label smoothing that can improve the generalization performance of the model is introduced. Comprehensive experiments are conducted to validate the method and achieve new state-of-the-art performance on three popular RS scene datasets, namely UC Merced, AID and OPTIMAL-31. Furthermore, two ablative studies also indicate that the components are conducive to fast convergence and high accuracy.

关键词： Image analysis Smoothing methods Learning (artificial intelligence) Linear programming Data models Task analysis Remote sensing

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the Development of the Flexible Periodic Vehicle Routing Problem Model for Gas Cylinders Distribution

The Development of the Flexible Periodic Vehicle Routing Pro...

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international conference on Business and Industrial Research (ICBIR)

作者： Nikko Gunawan Ahmad Rusdiansyah Fadila Isnaini Department of Industrial and Systems Engineering Institut Teknologi Sepuluh Nopember Indonesia Department of Business Management Institut Teknologi Sepuluh Nopember Indonesia

ISBN: (数字)9798350383027

ISBN: (纸本)9798350383034

Distribution plays a crucial role in business processes, and an efficient distribution system is necessary to minimize costs. Many companies, including those in the gas industry, are developing distribution models to reduce costs and maximize profits. Industrial gases are the main component of various sectors, such as the health industry, consumer goods, and more. Researchers have developed a model of Flexible Periodic Vehicle Routing Problem (FPVRP) for gas cylinder distribution, which considers profitability. the purpose of this model is to maximize profitability by considering storage costs, travel costs, and fixed costs. To achieve this, researchers have developed scheduling and routing methods by combining several models, such as the FPVRP, Inventory Routing Problem (IRP), Vehicle Routing Problem Simultaneous Delivery and Pickup (VRPSDP), and Vehicle Routing Problem with Profits (VRPPs). the model uses various models, such as the Visit Frequency Optimization Procedure (VFOP), which considers visit frequency and day combinations as decision variables, Nearest Neighbor, 2-opt Swap, and Taboo Search. the researchers have used Visual Basic Application (VBA) in Microsoft Excel to develop computerized models. the experiment results have shown that the proposed gas cylinder distribution model can provide maximum profit by reducing the costs of the entire system.

关键词： Costs Profitability Computational modeling Vehicle routing Stochastic processes Routing Linear programming Mathematical models Numerical models Vehicle dynamics

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A Learning Mechanism for BRBES Using Enhanced Belief Rule-Based Adaptive Differential Evolution

A Learning Mechanism for BRBES Using Enhanced Belief Rule-Ba...

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international conference on Informatics, Electronics & Vision (ICIEV)

作者： Raihan Ul Islam Mohammad Shahadat Hossain Karl Andersson Pervasive and Mobile Computing Laboratory Luleå University of Technology Sweden University of Chittagong Bangladesh

ISBN: (数字)9781728193311

ISBN: (纸本)9781728193328

Nowadays, belief rule-based expert systems (BRBESs) are widely used in various domains which provides a framework to handle qualitative and quantitative data by addressing several kinds of uncertainty. Learning plays an important role in BRBES to upgrade its knowledge base and parameters values, necessary for the improvement of the prediction accuracy. Different optimal training procedures such as Particle Swarm Optimisation (PSO), Differential Evolution (DE), and Genetic Algorithm (GA) have been used as learning mechanisms. Among these procedures, DE performs comparatively better than others. However, DE's performance depends significantly in assigning near optimal values to its control parameters including cross over and mutation factors. therefore, the objective of this article is to present a novel optimal training procedure by integrating DE with BRBES. this is named as enhanced belief rule-based adaptive differential evolution (eBRBaDE) algorithm because it has the ability to determine the near-optimal values of both the control parameters while ensuring the balanced exploitation and exploration in the search space. In addition, a new joint optimization learning mechanism by using eBRBaDE is presented where both parameter and structure of BRBES are considered. the reliability of the eBRBaDE has been compared with evolutionary optimization algorithms such as GA, PSO, BAT, DE and L-SHADE. this comparison has been carried out by taking account of both conjunctive and disjunctive BRBESs while predicting the Power Usage Effectiveness (PUE) of a datacentre. the comparison demonstrates that the eBRBaDE provides higher prediction accuracy of PUE than from other evolutionary optimization algorithms. Contribution-An enhanced differential evolution algorithm has been proposed in this paper, which is later used as a novel optimal training procedure for BRBES.

关键词： Optimization Statistics Sociology Training Uncertainty Learning systems Linear programming

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Turkish Sign Language Video Generation from Pose Sequences Using a Conditional GAN Model

Turkish Sign Language Video Generation from Pose Sequences U...

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international conference on Computer Science and Engineering (UBMK)

作者： Feyza Ozkan Hatice Kubra Tekin Hacer Yalim Keles Computer Engineering Department Hacettepe University Ankara Turkiye

ISBN: (数字)9798350365887

ISBN: (纸本)9798350365894

Sign language is a visual gestural language that uses hand shapes, facial expressions, and body movements to convey meaning, and it is essential for communication among individuals with hearing impairments. Sign language users often face challenges in environments where sign language is not readily available. that is primarily because producing sign language requires a real signer, which can be time-consuming and labor-intensive. One potential solution to make more available sign language to its users is the use of artificial intelligence to generate sign language. While there have been global studies exploring AI-generated sign language videos for various sign languages, the research in this field is still evolving and active. Specifically, for Turkish Sign Language (TSL), only a few studies have been conducted. Our study introduces a model that combines pose sequences with reference images of signers to generate authentic sign language videos. Utilizing a conditional generative adver-sarial network (cGAN), the model generates video sequences by particularly focusing on complex finger details, arm positions while preserving the appearance of the reference image. the AUTSL dataset is employed for training and testing our model. Our early results demonstrate our model's capability to produce realistic hand and arm movements while effectively capturing finger details; we got 45.5 with th e Frechet inception distance (FID), 35.8 with the peak-signal-to-noise ratio (PSNR), and 0.9 with the structural similarity index measure (SSIM).

关键词： Training Sign language Visualization Shape Video sequences Refining Focusing Training data Linear programming Videos

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Attribute Data Related to Permissible Range of Extreme Expressions in Japanese Reality Shows

Attribute Data Related to Permissible Range of Extreme Expre...

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Big Data, Cloud Computing, Data Science & Engineering (BCD)

作者： Yohei Mori Hironori Takuma Management Engineering Mayor Chiba Institute of Technology Chiba Japan Department of Digital Transtormation Chiba Institute of Technology Chiba Japan

ISBN: (数字)9798350394191

ISBN: (纸本)9798350394207

In recent years, television ratings have been on a declining trend. One reason for this is the regulation of extreme content, which has led to a homogenization of programming. Extreme content is deemed inappropriate for current societal conditions. However, many viewers feel that television has become boring due to the absence of such extreme content. therefore, we conducted a survey regarding extreme content broadcast on television. Using an online questionnaire, we created a survey with ten questions based on content that viewers judged as extreme from past programs. Additionally, the survey targeted respondents aged 18 to 24, enabling us to examine content considered too extreme to be aired by a demographic known for having a higher tolerance for extreme material. the survey results indicated that actions likely to cause accidents or lifelong disabilities cannot be broadcast. It was also inferred that if the survey included all age groups, the range of acceptable content would likely be even narrower. In this study, we will conduct a survey that includes viewers of all ages. We will use survey tools to gather a wide range of data and perform logistic regression analysis to predict the factors that differentiate the broadcasting of extreme content. then, based on the collected results and demographic data, we will consider the factors that lead to the rejection of extreme content.

关键词： Surveys Logistic regression Ethics Cloud computing TV programming Data science Broadcasting Market research Regulation

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Nanostructured silicon platform for detection of specific gene sequences 9

Nanostructured silicon platform for detection of specific ge...

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9th international conference on Advanced Topics in Optoelectronics, Microelectronics, and Nanotechnologies (ATOM-N)

作者： Banu, Melania Simion, Monica Popescu, Marian Savu, Lorand Natl Inst Res & Dev Microtechnol IMT Bucharest 126A Erou Iancu Nicolae St Bucharest 077190 Romania Univ Bucharest Fac Biol 91-95 Splaiul Independentei Ave Bucharest 050095 Romania Genet Lab SRL 9 Capitan Nicolae Drossu St Bucharest 012072 Romania

ISBN: (数字)9781510626140

ISBN: (纸本)9781510626140

the use of glass supports in microarray technology is favored by their chemical stability, low level of auto-fluorescence and excellent functionalization capabilities. However, the flat surfaces generate steric hindrance during the hybridization reaction, hence reducing the signal detection in genotyping applications. Herein, a new microarray platform based on nanostructured Si was designated to be used for detection of specific gene fragments corresponding to HPV strains. We investigated the contribution on detection of the functional groups deriving from the chemical surface modification, combined with the effects of nanostructured Si. Uniform spot shapes were associated to surface wetting behaviour and the immobilization and hybridization datasets were evaluated by fluorescence analysis.

关键词： microarray nanostructured silicon functionalization genotyping

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Zeroth-Order Feedback Optimization for Inverter-Based Volt-VAR Control in Wind Farm

Zeroth-Order Feedback Optimization for Inverter-Based Volt-V...

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IEEE international conference on Power and Power and Renewable Energy (ICPRE)

作者： Siyun Li Wenchuan Wu Jun Xu Jihui Dong Fanhua Wang Qihai Yuan Department of Electrical Engineering Tsinghua University Beijing China Sichuan Energy Internet Research Institute Tsinghua University Chengdu China Inner Mongolia Chahar New Energy Co. Ltd. China Ulanqab China Beijing Kedong Electric Power Control System Co. Ltd. China Beijing China

ISBN: (数字)9798350377460

ISBN: (纸本)9798350377477

Significant penetration of wind power into power systems gives rise to severe power quality concerns, especially voltage violations. In wind farms, the system model parameters are usually inaccurate or even unknown, which brings great difficulties to the implementation of conventional model-based control methods. Moreover, wind farms are usually partially observable since only a few measurements are available at critical nodes. To provide a practical Volt/Var control (VVC) strategy for such networks, a novel model-free VVC method based on zeroth-order feedback optimization is proposed in this paper, which doesn't rely on any system model parameters. Firstly, the proposed method continuously collects system output measurements and evaluates the objective function value at the current input and at the measured output, thus constructing gradient estimates. then, the control inputs are updated via an accelerated gradient projection algorithm, where the step length is selected based on Barzilai-Borwein-like rules for constrained optimization to improve the speed of convergence. Numerical tests exhibit a promising performance of the proposed method in voltage control.

关键词： Renewable energy sources Current measurement Wind farms Wind power generation Linear programming Numerical models Voltage control Projection algorithms Optimization Convergence

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Energy-Efficient Traffic Scheduling in IP over WDM Networks

Energy-Efficient Traffic Scheduling in IP over WDM Networks

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international conference on Next Generation Mobile Applications, Services and Technologies

作者： Zaid H. Nasralla Taisir E. H. El-Gorashi Mohamed O. I. Musa Jaafar M. H. Elmirghani School of Electronic and Electrical Engineering University of Leeds LS2 9JT United Kingdom

ISBN: (纸本)9781479986613

In this paper, we investigate the energy efficiency that can be achieved by using traffic scheduling in IP over WDM networks. A mixed integer linear programming model is developed to optimize routing and scheduling in dynamically arriving demands, where part of the demands can be allocated within a sliding window. the results show that scheduling improves the energy efficiency of non-bypass IP/WDM networks, with traffic grooming by up to 25% and blocking is reduced by 30%.

关键词： Traffic scheduling Advance Reservation Energy-Efficiency

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