Availability Of Continuous Data Research Articles

Pursuit of Happiness in Consumer Society: A Study on OECD Countries and Türkiye

Understanding the relationship between societal consumption desires and happiness levels contributes to the development of economic policies aimed at enhancing welfare. Therefore, this study, which investigates the relationship between consumption and happiness, consists of two stages. In the first stage, the happiness of economic units is measured by the Happiness Index, and consumption data is represented by the ratio of household disposable income to expenditures as provided by the OECD. Granger Causality Analysis was applied to data from 30 OECD countries, including Turkey, with continuous data availability for the period 2018-2021. The findings indicate no significant causality relationship. In the second stage, the relationship between consumption desires and happiness of economic units in Turkey was investigated using simple regression analysis. The results suggest that a 1% increase in consumption leads to an approximate 0,00287 unit decrease in happiness, indicating that an increase in the propensity to consume is associated with a decline in happiness levels. Consequently, this study finds no causality between happiness and consumption in OECD countries, while in Turkey, societal consumption desires negatively impact happiness. The findings are expected to contribute depth to the existing literature.

TO DISTRIBUTE THE ABNORMAL EVENT USING CM-DDS ALGORITHM, WITH SECURELY USING RSA RSA-IVDE ALGORITHM

Automating the secure distribution and storage of video data addresses inefficiencies in manual processes. The emphasis on secure distributed storage aligns with the increasing importance of safeguarding video data. Traditional approaches in distributed video data storage face limitations, like lack of scalability, privacy challenges in surveillance systems and suboptimal storage efficiency. This research addresses the existing limitations in distributed storage for video data by proposing a Central Moment-Driven Distributed Structure (CM-DDS) and an incremental RSA-driven Incremental Video Data Encryption (RSA-IVDE) method. The framework optimizes video data distribution across nodes, enhancing redundancy and fault tolerance for continuous data availability, even in the event of node failures. Emphasizing simplicity and accessibility, the user-friendly interface facilitates efficient management of large video datasets across various applications, including social networks, video games, surveillance and transportation networks. This comprehensive approach aims to provide a robust solution for secure distributed storage and transmission of video data while addressing the challenges identified in the existing research. The proposed approach surpasses other traditional methods with minimal decryption mean time (0.208s), minimal encryption mean time (0.182s) and minimal distribution mean time (1.620s).

Shared Parameter Network: An efficient process monitoring model

The use of deep learning methods for fault detection and diagnosis (FDD) has continued to gain research attention due to the continuous availability of data and the need for reliable FDD methods. In our previous work, we proposed a probabilistic bidirectional recurrent network (PBRN) for process prediction and detection of faults. A limitation of PBRN is the model size. In this paper, we reduce the computational requirements of the original PBRN by introducing a shared parameter network (SPN). The SPN uses a shared parameter space to learn relevant features for process prediction and fault detection. This shared parameter setting reduces the model size and training time significantly. Using the SPN, we achieved a 76 percent reduction in model size and a 48 percent reduction in training time. The training validation loss profile and fault detection performances of both models also demonstrate the superiority of the SPN.

Modelling PM2.5 for Data-Scarce Zone of Northwestern India using Multi Linear Regression and Random Forest Approaches

ABSTRACT PM2.5 (Particulate matter with aerodynamic diameter <2.5 m) concentrations above permissible limit causes air quality deterioration and hampers human health. Due to the lack of a good spatial network of ground-based PM monitoring sites and systematic checking, the availability of continuous data of PM2.5 concentrations at macro and meso scales is restricted. Present research estimated PM2.5 concentrations at high (1 km) resolution over Faridabad, Ghaziabad, Gurugram and Gautam Buddha Nagar, a data-scarce zone of the highly urbanized area of northwestern India for the year 2019 using Random Forest (RF), Multi-Linear Regression (MLR) models and Hybrid Model combining RF and MLR. It included Aerosol Optical Depth (AOD), meteorological data and limited in-situ data of PM2.5. For validation, the correlation coefficient (R), Root-Mean-Square Error (RMSE), Mean Absolute Error (MAE) and Relative Prediction Error (RPE) have been utilized. The hybrid model estimated PM2.5 with a greater correlation (R = 0.865) and smaller RPE (22.41%) compared to standalone MLR/RF models. Despite the inadequate in-situ data, Greater Noida has been found to have a high correlation (R = 0.933) and low RPE (32.13%) in the hybrid model. The most polluted seasons of the year are winter (137.28 µgm−3) and post-monsoon (112.93 µgm−3), whereas the wet monsoon (44.56 µgm−3) season is the cleanest. The highest PM2.5 level was recorded in Noida followed by Ghaziabad, Greater Noida and Faridabad. The findings of the present research will provide an input dataset for air pollution exposure risk research in parts of northwestern India with sparse monitoring data.

EPoSt: Practical and Client-Friendly Proof of Storage-Time

Data availability is the major concern of outsourced data storage services. While reliability is promoted by many storage providers, it is infeasible for users to verify these claims. Proofs of Storage-Time are proposed to address this issue: they allow a prover to convince a verifier that the prover indeed stores the outsourced data continuously during the whole storage period. These protocols, however, either fail to guarantee the actual duration of data possession, or require the client to perform a computationally expensive storing process for each file, marking them far from being practical. We present <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathsf {ePoSt}$ </tex-math></inline-formula> , the first secure, stateless and efficient Proof of Storage-Time protocol with public verifiability. Not only does it ensure continuous data availability, but it also minimizes the cost of the client, which is crucial for real-world deployment. Specifically, processing a 1GB file for outsourcing, in anticipation for 3 proof/verify interactions, each attesting a period of 1 year at 25 minutes intervals requires only 66.34 minutes. In contrast, state-of-the-art solution requires 51 hours of processing to prepare a file for outsourcing. Proof size and verification remains at a reasonable cost: a proof is of size 48.82KB, and can be verified in 36.05 ms. Furthermore, our solution enjoys public verifiability and remains stateless. The former allows the data owner to outsource the verification process, and the latter allows unlimited number of proofs and verification to be conducted after the file has been stored. These properties make <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathsf {ePoSt}$ </tex-math></inline-formula> particularly suitable for new business models such as decentralised storage networks (e.g., Filecoin).

Blockchain-based continuous data integrity checking protocol with zero-knowledge privacy protection

The cloud computing technology has emerged, developed, and matured in recent years, consequently commercializing remote outsourcing storage services. An increasing number of companies and individuals have chosen the cloud to store their data. However, accidents, such as cloud server downtime, cloud data loss, and accidental deletion, are serious issues for some applications that need to run around the clock. For some mission and business-critical applications, the continuous availability of outsourcing storage services is also necessary to protect users' outsourced data during downtime. Nevertheless, ensuring the continuous availability of data in public cloud data integrity auditing protocols leads to data privacy issues because auditors can obtain the data content of users by a sufficient number of storage proofs. Therefore, protecting data privacy is a burning issue. In addition, existing data integrity auditing schemes that rely on semi-trusted third-party auditors have several security problems, including single points of failure and performance bottlenecks. To deal with these issues, we propose herein a blockchain-based continuous data integrity checking protocol with zero-knowledge privacy protection. We realize a concrete construction by using a verifiable delay function with high efficiency and proof of retrievability, and prove the security of the proposal in a random oracle model. The proposed construction supports dynamic updates for the outsourced data. We also design smart contracts to ensure fairness among the parties involved. Finally, we implement the protocols, and the experimental results demonstrate the efficiency of the proposed protocol.

A general take on a Tecnomatix Process Simulate´s Digital Twin creation and its exchange of information with the TIA Portal and PLC SIM Advanced

Digital twins are rapidly establishing themselves as a necessary step in digital change also in the design of automated and robotic manufacturing systems. The digital twin serves as an interface between physical industrial products and digital worlds. This allows you to map the continuous availability of data throughout the lifecycle from product planning and development, production and commissioning to use and recycling. An important step towards this goal is to create digital twins of the components in order to create a database usable for the design of new production systems in a virtual environment. One of the possibilities of using the digital twins is testing and virtual commissioning of production systems. Instead of the classic CAD model, the digital twin replaces a detailed digital image of individual components, including their full functionality. The Digital Twin comprises the CAD model, kinematic behavior model a most important is the logical behavior model. Our goal is to create a digital twin component of the production system, integrate a CAD model, create a kinematic model and a logical behavior model. This digital twin will have signals assigned to it for logical behavior. The result is the verification and testing of the information exchange between the virtual control system and the virtual model, using the Software-in-the-Loop method and the Tecnomatix Process Simulate software environment on the digital twin side and the Siemens TIA Portal with PLC SIM Advanced on the controller side. The result of the knowledge is that the exchange of information is functional and usable for virtual commissioning.

ETPAC: ECC based trauma plight access control for healthcare Internet of Things

Healthcare Industry experiences a rapid change in the traditional way of providing Medical Services to Patients with the revolution of the Internet of Things (IoT) and the Digitization of services. The Healthcare IoT (HIoT) provides Hospitals to render excellent services to Patients at an optimized cost. The Healthcare IoT must ensure not to disrupt or tamper with sensitive Medical Information of the Patient in addition to the continuous availability of data and services. The proposed framework is designed for secure emergency access to Patient data over Healthcare IoT. Normally, the Doctor obtains the Shared Key directly from the Patient to access the Medical data. In Trauma Plight, a Patient pre-shares an Attribute based Key with a set of Secondary Authority in Trauma Plight (SATP) and access permission to the Doctor for utilizing Emergency Key from SATP. The Doctor retrieves the medical record by using the Attribute based key and the Emergency-key to medicate the Patient in Trauma. The proposed ECC model based Trauma Plight Access Control (ETPAC) reduces the Shared Secret Key generation time, Encryption, Decryption Time, Cipher-Text size with low Secret Key Size. The performance analysis indicates the enhanced security with reduced time complexity of Computation and Communication in ETPAC compared to Lightweight Break-glass Access Control, an Efficient Policy Hiding Attribute Based Access Control, and an Efficient and Robust Attribute based Encryption Supporting Access Policy Hiding in Healthcare IoT.

Суточная и сезонная динамика температуры поверхности города Волгограда

Цель – установить особенности суточной и сезонной динамики температуры поверхности в городе Волгограде (на примере 2018 года, «типового» по климатическим характеристикам) и выяснить, зависит ли её сезонный ход от особенностей подстилающей поверхности городской территории. Материалы и методы. Для выбора года исследования был проанализирован 20-летний ход температур воздуха в Волгограде, а также учитывалось наличие непрерывных данных о температурах подстилающей поверхности. Определение температуры городской поверхности проводилось путем обработки снимков теплого полугодия информационного продукта MOD11A2 (8-ми дневные растровые композиты дневной и ночной температур разрешением около 1 км). Геоинформационная обработка снимков осуществлялась в программе QGIS. По данным Global Land Cover (GLC) определены основные типы подстилающей поверхности на территории Волгограда. Результаты и обсуждение. Доля запечатанных поверхностей составляет 38,2 %. Составлена карта среднегодовых температур поверхности в Волгограде, отражающая основные особенности пространственного распределения положительных и отрицательных тепловых аномалий. Установлено, что сезонный ход среднесуточных, дневных и ночных температур подстилающей поверхности и приземного слоя воздуха в Волгограде представляет собой обращенную ветвями вниз параболу с максимумом, приходящимся на период 26 июня – 6 июля. Ход среднесуточных температур воздуха повторяет сезонный ход температуры поверхности города (r = 0,99). Выводы. Картографирование на основе данных MODIS с разрешением 1 км позволяет выявить пространственное распространение крупных положительных и отрицательных аномалий на территории города и его окрестностей. Выявлена значительная вариабельность значений среднесуточной температуры подстилающей поверхности в районах с высокой долей водных объектов, водно-болотных угодий и низкой степенью запечатанности почвенного покрова.

US Antiarrhythmic Drug Treatment for Patients With Atrial Fibrillation: An Insurance Claims-Based Report.

BackgroundCurrent American Heart Association/American College of Cardiology/Heart Rhythm Society guidelines and European Society of Cardiology guidelines recommend antiarrhythmic drugs (AADs) for maintenance of sinus rhythm in patients with atrial fibrillation. We assessed the concordance between healthcare provider real‐world practice and current guidelines with respect to first‐line AAD rhythm management.Methods and ResultsAdministrative claims data from the deidentified Optum Clinformatics Data Mart database were used. Patients were included if they were initiated on an AAD in 2015 to 2016, had 1 year of continuous data availability before their first AAD pharmacy claim, and had a diagnosis for atrial fibrillation within that period. Concordance was assessed by comparing the AAD initiated by the healthcare provider against guideline recommendations for first‐line treatment, given the presence of heart failure, coronary artery disease, both, or neither (as determined by International Classification of Diseases, Ninth Revision and Tenth Revision [ICD‐9 and ICD‐10] codes). Concordance was also assessed by provider type using Medicare taxonomy codes. For the 15 445 patients included, 51% of healthcare providers initiated AAD treatments with amiodarone, 18% flecainide, 15% sotalol, 8% dronedarone, 5% propafenone, and 2% dofetilide. The overall rate of guideline concordance was 61%, with differences by provider type: 67% for electrophysiologists, 61% for cardiologists, and 60% for others (internal medicine, etc).ConclusionsThere continues to be a sizable gap in concordance between practice and guidelines in first‐line rhythm management of patients with atrial fibrillation. Further research is needed to identify possible explanations for non–guideline‐recommended use of AADs, in addition to enhanced AAD educational strategies for practitioners.

Assessment of Different OPC UA Implementations for Industrial IoT-Based Measurement Applications

The industrial Internet of Things (IIoT) paradigm represents an attractive opportunity for new generation measurement applications, which are increasingly based on efficient and reliable communication systems to allow the extensive availability of continuous data from instruments and/or sensors, thus enabling real-time measurement analysis. Nevertheless, different communication systems and heterogeneous sensors and acquisition systems may be found in an IIoT-enabled measurement application, so that solutions need to be defined to tackle the issue of seamless, effective, and low-latency interoperability. A significant and appropriate solution is the open platform communications (OPCs) unified architecture (UA) protocol, thanks to its object-oriented structure that allows a complete contextualization of the information. The intrinsic complexity of OPC UA, however, imposes meaningful performance assessment to evaluate its suitability in the aforementioned context. To this aim, this article presents the design of a general yet accurate and reproducible measurement setup that will be exploited to assess the performance of the main open-source implementations of OPC UA. The final goal of this work is to provide a characterization of the impact of this protocol stack in an IIoT-enabled measurement system, in particular, in terms of both the latency introduced in the measurement process and the power consumption.

Perbandingan Quadratic Discriminant Analysis dan Support Vector Machine untuk Klasifikasi Tutupan Lahan di DKI Jakarta

DKI Jakarta is a center of government as well as economy and business of Indonesia, thus development projects in Jakarta continue every year. Therefore, monitoring for land use has to be improved in accordance to DKI Jakarta Spatial Planning. The attempt needs to be supported by continuous data availability regarding land cover condition in Jakarta. The aforementioned data collecting process become easier due to remote sensing technology development. Remote sensing technology can be utilized for analyzing the size of land use area by using classification analysis. It has been found that the level of accuracy depends on the type of classification method and number of training data. This research evaluated the level of overall accuracy, sensitivity, and specificity of Quadratic Discriminant Analysis (QDA) and Support Vector Machine (SVM) along with number of data training used in classifying Jakarta land cover in 2017. The results showed that in both methods, the variance of all the aforementioned criteria were getting smaller along with the increasing number of training data. QDA and SVM had similar performance based on overall accuracy and specificity. However, SVM was better than QDA on sensitivity.

A sustainability study of the flow regulation impacts by dams in a carp breeding river using the hydrodynamic model and building block analysis

Halda, one of the major tributaries of the mountainous river Karnaphuli, is well known as the country’s only natural carp spawning ground. Naturally fertilized eggs of carps collected from Halda River are hatched in mud-made scoops on the river bank for aquaculture purposes. However, the river habitat is under constant threat due to human interventions like loop cutting, pollution from the paper mill and power plant, blocking natural water flow of larger tributaries by introducing sluice gates, embankments and rubber dam over the river at upstream, as well natural causes like siltation, erosion and climate change impacts. A study is conducted to address the issues of the ecosystem, sustainable management and the flow regulation impacts of dams in the Halda River, although the flow regulation assessments are conducted based on the macroinvertebrate, index-based framework, land-use effects on the hydrology, new indicators development, hydrologic impact assessment, hydrodynamics in dam regulated rivers, surface-water hydrodynamics and regimes of a small mountain stream and wide range of initiatives. In our case, we considered runoff flow, mountainous flow and dams in the rivers are primary parameters for assessment, so based on previous studies we decided to simulate a hydrologic and hydrodynamic model for the dam and without dam scenarios. Major difficulties and challenges for the environmental flow analysis of a river are continuous data availability. In this research, a hydrologic model ArcSWAT has been built to assess the contribution of rainfall on the river discharge to be used as output from the tributaries in the hydrodynamic model Delft3D. The research findings help us to perceive the effect of the dams on fish breeding condition in the river. In order to perform the environment flow analysis of the river, Tennant method has been followed in the study, which is a secure and reliable approach. The flow regulation impacts are assessed for fish habitat and spawning in the river area based on the simulations. Finally, the findings are further analyzed for velocity profiles for dams by building block method for the sustainable aquatic habitat in the Halda River.

Coastal Mooring Observing Networks and Their Data Products: Recommendations for the Next Decade

Instrumented moorings (hereafter referred to as moorings), which are anchored buoys or an anchored configuration of instruments suspended in the water column, are highly valued for their ability to host a variety of interchangeable oceanographic and meteorological sensors. This flexibility makes them a useful technology for meeting end user and science-driven requirements. Overall, societal needs related to human health, safety, national security, and economic prosperity in coastal areas are met through the availability of continuous data from coastal moorings and other complementary observing platforms within the Earth-observing system. These data streams strengthen the quality and accuracy of data products that inform the marine transportation industry, the tourism industry, fisheries, the military, public health officials, coastal and emergency managers, educators, and research scientists, among many others. Therefore, it is critical to sustain existing observing system networks, especially during this time of extreme environmental variability and change. Existing fiscal and operational challenges affecting the sustainability of observing networks will likely continue into the next decade, threatening the quality of downstream data and information products - especially those used for long-term monitoring, planning, and decision-making. This paper describes the utility of coastal moorings as part of an integrated coastal observing system, with an emphasis on stakeholder engagement to inform observing requirements and to ensure data products are tailored to user needs. We provide 10 recommendations for optimizing moorings networks, and thus downstream data products, to guide regional planners and network operators: 1. Develop strategies to increase investment in coastal mooring networks 2. Collect stakeholder priorities through targeted and continuous stakeholder engagements 3. Include complementary systems and emerging technologies in implementation planning activities 4. Expand and sustain water column ecosystem moorings in coastal locations 5. Coordinate with operators and data managers across geographic scales 6. Standardize and integrate data management best practices 7. Provide open access to data 8. Promote environmental health and operational safety stewardship and regulatory compliance 9. Develop coastal mooring observing network performance metrics 10. Routinely monitor and assess the design of coastal mooring networks

Interrelationship between Capital Structure and Dividend Policy with Reference to Select Indian Companies

The present article examines the interrelationship between capital structure and dividend policy company-wise. In an earlier study (Kaur, Chattopadhyay, and Rakshit, 2018) this interrelation was empirically analysed taking BSE listed 40 sample companies. In the present study sample size is extended from 40 to 90 sample companies comprising 5 companies from each of 10 industries (namely, Automobile, Cement, Large Heavy Engineering, Fertilizer, Oil Exploration, Pharmaceutical, Refineries, Large Tea, Large Textile and Large Tyre) and by including 5 sample companies from each of 8 additional industries (namely, Computer Hardware, Computer Software, Construction, FMCG, Large Heavy Electricals, Mining/Minerals, Large Steel and Telecommunication) which are chosen from BSE listed companies on the basis of highest turnover for the year 2011. As per the non-fulfilment of criterion of availability of continuous data for the 15 year's study period i.e., from 1999-2000 to 2013-14 the study has not omitted 11 sample companies from the study. For analysing the said interrelationship, the study has applied Akaike's Information Criterion AIC), Granger Causality Test and Panel Data Regression technique. From the estimated results of Granger Causality Test, we observe that F-Statistic value, using Dividend Payout Ratio as independent variable, is significant for 14 sample companies, while F-Statistic value, using Leverage as independent factor, is significant for other 11 sample companies. In the cases of other 4 sample companies, both Dividend Payout Ratio and Leverage Ratio are Granger cause of other. Next, we have estimated two regression equations as per the prescription obtained from Granger Causality Test along with other control variables. On considering both the regression results jointly we may come to the final conclusion that leverage statistically negatively depends on dividend payout ratio, but the converse is not true. But this conclusion is valid for the sample companies, which cannot be generalised with certainty.

Single Disk Recovery and Load Balancing Using Parity Declustering

In the recent scenario, capacity of the storage system increases significantly due to increasing demands. Data availability is a major concern in the context of storage systems. In order to achieve high data availability, a Maximum Distance Separable (MDS) code such as Row-Diagonal Parity (RDP) is used in RAID 6 storage systems. In order to ensure continuous availability of data, even a failure in a single disk cannot be tolerated and hence it must be recovered at the earliest. Existing RDOR-RDP, a modified scheme of RDP that achieves minimal disk I/O access and reduced recovery time when compared with conventional scheme but yet fails to achieve load balancing during the recovery process. In this work, Parity declustering based load balancing is proposed, which provides optimal recovery time when compared to RDOR-RDP.

Advanced Support System Based on Precise Meteorological Data for Citrus Orchards

Rural districts located in mountainous or hilly regions are not only important in terms of food production but are also where civilization, culture and spirituality originated and are preserved. The policies supporting the sustainable development of agriculture in such regions are important in many countries. These policies will gain importance in the face of climate change because the complex terrain results in small and widely distributed farm lands with limited productivity, and these will be the first to be negatively affected. Many attempts have been made to use various meteorological conditions to increase the productivity of agriculture in the hilly and mountainous terrains of Japan. However, most of the meteorological data collected has not been fully used. We proposed that to optimize agricultural output from the mountainous and hilly regions, it is necessary to acquire precise meteorological data with three characteristics: precise position estimates, substantial data collection, and the availability of continuous data covering the past, present and future. We have developed a support system for the management of a database of precise meteorological data, including air temperature, humidity, solar radiation, precipitation and reference evapotranspiration. Data in the database have been developed to estimate data, having a few tens of meters resolution, based on a nearby existing observation station and its data: past, present and future. This system, with its precision meteorological data, should make citrus cultivation more profitable because Japanese citrus orchards are located in hilly areas, and the gradient of ∼45% of the orchard area has over a 15 degree slope. We expect that this system will contribute to developing advanced and flexible management systems of cultivation that respond to meteorological fluctuations. We will present the support system under the development of citrus orchards.

Mosquito Surveillance in Northwestern Italy to Monitor the Occurrence of Tropical Vector-Borne Diseases

Mosquito-borne arboviruses (MBV) represent an important health problem, causing diseases and deaths both in human and animals mainly in tropical and subtropical countries. In recent years, they have emerged also in temperate regions where they have caused epidemics. Of mounting concern among public health authorities in Europe are zoonotic mosquito-borne viruses belonging to the Flavivirus genus. The aim of this study was to carry out active surveillance on mosquitoes in two regions of northwestern Italy (Liguria and Piedmont) to gain a better knowledge of the mosquito populations by identifying potential vectors of arboviruses and to investigate arbovirus infection. A network of 61 CO₂ CDC traps was placed in the study area; sampling was conducted from May to October 2011. A total of 46,677 mosquitoes was collected, identified to species level, and classified according to their vector competence. Mosquitoes collected from 16 traps, selected according to risk-based factors, were tested by biomolecular analysis to detect flavivirus infection. This study highlights the importance of entomological surveillance in northwestern Italy because most of the mosquitoes collected were found to have high vector competence. Moreover, the risk-based virological surveillance allowed to detect the presence of mosquito flavivirus RNA, phylogenetically closely related to the MMV Spanish isolate, in three pools and USUV RNA in one pool in new areas where it has not been reported previously. The availability of continuous data on mosquito populations provides invaluable information for use in cases of an epidemic emergency. Maintenance of this integrated system for the next years will provide stronger data that can inform the design of a risk-based surveillance for the early detection of the occurrence of outbreaks of tropical MBDs.

Review of Data Replication Techniques for Mobile Computing Environment

With the tremendous growth of the portable computing devices and wireless communication, the mobile computing has become extremely popular. The wireless enabled portable computing devices with massive storage capacity and high-end processing capabilities have started to make the extensive use of mobile databases already. The rising popularity in these computing paradigms demands that the mobile computing be reliable enough to ensure the continuous data availability and integrity. However mobility comes at the cost of bandwidth, limited power, security and interference. In modern mobile computing systems data replication has been adopted as an efficient means to ensure the data availability and integrity as well as an effective means to achieve the fault tolerance. Data replication not only ensure the availability of the data but also reduce the communication cost, increase data sharing and increase the safety of the critical data. Furthermore, it also determine when and where (location) to place the replica of data, controlling the number of data replicas over a network for efficient utilization of the network resources. In this study we survey the research work in data replication for mobile computing. We reviewed some of the existing data replication techniques proposed by the research community for mobile computing environment for efficient management of data replicas.

Origin of Initial Burst in Activity for Trichoderma reesei endo-Glucanases Hydrolyzing Insoluble Cellulose

The kinetics of cellulose hydrolysis have long been described by an initial fast hydrolysis rate, tapering rapidly off, leading to a process that takes days rather than hours to complete. This behavior has been mainly attributed to the action of cellobiohydrolases and often linked to the processive mechanism of this exo-acting group of enzymes. The initial kinetics of endo-glucanases (EGs) is far less investigated, partly due to a limited availability of quantitative assay technologies. We have used isothermal calorimetry to monitor the early time course of the hydrolysis of insoluble cellulose by the three main EGs from Trichoderma reesei (Tr): TrCel7B (formerly EG I), TrCel5A (EG II), and TrCel12A (EG III). These endo-glucanases show a distinctive initial burst with a maximal rate that is about 5-fold higher than the rate after 5 min of hydrolysis. The burst is particularly conspicuous for TrCel7B, which reaches a maximal turnover of about 20 s(-1) at 30 °C and conducts about 1200 catalytic cycles per enzyme molecule in the initial fast phase. For TrCel5A and TrCel12A the extent of the burst is 2-300 cycles per enzyme molecule. The availability of continuous data on EG activity allows an analysis of the mechanisms underlying the initial kinetics, and it is suggested that the slowdown is linked to transient inactivation of enzyme on the cellulose surface. We propose, therefore, that the frequency of structures on the substrate surface that cause transient inactivation determine the extent of the burst phase.