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The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome
coronavirus 2 (SARS-CoV-2), has become a global pandemic. No specific therapeutic
agents or vaccines for COVID-19 are available, though several antiviral drugs, are under investigation as treatment agents for COVID-19. The use of convalescent plasma transfusion
that contain neutralizing antibodies for COVID-19 has become the major focus. This requires mass screening of populations for these antibodies. While several countries started
reporting population based antibody rate, its simple point estimate may be misinterpreted
without proper estimation of standard error and confidence intervals. In this paper, we review the importance of antibody studies and present the 95% confidence intervals
COVID-19 antibody rate for the Korean population using two recently performed antibody
tests in Korea. Due to the sparsity of data, the estimation of confidence interval is a big
challenge. Thus, we consider several confidence intervals using Asymptotic, Exact and
Bayesian estimation methods. In this article, we found that the Wald method gives the
narrowest interval among all Asymptotic methods whereas mid p-value gives the narrowest among all Exact methods and Jeffrey’s method gives the narrowest from Bayesian
method. The most conservative 95% confidence interval estimation shows that as of 00:00
on September 15, 2020, at least 32,602 people were infected but not confirmed in Korea.

The kinetics of Cr VI oxidation of D D-glucose to the corresponding lactone in the presence and absence of 2,2 0 -bipyridine (bipy) has been carried out under the conditions, [D D-glucose] T ) [Cr VI ] T at different temperatures in aqueous micellar media. The monomeric Cr VI species has been found to be kinetically active in the absence of bipy whereas in the bipy-catalysed path, the Cr VIbipy complex has been found to be the active oxidant. In the bipy-catalysed path, the Cr VI -bipy complex undergoes nucleophilic attack by the substrate to form a ternary complex. The ternary complex spontaneously experiences a redox decomposition (through two-electron transfer) in the rate-determining step leading to the product lactone and Cr IV -bipy complex. The Cr IV -bipy complex then takes part in faster steps in the further oxidation of D D-glucose and is ultimately converted into a Cr III -bipy complex. In the uncatalysed path, the Cr VI -substrate ester experiences acid catalysed redox decomposition (two-electron transfer) in the rate-determining step. The uncatalysed path shows a second order dependence on [H + ] and a first order dependence on each of the reactants [D D-glucose] T and [Cr VI ] T . In contrast, the bipy-catalysed path shows a first order dependence on each of the reactants [H + ], [D D-glucose] T and [Cr VI ] T . The bipy-catalysed path is first order in [bipy] T . These observations remain unaltered in the presence of externally added surfactants. The effect of the cationic surfactant, N-cetylpyridinium chloride (CPC) and anionic surfactant, sodium dodecyl sulfate (SDS) on both the uncatalysed and bipy-catalysed path has been studied. CPC inhibits both the uncatalysed and bipy-catalysed path, while SDS catalyses these reactions. The observed micellar effects have been explained by considering hydrophobic and electrostatic interactions between the surfactants and reactants.

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The kinetics and mechanism of chromic acid oxidation of maleic acid in the presence and absence of picolinic acid (PA) in aqueous acid media have been studied under the conditions [maleic acid] [Cr VI ] T at different temperatures. Under the kinetic conditions, the monomeric species of Cr VI has been found kinetically active in the absence of PA while in the PA-catalysed path, Cr VI -PA complex has been suggested as the active oxidant. In the PA-catalysed path, Cr VI -PA complex receives a nucleophilic attack by the substrate to form a ternary complex, which subsequently experiences a 2e-transfer redox decomposition leading to the epoxide and Cr IV -PA complex at the rate determining step. Subsequently, the epoxide produces pyruvic acid through the decarboxylation of ␤-keto acid in a faster step. Then Cr IV -PA complex participates further in the oxidation of maleic acid in faster steps and ultimately is converted into the inert Cr III -PA complex. In the uncatalysed path, Cr VI -substrate ester experiences a redox decomposition through 2e-transfer at the rate determining step in the same way. The uncatalysed path shows a mixed order (i.e. first order + second order) dependence on [H + ] while the PA-catalysed path shows a first order dependence on [H + ]. Both the uncatalysed path and PA-catalysed path show the first order dependence on both [maleic acid] T and [Cr VI ] T . The PA-catalysed path is first order in [PA] T . In the presence of surfactants like N-cetylpyridinium chloride (CPC, a cationic surfactant) and sodium dodecyl sulfate (SDS, an anionic surfactant), the reaction orders remain unchanged. CPC has been found to retard both the uncatalysed and PA-catalysed paths but the patterns are different while SDS shows the rate accelerating effect for the both paths in the same pattern. The observed micellar effects have been explained by considering hydrophobic and electrostatic interactions between the reactants and surfactants in terms of the proposed mechanism. (A.K. Das).

The kinetics and mechanism of Cr VI oxidation of fructose in the presence and absence of 2,2 -bipyridyl (bipy) and 1,10-phenanthroline (phen) in aqueous acid media have been studied under the condition [sugar] T [Cr VI ] T at different temperatures. Under the kinetic conditions, both the slower uncatalysed and faster catalysed (by heteroaromatic N-bases i.e., bipy, phen) paths go on. The monomeric species of Cr VI has been found to be kinetically active in the absence of bipy and phen whereas in the heteroaromatic N-base catalysed path, the Cr VI -bipy and Cr VI -phen complexes have been found to be the active oxidants. Both the paths show the first-order dependence on [sugar] T and [Cr VI ] T . The uncatalysed path shows a second-order dependence on [H + ]. But the catalysed path shows a first-order dependence on [H + ]. The heteroaromatic N-base-catalysed path is first-order in [bipy] T or [phen] T . These observations remain unaltered in the presence of externally added surfactants. Effect of the cationic surfactant (i.e. CPC) and anionic surfactant (i.e. SDS) on both the uncatalysed and heteroaromatic N-base-catalysed paths has been studied. CPC inhibits both the uncatalysed and catalysed paths while SDS accelerates the reactions. The observed effects have been explained by considering the hydrophobic and electrostatic interaction between the surfactants and reactants.

The satisfactory electronic delivery of multimedia material not only requires a particular quality of service (QoS) level to be maintained to fulfil users' expectations; there is in addition another goal: maximizing the revenue earned for the network owner. In this paper, we designed an admission controller (AC) along with the necessary algorithms to allow an enterprise network (EN) to satisfy both of these goals. We consider the selection of both a server from several alternatives, and the selection of a delivery route, plus the reservation of resources both in the selected server and on the delivery route to achieve the two goals of guaranteed absolute QoS and revenue optimization. We simulated the AC; simulation results are provided together with explanations.

System on Chip (SoC) design requires efficient communication between heterogeneous resources to meet the high-speed transmission needs. Therefore one of the key factors for the success of ultra-deep submicron technologies will be the capability of integrating different resources like processor core, memory, an FPGA, a custom hardware block or any other semiconductor intellectual property (SIP) block into a single piece of silicon. Non-scalable global wire delays, global synchronization failure, loss of signal integrity issues are the main problems. To address these problems, various interconnect architectures are proposed. Butterfly Fat Tree (BFT) is one of those. To improve the performance of BFT we introduce Extendedbutterfly Fay Tree Interconnection (EFTI). Routing algorithm is provided for EFTI and comparative analysis is performed through the simulation result.

The satisfactory electronic delivery of multimedia material not only requires a particular Quality of Service (QoS) level to be maintained to fulfill users' expectations; there is in addition another goal: maximizing the revenue earned for the network owner. In this paper, we designed an Admission Controller (AC) along with the necessary algorithms to allow an Enterprise Network (EN) to satisfy both of these goals. We consider the selection of both a server from several alternatives, and the selection of a delivery route, plus the reservation of resources both in the selected server and on the delivery route to achieve the two goals of guaranteed absolute QoS and revenue optimization. We simulated the AC; simulation results are provided together with explanations. 0-7803-9195-0/05/$20.00 ©2005 IEEE. 157 Authorized licensed use limited to: UNIVERSITY OF ROCHESTER. Downloaded on September 8, 2009 at 16:42 from IEEE Xplore. Restrictions apply.

Jagannath University, Faculty of Life and Earth Sciences, Department of Zoology, Dhaka-1100, Bangladesh. Jagannath University, Faculty of Sciences, Department of Statistics, Dhaka-1100, Bangladesh. Jagannath University, Faculty of Life and Earth Sciences, Department of Botany, Dhaka-1100, Bangladesh. University of Dhaka, Faculty of Biological Sciences, Department of Zoology, Dhaka-1000, Bangladesh.

The purpose of this study was to determine the fish species composition and appraise the status of fish diversity through sampling in six sample locations and to observe the socio economic conditions of the fishermen surrounding the river during the study period. There were 81 fish species found, classified into 13 orders, 40 families, and 69 genera. The most dominant order was Perciformes (55.42 %), followed by Clupeiformes (20.44 %), Cypriniformes (8.96 %), Siluriformes (8.13 %), and others (7.05%). To illustrate the species diversity, fish species richness and evenness in sampling areas, indices of fish community viz. Shannon-Wiener's Index (H), Simpson's Dominance Index (D), Simpson's Diversity Index (1-D), Margalef's Index (d) and Gibson's Evenness (€) were used and 3.29-3.48, 0.05-0.069, 0.93-0.95, 6.88-8.43 and 0.39-0.49 respectively were the overall values of the indices. S1 station is significantly differ in species richness from the rest of the five stations (P < 0.05). The analysis of similarity (ANOSIM) displayed significant (P-value < 0.05) variations in fish community among stations and months. In compliance with similarity percentage (SIMPER) analysis, 35.8% similarities were observed among the fish species from different stations, while 59.36% similarities were detected among the fish species from different months. One species is critically endangered (CR), three species are nearly threatened, eight species are endangered (EN), and eight species are vulnerable among the 81 fish species recorded at various sampling locations. The socioeconomic conditions of fishermen were determined on the basis of a personal interview and focus group discussion. Unfair fishing practices as well as environmental instabilities such as reduced water volume, increased sedimentation, water abstraction, and pollution have ravaged fish habitat and diminished fish diversity over time. As a result, fish preservation in the Andharmanik River has become imperative, and an integrated management plan should be designed and executed as soon as possible.

The widespread dissemination of misinformation and the diverse public sentiment observed during the COVID-19 pandemic highlight the necessity for accurate sentiment analysis of social media discourse. This study proposes a hybrid deep learning (DL) model that integrates Bidirectional Encoder Representations from Transformers (BERT) for contextual feature extraction with Long Short-Term Memory (LSTM) networks for sequential learning to classify COVID-19-related sentiments. To enhance data quality, advanced text preprocessing techniques, including Unicode normalization, contraction expansion, and emoji conversion, are applied. Additionally, to mitigate class imbalance, Random OverSampling (ROS) is employed, leading to significant improvements in model performance. Before applying ROS, the model exhibited lower accuracy and inconsistent performance across sentiment categories. After balancing the dataset, accuracy for binary classification increased to 92.10%, with corresponding precision, sensitivity, and specificity of 92.10%, 92.10%, and 91.50%, respectively. For three-class sentiment classification, accuracy improved to 89.47%, with precision, sensitivity, and specificity of 89.80%, 89.47%, and 94.10%, respectively. In five-class sentiment classification, accuracy reached 81.78%, with precision, sensitivity, and specificity of 82.19%, 81.78%, and 95.28%, respectively. These findings demonstrate the efficacy of combining deep learning-based sentiment analysis with advanced text preprocessing and class balancing techniques for accurately classifying public sentiment related to COVID-19 across multiple sentiment categories.

For high-dimensional data sets two-step model building algorithms usually select more important active covariates with fewer noise variates than one-step model building algorithms in liner models. In most of the previous studies, "learning curve", a manual procedure, has been used to determine the size of the reduced set in two-step model building procedure. In this paper, we propose a computer based automatic generation procedure instead of using this manual procedure to determine the size of the "reduced set" in two-step model building procedure. That is, the "reduced set" will be created automatically by computer based automatic generation procedure whichever occurs first from either or number of target variables = 8, and final model is obtained from the reduced set. We also made a comparison between one-step model building procedure and two-step automated robust model building procedure for clean data as well as contaminated data through a simulation study and real data applications. The performance of two-step automated robust model building procedure is much better than the robust one-step model building procedure in contaminated data as well as clean data.