‘Retournement’ of the aedeagus in Curculionidae (Coleoptera, Curculionoidea)

Retournement or turning of the aedeagus about its longitudinal axis through about 180o during development is known in Chrysomeloidea (Coleoptera). This change in the orientation of the organ may be observed during the postembryonic development. This change produces certain morphological effects. By observing these morphological features in the imago the retournement may be inferred. Such morphological features in Curculionidae (Coleoptera) are here recorded. From this it has been inferred not only that retournement of the aedeagus is included in the ontogeny of curculionids, but also that the change of orientation of the organ occurs by the same mechanism as in Chrysomeloidea. These inferences attest the notion of a close phyletic relationship between the superfamilies Curculionoidea and Chrysomeloidea

Web Content Analysis of National Libraries’ Websites in Asia: An Evaluation

The present study is carried out for analyzing the contents of national libraries’ websites in Asia. A checklist was designed, and library webpages were evaluated, such as the site description, TLDs, language used, design factor, statement of responsibility, general information, availability of aids and tools, authority details, currency, number of visitors, file format supported, use of web 2.0 tools, webpage size and download speed and ranking of Asian national library websites globally. It is observed that 39 national libraries have dedicated library websites. Further observed that all the national libraries have used graphics in their website, while few have used animations also. Most library websites have provided statements of responsibilities like postal address, email address, and phone numbers, and few have given fax numbers. Only a few have given the currency of their national library websites like date of update, which is an essential part of the website’s visibility. The National Library of Japan secured the top position based on global ranks with 8,662, Azerbaijan with 13,507 ranks, and Taiwan with 17,673 ranks.https://dorl.net/dor/ 20.1001.1.20088302.2022.20.1.24.

A webometric analysis of National Libraries’ websites in South Asia

The study analyses the number of web pages, link pages and calculates the Web Impact Factor i.e., Simple Web Impact Factor, Internal Link Web Impact Factor and External Link Web Impact Factor of National Libraries in South Asian countries and ranks the websites as per the WIF. The study used Open Site Explorer optimization tool and search engine for links. The result visualized that National Library of India leads with highest Domain Authority (15.27%) and Page Authority (14.48%), the National Library of Sri Lanka (88.65%) got the highest Internal Equity-Passing Links, National Library of India (84.96%) has the highest External Equity-Passing Links and Total Equity-Passing Links with 83.69%. The National Library of Sri Lanka has the highest (88.65%) Total Internal Links and National Library, India has the highest Total External Links (84.04%) and Total Links (82.80%). The Web Impact Factor of National Library of India is the highest followed by National Library of Sri Lanka and National Library of Bhutan among the other national libraries websites.

The new emission spectrum of selenium monoxide in the region 3185-2690 Å

The emission spectrum of SeO excited in an electrodeless discharge tube containing selenium dioxide powder by a high power microwave generator revealed the existence of a new band system in the region 3185 - 2690 Å consisting of 48 bands degraded to longer wavelengths. The vibrational analysis suggests that the bands arise from the transition C(³π) - X³∑⁻ (the states designated as C and D in earlier work by Reddy and Azam (1974) are hereafter to be referred to as D and E, respectively). Sub-systems, C(³π₀) - X³∑⁻ (F₂, F₃), C(³π₀) - X³∑⁻ (F₁), C(³π₁) - X³∑⁻ (F₂), C(³π₁) - X³∑⁻ (F₁) and C(³π₂) - X³∑⁻ (F₁) of C-X have been identified. The separations between the band heads having the same vibrational assignments (v', y") with a common upper electronic substate are consistent with the expected value of ∿ 2 λ, λ (= 86.4 cm⁻¹) being the spin-splitting constant of the X³∑⁻ state known from earlier work (Barrow and Deutsch, 1963; Azam and Reddy, 1973). Derived constants (in cm⁻¹) of state C are as follows: -- [special characters omitted] -- In addition, 8 new emission bands of Se0 degraded to longer wavelengths in the region 3040 - 2805 Å have been fitted into the vibrational scheme of the previously known B³∑ - X³∑⁻ system. -- Finally, Morse potential curves have been drawn for several known electronic states of Se0

Students’ Attitude towards Social Networking Sites (SNSs): A Case Study of Central Institute of Technology (CIT) Kokrajhar, Assam

The present study investigates the use of Social Networking Sites (SNSs) by the students of Central Institute of Technology (CIT) in Kokrajhar, Assam. The survey and random sampling technique have been used for the collection of data. Around 200 structured questionnaires were distributed among the students of CIT, Kokrajhar and filled-in questionnaires were collected on the same day itself and analyzed for data interpretation in the form of tables and charts. The study explored that all the respondents were aware of SNSs and are using more than one SNSs websites, it has found that Facebook is use in large number, while YouTube and Instagram follow it. Mobile is the most preferred tool for accessing SNSs, a majority expressed that low internet speed was the main problem, also indicates that students are using SNSs for entertainment purpose. The majority 47.47% of the CIT students are satisfied, while 35.35% are partially satisfied and very few 17.17% are highly satisfied

Equitable-FL: Federated Learning with Sparsity for Resource-Constrained Environment

In Federated Learning, model training is performed across multiple computing devices, where only parameters are shared with a common central server without exchanging their data instances. This strategy assumes abundance of resources on individual clients and utilizes these resources to build a richer model as user's models. However, when the assumption of the abundance of resources is violated, learning may not be possible as some nodes may not be able to participate in the process. In this paper, we propose a sparse form of federated learning that performs well in a Resource Constrained Environment. Our goal is to make learning possible, regardless of a node's space, computing, or bandwidth scarcity. The method is based on the observation that model size viz a viz available resources defines resource scarcity, which entails that reduction of the number of parameters without affecting accuracy is key to model training in a resource-constrained environment. In this work, the Lottery Ticket Hypothesis approach is utilized to progressively sparsify models to encourage nodes with resource scarcity to participate in collaborative training. We validate Equitable-FL on the $MNIST$, $F-MNIST$, and $CIFAR-10$ benchmark datasets, as well as the $Brain-MRI$ data and the $PlantVillage$ datasets. Further, we examine the effect of sparsity on performance, model size compaction, and speed-up for training. Results obtained from experiments performed for training convolutional neural networks validate the efficacy of Equitable-FL in heterogeneous resource-constrained learning environment.Comment: 12 pages, 7 figure

FAM: fast adaptive federated meta-learning

In this work, we propose a fast adaptive federated meta-learning (FAM) framework for collaboratively learning a single global model, which can then be personalized locally on individual clients. Federated learning enables multiple clients to collaborate to train a model without sharing data. Clients with insufficient data or data diversity participate in federated learning to learn a model with superior performance. Nonetheless, learning suffers when data distributions diverge. There is a need to learn a global model that can be adapted using client's specific information to create personalized models on clients is required. MRI data suffers from this problem, wherein, one, due to data acquisition challenges, local data at a site is sufficient for training an accurate model and two, there is a restriction of data sharing due to privacy concerns and three, there is a need for personalization of a learnt shared global model on account of domain shift across client sites. The global model is sparse and captures the common features in the MRI. This skeleton network is grown on each client to train a personalized model by learning additional client-specific parameters from local data. Experimental results show that the personalization process at each client quickly converges using a limited number of epochs. The personalized client models outperformed the locally trained models, demonstrating the efficacy of the FAM mechanism. Additionally, the sparse parameter set to be communicated during federated learning drastically reduced communication overhead, which makes the scheme viable for networks with limited resources.Comment: 13 Pages, 1 figur

Evolution of VANETS to IoV: Applications and Challenges

Advancement in wireless communication technology along with the evolution of low power computational devices, have given rise to the Internet of things paradigm. This paradigm is transforming conventional VANETs into Internet-of- vehicles. This transition has led to a substantial commercial interest; as a result, there has been a significant boost in the field of the Internet of vehicles during the past few years. IoV promises a wide range of applications of commercial interest as well as public entertainment and convenience (collision warning systems, on-demand in-car entertainment, smart parking, traffic information). Applications related to vehicular and passenger safety are particularly of great commercial as well as a research interest as such IoV is going to be a core component in implementing the smart city concept. This paper gives an overview of the transition of conventional VANETs to IoV and highlights the potential applications and challenges faced by the Internet of Vehicles (IoV) paradigm