Recovery after the Rupture: Linking Colonial Histories of Displacement with Affective Objects and Memories

The notion of home and belonging, specifically in the context of South Asian postcolonial diasporas, is connected to past traumas of colonization and displacement. This paper addresses how trauma, displacement, and colonialism can be understood through and with material culture, and how familial objects and items emit and/ or carry within them, emotional narratives. I turn to the affective currency that emit and are transferred on and down from objects, by diasporic subjects, to access the possible reclamation of otherwise silenced narratives within colonial and postcolonial histories. By following the events of the Partition of India in 1947 as a violent historical moment that saw the displacement of millions of people, I ultimately examine how affective objects can be read as alternative epistemological sites that create potential space for recovery to postcolonial trauma and violence

COMPARISON OF CERVICAL BIOPSY USING PUNCH BIOPSY FORCEPS VERSUS LOOP ELECTRODE

Context: The biopsy of cervix can be obtained by various methods with availability of newer modalities like loop electrode. Objectives: To compare the histo-pathological parameters and clinical outcome of cervical biopsy obtained using punch biopsy forceps versus loop electrode. Methods: Women attending OPD were screened for cervical pathology, and colposcopy was done for those who screened positive. Patients who required cervical biopsy after colposcopy were allocated into 2 group; one undergoing LEEP biopsy and other half biopsied with Punch forceps. During procedure patients were evaluated for the intra-op pain and bleeding and their severity. The histo- pathological diagnosis was carried out and the sample was studied for its size, adequacy, and presence of any thermal or crush artefacts. Result: The two methods of biopsy were comparable in intra-op parameters, except for the increased requirement for additional haemostasis in LEEP biopsy. There was no case of bleeding from biopsy site at the follow-up visit. LEEP biopsy was  associated with continued vaginal discharge more often than punch biopsy. An adequate sample for histopathological diagnosis was obtained in 91.25% of all cases.  The comparative findings were reflective of comparable efficacy of both methods in providing an acceptable tissue sample for diagnosis. Conclusion: After analysing and comparing the aforementioned parameters, we opined that neither method can be deemed clearly superior to the other as a cervical biopsy procedure. Keywords: Punch biopsy forceps; Loop electrode; Cervical biopsy

COMPARISON OF CERVICAL BIOPSY USING PUNCH BIOPSY FORCEPS VERSUS LOOP ELECTRODE

Context: The biopsy of cervix can be obtained by various methods with availability of newer modalities like loop electrode. Objectives: To compare the histo-pathological parameters and clinical outcome of cervical biopsy obtained using punch biopsy forceps versus loop electrode. Methods: Women attending OPD were screened for cervical pathology, and colposcopy was done for those who screened positive. Patients who required cervical biopsy after colposcopy were allocated into 2 group; one undergoing LEEP biopsy and other half biopsied with Punch forceps. During procedure patients were evaluated for the intra-op pain and bleeding and their severity. The histo- pathological diagnosis was carried out and the sample was studied for its size, adequacy, and presence of any thermal or crush artefacts. Result: The two methods of biopsy were comparable in intra-op parameters, except for the increased requirement for additional haemostasis in LEEP biopsy. There was no case of bleeding from biopsy site at the follow-up visit. LEEP biopsy was  associated with continued vaginal discharge more often than punch biopsy. An adequate sample for histopathological diagnosis was obtained in 91.25% of all cases.  The comparative findings were reflective of comparable efficacy of both methods in providing an acceptable tissue sample for diagnosis. Conclusion: After analysing and comparing the aforementioned parameters, we opined that neither method can be deemed clearly superior to the other as a cervical biopsy procedure. Keywords: Punch biopsy forceps; Loop electrode; Cervical biopsy

An Approximate Model for Event Detection from Twitter Data

The abundance and real-time availability of Twitter data have proved beneficial in detecting events in various domains such as emergency situations, crime detection, public health, place recommendations, etc. Nevertheless, two critical challenges occur while detecting events using social media data. First, the uncertainty in capturing the contextual relationship among tweets, which is the result of the limited availability of the contextual information due to the small length of tweets. Second, the high computation cost required in event detection due to massive data processing. Earlier research works, addressing these challenges, have tried to capture the contextual information by using the dense vector representations of texts leveraging deep neural word embedding generation models such as Word2Vec and GloVe. However, these models are trained on the Euclidean vector space which fails to amalgamate the directional information of the vectors with the semantic information in text, incurring high computational costs. To target both the problems simultaneously, we propose modeling Twitter data as a graph-of-sentences which retains the contextual relationships while maintaining lower computational cost. The proposed model captures contextual information using JoSE, a spherical vector representation leveraging the word-word and word-paragraph semantic co-occurrence statistics in a spherical generative model. Furthermore, the framework uses the weighted-graph model to capture all the relationships among the Twitter data efficiently. The graph is further pruned with the help of the graph component filtering approach. The graph clustering model, employed to detect the events, leverages the edge weights and the partial-k clustering approach maintaining low computation costs. The experimentation on the annotated benchmark Twitter data set and the real-world datasets show improved run-time performance up to 30% while maintaining the qualitative performance (F1-score) comparable to the state-of-the-art models

AI-based Twitter framework for assessing the involvement of government schemes in electoral campaigns

The government schemes (also known as programs and plans) or social welfare policies can be defined as the set of assistance and aids provided by the country's governance body. These schemes focus on the improved well-being of needful citizens. Some researchers have shown that introducing such policies and schemes has had an electoral impact in democratic countries. These earlier studies relied upon the post-poll and public survey data to reach conclusions. However, this data source has limitations and has to be collected manually, which makes it time-consuming and costly. The readily available internet inculcates the sharing of opinions freely on social media, facilitating government–citizen interactions. These interactions may show fluctuations in frequency and intensity on social media with the success and failure of some government schemes. Thus, this research proposes utilizing the Twitter data related to the government welfare schemes during the election duration to uncover the spatial and temporal relationships between the tweets’ information diffusion pattern and political elections. To start with, we perform tweet classification to identify the target communities or groups and multiple user-engagements by employing deep learning-based pre-trained language representation (LR) models. The scarcity of labeled data limits the application of the supervised classification models on real-time data. Thus, we propose Mod-EDA, a text augmentation method to upscale the labeled data for reduced overfitting. Going further, we propose two modules, where the classified tweets are studied to investigate the scheme tweets’ information diffusion pattern in correspondence to the election duration in terms of the voting phase and the electing parties, respectively. The proposed framework is evaluated for a case study of the 2019 Indian general elections. This study depicts that the voting phases and election duration trigger high government schemes related tweet generation. However, it is not affected by the location of the voting phase. The generation of complaints and negative tweets in one voting phase is covered with the positive news in subsequent voting phases. It is also seen that there is a strong influence of the ruling party on the scheme-related Twitter data generation

PROFICIENT CREDENTIAL LESS ENTRANCE SUPERVISE FOR REMOTE BODY ZONE

Remote body zone systems (WBANs) are normal to go about as a critical part in observing the wellbeing data also, making an exceptionally solid omnipresent social insurance framework. Since the information gathered by the WBANs are utilized to analyze and treat, just approved clients can get to these information. In this way, it is critical to outline an entrance control plot that can approve, verify, and disavow a client to get to the WBANs. In this paper, we first give an effective certificateless signcryption plan and after that outline an entrance control plot for the WBANs utilizing the given signcryption. Our plan accomplishes classification, trustworthiness, verification, non-renouncement, open unquestionable status, what's more, ciphertext genuineness. Contrasted and existing three access control plans utilizing signcryption, our plan has the minimum computational cost and vitality utilization for the controller. What's more, our plan has neither key escrow nor open key endorsements, since it depends on certificateless cryptography

Office endometrial sampling: a comparison between Endosampler and Karman cannula number 4

Background: Endometrial aspiration biopsy is one of the primary steps in diagnostic evaluation of a women presenting with suspected endometrial pathology. The aim of present study was to compare specimen adequacy, ease of doing the procedure, patient comfort and cost effectiveness in office endometrial sampling by endosampler vs Karman cannula number 4.Methods: This was a prospective comparative study where 102 patients were included. In 50% of patients, endosampler was used and Karman cannula was used in the rest. All procedures were noted, analysed and done in outpatient department and various parameters like specimen adequacy, pain score, ease of doing the procedure were analysed and compared in both groups.Results: The mean age of the patients was 37.1(±10) years with comparable distribution in the two groups. The parity was comparable in both groups. Authors further analysed the data on the basis of operator experience. The mean score of ease of insertion based on the experience of residents of 2 years was 3.1±1.48; 4.0±1.96 and 3.5±1.5; 3.7±2 in endosampler and Karman cannula group respectively. This difference was significant in the endosampler group (P: <0.001). The difference in pain score in two groups was not significant.  The specimen obtained was adequate in 32 (62.7 %) patients of the endosampler group and in 39 (76.4 %) patients of the Karman cannula group. (p-0.07). Endosampler is five times costlier than Karman cannula.Conclusions: Karman cannula is a good and cost-effective sampling device for endometrial biopsy

Estimating the household secondary attack rate and serial interval of COVID-19 using social media

We propose a method to estimate the household secondary attack rate (hSAR) of COVID-19 in the United Kingdom based on activity on the social media platform X, formerly known as Twitter. Conventional methods of hSAR estimation are resource intensive, requiring regular contact tracing of COVID-19 cases. Our proposed framework provides a complementary method that does not rely on conventional contact tracing or laboratory involvement, including the collection, processing, and analysis of biological samples. We use a text classifier to identify reports of people tweeting about themselves and/or members of their household having COVID-19 infections. A probabilistic analysis is then performed to estimate the hSAR based on the number of self or household, and self and household tweets of COVID-19 infection. The analysis includes adjustments for a reluctance of Twitter users to tweet about household members, and the possibility that the secondary infection was not acquired within the household. Experimental results for the UK, both monthly and weekly, are reported for the period from January 2020 to February 2022. Our results agree with previously reported hSAR estimates, varying with the primary variants of concern, e.g. delta and omicron. The serial interval (SI) is based on the time between the two tweets that indicate a primary and secondary infection. Experimental results, though larger than the consensus, are qualitatively similar. The estimation of hSAR and SI using social media data constitutes a new tool that may help in characterizing, forecasting and managing outbreaks and pandemics in a faster, affordable, and more efficient manner