Secret Key Generation Schemes for Physical Layer Security

Physical layer security (PLS) has evolved to be a pivotal technique in ensuring secure wireless communication. This paper presents a comprehensive analysis of the recent developments in physical layer secret key generation (PLSKG). The principle, procedure, techniques and performance metricesare investigated for PLSKG between a pair of users (PSKG) and for a group of users (GSKG). In this paper, a detailed comparison of the various parameters and techniques employed in different stages of key generation such as, channel probing, quantisation, encoding, information reconciliation (IR) and privacy amplification (PA) are provided. Apart from this, a comparison of bit disagreement rate, bit generation rate and approximate entropy is also presented. The work identifies PSKG and GSKG schemes which are practically realizable and also provides a discussion on the test bed employed for realising various PLSKG schemes. Moreover, a discussion on the research challenges in the area of PLSKG is also provided for future research

EVALUATION OF GENOTOXICITY PROFILE OF JASADA BHASMA (A ZINC-BASED MINERAL FORMULATION) IN SWISS ALBINO MICE

  Objective: Genotoxicity is regarded as one of the potential risk factors for causing pathological diseases. It was confirmed that many chemicals have the mutagenic activity which leads to cancer. A compound which interacts with genetic material DNA and shows adverse effects by altering its structure or function is referred to as genotoxic.Methods: The present study involved 40 Swiss albino mice weighing between 25 and 30 g body weights categorized into four different groups. Group-I (normal control) received 0.5% carboxymethyl cellulose as vehicle. Group-II (toxicant control) received 40 mg/kg/body weight cyclophosphamide on the 28th day. Group-III and IV received test drug JB 15.6 mg/kg and 78 mg/kg, respectively, for 28 consecutive days. Blood samples were collected and processed for evaluating by comet assay. The animals were sacrificed and collected the bone marrow from both the femur for chromosomal aberration and micronuclei assay.Results: JB administered at two different dose levels did not show any significant changes in the comet assay parameters, no micronucleus was found and did not produce any chromosomal aberrations both numerically and structurally when compared to positive test control group.Conclusion: The genotoxicity evaluation of JB did not show any chromosomal aberrations and presence of micronucleus. Thus, the safety data will refine therapeutic utility of JB encouraging their rationale use and translate into greater and broader utilization of JB

Hedge and Alder-Based Agroforestry Systems: Potential Interventions to Carbon Sequestration and Better Crop Productivity in Indian Sub-Himalayas

Not AvailableAgroforestry systems (AFSs) have potential to combat climate change and to ensure food security. AFSs can sequester carbon and amend the organic matter, thereby enhancing the crop productivity. Carbon sequestration depends on the type of AFSs, climate, cropping pattern, and management practices. The aim of this study was to evaluate different AFSs for their potential to sequester carbon and impact on soil organic matter (SOM) in the eastern sub-Himalayas, India. Hedge-, alder-, and guava-based AFSs were established along with control (without any tree), and the maize–mustard–potato cropping pattern was followed in each AFS. Soil samples were collected after the fifth crop cycle and further analyzed. The results showed that crop productivity was significantly higher in all the AFSs than control. On average, soil organic carbon (SOC) was found to be significantly higher by 62 and 64% in hedge-based AFSs as compared to guava-based AFSs and control, respectively, and at par with alder-based AFSs. Particulate organic carbon (POC) was higher in all the three AFSs than in the control. For microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) contents, the trend of AFSs was expressed as alder-based AFS > hedge-based AFS > guava-based AFS > control. Hedge- and alder-based AFSs had higher SOC stocks than guava-based AFSs and control. Carbon dioxide equivalent (CO2 eq.) emissions were greater in control than hedge-based AFSs (35.2 Mg ha−1), followed by alder-based AFSs (28.6 Mg ha−1), and the lowest was observed in guava-based AFSs. On an average, hedge species accumulated more nitrogen (N), phosphorus (P), and potassium (K), which were 60, 12, and 28 kg ha−1 yr−1, respectively. This conclusively proved that AFSs were significantly affecting SOM pools and crop productivity and had a significant role in carbon retention in the soil. Overall, hedge- and alder-based AFSs retained higher soil carbon, and hence, hedge- and alder-based AFSs may be promoted to achieve climate-smart agriculture practices in the acid soils of the Indian sub-Himalayan region.Not Availabl

Factify 2: A Multimodal Fake News and Satire News Dataset

The internet gives the world an open platform to express their views and share their stories. While this is very valuable, it makes fake news one of our society's most pressing problems. Manual fact checking process is time consuming, which makes it challenging to disprove misleading assertions before they cause significant harm. This is he driving interest in automatic fact or claim verification. Some of the existing datasets aim to support development of automating fact-checking techniques, however, most of them are text based. Multi-modal fact verification has received relatively scant attention. In this paper, we provide a multi-modal fact-checking dataset called FACTIFY 2, improving Factify 1 by using new data sources and adding satire articles. Factify 2 has 50,000 new data instances. Similar to FACTIFY 1.0, we have three broad categories - support, no-evidence, and refute, with sub-categories based on the entailment of visual and textual data. We also provide a BERT and Vison Transformer based baseline, which acheives 65% F1 score in the test set. The baseline codes and the dataset will be made available at https://github.com/surya1701/Factify-2.0.Comment: Defactify@AAAI202

Overview of Memotion 3: Sentiment and Emotion Analysis of Codemixed Hinglish Memes

Analyzing memes on the internet has emerged as a crucial endeavor due to the impact this multi-modal form of content wields in shaping online discourse. Memes have become a powerful tool for expressing emotions and sentiments, possibly even spreading hate and misinformation, through humor and sarcasm. In this paper, we present the overview of the Memotion 3 shared task, as part of the DeFactify 2 workshop at AAAI-23. The task released an annotated dataset of Hindi-English code-mixed memes based on their Sentiment (Task A), Emotion (Task B), and Emotion intensity (Task C). Each of these is defined as an individual task and the participants are ranked separately for each task. Over 50 teams registered for the shared task and 5 made final submissions to the test set of the Memotion 3 dataset. CLIP, BERT modifications, ViT etc. were the most popular models among the participants along with approaches such as Student-Teacher model, Fusion, and Ensembling. The best final F1 score for Task A is 34.41, Task B is 79.77 and Task C is 59.82.Comment: Defactify2 @AAAI 202

Findings of Factify 2: Multimodal Fake News Detection

With social media usage growing exponentially in the past few years, fake news has also become extremely prevalent. The detrimental impact of fake news emphasizes the need for research focused on automating the detection of false information and verifying its accuracy. In this work, we present the outcome of the Factify 2 shared task, which provides a multi-modal fact verification and satire news dataset, as part of the DeFactify 2 workshop at AAAI'23. The data calls for a comparison based approach to the task by pairing social media claims with supporting documents, with both text and image, divided into 5 classes based on multi-modal relations. In the second iteration of this task we had over 60 participants and 9 final test-set submissions. The best performances came from the use of DeBERTa for text and Swinv2 and CLIP for image. The highest F1 score averaged for all five classes was 81.82%.Comment: Defactify2 @AAAI 202

Counter Turing Test CT^2: AI-Generated Text Detection is Not as Easy as You May Think -- Introducing AI Detectability Index

With the rise of prolific ChatGPT, the risk and consequences of AI-generated text has increased alarmingly. To address the inevitable question of ownership attribution for AI-generated artifacts, the US Copyright Office released a statement stating that 'If a work's traditional elements of authorship were produced by a machine, the work lacks human authorship and the Office will not register it'. Furthermore, both the US and the EU governments have recently drafted their initial proposals regarding the regulatory framework for AI. Given this cynosural spotlight on generative AI, AI-generated text detection (AGTD) has emerged as a topic that has already received immediate attention in research, with some initial methods having been proposed, soon followed by emergence of techniques to bypass detection. This paper introduces the Counter Turing Test (CT^2), a benchmark consisting of techniques aiming to offer a comprehensive evaluation of the robustness of existing AGTD techniques. Our empirical findings unequivocally highlight the fragility of the proposed AGTD methods under scrutiny. Amidst the extensive deliberations on policy-making for regulating AI development, it is of utmost importance to assess the detectability of content generated by LLMs. Thus, to establish a quantifiable spectrum facilitating the evaluation and ranking of LLMs according to their detectability levels, we propose the AI Detectability Index (ADI). We conduct a thorough examination of 15 contemporary LLMs, empirically demonstrating that larger LLMs tend to have a higher ADI, indicating they are less detectable compared to smaller LLMs. We firmly believe that ADI holds significant value as a tool for the wider NLP community, with the potential to serve as a rubric in AI-related policy-making.Comment: EMNLP 2023 Mai

Vulval elephantiasis as a result of tubercular lymphadenitis: two case reports and a review of the literature

<p>Abstract</p> <p>Introduction</p> <p>Elephantiasis as a result of chronic lymphedema is characterized by gross enlargement of the arms, legs or genitalia, and occurs due to a variety of obstructive diseases of the lymphatic system. Genital elephantiasis usually follows common filariasis and lymphogranuloma venereum. It may follow granuloma inguinale, carcinomas, lymph node dissection or irradiation and tuberculosis but this happens rarely. Vulval elephantiasis as a consequence of extensive lymph node destruction by tuberculosis is very rare. We present two very unusual cases of vulval elephantiasis due to tuberculous destruction of the inguinal lymph nodes.</p> <p>Case presentation</p> <p>Two Indian women - one aged 40 years and the other aged 27 years, with progressively increasing vulval swellings over a period of five and four years respectively - presented to our hospital. In both cases, there was a significant history on presentation. Both women had previously taken a complete course of anti-tubercular treatment for generalized lymphadenopathy. The vulval swellings were extremely large: in the first case report, measuring 35 × 25 cm on the right side and 45 × 30 cm on the left side, weighing 20 lb and 16 lb respectively. Both cases were managed by surgical excision with reconstruction and the outcome was positive. Satisfactory results have been maintained during a follow-up period of six years in both cases.</p> <p>Conclusions</p> <p>Elephantiasis of the female genitalia is unusual and it has rarely been reported following tuberculosis. We report two cases of vulval elephantiasis as a consequence of extensive lymph node destruction by tuberculosis, in order to highlight this very rare clinical scenario.</p