Source Localization Using Virtual Antenna Arrays

Using antenna arrays for direction of arrival (DoA) estimation and source localization is a well-researched topic. In this paper, we analyze virtual antenna arrays for DoA estimation where the antenna array geometry is acquired using data from a low-cost inertial measurement unit (IMU). Performance evaluation of an unaided inertial navigation system with respect to individual IMU sensor noise parameters is provided using a state space based extended Kalman filter. Secondly, using Monte Carlo simulations, DoA estimation performance of random 3-D antenna arrays is evaluated by computing Cramér-Rao lower bound values for a single plane wave source located in the far field of the array. Results in the paper suggest that larger antenna arrays can provide significant gain in DoA estimation accuracy, but, noise in the rate gyroscope measurements proves to be a limiting factor when making virtual antenna arrays for DoA estimation and source localization using single antenna devices

Collaborative Public Participatory Web Geographic Information System: A Groupware-Based Online Synchronous Collaboration to Support Municipal Planning

Co-PPGIS has a wide variety of applications like municipal planning, emergency response, public health and security, etc. The main focus of this paper is on the development and design of a web collaborative PPGIS (Co-PPGIS) infrastructure. As part of municipality’s planning and management services, Co-PPGIS is developed for real-time map sharing application system. Co-PPGIS is an effective and essential online meeting system for supporting group collaborations on geographic information such as maps and imageries and capturing and sharing of local/domain knowledge in real time. Co-PPGIS permits amalgamation of geospatial data and collaborator’s input in the form of geo-referenced notations. It incorporates coherent components such as map sharing, real-time chat, video conferencing, and geo-referenced textual and graphical notations. The study aims to focus on public participation and geo-collaboration facilitated with information sharing, interactive geo-conferencing, real-time map, and data sharing with tools to draw features or add annotation to the map while discussions, uploading documents, and live communication. Co-PPGIS provides an efficient and reliable platform that will significantly reduce the time to acquire, process, and analyze data. The significance of this study is to contribute to existing public participation practices, to municipal planning, to decision-making, or to geographic information science

Extraction and characterization of pectin from grapefruit (Duncan cultivar) and its utilization as gelling agent

Globally, agro-industrial by products such as fruit waste has attained immense recognition to be used for the extraction of valuable functional ingredients. Pectin is naturally occurring biopolymer that is widely recognized in food industry as well as in biotechnology. Keeping in view, current research was conducted for extraction, characterization and utilization of grapefruit peel pectin from Duncan cultivar. The extracted pectin was characterized for different parameters that explored its role in value added products. Acid extraction was carried out and then pectin was characterized for equivalent weight, ash content and methoxyl content. With the addition of extracted pectin, jam was prepared and analysed for physicochemical analysis and sensory attributes. The maximum extraction (22.55%) was done from grapefruit peel at temperature-120°C with pH-1.5, while minimum extraction (0.41%) was obtained at temperature-120°C with pH-2. Moreover, adding pectin in jam formulation resulted in significant effect on texture of the final product. Conclusively, pectin holds a great potential to be extracted and utilized in fruit based products for best quality and value addition

R2S100K: Road-Region Segmentation Dataset For Semi-Supervised Autonomous Driving in the Wild

Semantic understanding of roadways is a key enabling factor for safe autonomous driving. However, existing autonomous driving datasets provide well-structured urban roads while ignoring unstructured roadways containing distress, potholes, water puddles, and various kinds of road patches i.e., earthen, gravel etc. To this end, we introduce Road Region Segmentation dataset (R2S100K) -- a large-scale dataset and benchmark for training and evaluation of road segmentation in aforementioned challenging unstructured roadways. R2S100K comprises 100K images extracted from a large and diverse set of video sequences covering more than 1000 KM of roadways. Out of these 100K privacy respecting images, 14,000 images have fine pixel-labeling of road regions, with 86,000 unlabeled images that can be leveraged through semi-supervised learning methods. Alongside, we present an Efficient Data Sampling (EDS) based self-training framework to improve learning by leveraging unlabeled data. Our experimental results demonstrate that the proposed method significantly improves learning methods in generalizability and reduces the labeling cost for semantic segmentation tasks. Our benchmark will be publicly available to facilitate future research at https://r2s100k.github.io/

Towards secure private and trustworthy human-centric embedded machine learning: An emotion-aware facial recognition case study

The use of artificial intelligence (AI) at the edge is transforming every aspect of the lives of human beings from scheduling daily activities to personalized shopping recommendations. Since the success of AI is to be measured ultimately in terms of how it benefits human beings, and that the data driving the deep learning-based edge AI algorithms are intricately and intimately tied to humans, it is important to look at these AI technologies through a human-centric lens. However, despite the significant impact of AI design on human interests, the security and trustworthiness of edge AI applications are not foolproof and ethicalneither foolproof nor ethical; Moreover, social norms are often ignored duringin the design, implementation, and deployment of edge AI systems. In this paper, we make the following two contributions: Firstly, we analyze the application of edge AI through a human-centric perspective. More specifically, we present a pipeline to develop human-centric embedded machine learning (HC-EML) applications leveraging a generic human-centric AI (HCAI) framework. Alongside, we also analyzediscuss the privacy, trustworthiness, robustness, and security aspects of HC-EML applications with an insider look at their challenges and possible solutions along the way. Secondly, to illustrate the gravity of these issues, we present a case study on the task of human facial emotion recognition (FER) based on AffectNet dataset, where we analyze the effects of widely used input quantization on the security, robustness, fairness, and trustworthiness of an EML model. We find that input quantization partially degrades the efficacy of adversarial and backdoor attacks at the cost of a slight decrease in accuracy over clean inputs. By analyzing the explanations generated by SHAP, we identify that the decision of a FER model is largely influenced by features such as eyes, alar crease, lips, and jaws. Additionally, we note that input quantization is notably biased against the dark skin faces, and hypothesize that low-contrast features of dark skin faces may be responsible for the observed trends. We conclude with precautionary remarks and guidelines for future researchers. 2022 The Author(s)This publication was made possible by NPRP grant # [13S-0206-200273] from the Qatar National Research Fund (a member of Qatar Foundation). Open Access funding provided by the Qatar National Library The statements made herein are solely the responsibility of the authors.Scopu

Novel Stimuli-Responsive Pectin-PVP-Functionalized Clay Based Smart Hydrogels for Drug Delivery and Controlled Release Application

Stimuli-responsive drug delivery systems are urgently required for injectable site-specific delivery and release of drugs in a controlled manner. For this purpose, we developed novel pH-sensitive, biodegradable, and antimicrobial hydrogels from bio-macromolecule pectin, polyvinylpyrrolidone (PVP), 3-aminopropyl (diethoxy)methyl silane (3-APDEMS), and sepiolite clay via blending and solution casting technique. The purified sepiolite (40 um) was functionalized with 3-APDEMS crosslinker (ex-situ modification) followed by hydrogels fabrication. FTIR and SEM confirmed crosslinked structural integrity and rod-like morphology of hydrogels respectively. The swelling properties of hydrogels could be controlled by varying the concentration of modified clay in pectin/PVP blends. Moreover, the decrease in pH increased the swelling of hydrogels indicating the pH-responsiveness of hydrogels. All hydrogels were degraded after 21 days in phosphate buffer saline pH 7.4 (human blood pH). In-vitro cytotoxicity against 3T3 mouse fibroblast cell line analysis confirmed cytocompatibility of all hydrogels. Ceftriaxone sodium (CTX-S) was selected as a model drug. The release profile of the hydrogel showed 91.82% release in PBS for 2 h in a consistent and controlled manner. The chemical structure of the drug remained intact during and after release confirmed through UV-Visible spectroscopy. Overall, these hydrogels could be used as potential scaffolds for future biomedical applications

Impressions and attitudes of adult residents of Karachi towards a possible public health insurance scheme

Objective: To gauge the general population\u27s knowledge and attitude towards a possible public health insurance scheme.Methods: This descriptive, cross-sectional study was conducted at the Aga Khan University Hospital, Karachi, from April to May 2015, and comprised permanent residents of the city. Convenience sampling was used. Data was collected via questionnaires. SPSS 22 was used for data analysis.Results: There were 340 participants in the study with an overall mean age of 32.9±12.4 years. Besides, 159(46.8%) participants were aware of the concept of medical insurance while the correct definition was identified by 160(50.5%) respondents. Overall, 256(75.3%) participants were willing to join a theoretical public health insurance scheme. Of all the respondents, 107(31.5%) had faced a catastrophic event in the past and consequently were more willing to join. Of those unsure or not willing to join, 33(37.9%) respondents identified lack of trust in government programmes as the main reason for their choice.CONCLUSIONS: A large majority of adults had a favourable attitude towards the implementation of a possible public health insurance scheme

Nigella sativa fixed and essential oil improves antioxidant status through modulation of antioxidant enzymes and immunity

The onset of 21st century witnessed the awareness among the masses regarding the diet-health linkages. The researchers attempted to explore traditional products/plants were in the domain of pharmacy and nutrition focussing on their health benefits. In the present research intervention, we investigate the role of Nigella sativa fixed oil (NSFO) and essential oil (NSEO) in improving antioxidant status and modulation of enzymes. The National Institute of Health (NIH) provided us 30 Sprague Dawley rats that were equally placed in three groups. The groups were fed on their respective diets (56 days) two experimental diets i.e. D2 (NSFO @ 4.0%) and D3 (NSEO @ 0.30%) and control. The indices pertaining to antioxidant status, antioxidant enzymes, and parameters pertaining to immunity were evaluated at 4 weeks interval. The experimental diets (NSFO@ 4.0% & NSEO@ 0.30%) modulated the activities of antioxidant enzymes i.e., catalase (CAT), superoxide dismutase (SOD), glutathione transferase (GST), glutathione reductase (GR) and glutathione peroxidase (GPx), positively. Indices of antioxidant status like tocopherols and glutathione were in linear relationship with that of GPx, GR and GST (P<0.01). Myeloperoxidase activities were in negative correlation with GST (P<0.01) but positive correlation with some other parameters. In the nutshell, the fixed and essential oil of Nigella sativa are effective in improving the indices pertaining to antioxidant status, however, the immune boosting potential needs further clarification. However, authors are of the view that there is need to explore the molecular targets of Nigella sativa fixed and essential oils. Findings from such studies would be useful to validate this instant study for health promoting potential against diabetes mellitus and cardiovascular disorders

Hyperbranched polyethyleneimine induced polycationic membranes for improved fouling resistance and high RO performance

The study shows a new method for hyperbranched polyethyleneimine (HPEI) induced polycation membranes with an objective of achieving better fouling resistance and high reverse osmosis (RO) performance. Chemically crosslinked composite membrane (CCCM) was prepared with polyvinyl alcohol (PVA), maleic acid (MA) and Pluronic F127 via chemical crosslinking methodology. Polycation induced membranes were fabricated by surface coating of HPEI onto the CCCM (PVA/MA/PluronicF127) RO membranes. Functional group analysis, morphology and surface roughness of CCCM and HPEI-RO membranes were analyzed by Fourier transform infrared spectroscopy, scanning electron microscopy and atomic force microscopy respectively. The hydrophilicity and water permeability of CCCM and HPEI-RO were examined with water contact angle measurement and RO performance test. Optimum RO performance was obtained for HPEI-RO3 membrane with NaCl and MgSO4, as for RNaCl = 96.1%, JNaCl = 58.2 L m�2 h�1 and RMgSO4 = 99.6%, JMgSO4 = 15.8 L m�2 h�1 (testing with 3.28 wt.% aqueous NaCl and MgSO4 solution at 25 �C and 55 bar). Moreover, cetyl trimethylammonium bromide (CTAB) as standard foulants presented a smaller fouling tendency for the modified HPEI-RO3 membrane. HPEI-RO3 compared to the unmodified membrane, was able to decrease the stickiness of charged bacteria, Gram negative Escherichia coli and Gram positive Staphylococcus epidermidis. Therefore, the permeation flux, salt rejection and fouling resistant property of membrane (HPEI-RO3) were significantly improved with polycation induction into the membranes

Outcomes with chimeric antigen receptor t-cell therapy in relapsed or refractory acute myeloid leukemia: a systematic review and meta-analysis

BackgroundWe conducted a systematic review and meta-analysis to evaluate outcomes following chimeric antigen receptor T cell (CAR-T) therapy in relapsed/refractory acute myeloid leukemia (RR-AML).MethodsWe performed a literature search on PubMed, Cochrane Library, and Clinicaltrials.gov. After screening 677 manuscripts, 13 studies were included. Data was extracted following PRISMA guidelines. Pooled analysis was done using the meta-package by Schwarzer et al. Proportions with 95% confidence intervals (CI) were computed.ResultsWe analyzed 57 patients from 10 clinical trials and 3 case reports. The pooled complete and overall response rates were 49.5% (95% CI 0.18-0.81, I2 =65%) and 65.2% (95% CI 0.36-0.91, I2 =57%). The pooled incidence of cytokine release syndrome, immune-effector cell associated neurotoxicity syndrome, and graft-versus-host disease was estimated as 54.4% (95% CI 0.17-0.90, I2 =77%), 3.9% (95% CI 0.00-0.19, I2 =22%), and 1.6% (95%CI 0.00-0.21, I2 =33%), respectively.ConclusionCAR-T therapy has demonstrated modest efficacy in RR-AML. Major challenges include heterogeneous disease biology, lack of a unique targetable antigen, and immune exhaustion