Geographical Evaluation of Socio-economic Condition of Sargodha City to Measure Urban Poverty

The current study presents the socio economic conditions of people of Sargodha city to analyze the urban poverty level. Research was accomplished during the year of 2016-2018. Urban poverty is a burning social issue in world when a person do not succeeds to carry out his family needs and wants. A survey was conducted in eleven different colonies and 188 households were visited. Poverty level was scrutinized according to international poverty line less than 1 Dollar per day. During the field survey it was perceived that 17 percent of the households have income of less than 1 Dollar per day and they were real poor. Different parameters were examined like slums, dependency ratio, income, transportation, drinking water scheme, sewerage system and literacy rate. These parameters have compared with poverty to analyze the affordability and living condition of people. It was examined that there were several reasons for poverty in city like unemployment / low income, less education, high dependency ratio etc. Most of the people have large families but low income due to not as much of education and more dependent people in households. It was also suggested that Government should make better living conditions for people by providing technical skills to uneducated person to diminish unemployment and should advance the sanitation problems for better lifestyle

Geographical Evaluation of Socio-economic Condition of Sargodha City to Measure Urban Poverty

The current study presents the socio economic conditions of people of Sargodha city to analyze the urban poverty level. Research was accomplished during the year of 2016-2018. Urban poverty is a burning social issue in world when a person do not succeeds to carry out his family needs and wants. A survey was conducted in eleven different colonies and 188 households were visited. Poverty level was scrutinized according to international poverty line less than 1 Dollar per day. During the field survey it was perceived that 17 percent of the households have income of less than 1 Dollar per day and they were real poor. Different parameters were examined like slums, dependency ratio, income, transportation, drinking water scheme, sewerage system and literacy rate. These parameters have compared with poverty to analyze the affordability and living condition of people. It was examined that there were several reasons for poverty in city like unemployment / low income, less education, high dependency ratio etc. Most of the people have large families but low income due to not as much of education and more dependent people in households. It was also suggested that Government should make better living conditions for people by providing technical skills to uneducated person to diminish unemployment and should advance the sanitation problems for better lifestyle

Robust CNN architecture for classification of reach and grasp actions from neural correlates: an edge device perspective

Brain-computer interfaces (BCIs) systems traditionally use machine learning (ML) algorithms that require extensive signal processing and feature extraction. Deep learning (DL)-based convolutional neural networks (CNNs) recently achieved state-of-the-art electroencephalogram (EEG) signal classification accuracy. CNN models are complex and computationally intensive, making them difficult to port to edge devices for mobile and efficient BCI systems. For addressing the problem, a lightweight CNN architecture for efficient EEG signal classification is proposed. In the proposed model, a combination of a convolution layer for spatial feature extraction from the signal and a separable convolution layer to extract spatial features from each channel. For evaluation, the performance of the proposed model along with the other three models from the literature referred to as EEGNet, DeepConvNet, and EffNet on two different embedded devices, the Nvidia Jetson Xavier NX and Jetson Nano. The results of the Multivariant 2-way ANOVA (MANOVA) show a significant difference between the accuracies of ML and the proposed model. In a comparison of DL models, the proposed models, EEGNet, DeepConvNet, and EffNet, achieved 92.44 ± 4.30, 90.76 ± 4.06, 92.89 ± 4.23, and 81.69 ± 4.22 average accuracy with standard deviation, respectively. In terms of inference time, the proposed model performs better as compared to other models on both the Nvidia Jetson Xavier NX and Jetson Nano, achieving 1.9 sec and 16.1 sec, respectively. In the case of power consumption, the proposed model shows significant values on MANOVA (p < 0.05) on Jetson Nano and Xavier. Results show that the proposed model provides improved classification results with less power consumption and inference time on embedded platforms

Sustainable and Resilient Smart Water Grids: A Solution for Developing Countries

According to a United Nations report, the world population will increase from 7 billion to 9 billion by 2050. Further, the water stress level is more than 70% in 22 countries while in another 31 countries it is between 25% and 70%. More than 2 billion people live in these 53 countries which are all underdeveloped. Water use has increased by 1% per year since the 1980s, so global demand is expected to rise by 30% by 2050. Thus, efficient water grid management is imperative to ensure there is sufficient water for the future. Information and Communication Technology (ICT) can be used to create smart water grids to optimize water distribution, reduce waste and leakage, and resolve quality and overuse issues. In this work, a low cost, real-time, reliable and sustainable IoT based solution called SmartTubewell is proposed for smart water grid management. It is composed of two components, a sensor node installed at tube wells and an application layer on Amazon Web Services (AWS) for data analysis, storage and processing. The sensor node is based on a Raspberry Pi with integrated current and voltage sensors and a local database. The sensor data is transmitted to AWS using a cellular (GPRS) network. A comparison between the proposed system and SCADA is presented which shows that SmartTubewell has a much lower cost. A field test with multiple tube wells in Peshawar, Pakistan indicates that this is a suitable solution for developing countries

Macroscopic Traffic Flow Characterization at Bottlenecks

Traffic congestion is a significant issue in urban areas. Realistic traffic flow models are crucial for understanding and mitigating congestion. Congestion occurs at bottlenecks where large changes in density occur. In this paper, a traffic flow model is proposed which characterizes traffic at the egress and ingress to bottlenecks. This model is based on driver response which includes driver reaction and traffic stimuli. Driver reaction is based on time headway and driver behavior which can be classified as sluggish, typical or aggressive. Traffic stimuli are affected by the transition width and changes in the equilibrium velocity distribution. The explicit upwind difference scheme is used to evaluate the Lighthill, Whitham, and Richards (LWR) and proposed models with a continuous injection of traffic into the system. A stability analysis of these models is given and both are evaluated over a road of length 10 km which has a bottleneck. The results obtained show that the behavior with the proposed model is more realistic than with the LWR model. This is because the LWR model cannot adequately characterize driver behavior during changes in traffic flow

A novel digital score for abundance of tumour infiltrating lymphocytes predicts disease free survival in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is the most common type of head and neck (H&N) cancers with an increasing worldwide incidence and a worsening prognosis. The abundance of tumour infiltrating lymphocytes (TILs) has been shown to be a key prognostic indicator in a range of cancers with emerging evidence of its role in OSCC progression and treatment response. However, the current methods of TIL analysis are subjective and open to variability in interpretation. An automated method for quantification of TIL abundance has the potential to facilitate better stratification and prognostication of oral cancer patients. We propose a novel method for objective quantification of TIL abundance in OSCC histology images. The proposed TIL abundance (TILAb) score is calculated by first segmenting the whole slide images (WSIs) into underlying tissue types (tumour, lymphocytes, etc.) and then quantifying the co-localization of lymphocytes and tumour areas in a novel fashion. We investigate the prognostic significance of TILAb score on digitized WSIs of Hematoxylin and Eosin (H&E) stained slides of OSCC patients. Our deep learning based tissue segmentation achieves high accuracy of 96.31%, which paves the way for reliable downstream analysis. We show that the TILAb score is a strong prognostic indicator (p = 0.0006) of disease free survival (DFS) on our OSCC test cohort. The automated TILAb score has a significantly higher prognostic value than the manual TIL score (p = 0.0024). In summary, the proposed TILAb score is a digital biomarker which is based on more accurate classification of tumour and lymphocytic regions, is motivated by the biological definition of TILs as tumour infiltrating lymphocytes, with the added advantages of objective and reproducible quantification

A digital score of tumour‐associated stroma infiltrating lymphocytes predicts survival in head and neck squamous cell carcinoma

The infiltration of T-lymphocytes in the stroma and tumour is an indication of an effective immune response against the tumour, resulting in better survival. In this study, our aim was to explore the prognostic significance of tumour-associated stroma infiltrating lymphocytes (TASILs) in head and neck squamous cell carcinoma (HNSCC) through an AI-based automated method. A deep learning-based automated method was employed to segment tumour, tumour-associated stroma, and lymphocytes in digitally scanned whole slide images of HNSCC tissue slides. The spatial patterns of lymphocytes and tumour-associated stroma were digitally quantified to compute the tumour-associated stroma infiltrating lymphocytes score (TASIL-score). Finally, the prognostic significance of the TASIL-score for disease-specific and disease-free survival was investigated using the Cox proportional hazard analysis. Three different cohorts of haematoxylin and eosin (H&E)-stained tissue slides of HNSCC cases (n = 537 in total) were studied, including publicly available TCGA head and neck cancer cases. The TASIL-score carries prognostic significance (p = 0.002) for disease-specific survival of HNSCC patients. The TASIL-score also shows a better separation between low- and high-risk patients compared with the manual tumour-infiltrating lymphocytes (TILs) scoring by pathologists for both disease-specific and disease-free survival. A positive correlation of TASIL-score with molecular estimates of CD8+ T cells was also found, which is in line with existing findings. To the best of our knowledge, this is the first study to automate the quantification of TASILs from routine H&E slides of head and neck cancer. Our TASIL-score-based findings are aligned with the clinical knowledge, with the added advantages of objectivity, reproducibility, and strong prognostic value. Although we validated our method on three different cohorts (n = 537 cases in total), a comprehensive evaluation on large multicentric cohorts is required before the proposed digital score can be adopted in clinical practice

Effects of a high-dose 24-h infusion of tranexamic acid on death and thromboembolic events in patients with acute gastrointestinal bleeding (HALT-IT): an international randomised, double-blind, placebo-controlled trial

Background: Tranexamic acid reduces surgical bleeding and reduces death due to bleeding in patients with trauma. Meta-analyses of small trials show that tranexamic acid might decrease deaths from gastrointestinal bleeding. We aimed to assess the effects of tranexamic acid in patients with gastrointestinal bleeding. Methods: We did an international, multicentre, randomised, placebo-controlled trial in 164 hospitals in 15 countries. Patients were enrolled if the responsible clinician was uncertain whether to use tranexamic acid, were aged above the minimum age considered an adult in their country (either aged 16 years and older or aged 18 years and older), and had significant (defined as at risk of bleeding to death) upper or lower gastrointestinal bleeding. Patients were randomly assigned by selection of a numbered treatment pack from a box containing eight packs that were identical apart from the pack number. Patients received either a loading dose of 1 g tranexamic acid, which was added to 100 mL infusion bag of 0·9% sodium chloride and infused by slow intravenous injection over 10 min, followed by a maintenance dose of 3 g tranexamic acid added to 1 L of any isotonic intravenous solution and infused at 125 mg/h for 24 h, or placebo (sodium chloride 0·9%). Patients, caregivers, and those assessing outcomes were masked to allocation. The primary outcome was death due to bleeding within 5 days of randomisation; analysis excluded patients who received neither dose of the allocated treatment and those for whom outcome data on death were unavailable. This trial was registered with Current Controlled Trials, ISRCTN11225767, and ClinicalTrials.gov, NCT01658124. Findings: Between July 4, 2013, and June 21, 2019, we randomly allocated 12 009 patients to receive tranexamic acid (5994, 49·9%) or matching placebo (6015, 50·1%), of whom 11 952 (99·5%) received the first dose of the allocated treatment. Death due to bleeding within 5 days of randomisation occurred in 222 (4%) of 5956 patients in the tranexamic acid group and in 226 (4%) of 5981 patients in the placebo group (risk ratio [RR] 0·99, 95% CI 0·82–1·18). Arterial thromboembolic events (myocardial infarction or stroke) were similar in the tranexamic acid group and placebo group (42 [0·7%] of 5952 vs 46 [0·8%] of 5977; 0·92; 0·60 to 1·39). Venous thromboembolic events (deep vein thrombosis or pulmonary embolism) were higher in tranexamic acid group than in the placebo group (48 [0·8%] of 5952 vs 26 [0·4%] of 5977; RR 1·85; 95% CI 1·15 to 2·98). Interpretation: We found that tranexamic acid did not reduce death from gastrointestinal bleeding. On the basis of our results, tranexamic acid should not be used for the treatment of gastrointestinal bleeding outside the context of a randomised trial