Estimation of individual causal effects in network setup for multiple treatments

We study the problem of estimation of Individual Treatment Effects (ITE) in the context of multiple treatments and networked observational data. Leveraging the network information, we aim to utilize hidden confounders that may not be directly accessible in the observed data, thereby enhancing the practical applicability of the strong ignorability assumption. To achieve this, we first employ Graph Convolutional Networks (GCN) to learn a shared representation of the confounders. Then, our approach utilizes separate neural networks to infer potential outcomes for each treatment. We design a loss function as a weighted combination of two components: representation loss and Mean Squared Error (MSE) loss on the factual outcomes. To measure the representation loss, we extend existing metrics such as Wasserstein and Maximum Mean Discrepancy (MMD) from the binary treatment setting to the multiple treatments scenario. To validate the effectiveness of our proposed methodology, we conduct a series of experiments on the benchmark datasets such as BlogCatalog and Flickr. The experimental results consistently demonstrate the superior performance of our models when compared to baseline methods.Comment: 7 pages, accepted at AAAI-GCLR 202

A state-of-the-art review of the electrocoagulation technology for wastewater treatment

The continued increase in urbanisation and industrialisation across the world has dramatically increased the amount and variety of waste, and, in particular, wastewater, being generated. Wastewaters contain a large variety of both organic and inorganic contaminants. Various wastewater treatment technologies have been developed over the last few decades to address the increasing concern around effective contaminant removal from wastewater. Electrocoagulation (EC) is one such technology that is broad-based, highly reliable, and cost-effective. It also has a high pollutant removal efficiency and generates less sludge when compared with other techniques. However, despite being effectively used to treat a wide range of wastewater, a thorough examination of its efficiency under various process variables has not been critically examined. Various operating factors, such as pH, current density, the conductivity of the solution, electrode material, and mixing conditions, impact the electrocoagulation system. This paper aims to provide a comprehensive overview of the electrocoagulation technique and examine the current challenges to the efficiency of the technique due to the various operating conditions. Some recent advances in the EC technology that present opportunities to improve treatment efficiency and increase the scope to treat newer varieties of wastewater are addressed

The impact of surgical delay on resectability of colorectal cancer: An international prospective cohort study

AimThe SARS-CoV-2 pandemic has provided a unique opportunity to explore the impact of surgical delays on cancer resectability. This study aimed to compare resectability for colorectal cancer patients undergoing delayed versus non-delayed surgery.MethodsThis was an international prospective cohort study of consecutive colorectal cancer patients with a decision for curative surgery (January-April 2020). Surgical delay was defined as an operation taking place more than 4 weeks after treatment decision, in a patient who did not receive neoadjuvant therapy. A subgroup analysis explored the effects of delay in elective patients only. The impact of longer delays was explored in a sensitivity analysis. The primary outcome was complete resection, defined as curative resection with an R0 margin.ResultsOverall, 5453 patients from 304 hospitals in 47 countries were included, of whom 6.6% (358/5453) did not receive their planned operation. Of the 4304 operated patients without neoadjuvant therapy, 40.5% (1744/4304) were delayed beyond 4 weeks. Delayed patients were more likely to be older, men, more comorbid, have higher body mass index and have rectal cancer and early stage disease. Delayed patients had higher unadjusted rates of complete resection (93.7% vs. 91.9%, P = 0.032) and lower rates of emergency surgery (4.5% vs. 22.5%, P ConclusionOne in 15 colorectal cancer patients did not receive their planned operation during the first wave of COVID-19. Surgical delay did not appear to compromise resectability, raising the hypothesis that any reduction in long-term survival attributable to delays is likely to be due to micro-metastatic disease