Integrating PV-based energy production utilizing the existing infrastructure of MRT-6 at Dhaka, Bangladesh.

In a very dense urban landscape, incorporating renewables becomes challenging due to a lack of space, planning, and mindset. Utilization of already existing large infrastructures in combination with existing technology and necessary adaptation can create the right synergy for harnessing renewables like solar. This paper proposes the installation of a solar power plant in Dhaka, Bangladesh, using available space on Metro Rail Line 6 to meet the increasing demand for clean and renewable energy. The proposed system involves the selection of suitable space, and PV panels, the calculation of annual electricity generation, and performing financial and environmental analyses. The proposed on-grid/grid-tied system offers the advantage of reducing dependence on power supplied to the grid, resulting in lower energy costs, and promoting the use of green energy. The system has a payback period of 7.7 years and a return on investment of 45.7 %. It is estimated that the system saves 14,053.203 tons of CO2 emissions per year and 281,064.06 tons of CO2 emissions over its lifetime. Also, the grid life cycle emission is 584 gCO2/kWh, and the system life cycle emission is 39,119.4 tCO2, which further proves that it is a feasible solution to meeting energy demands while reducing the dependency on fossil fuels and promoting sustainable energy utilization. The results of simulations run using PVsyst and HOMER confirm the economic viability of the proposed solar power station, supporting its viability. The levelized energy cost (LCOE), as projected by PVsyst, is $0.09 per kWh, nearly matching HOMER's prediction of $0.0835. This convergence of results from several simulation tools supports the solar power plant's predicted cost-effectiveness, demonstrating its potential as a key player in the effort to create a greener and more affordable energy landscape.

From superhydrophilicity to superhydrophobicity: high-resolution neutron imaging and modeling of water imbibition through porous surfaces treated with engineered nano-coatings.

This paper reports on a superhydrophilic to superhydrophobic transformation of TiO2 nanoparticles doped zinc phosphate coating systems when a hydrophobic agent is applied. The objective of the reported research was to demonstrate the feasibility of a neutron imaging technique for evaluating the performance of the proposed nano-coating system and reveal the differences in water ingress mechanisms which are specific to plain, superhydrophilic, overhydrophobic, and superhydrophobic specimens. The engineered nano-coatings were designed to improve hydrophobic response with inducing the required roughness pattern and introducing the photocatalytic performance. The effectiveness of the coatings was assessed using high-resolution neutron imaging (HR-NI), SEM, CLSM, and XRD techniques. High-resolution neutron imaging revealed that the superhydrophobic coating effectively prevents water ingress into the porous ceramic substrate, whereas water imbibition was observed for superhydrophilic coating during the test duration. The moisture transport kinetics was modeled based on the Richards equation for plain ceramic and superhydrophilic specimens using obtained penetration depth values from HR-NI. SEM, CLSM, and XRD studies confirm the desired TiO2-doped zinc phosphate coatings with increased surface roughness, photocatalytic reactivity, and chemical bonding. The research results demonstrated that a two-layer superhydrophobic system is capable of creating effective water barriers on the surface with contact angles of 153°, which remained effective even after surface damage.

Monitoring COVID-19 on Social Media: Development of an End-to-End Natural Language Processing Pipeline Using a Novel Triage and Diagnosis Approach.

BACKGROUND: The COVID-19 pandemic has created a pressing need for integrating information from disparate sources in order to assist decision makers. Social media is important in this respect; however, to make sense of the textual information it provides and be able to automate the processing of large amounts of data, natural language processing methods are needed. Social media posts are often noisy, yet they may provide valuable insights regarding the severity and prevalence of the disease in the population. Here, we adopt a triage and diagnosis approach to analyzing social media posts using machine learning techniques for the purpose of disease detection and surveillance. We thus obtain useful prevalence and incidence statistics to identify disease symptoms and their severities, motivated by public health concerns. OBJECTIVE: This study aims to develop an end-to-end natural language processing pipeline for triage and diagnosis of COVID-19 from patient-authored social media posts in order to provide researchers and public health practitioners with additional information on the symptoms, severity, and prevalence of the disease rather than to provide an actionable decision at the individual level. METHODS: The text processing pipeline first extracted COVID-19 symptoms and related concepts, such as severity, duration, negations, and body parts, from patients' posts using conditional random fields. An unsupervised rule-based algorithm was then applied to establish relations between concepts in the next step of the pipeline. The extracted concepts and relations were subsequently used to construct 2 different vector representations of each post. These vectors were separately applied to build support vector machine learning models to triage patients into 3 categories and diagnose them for COVID-19. RESULTS: We reported macro- and microaveraged F1 scores in the range of 71%-96% and 61%-87%, respectively, for the triage and diagnosis of COVID-19 when the models were trained on human-labeled data. Our experimental results indicated that similar performance can be achieved when the models are trained using predicted labels from concept extraction and rule-based classifiers, thus yielding end-to-end machine learning. In addition, we highlighted important features uncovered by our diagnostic machine learning models and compared them with the most frequent symptoms revealed in another COVID-19 data set. In particular, we found that the most important features are not always the most frequent ones. CONCLUSIONS: Our preliminary results show that it is possible to automatically triage and diagnose patients for COVID-19 from social media natural language narratives, using a machine learning pipeline in order to provide information on the severity and prevalence of the disease for use within health surveillance systems.

Degradation of Perovskite Thin Films and Solar Cells with Candle Soot C/Ag Electrode Exposed in a Control Ambient.

Perovskite solar cells (PSCs) have already achieved efficiencies of over 25%; however, their instability and degradation in the operational environment have prevented them from becoming commercially viable. Understanding the degradation mechanism, as well as improving the fabrication technique for achieving high-quality perovskite films, is crucial to overcoming these shortcomings. In this study, we investigated details in the changes of physical properties associated with the degradation and/or decomposition of perovskite films and solar cells using XRD, FESEM, EDX, UV-Vis, Hall-effect, and current-voltage (I-V) measurement techniques. The dissociation, as well as the intensity of perovskite peaks, have been observed as an impact of film degradation by humidity. The decomposition rate of perovskite film has been estimated from the structural and optical changes. The performance degradation of novel planner structure PSCs has been investigated in detail. The PSCs were fabricated in-room ambient using candle soot carbon and screen-printed Ag electrode. It was found that until the perovskite film decomposed by 30%, the film properties and cell efficiency remained stable.

Learning structured medical information from social media.

Our goal is to summarise and aggregate information from social media regarding the symptoms of a disease, the drugs used and the treatment effects both positive and negative. To achieve this we first apply a supervised machine learning method to automatically extract medical concepts from natural language text. In an environment such as social media, where new data is continuously streamed, we need a methodology that will allow us to continuously train with the new data. To attain such incremental re-training, a semi-supervised methodology is developed, which is capable of learning new concepts from a small set of labelled data together with the much larger set of unlabelled data. The semi-supervised methodology deploys a conditional random field (CRF) as the base-line training algorithm for extracting medical concepts. The methodology iteratively augments to the training set sentences having high confidence, and adds terms to existing dictionaries to be used as features with the base-line model for further classification. Our empirical results show that the base-line CRF performs strongly across a range of different dictionary and training sizes; when the base-line is built with the full training data the F1 score reaches the range 84%-90%. Moreover, we show that the semi-supervised method produces a mild but significant improvement over the base-line. We also discuss the significance of the potential improvement of the semi-supervised methodology and found that it is significantly more accurate in most cases than the underlying base-line model.

Chemotherapeutic resistance of head and neck squamous cell carcinoma is mediated by EpCAM induction driven by IL-6/p62 associated Nrf2-antioxidant pathway activation.

Overexpression of epithelial cell adhesion molecule (EpCAM) has been associated with chemotherapeutic resistance, leads to aggressive tumor behavior, and results in an adverse clinical outcome. The molecular mechanism by which EpCAM enrichment is linked to therapeutic resistance via Nrf2, a key regulator of antioxidant genes is unknown. We have investigated the link between EpCAM and the Nrf2 pathway in light of therapeutic resistance using head and neck squamous cell carcinoma (HNSCC) patient tumor samples and cell lines. We report that EpCAM was highly expressed in Nrf2-positive and HPV-negative HNSCC cells. In addition, cisplatin-resistant tumor cells consisted of a higher proportion of EpCAMhigh cells compared to the cisplatin sensitive counterpart. EpCAMhigh populations exhibited resistance to cisplatin, a higher efficiency in colony formation, sphere growth and invasion capacity, and demonstrated reduced reactive oxygen species (ROS) activity. Furthermore, Nrf2 expression was significantly higher in EpCAMhigh populations. Mechanistically, expression of Nrf2 and its target genes were most prominently observed in EpCAMhigh populations. Silencing of EpCAM expression resulted in the attenuation of expressions of Nrf2 and SOD1 concomitant with a reduction of Sox2 expression. On the other hand, silencing of Nrf2 expression rendered EpCAMhigh populations sensitive to cisplatin treatment accompanied by the inhibition of colony formation, sphere formation, and invasion efficiency and increased ROS activity. The molecular mechanistic link between EpCAM expression and activation of Nrf2 was found to be a concerted interaction of interleukin-6 (IL-6) and p62. Silencing of p62 expression in EpCAMhigh populations resulted in the attenuation of Nrf2 pathway activation suggesting that Nrf2 pathway activation promoted resistance to cisplatin in EpCAMhigh populations. We propose that therapeutic targeting the Nrf2-EpCAM axis might be an excellent approach to modulate stress resistance and thereby survival of HNSCC patients enriched in EpCAMhigh populations.

Widespread expression of Sonic hedgehog (Shh) and Nrf2 in patients treated with cisplatin predicts outcome in resected tumors and are potential therapeutic targets for HPV-negative head and neck cancer.

BACKGROUND: Sonic hedgehog (Shh) and Nrf2 play a critical role in chemotherapeutic resistance. These two genes have been found to be dysregulated in head and neck squamous cell carcinomas (HNSCC). The purpose of this study was to analyze the expression, function and clinical prognostic relationship of Shh and Nrf2 in HNSCC in the context of therapeutic resistance and cancer stem cells (CSCs). METHODS: We analyzed a cohort of patients with HNSCC to identify potential therapeutic biomarkers correlating with overall survival (OS) as well as disease-free survival (DFS) from our own data and validated these results using The Cancer Genome Atlas dataset. Expression of Shh and Nrf2 was knocked down by siRNA and cell growth, sphere growth and chemotherapeutic resistance were evaluated. RESULTS: Widespread abundant expression of Shh and Nrf2 proteins were associated with shorter OS and DFS. The combination of Shh and Nrf2 expression levels was found to be a significant predictor of patient DFS. The tumor stromal index was correlated with Shh expression and inversely associated with shorter OS and DFS. Inhibition of Shh by siRNA or cyclopamine resulted in the attenuation of resistant CSC self-renewal, invasion, clonogenic growth and re-sensitization to the chemotherapeutic agents. Concomitant upregulation of Shh and Nrf2 proved to be an independent predictor of poor OS and DFS in patients with HNSCC. CONCLUSIONS: These findings suggest that Shh and Nrf2 could serve as therapeutic targets as well as promising dual prognostic therapeutic biomarkers for HNSCC.

Anal Extrusion of Ventriculoperitoneal Shunt: A Report of Two Cases and Review of Literature.

We report two cases of gastrointestinal perforation by ventriculoperitoneal (VP) shunts and review the literature on the topic. The time interval between shunt surgery and detection of bowel perforation is minimum in infants and increases with age. Sigmoid and transverse colon followed by stomach are the most frequent sites of gastrointestinal perforations by VP shunts.

Agile Blocker and Clock Jitter Tolerant Low-Power Frequency Selective Receiver with Energy Harvesting Capability.

In this article, a novel tunable, blocker and clock jitter tolerant, low power, quadrature phase shift frequency selective (QPS-FS) receiver with energy harvesting capability is proposed. The receiver's design embraces and integrates (i) the baseband to radio frequency (RF) impedance translation concept to improve selectivity over that of conventional homodyne receiver topologies and (ii) broadband quadrature phase shift circuitry in the RF path to remove an active multi-phase clock generation circuit in passive mixer (PM) receivers. The use of a single local oscillator clock signal with a passive clock division network improves the receiver's robustness against clock jitter and reduces the source clock frequency by a factor of N, compared to PM receivers using N switches (N≥4). As a consequence, the frequency coverage of the QPS-FS receiver is improved by a factor of N, given a clock source of maximum frequency; and, the power consumption of the whole receiver system can eventually be reduced. The tunable QPS-FS receiver separates the wanted RF band signal from the unwanted blockers/interferers. The desired RF signal is frequency down-converted to baseband, while the undesired blocker/interferer signals are reflected by the receiver, collected and could be energy recycled using an auxiliary energy harvesting device.

Effects of weaning biscuits on the nutritional profile and the cognitive development in preschool children.

AIM: To study the effect of weaning biscuits supplementation of the nutritional parameters and cognitive performance of the selected children. METHODS: Three primary schools situated in Salem District, Tamilnadu, India were selected. A total number of 150 school children, 61 from primary school I, 46 from primary school II and 43 from primary school III comprised the study sample. About 80 primary school children with Grade II malnutrition were selected for the experimental study. Home diet without any supplementation was followed by Group I (n=20, control group), potato flour biscuit was supplemented to Group II (n=20), wheat biscuits was given to Group III (n=20) and ragi biscuits were given to Group IV (n=20) for the period of 3 months. Parameters like anthropometric measurements, hemoglobin content clinical picture and cognitive performance were analyzed before and after supplementation. RESULTS: Results about Group I (control group) showed no significant difference in height, weight and clinical picture and cognitive performance after three months on their home diet. In Group II, III and IV significant increase in all the above parameters was noticed. More increase was found in Group II children supplemented with potato flour biscuits for a period of 3 months. About cognitive performance better results was obtained in Group II followed by Group III (supplemented with wheat biscuits) and Group IV (supplemented with ragi biscuits). Least was obtained by control group children who are in their home diet. CONCLUSION: All these observations evident that if such weaning biscuits made with potato flour, wheat and Ragi can form a daily ingredient in their diets, it will bring out better all round development of the children.

Dyspnea reproducibility in a rural Bangladesh population.

BACKGROUND AND AIMS: Dyspnea may signal serious disease with increased morbidity/mortality. Dyspnea screening would only be valid if reproducible. The study aim was to determine the reliability (reproducibility) of assessing dyspnea through a simple questionnaire among a rural population. METHODS: Participants were recruited from a Health Effects of Arsenic Longitudinal Study in Araihazar, Bangladesh. Dyspnea assessment used a questionnaire among 129 participants at two time points: at baseline and after 2 weeks to 9 months by trained physicians. All subjects were asked about the presence/absence of dyspnea in the last 6 months. At the second interview, a physician (blinded to questionnaire) conducted a clinical heart/lung examination and obtained a pulse oximeter reading. RESULTS: Dyspnea prevalence by baseline questionnaire was 2.4%. Overall dyspnea reliability was 94% (121 out of 129). If the initial response was 'yes' for the presence of dyspnea, reliability was 91% (49 out of 54). For an initial response of 'no' for the presence of dyspnea, reliability was 96% (72 out of 75). The pulmonary examination and pulse oximeter readings were significantly more likely to be abnormal in those with dyspnea (P < 0.01). CONCLUSIONS: The reliability of a simple question on dyspnea is very high when obtained by physicians. Although validity was not the primary outcome, the increased likelihood of an abnormal chest examination or low pulse oximeter saturation for those reporting 'yes' to the dyspnea question suggests more significant underlying cardiopulmonary disease in those reporting recent dyspnea.

Successful repair of ascending aortic pseudoaneurysm using autograft patch from fascia lata and saphenous vein.

An 80-year-old man developed a pseudoaneurysm in the ascending aorta due to mediastinitis following cardiac surgery. We successfully repaired the pseudoaneurysm with an autograft patch harvested from fascia lata and the saphenous vein. The repair, which was carried out in two layers, can be expected to be durable.