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Thin films are an integral part of many electronic and optoelectronic devices. They also provide an excellent platform for material characterization. Therefore, strategies for the fabrication of thin films are constantly developed and have significantly benefited from the advent of high-throughput synthesis (HTS) platforms. This perspective summarizes recent advances in HTS of thin films from experimentalists' point of view. The work analyzes general strategies of HTS and then discusses their use in developing new energy materials for applications that rely on thin films, such as solar cells, light-emitting diodes, batteries, superconductors, and thermoelectrics. The perspective also summarizes some key challenges and opportunities in the HTS of thin films.

Pulmonary medical image analysis using image processing and deep learning approaches has made remarkable achievements in the diagnosis, prognosis, and severity check of lung diseases. The epidemic of COVID-19 brought out by the novel coronavirus has triggered a critical need for artificial intelligence assistance in diagnosing and controlling the disease to reduce its effects on people and global economies. This study aimed at identifying the various COVID-19 medical imaging analysis models proposed by different researchers and featured their merits and demerits. It gives a detailed discussion on the existing COVID-19 detection methodologies (diagnosis, prognosis, and severity/risk detection) and the challenges encountered for the same. It also highlights the various preprocessing and post-processing methods involved to enhance the detection mechanism. This work also tries to bring out the different unexplored research areas that are available for medical image analysis and how the vast research done for COVID-19 can advance the field. Despite deep learning methods presenting high levels of efficiency, some limitations have been briefly described in the study. Hence, this review can help understand the utilization and pros and cons of deep learning in analyzing medical images.

Type 1 interferon (IFN-I) response is the first line of host defense against invading viruses. In the absence of definite mouse models, the role of IFN-I in SARS-CoV-2 infections remained to be perplexing. Here, we developed two mouse models, one with constitutively high IFN-I response (hACE2;Irgm1−/−) and the other with dampened IFN-I response (hACE2;Ifnar1−/−) to comprehend the role of IFN-I response during SARS-CoV-2 invasion. We found that hACE2;Irgm1−/−mice were resistant to lethal SARS-CoV-2 infection with substantially reduced cytokine storm and immunopathology. In striking contrast, a severe SARS-CoV-2 infection along with immune cells infiltration, inflammatory response, and enhanced pathology was observed in the lungs of hACE2;Ifnar1−/−mice. Additionally, hACE2;Ifnar1−/−mice were highly susceptible to SARS-CoV-2 neuroinvasion in the brain accompanied by immune cell infiltration, microglia/astrocytes activation, cytokine response, and demyelination of neurons. The hACE2;Irgm1−/−Ifnar1−/−double knockout mice or hACE2;Irgm1−/−mice treated with STING or RIPK2 pharmacological inhibitors displayed loss of the protective phenotypes observed in hACE2;Irgm1−/−mice suggesting that heightened IFN-I response accounts for the observed immunity. Taken together, we explicitly demonstrate that IFN-I protects from lethal SARS-CoV-2 infection, andIrgm1(IRGM) could be an excellent therapeutic target.GRAPHICAL ABSTRACT

As bisphenol A (BPA) effortlessly crosses the blood-brain barrier, its serious impacts on the neuronal microenvironment towards precocious induction of oxidative stress and neuromorphological alteration can't be ignored. Incidentally, a symmetric study establishing the possible link of transformed neurobehavior with heightened monoamine oxidase (MAO) activity and neuromorphological alteration in zebrafish brain subsequent to BPA-exposure is limiting in the literature. The study was conducted to delineate the role of BPA towards the genesis of aggressive behaviour in zebrafish and its correlation with brain MAO activity. Mirror biting test and open field test were conducted to evaluate the aggressive and explorative behaviour respectively. Biochemical studies were performed to delineate the modulation of the antioxidant defence system. Cresyl violet staining and Hoechst staining in the periventricular grey zone of the zebrafish brain were conducted to evaluate neuronal pyknosis and chromatin condensation. Our study showed that BPA exposure is associated with the genesis of aggressive neurobehavioral response. Moreover, the brain MAO activity, oxidative stress and chromatin condensation were increased with increase in exposure duration. The results of the present study gave conclusive evidence that BPA act as a potent neurotoxicant in transforming the native neurobehavioral response of zebrafish through heightened oxidative stress, MAO activity and altered neuromorphology.

In rural areas of developing countries, solid fuels are still widely used for cooking, heating, and lighting purposes. This study investigates the effects of household air pollutants (HAPs) exposure on the occurrence of respiratory symptoms, blood pressure, and lung function. In this study, we randomly selected 123 (83 biomass and 40 clean fuel user) subjects to assess the impact of smoke generated from solid biomass fuel by assessing their health status along with the ventilation pattern of the kitchens and living rooms. HAPs (PM10, PM2.5, and CO) and different health parameters were measured along with monitoring of self-reported health symptoms for a consecutive period of eight months. Results revealed that the concentration of CO, PM2.5, and PM10 were found highest in biomass using households. Higher odds of the upper respiratory symptoms, runny nose (OR: 4.08, 95% CI: 1.22-22.14, p 0.03), nasal congestion (OR: 9.07, 95% CI: 1.39-97.89, p 0.01) and the odds of the lower respiratory symptoms like wheezing (OR: 1.62, 95% CI: 1.23-10.94, p 0.01), breathlessness (OR: 4.44, 95% CI: 1.3-14.75, p 0.01), chest tightness (OR: 4.89, 95% CI: 1.23-22.14, p 0.03) and dry cough (OR: 3.661, 95% CI: 1.05-12.25, p 0.04) were significantly higher in biomass fuel user. Similarly higher systolic (+11.41 mmHg), higher diastolic pressure (+3.3 mmHg), higher pulse pressure (+8.11 mmHg), and a 6 mmHg higher mean arterial pressure among biomass fuel using tribal women. The risk of hypertension was significantly (p 0.03) higher (OR: 3.04; 95% CI: 1.18-7.89) among solid biomass fuel users. The lung abnormality was recorded 28.91% (OR: 5.02, 95% CI: 1.50 to 16.56, p 0.01) among biomass fuel user. Finally, it is suggested that the use of efficient cookstoves, increase in cross ventilation, and cleaner fuel are urgently needed to curb the pollution load.

Critical energy infrastructures are increasingly relying on advanced sensing and control technologies for efficient and optimal utilization of flexible energy resources. Algorithmic procedures are needed to ensure that such systems are designed to be resilient to a wide range of cyber-physical adversarial events. This paper provides a robust optimization framework to quantify the range of adversarial perturbations that a system can accommodate without violating pre-specified resiliency metrics. An inner-approximation of the set of adversarial events which can be mitigated by the available flexibility is constructed using an optimization based approach. The proposed algorithm is illustrated on an islanded microgrid example: a modified IEEE 123-node feeder with distributed energy resources. Simulations are carried out to validate that the resiliency metrics are met for any event sampled from the constructed adversarial set for varying levels of available flexibility (energy reserves)., accepted at the IEEE American Control Conference 2022

SummaryCongenital heart defects, the most common birth disorders, are the clinical manifestation of anomalies in fetal heart development - a complex process involving dynamic spatiotemporal coordination among various precursor cell lineages. This complexity underlies the incomplete understanding of the genetic architecture of congenital heart diseases (CHDs). To define the multi-cellular epigenomic and transcriptional landscape of cardiac cellular development, we generated single-cell chromatin accessibility maps of human fetal heart tissues. We identified eight major differentiation trajectories involving primary cardiac cell types, each associated with dynamic transcription factor (TF) activity signatures. We identified similarities and differences of regulatory landscapes of iPSC-derived cardiac cell types and their in vivo counterparts. We interpreted deep learning models that predict cell-type resolved, base-resolution chromatin accessibility profiles from DNA sequence to decipher underlying TF motif lexicons and infer the regulatory impact of non-coding variants. De novo mutations predicted to affect chromatin accessibility in arterial endothelium were enriched in CHD cases versus controls. We used CRISPR-based perturbations to validate an enhancer harboring a nominated regulatory CHD mutation, linking it to effects on the expression of a known CHD gene JARID2. Together, this work defines the cell-type resolved cis-regulatory sequence determinants of heart development and identifies disruption of cell type-specific regulatory elements as a component of the genetic etiology of CHD.