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The COVID-19 pandemic has subjected healthcare workers to enormous stress. Measuring the impact of this public health emergency is essential to developing strategies that can effectively promote resilience and wellness. The Epidemic-Pandemic Impacts Inventory Supplemental Healthcare Module-Brief Version (EPII-SHMb) was developed to measure impacts among occupational cohorts serving on the front lines of healthcare. While this instrument has been utilized in COVID-19 related studies, little is known about its psychometric properties. This study collects evidence for validity of the EPII-SHMb by evaluating its internal structure and how its scores associate with other variables. Physicians and nursing staff across a large New York health system were cross-sectionally surveyed using an online questionnaire between June and November 2020. Exploratory factor analysis resulted in a 3-factor solution, identifying factors Lack of Workplace Safety (7 items), Death/Dying of Patients (3 items), and Lack of Outside Support (2 items). Internal consistency was high overall and within physician/nursing and gender subgroups (Cronbach’s alpha: 0.70 − 0.81). Median scores on Death/Dying of Patients were higher among those who directly cared for COVID-19 patients or worked in COVID-19 hospital units. These results are promising. Additional studies evaluating other dimensions of validity are necessary.

Objective: To examine the association between a number of negative COVID-19 occupational experiences and probable anxiety, depression, and PTSD among physicians. Methods: Cross-sectional examination of longitudinal registry data consisting of physician personal and occupational well-being. Multivariable logistic regressions were performed to determine the association between negative COVID-19 experiences and outcomes. Results: Of the 620 eligible physicians, approximately half were female (49%), and 71% white with a mean age of 46.51 (SD = 13.28). A one-point increase in negative experience score was associated with a 23% increase in probable anxiety (OR = 1.23, 95% CI: 1.14–1.34), a 23% increase in probable depression (OR = 1.23, 95% CI: 1.13–1.33), and a 41% increase in probable PTSD (OR = 1.41, 95% CI: 1.30–1.52). Conclusions: Negative pandemic experiences were strongly associated with adverse mental health outcomes while greater resilience was protective.

In the coming years, farmers will face challenges to feed the increasing number of populations. They need to ensure food security and reduce the dependency on imports. The effective use of new technologies to increase the efficiency of farming will help the farmers to meet the need of increased population AI and IOT related automation to be designed to improve the way a farmer operates for various tasks. We propose a framework for IoT based Soil Nutrition and Plant Disease detection which uses various sensors to collect the plant-related data in form of images at different time intervals using MY THINGS smart sensor and Soil sensors such as proximal soil sensor (PSS) to test the soil fertility which helps to analyze the condition of soil new cultivation, ploughing, water or the land for harvesting. Temperature sensors are also used. Water quality sensors are used that will keep monitoring the quality of the water. All the data will we be sent to the farmer with the help of the IoT. For image classification, Local binary thresholding is used. At harvesting time robot performs image recognition and classification. The farmer will enter the required data to use the robotic arm to automatically harvest the crop. The arm is proposed to have four degrees of freedom and will be driven by the motors. Robotic arms will identify the crop using image recognition and will put that batch in the appropriate basket to be considered by the farmer for analysis. With regular monitoring, this proposed framework can greatly aid the farmers in maintaining crop health as well as quality.

Uncertainty in weather dynamics makes it important to build accurate weather prediction systems because it can save lives by better preparing people for an upcoming incidence. The aim of present research study is to present a comprehensive review of recent scientific works for short term temperature and rainfall prediction on both local and global spatial scale. The literature shows that some meteorological factors like Atmospheric pressure, precipitation, dew point temperature, solar radiation, vapor pressure, cloud cover, snowfall, humidity, wind velocity and wind direction are potential measures to predict future temperature and rainfall. We focused on recent applications of machine learning and deep learning models like Deep Echo State Network, recurrent neural network, convolutional recurrent neural network, and graph convolutional network, Autoencoders, Multi layer Perceptron and Long short-term memory. Applications of multimodal learning, reservoir computing and multitask learning have shown noticeable enhancement in the prediction accuracy of other state of art the models. Fine capability of CNN to extract suitable patterns from numeric weather data is also reported. The time interval of data recording also affects the prediction accuracy greatly. More frequently recorded input data worked better than less frequently recorded data. The use of electromagnetic sensors instead of satellite and radar setups is reliable as well as cost effective for collecting data for prediction. Evaluation indices related to hit rate of rainfall and no rainfall, caching rate, overlooking rate and Swing-and-miss rate can be considered as statistical measures along with other statistical metrics in case of rainfall prediction.

Spindle cell hemangioendothelioma (SCH) was first described in 1986 by Weiss and Enzinger as a vascular neoplasm, characterized by cavernous blood vessels and spindled areas reminiscent of Kaposi’s sarcoma. The head and neck region is rarely involved with extremely rare muscular involvement; this being the first case of intramasseteric SCH. A 30 year old male presented with a 2-year history of a painless, slow growing swelling on the left side of face. Fine needle aspiration cytology and Magnetic Resonance Imaging revealed it to be a vascular malformation. As the lesion did not respond to intralesional sclerotherapy, the lesion was surgically excised under general anaesthesia. The final diagnosis was aided by histopathological analysis and immunohistochemistry which revealed the lesion to be an intramassteric spindle cell hemangioendothelioma. On reviewing the literature, it can be established that spindle cell hemangioendothelioma is an unusual vascular tumor of the head and neck that is important to recognize to avoid misdiagnosis. Immunohistochemistry is considered as the final diagnostic aid and local surgical excision has been the most accepted treatment modality.

Classification of breast cancers into different molecular subtypes using immunohistochemistry as a surrogate tool to DNA microarray technology has been identified. Aim of this study was to find the precise prevalence of molecular subtypes of invasive breast carcinoma using immunohistochemistry and to correlate it with histological and clinical prognostic factors.A descriptive study design wherein 56 breast carcinoma cases diagnosed between May 2012 and Apr 2014 were reviewed and molecular subtyped using relevant immunohistochemical markers. Age, histological type, tumor size, tumor grade, lymphovascular emboli (LVE), nodal status and basal marker expressions were analyzed for all cases. Correlations between molecular subtypes and clinico-pathological characteristics were evaluated statistically.In our study group, average age of patients was 50.5 years and most of patients were diagnosed in stage II (54%). Luminal A subtype was most prevalent 34%, followed by Basal like/Triple negative subtype 25%. Luminal B and Her2/neu subtypes had same prevalence i.e. 18% each and Breast Tissue like/Unclassified subtype/Penta Negative subtype was 5%. All cases demonstrated positivity for the luminal cytokeratins 8/18. Histological grade and ER negative status showed strong correlations with basal markers.On the basis of hormone receptor, Her2 neu, EGFR and CK 5/6 expressions, breast carcinoma cases were classified into five distinct molecular subtypes which show significant differences in regards to morphological features, prognostic markers and there by predicting possible clinical outcome.

On-going revolution in ever-improving wireless communication enforces the necessity of a self configuring, rapidly deployable and infrastructure less network. MANET is such an autonomous wireless network that meets the requirements. At the same time MANET’s random behavior and absence of any central intelligence to gather unambiguous knowledge about user contexts complexes QoS maintenance and hampers proper utilization of network resources resulting into unnecessary handovers. In past, few policy driven handover approaches have been proposed for MANET but none of them explores a comprehensive policy design. Therefore in this paper we propose an adaptive and optimized policy based handover mechanism which is based on explicitly designed policies like load balancing, service discovery and next hop selection .Efficient procedures for these policies are also explored .This work predicts the high time of handover need on the basis of application specific needs of individual freely roaming mobile nodes, avoiding unnecessary handovers and provides efficient handover procedure with optimized resource consumption, reduced latency and interruption time.

We present an atomically resolved study of metal-organic vapor epitaxy grown Mn doped InSb. Both topographic and spectroscopic measurements have been performed by cross-sectional scanning tunneling microscopy (STM). The measurements on the Mn doped InSb samples show a perfect crystal structure without any precipitates and reveal that Mn acts as a shallow acceptor. TheMn concentration of the order of 1020cm3 obtained from the cross-sectional STM data compare well with the intended doping concentration. While the pair correlation function of the Mn atoms showed that their local distribution is uncorrelated beyond the STM resolution for observing individual dopants, disorder in the Mn ion location giving rise to percolation pathways is clearly noted. The amount of clustering that we see is thus as expected for a fully randomly disordered distribution of the Mn atoms and no enhanced clustering or second phase material was observed.

Background The aim of this study was to examine the functioning of fronto-striatal brain circuits that support self-regulatory capacities including conflict resolution and sequential processing in unmedicated adults with obsessive-compulsive disorder (OCD). Methods We compared functional magnetic resonance imaging blood oxygen level–dependent response in 22 adults with OCD with 22 healthy, age-matched control subjects during performance of a Simon Spatial Incompatibility task. We used general linear modeling to compare groups in their patterns of brain activation during correct responses to conflict-laden stimuli and explore the effects of trial sequence on group differences. Results Behavioral performance on the Simon task did not differ between groups. In response to conflict-laden stimuli, OCD participants activated fronto-striatal regions significantly more than control subjects, specifically a right hemisphere cluster encompassing the putamen, insula, and inferior frontal gyrus. Their activation of this cluster was driven not by conflict on a current trial but by their response to the alternation of stimulus congruence (incongruent or congruent) across trial sequences (i.e., current and preceding trials) and was most accentuated in participants with more severe symptoms in the doubt/checking dimension. Functional connectivity from the putamen to other fronto-striatal regions was also greater in the OCD compared with control participants. Conclusions When engaging the self-regulatory control necessary to resolve conflict and process alternating stimuli, OCD participants displayed excessive activation in a fronto-striatal circuit that differs from the orbitofrontal cortex–anterior cingulate cortex–caudate circuit typically implicated in OCD. Dysfunction in this circuit was associated with processing changes in the stimulus context. We speculate that this dysfunction might be related to the cognitive inflexibility typical of persons with OCD.

MANET’s random behavior and absence of any central intelligence to gather unambiguous knowledge about user contexts complexes QoS maintenance and hampers proper utilization of network resources resulting into unnecessary handovers. In such network uninterrupted connectivity requires the development of an efficient handover mechanism. A set of policies can be applied to efficiently manage the network resources. Therefore in this paper we propose an adaptive and optimized policy based handover mechanism which is based on explicitly designed policies and predicts the high time of handover need on the basis of application specific needs of individual freely roaming mobile nodes, avoiding unnecessary handovers and provides efficient handover procedure with optimized resource consumption, reduced latency and interruption time.