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Project management is an important domain, especially in the allocation of resources and smooth operation with an assigned budget. To successfully complete a project, it is important to follow effective ways to use available tools, technique, and methods, considering present technology and management. Recently, Building Information Modelling is one of the techniques which creates, manage, or generate a model by taking physical and functional characteristics of building by using digital presentations. Term 4D modeling refers to fourth dimension that associates the 3D model of any construction project with the planned schedule and provides visualization of the actual sequence of construction activities. The study was carried out to understand the uses and benefits of BIM for better proper functioning of the project in accordance with the project schedule. The objective of the study is to minimise the challenge associated with traditional or conventional scheduling process of construction sequences and misunderstanding brought by the lack of visualization. To fulfill the objective of the study, the uses of different dimensions of Building Information Modelling (2D, 3D and 4D) for preconstruction and construction phase was identified. Then a prototype 4D Building Information Model was created and the BIM based schedule was integrated with it and studied. The software used for scheduling, 3D modelling and 4D simulation are Primavera, Autodesk Revit, and Autodesk Navisworks respectively.

Toxicity from digitalis is a typical clinical issue. In this case, the interaction of digoxin and furosemide is becoming more widely recognised as a major cause of digitalis toxicity. We present an abnormal ECG that demonstrates digoxin-induced cardiotoxicity. We report a case of a Digoxin toxicity in a 79-year-old male patient admitted with complains of nausea, increase frequency of micturition, decrease appetite, increase nocturia, shortness of breathing. The patient is taking furosemide and digoxin as past medication for Heart block and Chronic kidney disease treatment. In patient, Serum digoxin level is high due to hypokalemia because of digoxin and furosemide drug interaction. The Electrocardiogram interpretation shows sinus bradycardia, ST segment depression, and T wave inversion which mainly due to digoxin toxicity. So for the management digoxin is omitted from the current treatment. The patient needs to be constantly monitored since digitalis poisoning is deadly. A digoxin-binding antibody is the only treatment for digoxin overdose that can reverse its effects by its antidote but it’s not available. So, the most successful course of treatment is symptomatic or efficient methods of extracorporeal drug removal. Keywords: Digoxin toxicity, furosemide, hypokalemia, cardiotoxicity, complete heart block, ST segment depression.

Messenger RNA (mRNA) vaccines have emerged as a flexible platform for vaccine development. The evolution of lipid nanoparticles as effective delivery vehicles for modified mRNA encoding vaccine antigens was demonstrated by the response to the COVID-19 pandemic. The ability to rapidly develop effective SARS-CoV-2 vaccines from the spike protein genome, and to then manufacture multibillions of doses per year was an extraordinary achievement and a vaccine milestone. Further development and application of this platform for additional pathogens is clearly of interest. This comes with the associated need for new analytical tools that can accurately predict the performance of these mRNA vaccine candidates and tie them to an immune response expected in humans. Described here is the development and characterization of an imaging based in vitro assay able to quantitate transgene protein expression efficiency, with utility to measure lipid nanoparticles (LNP)-encapsulated mRNA vaccine potency, efficacy, and stability. Multiple biologically relevant adherent cell lines were screened to identify a suitable cell substrate capable of providing a wide dose–response curve and dynamic range. Biologically relevant assay attributes were examined and optimized, including cell monolayer morphology, antigen expression kinetics, and assay sensitivity to LNP properties, such as polyethylene glycol-lipid (or PEG–lipid) composition, mRNA mass, and LNP size. Collectively, this study presents a strategy to quickly optimize and develop a robust cell-based potency assay for the development of future mRNA-based vaccines.

India witnessed its first case of coronavirus infection (COVID-19) on January 27, 2020, in Kerala, India. Since then, the infection has spread rapidly across the country and the pandemic outbreak has affected all industries severely including the construction sector. This study aims to understand the effect of the COVID-19 pandemic on the construction sector, particularly the ready-mix concrete (RMC) industry. An attempt was made to investigate the liabilities and the losses incurred by the RMC industry in terms of income and change in the production of concrete during the coronavirus outbreak. A preliminary survey was carried out to create a database of the RMC plants located nearby the study area i.e., Ahmedabad City in the state of Gujarat, and to prepare a questionnaire using google forms. The RMC plants were visited and from the inputs of RMC officials, statistical insights were drawn. The study reveals that during the COVID-19 lockdown period there was almost a 40% loss in concrete production60% loss in the income generated by the ready-mix concrete industry. In addition to this, it was also found that the industry had to pay off liabilities like land rent, electricity bills, staff salaries, etc. during the time of the pandemic. This study provides the opportunity for RMC plants to identify the vital elements involved in the operation of the plant which can be affected due to such pandemic and provides guidelines to reduce the effect of any such pandemic on the plant's productionsales by ensuring the stability of all assets involved in its supply chain.

The explosive growth of Electric Vehicles has made developing a robust system for managing batteries that are one of the crucial components of an EV, the need of the hour. Accuracy of the estimation models for determining the State of Charge and State of Health levels of the battery packs plays a key role. There are many sophisticated systems to determine these parameters we have tried to review a few of these systems in this paper. The complete electrification of the automotive industry heavily depends on the energy density and longevity that the battery packs provide and maintaining these packs in a safe operating condition can help achieve these goals. Keywords: BMS (Battery management system), SoC(state of charge), SoH (State of Health), Battery Thermal Management Systems (BTMS)

Chimeric antigen receptors (CARs) repurpose natural signaling components to retarget T cells to refractory cancers but have shown limited efficacy in persistent, recurrent malignancies. Here, we introduce “CAR Pooling,” a multiplexed approach to rapidly identify CAR designs with clinical potential. Forty CARs with signaling domains derived from a range of immune cell lineages were evaluated in pooled assays for their ability to stimulate critical T cell effector functions during repetitive stimulation that mimics long-term tumor antigen exposure. Several domains were identified from the tumor necrosis factor (TNF) receptor family that have been primarily associated with B cells. CD40 enhanced proliferation, whereas B cell–activating factor receptor (BAFF-R) and transmembrane activator and CAML interactor (TACI) promoted cytotoxicity. These functions were enhanced relative to clinical benchmarks after prolonged antigen stimulation, and CAR T cell signaling through these domains fell into distinct states of memory, cytotoxicity, and metabolism. BAFF-R CAR T cells were enriched for a highly cytotoxic transcriptional signature previously associated with positive clinical outcomes. We also observed that replacing the 4-1BB intracellular signaling domain with the BAFF-R signaling domain in a clinically validated B cell maturation antigen (BCMA)–specific CAR resulted in enhanced activity in a xenotransplant model of multiple myeloma. Together, these results show that CAR Pooling is a general approach for rapid exploration of CAR architecture and activity to improve the efficacy of CAR T cell therapies.

In this paper, we used the single-photon emission computerized tomography (SPECT) imaging technique to visualize the deficiency of dopamine-generated patterns inside the brain. These patterns are used to establish a patient’s disease progression, which helps distinguish the patients into different categories. Furthermore, we used a convolutional neural network (CNN) model to classify the patients based on the dopamine level inside the brain. The dataset used throughout this paper is the Parkinson’s progressive markers initiative (PPMI) dataset. The collected dataset was pre-processed and data amplification was performed to balance the imbalanced dataset. A CNN-based neural network was defined to classify input SPECT images into four categories. The motivation behind the proposed model is to reduce the number of resources consumed while maintaining the performance of the classification model. This will help the healthcare ecosystem run the classification model on mobile devices. The proposed model contains 14 layers with input layers, convolutional layers, max-pool layers, flatten layers, and dense layers with different dimensions. The dense layer classifies the patients into four different categories, including PSD, healthy control, scans without evidence of dopaminergic deficit (SWEDD), and GenReg PSD from the entire SPECT imaging dataset, which is used to establish the disease progression of different patients using SPECT images. The proposed model is trained with a large dataset with 58,692 images for training and 11,738 images for validation, and 7826 for testing. The proposed model outperforms the classification models from the surveyed papers. The proposed model’s accuracy is 0.889, recall is 0.9012, the precision is 0.9104, and the F1-score is 0.9057.

Hospitalized patients with opioid use disorder who present with acute pain are challenging to manage. Without any treatment, their mortality in the first 28 days after discharge is substantially increased. Unlike extended-release naltrexone, which requires a period of withdrawal, or methadone, which can cause prolonged corrected QT (QTc) and carries a higher risk of respiratory depression, buprenorphine provides potent analgesia with low respiratory risk. Hospitalization provides a unique opportunity for clinicians to perform buprenorphine induction, which could potentially reduce mortality without affecting analgesia. Our acute pain management service uses multimodal analgesia to maintain adequate analgesia and minimize withdrawal during buprenorphine induction in the hospital. With the assistance of narcotics addiction rehabilitation program specialists, we help link patients to outpatient buprenorphine providers and maximize the chance of successful recovery. The primary outcome of this study was to determine the percentage of patients who filled an outpatient buprenorphine prescription after undergoing inpatient induction.

Introduction: Lateral malleoli fractures are one of the most commonly encountered injuries. Conventionally lateral fibula plating was done for fibula fracture but several studies have come up showing advantages of posterior antiglide plating for fibula. In this study, we aim at comparing the functional and radiological outcome in patients treated with conventional lateral fibula plating and posterior antiglide plating.Materials and methods: 30 patients with external rotation lateral malleoli fractures were studied prospectively. Lauge-hansen’s classification was used to classify these injuries. Patients were randomly divided into 2 groups. Group 1 was operated by lateral fibula plating and Group 2 by posterior antiglide plating. Comparison of the outcome between the 2 groups was done using Weber’s criteria.Result: The most common age group was 40-59 years with male dominance. Majority were supination-external rotation injuries. Both groups showed 33% excellent, 60% good and 7% poor outcomes. Lateral plating group exhibited few technical disadvantages like more hardware use, implant prominence and patient discomfort. But both groups were comparable in terms of surgical time, complications and final functional and radiological outcome.Conclusion: The outcome of the surgical management of a displaced lateral malleolus fracture is comparable with both techniques. Although few studies have reported some advantages using the antiglide technique, our data do not support one technique over the other.

In multi-agent settings, such as IoT and robotics, it is necessary to coordinate the actions of independent agents in order to achieve a joint behavior. While it is often easy to specify the desired joint behavior, programming the necessary coordination can be difficult. In this work, we develop theory and methods to synthesize coordination strategies that are guaranteed not to initiate unnecessary actions. We refer to such strategies as being “compact.” We formalize the intuitive notion of compactness; show that existing methods do not guarantee compactness; and propose a solution. The solution transforms a given temporal logic specification, using automata-theoretic constructions, to incorporate a notion of minimality. The central result is that the winning strategies for the transformed specification are precisely the compact strategies for the original. One can therefore apply known synthesis methods to produce compact strategies. We report on prototype implementations that synthesize compact strategies for temporal logic specifications and for specifications of multi-robot coordination.

Solar panels with a bi-facial design provide energy from both sides; thus, it would be interesting to examine the viability of such modules in an extremely hot and dry city like Ahmedabad, Gujarat, India. This study assesses the temperature, efficiency, and bifacial gain of PV bifacial modules as a function of solar irradiation, ambient temperature, wind speed, and additional parameters. The global horizontal irradiance has been used in this study to calculate Direct Normal Irradiance (DNI), Diffuse Horizontal Irradiance (DHI) and Front and Rear Irradiance. The results show that an optimal tilt angle of 43.5° provides the best efficiency of 24% at ambient temperature. For a constant value of tilt angle, the bi-facial gain of the module increases linearly with albedo factor. It has also been discovered that continuing to raise the elevation beyond 1 meter will eventually diminish the bifacial gain because the reflected and diffuse irradiance will become less intense on the rear side of the bifacial module.

SUMMARYChimeric antigen receptors (CARs) repurpose natural signaling components to retarget T cells to refractory cancers, but have shown limited efficacy against solid tumors. Here, we introduce ‘CAR Pooling’, a multiplexed approach to rapidly identify CAR designs with clinical potential. Forty CARs with diverse immune costimulatory domains were assessed in pooled assays for their ability to stimulate critical T cell effector functions during repetitive stimulation that mimics long-term tumor antigen exposure. Several non-native domains from the TNF receptor family exhibited enhanced proliferation (CD40) or cytotoxicity (BAFF-R and TACI) relative to clinical benchmarks, and fell into distinct states of memory, cytotoxicity, and metabolism. BAFF-R CAR T cells were enriched for a highly cytotoxic and NK-cell-like innate phenotype previously associated with positive clinical outcomes. ‘CAR Pooling’ enables efficient exploration of how CAR design affects cell activity and can be applied to optimize receptors across a range of applications and cell types.

In this paper, we propose the design to accommodate for the Ku-band (12–18 GHz), K-band (18–27 GHz), and Ka-band (26.5–40 GHz) frequency used cases as high-fidelity broadcasting for military applications, short-range terrestrial communication, and advanced weather forecasting applications by implementing the design structure with horn antenna having bottleneck profile. To have a ubiquitous application embedded with a single antenna, this structure was developed using advanced design analysis to determine the paragon shape responsible for high radiation efficiency. This constraint is evaluated in terms of return loss, radiation pattern, electromagnetic field patterns, and current distribution. The simulated impedance bandwidth of the bottleneck horn antenna is 100% showing that the antenna is operational at the entire intended frequency band range. The accounted gain is of 23.18 dB and directivity of 23.23 dB having 99.78% efficiency and low operating power of 0.5 W making the antenna high-line ideal for the desired satellite communication.

This project involves the use of friction stir processing with a change in the number of passes on grain refinement of pure copper. FSP is a rising metal processing technique for manufacturing fine-grained structures. The project’s main goal was to determine the outcome of change in the number of passes and pass direction on the grain size and microstructure. The change in microstructure is accompanied by changes in properties like grain structure, tensile strength, and hardness. FSP has been done on 3-mm-thick pure copper plates, using a tungsten carbide tool of 18 mm diameter shoulder with a tapered pin of diameter 3 mm, a tool rotation speed of 1500 rpm, 2° tilt angle and tool traverse speed of 20 mm/min with the variable being the number of passes and pass direction. The optical microscopy, grain size measurements of the nugget region, and time–temperature plot is presented. The specimen with smaller grain sizes are further tested for tensile strength.

Pneumonia is one of symptom cause for one of the most widespread Contagious diseases emerged as Coronavirus 2019 known as CoVID-19. This diseases is sharply spreading in most of part of the world effecting small aged and elderly aged people which is causing more than Nine Thousand deaths from all parts of the world. Identification of Pneumonia in Covid cases is happened by analysis of Posteroanterior views (P.A.) X-Rays. Thus, developing a smart and efficient system for detecting Pneumonia must-have utilities even in the future. In Recent Researches, Convolutional neural networks were found to be more accurate and efficient. Nowadays, Features are pre-trained in CNN models on a vast scale of datasets that make medical image identification more efficient. However, analyzing the medical image for Pneumonia’s detection is hard to assess because professional expertise is needed to label them. This Paper shows how a convolutional neural network can be used to detect Pneumonia using any generic python notebook with computer vision support.

Multicopy search structures such as log-structured merge (LSM) trees are optimized for high insert/update/delete (collectively known as upsert) performance. In such data structures, an upsert on key $k$, which adds $(k,v)$ where $v$ can be a value or a tombstone, is added to the root node even if $k$ is already present in other nodes. Thus there may be multiple copies of $k$ in the search structure. A search on $k$ aims to return the value associated with the most recent upsert. We present a general framework for verifying linearizability of concurrent multicopy search structures that abstracts from the underlying representation of the data structure in memory, enabling proof-reuse across diverse implementations. Based on our framework, we propose template algorithms for a) LSM structures forming arbitrary directed acyclic graphs and b) differential file structures, and formally verify these templates in the concurrent separation logic Iris. We also instantiate the LSM template to obtain the first verified concurrent in-memory LSM tree implementation., Comment: Extended version of an article to appear in OOPSLA'21

Lung volume reduction surgery (LVRS) is an option for carefully selected patients with severe, chronic obstructive pulmonary disease (COPD) where damaged, unhealthy lung is resected to improve the mechanical function of the remaining healthy lung. The patients most likely to benefit from this surgery are those with upper lobe-predominant emphysema and a low baseline exercise capacity. It is important for the anesthesia provider to have a complete understanding of the underlying pathophysiology of severe lung disease in order to safely navigate the patient through the perioperative period. Furthermore, close collaboration with the surgeon, an effective analgesic plan, proper hemodynamic monitoring, and the ability to troubleshoot the potential intraoperative complications are essential for a successful outcome.

Cell phones have been known as most usually utilized electronic gadgets in everyday life today. As equipment inserted in cell phones can perform significantly more assignment than customary telephones, the cell phones are not, at this point only a specialized gadget yet additionally considered as a ground-breaking processing gadget which is ready to catch pictures, record recordings, surf the web and so on. With the headway of innovation, it is conceivable to apply a few strategies to perform content discovery and interpretation. Consequently, an application that permits cell phones to catch a picture and concentrate the content from it to extract its language and information values and discourse it out is not, at this point a dream. In this paper, we address an Android application that is created by coordinating firebase machine learning kit and the WaveNet API with an approach of reinforcement learning to vocalize the texts using advanced speech synthesis algorithms. By utilizing this application, travelers who visit a remote nation ready to comprehend messages depicted in various languages as well as for the users who want to grab the information on the go by listening to the article.

Cannabis is one of the most widely used illicit drug worldwide. Delta-9-tetrahydrocannabinol (THC) is the main intoxicating ingredient in cannabis that impair a person’s ability to drive. While operating a motor vehicle while impaired by drug is prohibited, the problem of drug-impaired driving has become more prevalent in recent years [1] . In addition, workplace safety field studies suggest that acute intoxication from cannabis smoking significantly impair employees’ performance, leading to increased risks of work-related accidents [2] . Therefore, there is currently an unmet need for rapid, accurate and on-site screening devices for cannabis consumption detection in both workplaces and law enforcement. To address this need, detection of THC in oral fluids using affinity chromatography technologies such as lateral flow immunoassays (LFAs) has been recently explored. While LFA technologies offer simple, portable and non-invasive detection of THC from oral fluid, their limit of detection is normally limited to greater than 25 ng/ml which is insufficient for proper enforcement of per se regulations. In this work, we present an alternative method of detecting THC in LFAs which enhances the limit of detection by over an order of magnitude. Unlike conventional LFA detection/reader technologies that are based on the scattering of light by immobilized gold nanoparticles (GNPs), our innovation explores the thermal signatures of GNPs in response to modulated laser illumination [3] - [4] . Our results (n=240) suggest that the demodulation of localized surface plasmon resonance responses of GNPs captured by infrared cameras allows for detection of THC concentrations as low as 2 ng/ml with an accuracy of 95%. In order to demonstrate the viability of our technology for commercialization, we have also constructed a portable prototype using low-cost ($250) cellphone attachment infrared cameras with which detection cut off of 2ng/ml has been achieved.

Corona virus is formulated from large group of the viruses that causes illness range from common cold to more severe diseases. This virus has transmitted from animals to human beings. Millions of people throughout the world are affected to this deadly virus. So it is vital to detect this threatening virus. The Genomic Signal processing techniques is a constructive tool to detect infection as it deals with the advance research in the genetics. In this article we delineate the Genomic sequences of Corona Virus infected samples and convert the genomic data into digital signal and on applying Discrete Wavelet Transform and Fast Fourier Transform we performed mathematical modeling of the Corona-Virus gene so that it becomes effortless to predict the Corona-Virus Gene statistically. The motive of this research is to provide predicted results to drug designer for better response to this life threating Virus. We have tested these algorithms on most significant genes of the Corona Virus as well as Normal Cells of Homosapiens. The dataset of all the genomes are available on the National Center of Biotechnology Information (NCBI) website.

Monoclonal antibodies (mAbs) are widely used as critical reagents in analytical assays. While regulatory guidelines exist for stability monitoring of biopharmaceutical antibodies, they do not apply directly to the stability of mAbs used as assay reagent. We investigated alternative approaches to real-time stability monitoring of assay reagents. We compared functional (ELISA and cell-based) and biochemical (aggregation, deamidation) assay results using temperature-stressed mAb reagents. Data from both assay groups were compared for indications of antibody degradation. Arrhenius model kinetics was used to further extrapolate stability trends. Changes detected by traditionally monitored biochemical changes were not directly predictive of assay function. Instead, monitoring of reportable results was a closer indication of changes in assay performance related to mAb degradation. Using Arrhenius kinetic modeling, we combined forced degradation of individual reagents with reportable assay results to classify reagents into risk groups with associated re-evaluation and monitoring plans. This combined approach mitigates risk by monitoring each mAb reagent individually under stressed conditions while streamlining expiry assignment through simplified Arrhenius kinetics with only limited real-time stability data.