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Does adopting social distancing policies amid a health crisis, e.g., COVID-19, hurt economies? Using a machine learning approach at the intermediate stage, we applied a generalized synthetic control method to answer this question. We utilize state policy response differences. Cross-validation, a machine learning approach, is used to produce the "counterfactual" for adopting states-how they "would have behaved" without lockdown orders. We categorize states with social distancing as the treatment group and those without as the control. We employ the state time-period for fixed effects, adjusting for selection bias and endogeneity. We find significant and intuitively explicable impacts on some states, such as West Virginia, but none at the aggregate level, suggesting that social distancing may not affect the entire economy. Our work implies a resilience index utilizing the magnitude and significance of the social distancing measures to rank the states' resilience. These findings help governments and businesses better prepare for shocks.

Due to the brittle nature of ceramic, the ceramic and construction industry produces a large volume of waste that imposes a severe environmental threat due to its non-biodegradability. In this study, the suitability of ceramic waste as a replacement of natural coarse and fine aggregate in concrete has been investigated by evaluating engineering properties such as bulk density, water absorption, workability, etc. with respect to different concrete samples made with different mix proportions. Furthermore, a prediction model is introduced to predict compressive and splitting tensile strength using the machine learning tool support vector machine (SVM). A data set containing 108 records either for compressive or tensile strength was used for the training and testing purposes of the SVM model. A total of 9 mix proportions was selected and cast cylinders were cured for 7, 28, and 56 days. Four different kernel functions were used to optimize the results and different accuracy parameters like the value of R2, mean absolute error, mean square error, root mean square error, etc. were compared to find the best kernel function for this study. By primarily evaluating the coefficient of determination (R2), SVM showed an acceptable result with an accuracy of over 90%. Moreover, in terms of other accuracy measurement parameters result indicates that the SVM is an effective tool to predict the compressive and splitting tensile strength of concrete comprised of different proportions of ceramic content.

This study employs betalain extract from beetroot and curcumin extract from turmeric as sensitizer source for TiO2 based dye-sensitized solar cell (DSSC) that has completely different absorption spectrum. The dye mixture has shown a wider absorption spectrum and higher light absorption than single individual dye. As a result, DSSC co-sensitized by the combination of dyes has shown enhanced cell performance. According to experimental results, DSSC sensitized by betalain and curcumin dye yield cell efficiency of 0.220% and 0.473% respectively. DSSCs have been co-sensitized with the mixture of dyes at 3 different volume ratios (1:1, 1:2 and 2:1) to find the optimized combination. The optimized mixture of betalain and curcumin dye (at 1:2 volume ratio) yields the maximum efficiency of 0.649%. The cell efficiency can be further improved by the incorporation of single-walled carbon nanotubes (SWCNTs) and post TiCl4 treatment. DSSC fabricated with FTO/SWCNT-TiO2 and TiCl4 treated FTO/SWCNT-TiO2 sensitized with the optimized dye mixture has the cell efficiency of 0.903% and 1.108%, respectively. Finally, the cell performance degradation has been measured by maturing the dye for 360 h in the normal atmospheric condition.

Evolution of solar cell based on natural molecules flourished expeditiously, which is a good alternative for silicon-based solar cells or thin film technologies due to their low assembling cost, lightweight and flexibility. But natural dye-based dye-sensitized solar cell (DSSC) has low cell efficiency and stability, which limits the use of organic solar cells. In this research, natural green dye extracted from spinach (Spinacia oleracea) and used as a sensitizer source for natural dye-based DSSC. The measured cell efficiency of natural green dye-sensitized DSSC was 0.398%. Also, the cell stability test has been carried out by measuring the degradation rate (cell efficiency) by aging the dye molecule for DSSC has been conducted after 48, 96, 144 and 196 h under 100mW/cm2 illumination (1.5 AM) at the ambient condition.

In this paper, various impacts of the blocking layer on the cell stability in natural dye-based DSSC have been investigated. Introducing the blocking layer into the DSSC gives an increase in the photovoltaic performance. Blocking layer increases photogenerated current in the cell by reducing charge carrier recombination. Almost 24% current has been increased in the cell after using the blocking layer. In addition, open circuit voltage and fill factor have also been increased. TiCl4 (blocking layer) treated with TiO2 has been showed 28% higher cell efficiency than without TiCl4 treated with TiO2. The cell performance increased from 0.477% to 0.612%. Furthermore, cell stability test has been carried out by aging the dye molecule in the ambient condition. Cell stability has been experienced by measuring the cell parameter after 360 h, 720 h and 1080 h (under 100 mW/cm2 illumination by standard A.M. 1.5 solar simulator) respectively. An increase in 38∼44.5% cell stability has been found after introducing the blocking layer into the cell.

Small and Medium Enterprises (SMEs) are one of the major sources of economic growth. Recent economic growth and development of Bangladesh have been highly linked with the flourishment of SMEs. Access to formal finance is one of the major impediments for the growth of SMEs. The recent economic slowdown due to the COVID-19 pandemic causes the SMEs to suffer to remain in the business. Supply chain disruption, unsold products, lack of product demand, liquidity crisis become more severe in this case. The government of Bangladesh is trying to help SMEs by providing funds through the banking sector but previous studies show the banking sector is not as effective for SME financing. Besides recent banking sector performance seems to be very poor. Therefore, to ensure the best use of funds we need an alternative channel. Mico-Finance Institutions (MFIs) can play a better role in this case. Several studies have shown microfinance was a successful tool to recover small businesses after natural disasters. This paper aims to address the role of microfinance to post-disaster SME financing and identifies the current gap between these two.

Excessive consumption of fossil fuel leading to high environmental cost and the possibility of exhaustion of these nonrenewable energies is a compelling man to switch to alternative energy sources. These resources include renewable energies that are clean and sustainable. Renewable energy is such energy sources that are naturally replenished and are abundantly available. These energy sources beget from solar energy, wind, geothermal and hydro-power plants, etc. Therefore, instead of growing reliance on declining underground resources (fossil fuel resources), it must invest in the development of renewable energy utilization. This paper aims to provide renewable energy consumption patterns, in the long run, incorporating economic growth and fossil fuel energy consumption. In this analysis four, South Asian counties have been taken. These are Bangladesh, India, Pakistan, Sri-Lanka. By analyzing the data from 1990 -2014 with the Johansen Co-integration Method, renewable energy consumption is negatively related to economic growth (except India), whereas fossil fuel energy consumption is increasing with economic growth in the long run for the mentioned South Asian counties. Considering the climate issues, we addressed the opportunities and challenges providing some policy recommendations to increase renewable energy consumption.

This paper aims to analyze the performance of non-financial SOEs and seeks possible remedial for the problems. State-owned enterprises play a vital role in Bangladesh. After the liberation war in 1971, the Bangladesh government had taken extensive measurements to nationalize some enterprises but due to lack to profitability, accountability, poor management, corruption caused these enterprises to fail in providing enough support to our economy. Bangladesh government has initiated the “Privatization of Public Enterprises” in a massive scale but the performance of these SOEs have not been improved. There are 49 non-financial SOEs in Bangladesh. These non-financial SOEs are classified under seven major sectors- industry, utility, transportation and communication, trade, agriculture, construction, and service. Among these seven major sectors, the service and utility sector have the highest contribution to the public exchequer. Most of the enterprises are facing loss (i.e. mainly industrial sector SOEs) and some others have vulnerable performance. The government is providing a huge subsidy, but the overall performance has not been improved. These SOEs need a reformation in cost minimization, management system, corruption prevention, and most importantly a proper effective policy formulation.

Non-invasive methods in the assessment of health parameters are important for various kinds of patient, but only few expensive and inconvenient solutions are available. Investigations of non-invasive methods beginning with simple red-green-blue (RGB) imaging extending to hyperspectral camera-based image have encountered portability, usability, and reliability issues. This paper presents a smartphone-based non-invasive hemoglobin level prediction model that addresses portability, accuracy and ease-of-use problems by taking advantage of the built-in high-resolution camera, significant computation ability, storage, and communication facility of current smartphones. In this research work, RGB information of a 10-second fingertip videois used to convert into different color spaces including hue (H), saturation (S), value (V), lightness (L), a, b (a and b for the color dimensions) and gray (g). Later, features are extracted from all the combinations of ten different colors and applied to a Partial Least Squares (PLS) algorithm. We have evaluated the best color combination to generate a prediction model with the data collected from American and Bangladeshi patients. Our model with a specific pixel color combination achieves a reliable accuracy.

The concept of maintenance has advanced significantly over the last decades from a reactive service activity towards a pro-active one with more C-level attention. Among them, predictive maintenance has become a widely used term in industrial arena and academic research. This is being developed constantly by engineers and researchers based on monitoring historical data, modeling, simulation, and failure probabilities to predict fault and system deterioration over their useful life. Generally, the effective lifetime of machines depends on available and accessible data. However, certain unexpected situations may arise that are hard to predict, such as shock damage and unwanted degradation of the tool. Researchers are still working on understanding these problems and their effects on predictive maintenance. This paper presents an overview of condition-based predictive maintenance solutions that aim to avoid unexpected and unplanned failures during the manufacturing and operational process based on advanced data analytics. Furthermore, a brief illustration & discussion is presented on the challenges and opportunities of condition-based predictive maintenance and conclude a summary on future research.

Now-a-days water pollution is one of the most concerned problem as it is increasing due to industrialization and human activities. The applications of electrospun nanofibers are increasing day by day due to their special properties such as huge surface-to-volume ratio, possibilities of surface modification and conversion to small mesh mat or membrane etc. Chitosan-based electrospun nanofibers have more avenues due to their additional benefits of non-toxicity, biocompatibility, biodegradability and cost-effectiveness. Although chitosan-based nanofibers have been using in various biomedical fields and reviewed, applications as adsorbents for the removal of heavy metals, dyes and other pollutants are relatively new and not reviewed yet. In this regard, the present review explores various types of chitosan-based nanofibers prepared with pure chitosan, mixed with other materials, surface-modified chitosan, magnetic chitosan etc., their adsorption performance and applications for the removal of heavy metals, dyes, and miscellaneous pollutants.

At present, supercapacitors are the most promising form of high capacity, mobile energy storage devices. Among different supercapacitor materials, manganese-based supercapacitors are of great importance because of its cost-efficient simple fabrication and less hazardous environmental impact. MnOx and MnS are the most commonly found forms of manganese-based supercapacitors. The manganese-based supercapacitor electrodes are generally fabricated by hydrothermal, precipitation, CVD, or electrodeposition methods. Different surface modifications, structural changes and doping results in high-performance supercapacitors. While introducing graphene, CNTs and other carbon materials and polymers help increase the faradic reaction of manganese supercapacitors by enhancing active surface area, double metal oxides, and structural modification nanoscale also improves supercapacitor performance. This review article briefly discusses all the recent findings on manganese-based supercapacitors as a promising next-generation high-performance alternative of batteries or capacitors.

Waste management is one of the major challenging issues in the modern world due to rapid urbanization and industrialization over the past decades. The use of ceramic waste, originated from construction sites and industries, as fine and coarse aggregate in concrete presents an effective and sustainable endeavor to environmental problems through the reduction in the degradation of natural resources caused by extraction of natural aggregates and decrease in dumping volume as well. A plethora of researches has been attempted to analyze the suitability of ceramic wastes from various sources as a possible alternative to natural aggregates in concrete. This paper presents an assembled and up-to-date review of the physical, mechanical, durability, and other notable functional properties of ceramic aggregate concrete. From the outcome of the researches, it has been observed that ceramic aggregate concrete possesses comparable mechanical and durability properties to that of conventional concrete. The results show that it is possible to produce medium and high strength concrete with the incorporation of ceramic aggregates instead of natural aggregate. It is also seen from the results that the compressive strength , permeability characteristics, bond strength, etc. of ceramic aggregate concrete met the required criteria set by various international standards and codes, which confirms the potentiality of ceramic waste to be used as an efficient substitute to natural aggregates in structural concrete. However, the structural performance of ceramic waste-based reinforced concrete members is not yet explored in the researches, and therefore, recommendations are provided for future research.

Marine Spatial Planning (MSP) was designed to replace the contemporary fragmented system of sectoral decision making in order to reduce the existing over regulations with a coordinated and coherent spatial allocation system for marine users. MSP was also adopted as a tool for protecting the marine environment and support ecosystem based sustainable sea use management. One of the activities MSP is aiming to address is shipping, to date which is largely managed through regional sectoral approaches and regulations set by the International Maritime Organization (IMO). However, in the field of marine environmental protection, IMO welcomes regional initiatives and even supports them through its Special Areas, Particularly Sensitive Sea Areas (PSSA) and the Port State Control provisions. This research therefore aims to open up new perspectives to the potential function of MSP at the crossroads of environmental protection and maritime transport by analyzing the synergies of MSP with the PSSA regime. Finally, this study concludes that, by introducing spatially explicit regulations, MSP may offer opportunities to enhance regional efforts on reducing pollution from shipping activity within the global legal framework.

The oil and gas supply chain (OGSC) is considered to have one of the most significant stakes in the U.S. economy because of its interconnectedness with supply chains in other sectors, such as health and medicine, food, heavy manufacturing, and services. While oil and gas development is expanding exponentially, various factors ranging from man-made to natural disasters can hinder OGSC processes, which, in turn, can result in inefficient and costly operations in other sectors. This study presents a Bayesian Network (BN) model to predict and assess disasters in the OGSC based on seven main factors: technical, economic, social, political, safety, environmental, and legal. BBN is a probabilistic graphical model that is predominantly used in risk analysis to illustrate and assess probabilistic relationships among different variables. To draw meaningful managerial insights into the proposed model, sensitivity analysis and belief propagation are used. The results indicate that of the seven factors responsible for OGSC disasters, technical factors have the highest impact while legal and political factors have the lowest.

Neurolymphomatosis is a rare neurological syndrome in lymphomas. It is reported as infiltration of peripheral nerves by lymphoma. It is important to distinguish neurolymphomatosis from other types of neuropathies, particularly infectious and inflammatory conditions. However, it is difficult to isolate a cancer-related inflammatory vasculitis and mononeuritis multiplex without definitive histopathologic examination. In this report, we describe a case of non-Hodgkin's lymphoma involving the peroneal nerve and presenting as neurolymphomatosis.

In this paper, a proper concept of a kind of photonic crystal fiber known as D-shaped PCF sensor based on SPR or Surface Plasmon Resonance phenomenon has been discussed. The analysis has been performed numerically using FEM or Finite Element Method and PML (Perfectly Matched Layer) boundary conditions. Modal analysis has been performed keeping the smallest mesh as possible. The main mechanism of the sensor is the interaction between the core guided light beam and the metal layer surface that generates free electrons. The proposed sensor shows a refractive index detection range of 1.42–1.46 RIU, with a metal thickness variation of 35 nm-45 nm and a pitch variation of 1.8 μm–2.0 μm. The sensor obtained the highest sensitivity of 15000 nm/RIU with a maximum 6.67 × 10 - 6 RIU resolution, using the wavelength interrogation method. Average spectral sensitivity is 8000 nm/RIU. The amplitude interrogation method found a maximum sensitivity of 230 RIU−1 with a resolution of 4.348 × 10 - 5 RIU. The sensor also shows high linearity fitting and Figure of Merit (FoM). For ease of design, high detection range, high wavelength and amplitude sensitivity, less fabrication complexity, high linearity and stability, the sensor can be a great competitor of the PCF sensors previously proposed.

OBJECTIVES: To investigate the factors associated with whether assisted living communities (ALCs) in Florida evacuated or sheltered in place for Hurricane Irma in 2017, focusing on license type as a proxy for acuity of care. DESIGN: Cross-sectional study using data collected by the state through its emergency reporting system and a post-hurricane survey. SETTING AND PARTICIPANTS: Analyses included all 3,112 ALCs in the emergency reporting system. A subset of 1,880 that completed the survey provided supplementary data. METHODS: Chi-square tests were used to examine differences between ALC characteristics - license type, size, payment, profit status, rural location, geographical region, and being under an evacuation order – and whether they evacuated. Logistic regression was used to test associations between characteristics and evacuation status. RESULTS: Of 3,112 ALCs, 560 evacuated, 2,552 sheltered in place. Bivariate analysis found significant associations between evacuation status and evacuation order, license type (mental health care), payment, and region. In the adjusted analysis, medium and larger ALCs were 43% (p

Graphene, the thinnest two-dimensional atomic material, has immerged as a revolutionary material and sparked a flurry of research and innovation owing to its outstanding mechanical, electrical, optical and thermal properties as well as high specific surface area. Graphene-based materials and their composites possess promising applications in a wide range of fields such as sensors, actuators, electronics, biomedical aids and membranes. In this review paper, a critical and comprehensive review has been carried out on the synthesis process and mechanical properties of graphene and graphene-based nanocomposites. Firstly, the concept and structure of graphene materials are discussed then different synthesis techniques and their advantages and limitations have been reviewed. The addition of graphene and its derivatives in producing different polymer and metal-based nanocomposite as well as fabricating hybrid nanocomposite has been thoroughly reviewed. Almost all the papers show that the presence of graphene even at very low loadings can provide significant improvement to the final material. Besides, other parameters that affect the nanocomposite are thoroughly reviewed. Furthermore, the perspective application of graphene materials and its nanocomposite in different promising fields has been discussed.

A highly sensitive Photonic Crystal Fiber (PCF) based Surface Plasmon Resonance (SPR) sensor is demonstrated in this paper in the optimized form of circular slotted lattice (CSL) structure. This proposed model performance is numerically scrutinized by using Finite Element Method (FEM) in presence of Perfectly Matched Layer (PML) and Scattering Boundary Condition. Plasmonic material ‘Gold’ which is chemically inert is used in this structure at the outer surface of the slotted area to mitigate fabrication challenge. This model indicates the highest wavelength sensitivity of 16000 nm/RIU using wavelength interrogation, the amplitude sensitivity of 780 RIU−1 by using amplitude interrogation method and the average spectral sensitivity of 6666 nm/RIU, respectively. Besides, this sensor has the potentiality of detecting analytes within Refractive Index (RI) range 1.4 to 1.46 with maximum wavelength resolution of 6.25 × 10−6 RIU and amplitude resolution of 1.28 × 10−6 RIU, respectively and the maximum figure of merits of 400 RIU−1. Moreover, the variation of structural parameters (such as pitch, plasmon layer thickness etc.) and the impact of these changes are also discussed in details. According to the high sensitivity performance, polynomial fit and high Figure of Merit (FOM), this amend structure can be a strong competitor in the field of biosensing.