The book offers a new explanation of the decline in agricultural productivity in developing countries. It transcends the conventional approach to understanding productivity using factors of ...production. It employs the role of formal and informal institutions that govern transactions, property rights and accumulation among farm-holder communities, and seeks to understand agricultural productivity using both new and conventional variables, using a combined ethnographic and empirical methodology. The book engages with the debate on the market and non-market forces driving agrarian transition and advances that the agrarian transition be understood in relation to the wider (non-agrarian) economic development in society, as political settlement and primitive accumulation permit (inhibit) property rights being re-allocated in growth-enhancing directions. It also demonstrates that the existing process of accumulation prevents sustainable agriculture because of market failures caused by weak institutions, resulting in arrested productivity growth.
This study analyzed the morbidity and mortality rates of the coronavirus disease (COVID-19) pandemic in different prefectures of Japan. Under the constraint that daily maximum confirmed deaths and ...daily maximum cases should exceed 4 and 10, respectively, 14 prefectures were included, and cofactors affecting the morbidity and mortality rates were evaluated. In particular, the number of confirmed deaths was assessed, excluding cases of nosocomial infections and nursing home patients. The correlations between the morbidity and mortality rates and population density were statistically significant (
-value < 0.05). In addition, the percentage of elderly population was also found to be non-negligible. Among weather parameters, the maximum temperature and absolute humidity averaged over the duration were found to be in modest correlation with the morbidity and mortality rates. Lower morbidity and mortality rates were observed for higher temperature and absolute humidity. Multivariate linear regression considering these factors showed that the adjusted determination coefficient for the confirmed cases was 0.693 in terms of population density, elderly percentage, and maximum absolute humidity (
-value < 0.01). These findings could be useful for intervention planning during future pandemics, including a potential second COVID-19 outbreak.
Breast cancer is one of the most common diseases among women worldwide. It is considered one of the leading causes of death among women. Therefore, early detection is necessary to save lives. ...Thermography imaging is an effective diagnostic technique which is used for breast cancer detection with the help of infrared technology. In this paper, we propose a fully automatic breast cancer detection system. First, U-Net network is used to automatically extract and isolate the breast area from the rest of the body which behaves as noise during the breast cancer detection model. Second, we propose a two-class deep learning model, which is trained from scratch for the classification of normal and abnormal breast tissues from thermal images. Also, it is used to extract more characteristics from the dataset that is helpful in training the network and improve the efficiency of the classification process. The proposed system is evaluated using real data (A benchmark, database (DMR-IR)) and achieved accuracy = 99.33%, sensitivity = 100% and specificity = 98.67%. The proposed system is expected to be a helpful tool for physicians in clinical use.
Why Agriculture Productivity Falls: The Political Economy of Agrarian Transition in Developing Countries offers a new explanation for the decline in agricultural productivity in developing countries. ...Transcending the conventional approaches to understanding productivity using agricultural inputs and factors of production, this work brings in the role of formal and informal institutions that govern transactions, property rights, and accumulation. This more robust methodology leads to a comprehensive, well-balanced lens to perceive agrarian transition in developing countries. It argues that the existing process of accumulation has resulted in nonsustainable agriculture because of market failures—the result of asymmetries of power, diseconomies of scale, and unstable property rights. The book covers the historical shifts in land relations, productivity, and class relations that have led to present-day challenges in sustainability. The result is arrested productivity growth. Agrarian transition should be understood in the context of the wider economic development in society, including how political settlement and primitive accumulation inhibited the kind of property rights that encourage growth. Why Agriculture Productivity Falls is a much-needed corrective to the traditional understanding, because before we can increase productivity, we must understand the root causes of those challenges.
The averaged absorbed power density (APD) and temperature rise in body models with nonplanar surfaces were computed for electromagnetic exposure above 6 GHz. Different calculation schemes for the ...averaged APD were investigated. Additionally, a novel compensation method for correcting the heat convection rate on the air/skin interface in voxel human models was proposed and validated. The compensation method can be easily incorporated into bioheat calculations and does not require information regarding the normal direction of the boundary voxels, in contrast to a previously proposed method. The APD and temperature rise were evaluated using models of a two-dimensional cylinder and a three-dimensional partial forearm. The heating factor, which was defined as the ratio of the temperature rise to the APD, was calculated using different APD averaging schemes. Our computational results revealed different frequency and curvature dependences. For body models with curvature radii of >30 mm and at frequencies of >20 GHz, the differences in the heating factors among the APD schemes were small.
The significant health and economic effects of COVID-19 emphasize the requirement for reliable forecasting models to avoid the sudden collapse of healthcare facilities with overloaded hospitals. ...Several forecasting models have been developed based on the data acquired within the early stages of the virus spread. However, with the recent emergence of new virus variants, it is unclear how the new strains could influence the efficiency of forecasting using models adopted using earlier data. In this study, we analyzed daily positive cases (DPC) data using a machine learning model to understand the effect of new viral variants on morbidity rates. A deep learning model that considers several environmental and mobility factors was used to forecast DPC in six districts of Japan. From machine learning predictions with training data since the early days of COVID-19, high-quality estimation has been achieved for data obtained earlier than March 2021. However, a significant upsurge was observed in some districts after the discovery of the new COVID-19 variant B.1.1.7 (Alpha). An average increase of 20–40% in DPC was observed after the emergence of the Alpha variant and an increase of up to 20% has been recognized in the effective reproduction number. Approximately four weeks was needed for the machine learning model to adjust the forecasting error caused by the new variants. The comparison between machine-learning predictions and reported values demonstrated that the emergence of new virus variants should be considered within COVID-19 forecasting models. This study presents an easy yet efficient way to quantify the change caused by new viral variants with potential usefulness for global data analysis.
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•SWCNTs/mesoporous silicon nanocomposite via facile stain etching and sonothemical routes.•SWCNTs/mesoporous silicon/Nafion modified GCE as efficient nonenzymatic glucose ...electrochemical sensor.•Good sensitivity 0.0614 μAmM−1 cm−2, low LOD 9.6 µM and wide linear range 0.5–28.5 mM.•Excellent reproducibility, repeatability with long-term stability and validation in human blood serum analysis.
The development and designing of self-testing blood-glucose electrochemical biosensor is an effective approach for diabetic patients to overcome and control this high health concerning issue. Herein, we successfully designed novel single-walled carbon nanotubes-porous silicon nanocomposites framework (SWCNTs-PSi NCs) via simple stain etching and ultrasonication techniques. X-ray Diffraction (XRD), Raman spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), Field Emission Scanning Electron Microscopy (FESEM), Transmission Electron Microscopy (TEM), Energy-Dispersive Spectroscopy (EDS), and X-ray Photoelectron Spectroscopy (XPS) were employed to study the porous morphology with ~30 nm pore size and overall structural characterization of the SWCNTs-PSi NCs. This newly fabricated SWCNTs-PSi modified glassy carbon electrode (GCE) biosensor can measure an extremely wide range of glucose (0.5–28.5 mM) in phosphate buffer solution (PBS) compared to the regular glucose concentration level in human blood serum (3.9–7.1 mM) with a sensitivity 0.0614 μAmM−1 cm−2 and detection limit 9.6 ± 0.1 μM. This non-enzymatic glucose biosensor demonstrated excellent selectivity during the investigation of the possible impact of common interfering substances that are present in human blood. This proposed non-enzymatic glucose biosensor has also been tested for real human blood serum analysis to determine blood glucose levels showing highly motivated results. The newly designed SWCNTs-PSi/GCE biosensor exhibits excellent reproducibility and repeatability, along with long-term stability.
This research was executed to study the impacts of adding betaine (BT) to broiler diets on intestinal inflammatory response and barrier integrity under heat stress (HS). At 21 d of age, 150 male ...broilers (Ross 308) were randomly assigned to 3 treatment groups: control (CON) group, in which broilers were provided standard finisher feed under thermoneutral condition (22 ± 1°C); HS group and HS + BT group, in which broilers were given the standard feed supplied with 0 and 1,000 mg/kg BT, respectively, under cyclic HS condition (33 ± 1°C for 8 h from 08:00 to 16:00 h and the thermoneutral temperature for the residual hours). Each treatment was replicated ten times with 5 broilers per replicate. The HS group showed an elevation (P < 0.05) in serum corticosterone (CORT) concentration, D-lactate acid (D-LA) content, and diamine oxidase (DAO) activity, mucosal interleukin-1β (IL-1β) level, and expression of heat shock protein 70 (HSP70) gene, and a reduction (P < 0.05) in mucosal interleukin-10 (IL-10) level and secretory immunoglobulin A (SIgA) content and relative abundance of mRNA for occludin (OCLN), zonula occludens-1 (ZO-1), claudin-1 (CLDN1), and claudin-4 (CLDN4). In contrast, broilers in the HS + BT group exhibited a raise (P < 0.05) in mucosal IL-10 level and SIgA content and relative expression of OCLN and ZO-1 genes, and a decline (P < 0.05) in serum CORT concentration and DAO activity, mucosal IL-1β level, and expression of HSP70 mRNA. These results indicate that supplemental BT can ameliorate intestinal injury in heat-challenged broilers by suppressing inflammatory responses and enhancing mucosal barrier function.
In the present study, the flow field and heat transfer of a water–copper nanofluid with variable properties in a trapezoidal enclosure saturated with porous media are studied. The governing equations ...are solved by finite volume method and the SIMPLER algorithm. The nanofluid flow is assumed to be laminar, steady and incompressible. Simulations are performed for sidewall (trapezoid legs) angles of 30°, 45° and 60° with respect to horizontal axis, Reynolds numbers from 10 to 1000, Darcy numbers of 10
−2
, 10
−3
, 10
−4
and volume fractions of 0 to 0.04 of nanoparticles. Numerical results show that the average Nusselt number increases with increasing volume fraction of nanoparticles for all studied Darcy numbers. The convection and motion of the nanofluid decrease by reducing the Darcy number which leads to a reduction in the velocity and local Nusselt number. The average Nusselt number increases by increasing the Darcy number for all aspect ratios. Also, the average Nusselt number increases with increasing Reynolds number for all Darcy numbers, aspect ratios and volume fractions of nanoparticles.
This article presents a technique for controlling energy coupling in a coupled transmission line system based on the space-time modulation concept. The per-unit-length mutual capacitance and mutual ...inductance of the structure are modulated in space and time. The main idea is based on the harmonic generation property of space-time modulated media. As the amplitude of harmonics is a function of modulation parameters it is demonstrated that by choosing an appropriate space-time modulation scheme energy of different harmonics can be engineered leading to crosstalk reduction. In the quest for designing an effective space-time modulation scheme, an analytical method is developed for the examination of the space-time modulated coupled transmission line. The proposed method which is based on the state space formulation and benefits from the coupled mode theory is fast and accurate making it feasible for design problems. To validate the proposed analytical method, a full-wave simulation method has been used. The time-varying nature of the problem makes the finite-difference-time-domain the most appropriate choice. The validity of the analytical method is rigorously verified against the developed finite-difference-time-domain technique. The interest in circuit design techniques in an IC-compatible fashion in microwave circuits and the introduction of tunable material such as graphene in the THz regime leads to a positive future for the proposed space-time modulation-based crosstalk reduction method.
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