The aim of this paper is to examine how labor transfer can alleviate poverty caused by regional inequality. Based on a survey dataset of poor farmers in traditionally poverty-stricken areas in the Jiangxi province of China, we concluded that labor transfer and improvement in health can positively affect poverty reduction. Particularly, the labor transfer distance has a significant and positive effect on poor households in the middle- and low-income levels. In contrast, families occupying the middle and upper strata in society are forced to improve their wealth level in response to a potential drop in health levels through accumulating wealth. Additionally, we found that poor households with health obstacles had to traverse a longer distance to improve their income levels.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.jenvman.2020.110981 | DOI Listing |
Vaccines (Basel)
December 2024
Analytical Research & Development, Merck & Co., Inc., Rahway, NJ 07065, USA.
Background/objectives: Host cell protein (HCP) content is a major attribute for biological and vaccine products that must be extensively characterized prior to product licensure. Enzyme Linked Immunosorbent Assay (ELISA) and Mass Spectrometry (MS) are conventional methods for quantitative host cell protein analysis in biologic and vaccine products. Both techniques are usually very tedious, labor-intensive, and challenging to transfer to other laboratories.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Informática Industrial y Redes de Computadores (I2RC), University of Alicante, 03690 Alicante, Spain.
Automated systems, regulated by algorithmic protocols and predefined set-points for feedback control, require the oversight and fine tuning of skilled technicians. This necessity is particularly pronounced in automated greenhouses, where optimal environmental conditions depend on the specialized knowledge of dedicated technicians, emphasizing the need for expert involvement during installation and maintenance. To address these challenges, this study proposes the integration of data acquisition technologies using Internet of Things (IoT) protocols and optimization services via reinforcement learning (RL) methodologies.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Electrical Engineering, University of Belgrade, 11000 Belgrade, Serbia.
Traditional tactile brain-computer interfaces (BCIs), particularly those based on steady-state somatosensory-evoked potentials, face challenges such as lower accuracy, reduced bit rates, and the need for spatially distant stimulation points. In contrast, using transient electrical stimuli offers a promising alternative for generating tactile BCI control signals: somatosensory event-related potentials (sERPs). This study aimed to optimize the performance of a novel electrotactile BCI by employing advanced feature extraction and machine learning techniques on sERP signals for the classification of users' selective tactile attention.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Computer Science, Universidad de Alcalá, 28805 Alcalá de Henares, Spain.
This work presents the mathematical definition and programming considerations of an efficient geometric algorithm used to add roofs to polyhedral 3D building models obtained from OpenStreetMap. The algorithm covers numerous roof shapes, including some well-defined shapes that lack an explicit reconstruction theory. These shapes include gabled, hipped, pyramidal, skillion, half-hipped, gambrel, and mansard.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Institute of Applied Physics, Jiangxi Academy of Sciences, Nanchang 330000, China.
Although approaches for the online surface detection of automotive pipelines exist, low defect area rates, small-sample and long-tailed data, and the difficulty of detection due to the variable morphology of defects are three major problems faced when using such methods. In order to solve these problems, this study combines traditional visual detection methods and deep neural network technology to propose a transfer learning multi-channel fusion decision network without significantly increasing the number of network layers or the structural complexity. Each channel of the network is designed according to the characteristics of different types of defects.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!