Parabrachial Neurons Promote Behavior and Electroencephalographic Arousal From General Anesthesia

General anesthesia has been used clinically for more than 170 years, yet its underlying mechanisms are still not fully understood. The parabrachial nucleus (PBN) in the brainstem has been known to be crucial for regulating wakefulness and signs of arousal on the cortical electroencephalogram (EEG). Lesions of the parabrachial complex lead to unresponsiveness and a monotonous high-voltage, and a slow-wave EEG, which are the two main features of general anesthesia. However, it is unclear whether and how the PBN functions in the process of general anesthesia. By recording the levels of calcium in vivo in real-time, we found that the neural activity in PBN is suppressed during anesthesia, while it is robustly activated during recovery from propofol and isoflurane anesthesia. The activation of PBN neurons by “designer receptors exclusively activated by designer drugs” (DREADDs) shortened the recovery time but did not change the induction time. Cortical EEG recordings revealed that the neural activation of PBN specifically affected the recovery period, with a decrease of δ-band power or an increase in β-band power; no EEG changes were seen in the anesthesia period. Furthermore, the activation of PBN elicited neural activation in the prefrontal cortex, basal forebrain, lateral hypothalamus, thalamus, and supramammillary nucleus. Thus, PBN is critical for behavioral and electroencephalographic arousal without affecting the induction of general anesthesia

Multi-scale diff-changed feature fusion network for hyperspectral image change detection.

For hyperspectral images (HSI) change detection (CD), multi-scale features are usually used to construct the detection models. However, the existing studies only consider the multi-scale features containing changed and unchanged components, which is difficult to represent the subtle changes between bi-temporal HSIs in each scale. To address this problem, we propose a multi-scale diff-changed feature fusion network (MSDFFN) for HSI CD, which improves the ability of feature representation by learning the refined change components between bi-temporal HSIs under different scales. In this network, a temporal feature encoder-decoder sub-network, which combines a reduced inception module and a cross-layer attention module to highlight the significant features, is designed to extract the temporal features of HSIs. A bidirectional diff-changed feature representation module is proposed to learn the fine changed features of bi-temporal HSIs at various scales to enhance the discriminative performance of the subtle change. A multi-scale attention fusion module is developed to adaptively fuse the changed features of various scales. The proposed method can not only discover the subtle change of bi-temporal HSIs but also improve the discriminating power for HSI CD. Experimental results on three HSI datasets show that MSDFFN outperforms a few state-of-the-art methods

Would more extensive out-migration of rural farmers expedite farm mechanization? Evidence from a changing Chinese agricultural sector

Changes in agricultural population can significantly influence the progress of mechanization, which provides efficient momentum to the further development of agriculture. We examine the effect of the declining agricultural population on mechanization and determine the variables that have decisive power over mechanical adoption decisions. This analysis of a panel data of top six out-migration provinces in China under a fixed effect model, we find that the overly fast and unusual decline in agricultural population actually slowed down the progress of mechanization, and the many years of large scale out-migration encouraged by government actually jeopardized sustainable agricultural development. Results underscore the need for considerable attention on the growth of annual farm incomes and agricultural products import that could have substantial effects on agricultural mechanization decisions

Determinants of Occupational Changes of U.S. Migrant Farm Workers under Recessionary Times

This paper studies the factors influence the labor decisions of agricultural labor in the U.S. and finds the distinction among the three types of agricultural workers. Undocumented farmers are unresponsive to wage changes while other farmers are not; enhanced education decreases the probability of exiting farm for foreign-born farmers

Health Care Service Utilization of Documented and Undocumented U.S. Farm Workers

This article analyzes issues related to the U.S. farm workers’ utilization to health care services and their specific choices among health care provider and health bill payment method options. Our findings validate the significant influence of health insurance coverage on health care access, and emphasize the reality of constrained access due to federal regulations, among other factors, prevalent among immigrant farm worker groups, who have relatively lower probability of using health care than citizen farm workers. Moreover, as most farm workers patronize private clinics and community health centers, they usually are also left only with the option to settle health care bills with out-of-pocket funds

Employer-Provided Health Insurance Benefit and the Employment Decisions of Documented and Undocumented Farm Workers

In addition to direct compensation (salaries and bonuses), fringe benefits such as employer-provided health insurance (EPHI) may also influence an individual’s decisions on actual and expected employment duration. This study analyzes the potential of EPHI in job retention among documented and undocumented farm workers in the United States at a time period when the farm sector is experiencing labor shortage crisis attributed to stricter immigration controls. In this study, farm worker-level data was preprocessed using Coarsened Exact Matching and analyzed under an ordered probit model. The results indicate that documented farm workers are generally responsive to EPHI in terms of both their actual employment duration and subjective working expectations. However, the EPHI did not significantly influence the subjective work expectations of undocumented farm workers. Moreover, the results imply that EPHI could not possibly be an effective tool for retaining undocumented workers on the farm once they are legalized