Does China’s Fertility Policy Induce Employment Discrimination Against Women? Evidence from a Nationwide Correspondence Experiment

We apply a two-wave nationwide correspondence experiment to assess the effects of the two-child and three-child policies in China. Using 13,751 observations collected through this experiment, we find that the announcement of the two-child policy led to a 4.9% decrease in total interview callbacks overall, and decreases of 4.3%, 5.7%, and 5.6% for single women, those married with no children, and those married with one child, respectively. The implementation of the three-child policy led to a 10.4% decrease, but only for married women with two children. The discrimination broadly affected all women, whether they disclose marriage and fertility status information or not, as we find their callback rates decreased by 4.5% under the universal two-child policy and 6.6% after the three-child policy.

Robust Security Beamforming for SWIPT-Assisted Relay System with Channel Uncertainty

This paper considers the physical layer security (PLS) of a simultaneous wireless information and power transfer (SWIPT) relay communication system composed of a legitimate source–destination pair and some eavesdroppers. Supposing a disturbance of channel status information (CSI) between relay and eavesdroppers in a bounded ellipse, we intend to design a robust beamformer to maximum security rate in the worst case on the constraints of relay energy consumption. To handle this non-convex optimization problem, we introduce a slack variable to transform the original problem into two sub-problems firstly, then an algorithm employing a semidefinite relaxation (SDR) technique and S-procedure is proposed to tackle above two sub-problems. Although our study was conducted in the scene of a direct link among source, destination, and eavesdroppers that is non-existing, we demonstrate that our conclusions can be easily extended to the scene for which a direct link among source, destination and eavesdroppers exist. Numerical simulation results compared with the benchmark scheme are provided to prove the effectiveness and superior performance of our algorithm.

Linking Free Text Documentation of Functioning and Disability to the ICF With Natural Language Processing

Background: Invaluable information on patient functioning and the complex interactions that define it is recorded in free text portions of the Electronic Health Record (EHR). Leveraging this information to improve clinical decision-making and conduct research requires natural language processing (NLP) technologies to identify and organize the information recorded in clinical documentation.Methods: We used natural language processing methods to analyze information about patient functioning recorded in two collections of clinical documents pertaining to claims for federal disability benefits from the U.S. Social Security Administration (SSA). We grounded our analysis in the International Classification of Functioning, Disability, and Health (ICF), and used the Activities and Participation domain of the ICF to classify information about functioning in three key areas: mobility, self-care, and domestic life. After annotating functional status information in our datasets through expert clinical review, we trained machine learning-based NLP models to automatically assign ICF categories to mentions of functional activity.Results: We found that rich and diverse information on patient functioning was documented in the free text records. Annotation of 289 documents for Mobility information yielded 2,455 mentions of Mobility activities and 3,176 specific actions corresponding to 13 ICF-based categories. Annotation of 329 documents for Self-Care and Domestic Life information yielded 3,990 activity mentions and 4,665 specific actions corresponding to 16 ICF-based categories. NLP systems for automated ICF coding achieved over 80% macro-averaged F-measure on both datasets, indicating strong performance across all ICF categories used.Conclusions: Natural language processing can help to navigate the tradeoff between flexible and expressive clinical documentation of functioning and standardizable data for comparability and learning. The ICF has practical limitations for classifying functional status information in clinical documentation but presents a valuable framework for organizing the information recorded in health records about patient functioning. This study advances the development of robust, ICF-based NLP technologies to analyze information on patient functioning and has significant implications for NLP-powered analysis of functional status information in disability benefits management, clinical care, and research.

Preference Evaluation of Realistic Fire Management Services: Difference in Preferences between Workers in Low- and High-Rise Buildings

This study entailed an evaluation of preferences of workers for aspects of realistic fire management services aimed at providing effective fire prevention and real-time response using conjoint techniques. The analysis of the responses indicated that a combination of real-time disaster-situation dissemination and real-time 3D indoor status information displays was preferred. For workers in both low and high-rise buildings, real-time disaster-situation dissemination within the building received the highest evaluation. Workers in low-rise buildings also showed a preference for the 3D indoor status information displays that provide optimal dynamic evacuation routes. Future studies will include demonstrations of such techniques through local governments to put realistic fire management services into practical use, promoting safe living environments from fire.

Real-Time Sensory Information for Remote Supervision of Autonomous Agricultural Machines

The concept of the driverless tractor has been discussed in the scientific literature for decades and several tractor manufacturers now have prototypes being field-tested. Although farmers will not be required to be physically present on these machines, it is envisioned that they will remain a part of the human-automation system. The overall efficiency and safety to be attained by autonomous agricultural machines (AAMs) will be correlated with the effectiveness of information sharing between the AAM and the farmer through what might be aptly called an automation interface. In this supervisory scenario, the farmer would be able to both receive status information and send instructions. In essence, supervisory control of an AAM is similar to the current scenario where farmers physically present on their machines obtain status information from displays integrated into the machine and from general sensory information that is available due to their proximity to the operating machine. Therefore, there is reason to expect that real-time sensory information would be valuable to the farmer when remotely supervising an AAM through an automation interface. This chapter will provide an overview of recent research that has been conducted on the role of real-time sensory information to the task of remotely supervising an AAM.

Mobile Apps to Fight the COVID-19 Crisis

The COVID-19 pandemic led to a multi-faceted global crisis, which triggered the diverse and quickly emerging use of old and new digital tools. We have developed a multi-channel approach for the monitoring and analysis of a subset of such tools, the COVID-19 related mobile applications (apps). Our approach builds on the information available in the two most prominent app stores (i.e., Google Play for Android-powered devices and Apple’s App Store for iOS-powered devices), as well as on relevant tweets and digital media outlets. The dataset presented here is one of the outcomes of this approach, uses the content of the app stores and enriches it, providing aggregated information about 837 mobile apps published across the world to fight the COVID-19 crisis. This information includes: (a) information available in the mobile app stores between 20 April 2020 and 2 August 2020; (b) complementary information obtained from manual analysis performed until mid-September 2020; and (c) status information about app availability on 28 February 2021, when we last collected data from the mobile app stores. We highlight our findings with a series of descriptives, which depict both the activities in the app stores and the qualitative information that was revealed by the manual analysis.

Optimization of reproduction of ricefish endemic to Southeast Sulawesi Oryzias woworae Parenti & Hadiaty, 2010 through different sex ratios in spawning

Oryzias woworae has a beautiful color and has been traded as ornamental fish. This species is an endemic ricefish from Muna Island, Southeast Sulawesi, and is threatened with endangered status. Information on the optimal spawning sex ratio in O. woworae is unknown. This study aimed was to examine the optimization of reproduction based on the sex ratio of male: female broodstock O. woworae involved in spawning. The sex ratio of male: female spawning broodstock used were 1:1, 1:2, 1:3, and 1:4. The male and female brooders used had a total length of 3,1 ± 0,5 cm and 2,5 ± 0,5 cm. After adaptation, the broodstock of O. woworae was put into aquariums according to the treatment, and each container contained three spawning substrates. The harvesting of eggs on the substrate is carried out two times a day. The results showed that spawning O. woworae with a ratio of 1♂: 4♀ produced the lowest number of eggs and was significantly different with ratios of 1♂: 1♀ and 1♂: 2♀ (P<0,05). The ratio of 1♂ : 3♀ gave the highest egg hatching of 55% but was not significantly different from other treatments (P>0,05). The difference in male and female ratios did not affect the survival rate of O. woworae larvae (P>0,05), with values from 91,9-100%. The highest larvae produced was found in the spawning ratio of 1♂ : 3♀ with 37 larvae but not significantly different from other treatments (P>0,05). The water quality values during the study were temperature 26,5-310C, pH 5,5-8,8, and dissolved oxygen 5,3-6,0 mg L-1. O. woworae broodstock spawning can be optimized with a male to female ratio of 1:3.

1196Trajectories of disability throughout adolescence and labour force status as a young adult

Background Young people with disabilities have poorer labour force outcomes than their peers without disabilities. Existing studies typically assess disability at one time point, obscuring potential variation in the experience of disability over time. This study aimed to identify trajectories of disability during childhood/adolescence and assess associations between trajectory membership and labour force status in young adulthood. Methods Group-based trajectory modeling was applied to disability status information from Waves 2-7 (age 4/5 to 16/17 years) of the Longitudinal Study of Australian Children; labour force participation (employed, unemployed, not in the labour force (NILF)) was measured at Wave 8 (18/19 years). Two logistic regression models assessed the relationship between trajectory group membership and labour force participation, adjusted for confounders. Results Four trajectory groups were identified: low (75.5% of cohort), low increasing (9.7%), high decreasing (10.9%), and consistently high (3.9%) prevalence of disability. Compared to individuals in the low trajectory (reference group), individuals in the consistently high trajectory had increased odds of being NILF at age 18/19 years (AOR 3.48, 95%CI 2.14, 5.68). Individuals in the low increasing trajectory had increased odds of unemployment at age 18/19 years compared to the reference group (AOR 2.93, 95%CI 1.91-4.48). Conclusions Results suggest that early experiences of disability among young Australians may differentially impact future labour force outcomes. Key messages Additional supports to prepare young people for the labour force should focus on individuals with consistently high or increasing prevalence of disability trajectories.

Policy-relevant indicators for invasive alien species assessment and reporting

Invasive alien species are repeatedly shown to be amongst the top threats to biodiversity globally. Robust indicators for measuring the status and trends of biological invasions are lacking, but essential for monitoring biological invasions and the effectiveness of interventions. Here, we formulate and demonstrate three such indicators that capture the key dimensions of species invasions, each a significant and necessary advance to inform invasive alien species policy targets: 1) Rate of Invasive Alien Species Spread, which provides modelled rates of ongoing introductions of species based on invasion discovery and reporting. 2) Impact Risk, that estimates invasive alien species impacts on the environment in space and time and provides a basis for nationally targeted prioritization of where best to invest in management efforts. 3) Status Information on invasive alien species, that tracks improvement in the essential dimensions of information needed to guide relevant policy and data collection and in support of assessing invasive alien species spread and impact. We show how proximal, model-informed status and trend indicators on invasive alien species can provide more effective global (and national) reporting on biological invasions, and how countries can contribute to supporting these indicators.