Revisiting the Relationship between Poverty and Environmental Sustainability in Sub-Saharan African Countries using Dynamic Econometric Models

Sustainable development remains an important issue in the quest to achieve a safe and a better world. The expansion of the 8 millennium development goals into the 17 sustainable development goals is a testament of the conscious desire to improve the human environment to ensure better quality of life for its citizens. This study assembles a collection of four sophisticated econometric models to determine the impact of poverty and other variables on two indicators of environmental sustainability. Beside, economic development, the study confirmed the negative impact of poverty on both indicators of sustainable development. The results prove that poverty in sub-Saharan Africa is a threat to environmental quality and its consequential challenges. The call to promote environmentally responsible behaviours should not be focused on developed countries alone. Poverty is also associated with high levels of pollution and poor countries including countries in sub-Saharan Africa contributes must equally restrategise for effective environmental goals. The study further discloses that poverty is one of the strongest factors that affect environmental sustainability. This observation is not a contradiction to the well-established fact that prosperity or economic growth is a major precursor of unsustainable environment. On the contrary the evidence in this paper amplifies a consequence of a social crisis if they fester at both ends. In one breath, whereas economic growth or economic prosperity can compromise the quality of the environment. In conclusion, this result implies that African countries in their pursuit of economic growth, education and effective healthcare to ameliorate poverty must incorporate other aggressive strategies to hasten poverty reduction

SPSTracker: Sub-Peak Suppression of Response Map for Robust Object Tracking

Modern visual trackers usually construct online learning models under the assumption that the feature response has a Gaussian distribution with target-centered peak response. Nevertheless, such an assumption is implausible when there is progressive interference from other targets and/or background noise, which produce sub-peaks on the tracking response map and cause model drift. In this paper, we propose a rectified online learning approach for sub-peak response suppression and peak response enforcement and target at handling progressive interference in a systematic way. Our approach, referred to as SPSTracker, applies simple-yet-efficient Peak Response Pooling (PRP) to aggregate and align discriminative features, as well as leveraging a Boundary Response Truncation (BRT) to reduce the variance of feature response. By fusing with multi-scale features, SPSTracker aggregates the response distribution of multiple sub-peaks to a single maximum peak, which enforces the discriminative capability of features for robust object tracking. Experiments on the OTB, NFS and VOT2018 benchmarks demonstrate that SPSTrack outperforms the state-of-the-art real-time trackers with significant margins.Comment: Accepted as oral paper at AAAI202

Increasing but Variable Trend of Surface Ozone in the Yangtze River Delta Region of China

Surface ozone (O-3) increased by similar to 20% in the Yangtze River Delta (YRD) region of China during 2014-2020, but the aggravating trend is highly variable on interannual time and city-level space scales. Here, we employed multiple air quality observations and numerical simulation to describe the increasing but variable trend of O-3 and to reveal the main driving factors behind it. In 2014-2017, the governmental air pollution control action plan was mostly against PM2.5 (mainly to control the emissions of SO2, NOx, and primary PM2.5) and effectively reduced the PM2.5 concentration by 18%-45%. However, O-3 pollution worsened in the same period with an increasing rate of 4.9 mu g m(-3) yr(-1), especially in the Anhui province, where the growth rate even reached 14.7 mu g m(-3) yr(-1). After 2018, owing to the coordinated prevention and control of both PM2.5 and O-3, volatile organic compound (VOC) emissions in the YRD region has also been controlled with a great concern, and the O-3 aggravating trend in the same period has been obviously alleviated (1.1 mu g m(-3) yr(-1)). We further combined the precursor concentration and the corresponding O-3 formation regime to explain the observed trend of O-3 in 2014-2020. The leading O-3 formation regime in 2014-2017 is diagnosed as VOC-limited (21%) or mix-limited (58%), with the help of a simulated indicator HCHO/NOy. Under such condition, the decreasing NO2 (2.8% yr(-1)) and increasing VOCs (3.6% yr(-1)) in 2014-2017 led to a rapid increment of O-3. With the continuous reduction in NOx emission and further in ambient NOx/VOCs, the O-3 production regime along the Yangtze River has been shifting from VOC-limited to mix-limited, and after 2018, the mix-limited regime has become the dominant O-3 formation regime for 55% of the YRD cities. Consequently, the decreases of both NOx (3.3% yr(-1)) and VOCs (7.7% yr(-1)) in 2018-2020 obviously slowed down the aggravating trend of O-3. Our study argues that with the implementation of coordinated regional reduction of NOx and VOCs, an effective O-3 control is emerging in the YRD region.Peer reviewe

Isolation and analysis of a very virulent Marek’s disease virus strain in China

BACKGROUND: A severe MD was broken out at a farm in Shandong, China, despite FC126 vaccination of the chickens at 1-day-old. The mortality of the flocks reached up to 38.3%. The infected chickens were found to have MD pathological changes, including enlargement of spleens, livers and kidneys, and tumors occured on organs later. Samples were collected from the chickens for diagnosis. METHODS: The collected samples were inoculated into primary duck embryo fibroblast (DEF) cells, and the MDV strain named SD2012-1 was isolated. In order to identify the isolate, amplification by PCR and sequencing of oncogenic Meq and vIL-8 gene were processed, the obtained sequences were compared with the sequences of reference strains, and SD2012-1 was used to challenge immunized SPF chickens. RESULTS: A very virulent MDV isolate strain, SD2012-1, was isolated from a chicken flock in Shandong Province, China, the isolate had the characteristics of very virulent MDV-1, nucleotide and deduced amino acid sequence comparisons of Meq and vIL-8 gene of SD2012-1 with those of reference strains showed SD2012-1 had high homology with MDV strains isolated from China, SD2012-1 could break through the protection provided by HVT vaccine and HVT + SB-1 vaccine immunization and caused the mortality of SPF chickens over 60%. The immune failure occured at the farm could be due to the improper selection of vaccines. SD2012-1 produced death later and the gross postmortem lesions of chickens died early and later were different. CONCLUSIONS: MDV strain SD2012-1 isolated from Shandong Province, China was found to have the characteristics of very virulent MDV-1, which could break through the protection provided by HVT vaccine and HVT + SB-1 vaccine, the virus seemed to have a long latent period, and cause different gross postmortem lesions of chickens between chickens died early and later. A better immunization way should be chosen to prevent infection of this MDV strain in field

One-Year Simulation of Ozone and Particulate Matter in China Using WRF/CMAQ Modeling System

Abstract. China has been experiencing severe air pollution in recent decades. Although an ambient air quality monitoring network for criteria pollutants has been constructed in over 100 cities since 2013 in China, the temporal and spatial characteristics of some important pollutants, such as particulate matter (PM) components, remain unknown, limiting further studies investigating potential air pollution control strategies to improve air quality and associating human health outcomes with air pollution exposure. In this study, a yearlong (2013) air quality simulation using the Weather Research and Forecasting (WRF) model and the Community Multi-scale Air Quality (CMAQ) model was conducted to provide detailed temporal and spatial information of ozone (O3), total PM2.5, and chemical components. Multi-resolution Emission Inventory for China (MEIC) was used for anthropogenic emissions and observation data obtained from the national air quality monitoring network were collected to validate model performance. The model successfully reproduces the O3 and PM2.5 concentrations at most cities for most months, with model performance statistics meeting the performance criteria. However, overprediction of O3 generally occurs at low concentration range while underprediction of PM2.5 happens at low concentration range in summer. Spatially, the model has better performance in southern China than in northern China, central China, and Sichuan Basin. Strong seasonal variations of PM2.5 exist and wind speed and direction play important roles in high PM2.5 events. Secondary components have more boarder distribution than primary components. Sulfate (SO42−), nitrate (NO3−), ammonium (NH4+), and primary organic aerosol (POA) are the most important PM2.5 components. All components have the highest concentrations in winter except secondary organic aerosol (SOA). This study proves the ability of the CMAQ model to reproduce severe air pollution in China, identifies the directions where improvements are needed, and provides information for human exposure to multiple pollutants for assessing health effects. </jats:p

G2PTL: A Pre-trained Model for Delivery Address and its Applications in Logistics System

Text-based delivery addresses, as the data foundation for logistics systems, contain abundant and crucial location information. How to effectively encode the delivery address is a core task to boost the performance of downstream tasks in the logistics system. Pre-trained Models (PTMs) designed for Natural Language Process (NLP) have emerged as the dominant tools for encoding semantic information in text. Though promising, those NLP-based PTMs fall short of encoding geographic knowledge in the delivery address, which considerably trims down the performance of delivery-related tasks in logistic systems such as Cainiao. To tackle the above problem, we propose a domain-specific pre-trained model, named G2PTL, a Geography-Graph Pre-trained model for delivery address in Logistics field. G2PTL combines the semantic learning capabilities of text pre-training with the geographical-relationship encoding abilities of graph modeling. Specifically, we first utilize real-world logistics delivery data to construct a large-scale heterogeneous graph of delivery addresses, which contains abundant geographic knowledge and delivery information. Then, G2PTL is pre-trained with subgraphs sampled from the heterogeneous graph. Comprehensive experiments are conducted to demonstrate the effectiveness of G2PTL through four downstream tasks in logistics systems on real-world datasets. G2PTL has been deployed in production in Cainiao's logistics system, which significantly improves the performance of delivery-related tasks

Risk of Target Organ Damage in Patients with Masked Hypertension versus Sustained Hypertension: A Meta-analysis

Objective: To compare the risk of target organ damage in masked hypertension (MH) and sustained hypertension (SH). Methods: A systematic review and meta-analysis was performed. A search of PubMed, Embase, and the Cochrane Library of relevant case-control studies was performed from inception to December 2019, and articles on MH and SH selected according to the inclusion criteria were analyzed. The primary end point was target organ damage in the heart. The secondary end points were target organ damage in the kidneys and blood vessels. Results: Seventeen studies that met the screening criteria were included in the meta-analysis. Compared with the SH group, in the MH group carotid intima-media thickness (IMT) and E/A ratio were significantly greater and the prevalence of left ventricular remodeling and the pulse wave velocity were significantly lower. Other indicators in the heart, kidneys, and blood vessels were not statistically different between the two groups. IMT: P=0.01, E/A ratio: P=0.01, prevalence of left ventricular remodeling: P=0.02, pulse wave velocity: P=0.01. Conclusion: Our study has shown that MH may have almost the same degree of target organ damage as SH, so clinicians may need to consider target organ damage