Globalization, Employment and Agriculture: A Review of the Eleventh Forum of the World Association for Political Economy

Economic globalization has greatly affected the economy, society and other aspects of individual countries and the world as a whole. As is well known, agriculture is the important foundation of the global economy, and most developing countries have a large rural population where agriculture is a significant part of the economy. Employment is the foundation of people's livelihood and full employment is difficult to achieve. Therefore, the study of how economic globalization affects agriculture and employment, and how developing countries and socialist countries should respond rationally and effectively, is worthy of attention

Adaptive Mean-Residue Loss for Robust Facial Age Estimation

Automated facial age estimation has diverse real-world applications in multimedia analysis, e.g., video surveillance, and human-computer interaction. However, due to the randomness and ambiguity of the aging process, age assessment is challenging. Most research work over the topic regards the task as one of age regression, classification, and ranking problems, and cannot well leverage age distribution in representing labels with age ambiguity. In this work, we propose a simple yet effective loss function for robust facial age estimation via distribution learning, i.e., adaptive mean-residue loss, in which, the mean loss penalizes the difference between the estimated age distribution's mean and the ground-truth age, whereas the residue loss penalizes the entropy of age probability out of dynamic top-K in the distribution. Experimental results in the datasets FG-NET and CLAP2016 have validated the effectiveness of the proposed loss. Our code is available at https://github.com/jacobzhaoziyuan/AMR-Loss.Comment: Accepted by IEEE International Conference on Multimedia and Expo (ICME 2022

Characterizing corn-straw-degrading actinomycetes and evaluating application efficiency in straw-returning experiments

Corn straw is an abundant lignocellulose resource and by-product of agricultural production. With the continuous increase in agricultural development, the output of corn straw is also increasing significantly. However, the inappropriate disposal of straw results in wasting of resources, and also causes a serious ecological crisis. Screening microorganisms with the capacity to degrade straw and understanding their mechanism of action is an efficient approach to solve such problems. For this purpose, our research group isolated three actinomycete strains with efficient lignocellulose degradation ability from soil in the cold region of China: Streptomyces sp. G1T, Streptomyces sp. G2T and Streptomyces sp. G3T. Their microbial properties and taxonomic status were assessed to improve our understanding of these strains. The three strains showed typical characteristics of the genus Streptomyces, and likely represent three different species. Genome functional annotation indicated that most of their genes were related to functions like carbohydrate transport and metabolism. In addition, a similar phenomenon also appeared in the COG and CAZyme analyses, with a large number of genes encoding carbohydrate-related hydrolases, such as cellulase, glycosidase and endoglucanase, which could effectively destroy the structure of lignocellulose in corn straw. This unambiguously demonstrated the potential of the three microorganisms to hydrolyze macromolecular polysaccharides at the molecular level. In addition, in the straw-returning test, the decomposing consortium composed of the three Streptomyces isolates (G123) effectively destroyed the recalcitrant bonds between the various components of straw, and significantly reduced the content of active components in corn straw. Furthermore, microbial diversity analysis indicated that the relative abundance of Proteobacteria, reportedly associated with soil antibiotic resistance and antibiotic degradation, was significantly improved with straw returning at both tested time points. The microbial diversity of each treatment was also dramatically changed by supplementing with G123. Taken together, G123 has important biological potential and should be further studied, which will provide new insights and strategies for appropriate treatment of corn straw

Boosting oxygen evolution reaction by activation of lattice‐oxygen sites in layered Ruddlesden‐Popper oxide

Emerging anionic redox chemistry presents new opportunities for enhancing oxygen evolution reaction (OER) activity considering that lattice-oxygen oxidation mechanism (LOM) could bypass thermodynamic limitation of conventional metal-ion participation mechanism. Thus, finding an effective method to activate lattice-oxygen in metal oxides is highly attractive for designing efficient OER electrocatalysts. Here, we discover that the lattice-oxygen sites in Ruddlesden-Popper (RP) crystal structure can be activated, leading to a new class of extremely active OER catalyst. As a proof-of-concept, the RP Sr3(Co0.8Fe0.1Nb0.1)2O7-δ (RP-SCFN) oxide exhibits outstanding OER activity (eg, 334 mV at 10 mA cm−2 in 0.1 M KOH), which is significantly higher than that of the simple SrCo0.8Fe0.1Nb0.1O3-δ perovskite and benchmark RuO2. Combined density functional theory and X-ray absorption spectroscopy studies demonstrate that RP-SCFN follows the LOM under OER condition, and the activated lattice oxygen sites triggered by high covalency of metal-oxygen bonds are the origin of the high catalytic activity.This work was financially supported by the Australian Research Council (Discovery Early Career Researcher Award No. DE190100005)

Detecting Neutrinos from Supernova Bursts in PandaX-4T

Neutrinos from core-collapse supernovae are essential for the understanding of neutrino physics and stellar evolution. The dual-phase xenon dark matter detectors can provide a way to track explosions of galactic supernovae by detecting neutrinos through coherent elastic neutrino-nucleus scatterings. In this study, a variation of progenitor masses as well as explosion models are assumed to predict the neutrino fluxes and spectra, which result in the number of expected neutrino events ranging from 6.6 to 13.7 at a distance of 10 kpc over a 10-second duration with negligible backgrounds at PandaX-4T. Two specialized triggering alarms for monitoring supernova burst neutrinos are built. The efficiency of detecting supernova explosions at various distances in the Milky Way is estimated. These alarms will be implemented in the real-time supernova monitoring system at PandaX-4T in the near future, providing the astronomical communities with supernova early warnings.Comment: 9 pages,6 figure

Search for light dark matter from atmosphere in PandaX-4T

We report a search for light dark matter produced through the cascading decay of $\eta$ mesons, which are created as a result of inelastic collisions between cosmic rays and Earth's atmosphere. We introduce a new and general framework, publicly accessible, designed to address boosted dark matter specifically, with which a full and dedicated simulation including both elastic and quasi-elastic processes of Earth attenuation effect on the dark matter particles arriving at the detector is performed. In the PandaX-4T commissioning data of 0.63 tonne$\cdot$year exposure, no significant excess over background is observed. The first constraints on the interaction between light dark matter generated in the atmosphere and nucleus through a light scalar mediator are obtained. The lowest excluded cross-section is set at $5.9 \times 10^{-37}{\rm cm^2}$ for dark matter mass of $0.1$ MeV$/c^2$ and mediator mass of 300 MeV$/c^2$. The lowest upper limit of $\eta$ to dark matter decay branching ratio is $1.6 \times 10^{-7}$

A Search for Light Fermionic Dark Matter Absorption on Electrons in PandaX-4T

We report a search on a sub-MeV fermionic dark matter absorbed by electrons with an outgoing active neutrino using the 0.63 tonne-year exposure collected by PandaX-4T liquid xenon experiment. No significant signals are observed over the expected background. The data are interpreted into limits to the effective couplings between such dark matter and electrons. For axial-vector or vector interactions, our sensitivity is competitive in comparison to existing astrophysical bounds on the decay of such dark matter into photon final states. In particular, we present the first direct detection limits for an axial-vector (vector) interaction which are the strongest in the mass range from 25 to 45 (35 to 50) keV/c$^2$

Soy protein isolate-sodium alginate colloidal particles for improving the stability of high internal phase Pickering emulsions: Effects of mass ratios

The potential of sodium alginate (SA) at different mass ratios to improve the emulsifying ability of soy protein isolate (SPI) in high internal phase Pickering emulsions (HIPPEs) was evaluated in this work. SPI-SA particles were used as a natural particle stabilizer of HIPPEs with 80 % oil phase. The properties of particles with varying SPI to SA ratios (10:0, 10:1, 10:3, 10:5, 10:10, and 10:15 w/w) were evaluated. HIPPEs with a 10:10 SPI to SA ratio exhibited the smallest droplet sizes. Both the storage modulus and loss modulus of the HIPPEs increased with increasing SA addition ratios, implying that HIPPEs with higher SA addition have stronger gel characteristics. In addition, super-resolution microscopy and cryogenic scanning electron microscopy indicated that SA addition strengthened the compactness of the interface film and increased the distribution uniformity of HIPPEs. In conclusion, the combination of SPI and SA is beneficial for improving the performance of HIPPEs

Weighted-traffic-network–based geographic profiling for serial crime location prediction

Geographic profiling plays a significant role in serial crime detection nowadays, in which Rossmo's formula is applied for future crime location prediction. However, the limited accuracy and demanding for vast data have largely impeded the efficiency of this technology. In this letter, a traffic network is introduced to geographic profiling. The problem is remodeled with weighted traffic network and the original Euclidean distance is replaced by the shortest path between nodes for better location prediction. A serial crime case is used to validate the correctness, efficiency and robustness of the proposed method. The main contributions of this letter can be concluded as follows: 1) the proposed model displays a higher accuracy and is less dependent on crime data; 2) strong robustness is testified by sensitive analysis, i.e. the developed model can produce an accurate prediction based on somewhat inaccurate former crime data; 3) further application in counter-terrorism is put forward with some adjustments