The impact of COVID-19 on labor migration and the roles of small-scale farming in the pandemic in Vietnam

Drawing on in-depth interviews of migrant workers and their families in rural Vietnam, this study explores the impact of the COVID-19 pandemic on transnational and rural-urban migration as well as the role of small-scale farming in remittance-receiving households. Fieldwork was conducted in two provinces: the Son La province where ethnic minority women and men work in urban construction sites, and the Ha Tinh province where young men work in East Asia, such as Japan, South Korea, and Taiwan. Research findings show that in Son La, the pandemic exacerbated the already precarious lives and livelihoods of labor migrants, especially women and children. On the other hand, in Ha Tinh non-market-oriented small-scale farming and livestock production support remittance-receiving households, thereby limiting the impact of reduced remittances from transnational migration in the short-term. In both study sites, the pandemic did not change respondents’ perceptions of livelihood strategies. Labor migration remains the only available option for Son La farmers from the poor households to provide for their families and the best option for many young men in Ha Tinh to gain financial autonomy. These individuals are deeply affected by structural injustice in the commodification of the labor market, which is inherently unequal and exploitative. Current agricultural development must offer diverse options to accommodate the various needs of marginalized households that depend on off-farm incomes as well as small-scale farming

Women’s roles and opportunities in cassava value chains in Son La province in Vietnam: A technical report

Cassava is a major export-oriented cash crop in Vietnam. Unlike other cash crops, such as coffee, fruits, and maize, cassava requires limited agricultural input and labour and can grow in nutrient-poor uplands. Research on cassava breeding, seed systems and value chains in Southeast Asia is increasingly focused on market-oriented aspects such as developing hybrid varieties favourable to the cassava starch industry, disease control on large scale farms, and seed systems driven by the private sector. However, in the northern mountainous areas of Vietnam, ethnic minority farmers use cassava roots, leaves and sticks for numerous reasons, including starch production, fish and animal feed, firewood, and home consumption. Women play significant roles in those non market-oriented activities (often collecting left-over small roots in the field, drying roots, and cutting leaves and stems) but little is known about how this work influences women’s roles, decision-making and opportunities in cassava value chains. Hence, this study provides that data with an eye to see how women may find more opportunity for creating small business enterprises with cassava. Fieldwork was conducted in July 2021 in the Chieng La commune (Thuan Chau district) and the Muong Bon Commune (Mai Son district). Findings show that although women are less involved in decision making on cassava production and overall agricultural investment, they play important roles in cassava production and post-harvest activities. Therefore, it is extremely important to collect and analyze women’s preferences, concerns and constraints in cassava research and interventions. In the conclusion, we highlight additional areas for research on this topic

Does Bitcoin hedge commodity uncertainty?

This paper examines the connectedness between Bitcoin and commodity volatilities, including oil, wheat, and corn, during the period Oct. 2013–Jun. 2018, using time- and frequency-domain frameworks. The time-domain framework’s results show that the connectedness is 23.49%, indicating a low level of connection between Bitcoin and the commodity volatilities. Bitcoin contributes only 2.55% to the connectedness, while the wheat volatility index accounts for 12.51% of the total connectedness. The frequency connectedness shows that Bitcoin’s contribution to the total connectedness increases from high-frequency to low-frequency bands, and the total connectedness reaches up to 22.47%. It also indicates that Bitcoin is the spillover transmitter to the wheat volatility, while being the spillover receiver from the oil and corn volatilities. The findings suggest that Bitcoin could be a hedger for commodity volatilities

Generic Mechanism of Emergence of Amyloid Protofilaments from Disordered Oligomeric aggregates

The presence of oligomeric aggregates, which is often observed during the process of amyloid formation, has recently attracted much attention since it has been associated with neurodegenerative conditions such as Alzheimer's and Parkinson's diseases. We provide a description of a sequence-indepedent mechanism by which polypeptide chains aggregate by forming metastable oligomeric intermediate states prior to converting into fibrillar structures. Our results illustrate how the formation of ordered arrays of hydrogen bonds drives the formation of beta-sheets within the disordered oligomeric aggregates that form early under the effect of hydrophobic forces. Initially individual beta-sheets form with random orientations, which subsequently tend to align into protofilaments as their lengths increases. Our results suggest that amyloid aggregation represents an example of the Ostwald step rule of first order phase transitions by showing that ordered cross-beta structures emerge preferentially from disordered compact dynamical intermediate assemblies.Comment: 14 pages, 4 figure

Machine Learning-Enabled Joint Antenna Selection and Precoding Design: From Offline Complexity to Online Performance

We investigate the performance of multi-user multiple-antenna downlink systems in which a base station (BS) serves multiple users via a shared wireless medium. In order to fully exploit the spatial diversity while minimizing the passive energy consumed by radio frequency (RF) components, the BS is equipped with M RF chains and N antennas, where M <; N. Upon receiving pilot sequences to obtain the channel state information (CSI), the BS determines the best subset of M antennas for serving the users. We propose a joint antenna selection and precoding design (JASPD) algorithm to maximize the system sum rate subject to a transmit power constraint and quality of service (QoS) requirements. The JASPD algorithm overcomes the non-convexity of the formulated problem via a doubly iterative algorithm, in which an inner loop successively optimizes the precoding vectors, followed by an outer loop that tests all valid antenna subsets. Although approaching (near) global optimality, the JASPD suffers from a combinatorial complexity, which may limit its application in real-time network operations. To overcome this limitation, we propose a learning-based antenna selection and precoding design algorithm (L-ASPA), which employs a deep neural network (DNN) to establish underlaying relations between key system parameters and the selected antennas. The proposed L-ASPD algorithm is robust against the number of users and their locations, the transmit power of the BS, as well as the small-scale channel fading. With a well-trained learning model, it is shown that the L-ASPD algorithm significantly outperforms baseline schemes based on the block diagonalization and a learning-assisted solution for broadcasting systems and achieves a better effective sum rate than that of the JASPA under limited processing time. In addition, we observed that the proposed L-ASPD algorithm can reduce the computation complexity by 95% while retaining more than 95% of the optimal performance

A Condensation-Ordering Mechanism in Nanoparticle-Catalyzed Peptide Aggregation

Nanoparticles introduced in living cells are capable of strongly promoting the aggregation of peptides and proteins. We use here molecular dynamics simulations to characterise in detail the process by which nanoparticle surfaces catalyse the self- assembly of peptides into fibrillar structures. The simulation of a system of hundreds of peptides over the millisecond timescale enables us to show that the mechanism of aggregation involves a first phase in which small structurally disordered oligomers assemble onto the nanoparticle and a second phase in which they evolve into highly ordered beta-sheets as their size increases

Mechanical Strength of 17 134 Model Proteins and Cysteine Slipknots

A new theoretical survey of proteins' resistance to constant speed stretching is performed for a set of 17 134 proteins as described by a structure-based model. The proteins selected have no gaps in their structure determination and consist of no more than 250 amino acids. Our previous studies have dealt with 7510 proteins of no more than 150 amino acids. The proteins are ranked according to the strength of the resistance. Most of the predicted top-strength proteins have not yet been studied experimentally. Architectures and folds which are likely to yield large forces are identified. New types of potent force clamps are discovered. They involve disulphide bridges and, in particular, cysteine slipknots. An effective energy parameter of the model is estimated by comparing the theoretical data on characteristic forces to the corresponding experimental values combined with an extrapolation of the theoretical data to the experimental pulling speeds. These studies provide guidance for future experiments on single molecule manipulation and should lead to selection of proteins for applications. A new class of proteins, involving cystein slipknots, is identified as one that is expected to lead to the strongest force clamps known. This class is characterized through molecular dynamics simulations.Comment: 40 pages, 13 PostScript figure

Multi-Scale Simulations Provide Supporting Evidence for the Hypothesis of Intramolecular Protein Translocation in GroEL/GroES Complexes

The biological function of chaperone complexes is to assist the folding of non-native proteins. The widely studied GroEL chaperonin is a double-barreled complex that can trap non-native proteins in one of its two barrels. The ATP-driven binding of a GroES cap then results in a major structural change of the chamber where the substrate is trapped and initiates a refolding attempt. The two barrels operate anti-synchronously. The central region between the two barrels contains a high concentration of disordered protein chains, the role of which was thus far unclear. In this work we report a combination of atomistic and coarse-grained simulations that probe the structure and dynamics of the equatorial region of the GroEL/GroES chaperonin complex. Surprisingly, our simulations show that the equatorial region provides a translocation channel that will block the passage of folded proteins but allows the passage of secondary units with the diameter of an alpha-helix. We compute the free-energy barrier that has to be overcome during translocation and find that it can easily be crossed under the influence of thermal fluctuations. Hence, strongly non-native proteins can be squeezed like toothpaste from one barrel to the next where they will refold. Proteins that are already fairly close to the native state will not translocate but can refold in the chamber where they were trapped. Several experimental results are compatible with this scenario, and in the case of the experiments of Martin and Hartl, intra chaperonin translocation could explain why under physiological crowding conditions the chaperonin does not release the substrate protein

Inversion of the balance between hydrophobic and hydrogen bonding interactions in protein folding and aggregation.

Identifying the forces that drive proteins to misfold and aggregate, rather than to fold into their functional states, is fundamental to our understanding of living systems and to our ability to combat protein deposition disorders such as Alzheimer's disease and the spongiform encephalopathies. We report here the finding that the balance between hydrophobic and hydrogen bonding interactions is different for proteins in the processes of folding to their native states and misfolding to the alternative amyloid structures. We find that the minima of the protein free energy landscape for folding and misfolding tend to be respectively dominated by hydrophobic and by hydrogen bonding interactions. These results characterise the nature of the interactions that determine the competition between folding and misfolding of proteins by revealing that the stability of native proteins is primarily determined by hydrophobic interactions between side-chains, while the stability of amyloid fibrils depends more on backbone intermolecular hydrogen bonding interactions

Using Entropy Maximization to Understand the Determinants of Structural Dynamics beyond Native Contact Topology

Comparison of elastic network model predictions with experimental data has provided important insights on the dominant role of the network of inter-residue contacts in defining the global dynamics of proteins. Most of these studies have focused on interpreting the mean-square fluctuations of residues, or deriving the most collective, or softest, modes of motions that are known to be insensitive to structural and energetic details. However, with increasing structural data, we are in a position to perform a more critical assessment of the structure-dynamics relations in proteins, and gain a deeper understanding of the major determinants of not only the mean-square fluctuations and lowest frequency modes, but the covariance or the cross-correlations between residue fluctuations and the shapes of higher modes. A systematic study of a large set of NMR-determined proteins is analyzed using a novel method based on entropy maximization to demonstrate that the next level of refinement in the elastic network model description of proteins ought to take into consideration properties such as contact order (or sequential separation between contacting residues) and the secondary structure types of the interacting residues, whereas the types of amino acids do not play a critical role. Most importantly, an optimal description of observed cross-correlations requires the inclusion of destabilizing, as opposed to exclusively stabilizing, interactions, stipulating the functional significance of local frustration in imparting native-like dynamics. This study provides us with a deeper understanding of the structural basis of experimentally observed behavior, and opens the way to the development of more accurate models for exploring protein dynamics