Dynamic agricultural supply response under economic transformation

China has experienced dramatic economic transformation and is facing the challenge of ensuring steady agricultural growth. This study examines the crop sector by estimating the supply response for major crops in Henan province from 1998 to 2007. We use a Nerlovian adjustment adaptive expectation model. The estimation uses dynamic Generalized Method of Moments (GMM) panel estimation based on pooled data across 108 counties. We estimate acreage and yield response functions and derive the supply response elasticities. This research links supply response to exogenous factors (weather, irrigation, government policy, capital investment, and infrastructure) and endogenous factors (prices). The significant feature of the model specification used in the study is that it addresses the endogeneity problem by capturing different responses to own- and cross-prices. Empirical results illustrate that there is still great potential to increase crop production through improvement of investment priorities and proper government policy. We confirm that farmers respond to price by both reallocating land and more intensively applying non-land inputs to boost yield. Investment in rural infrastructure, human capacity, and technology are highlighted as major drivers for yield increase. Policy incentives such as taxes and subsidies prove to be effective in encouraging grain production.acreage and yield response, dynamic panel model, Generalized Method of Moments (GMM), supply elasticity,

Cellulose-starch hybrid films plasticized by aqueous ZnCl2 solution

Starch and cellulose are two typical natural polymers from plants that have similar chemical structures. The blending of these two biopolymers for materials development is an interesting topic, although how their molecular interactions could influence the conformation and properties of the resultant materials has not been studied extensively. Herein, the rheological properties of cellulose/starch/ZnCl2 solutions were studied, and the structures and properties of cellulose-starch hybrid films were characterized. The rheological study shows that compared with starch (containing mostly amylose), cellulose contributed more to the solution’s viscosity and has a stronger shear-thinning behavior. A comparison between the experimental and calculated zero-shear-rate viscosities indicates that compact complexes (interfacial interactions) formed between cellulose and starch with ≤50 wt % cellulose content, whereas a loose structure (phase separation) existed with ≥70 wt % cellulose content. For starch-rich hybrid films prepared by compression molding, less than 7 wt % of cellulose was found to improve the mechanical properties despite the reduced crystallinity of the starch; for cellulose-rich hybrid films, a higher content of starch reduced the material properties, although the chemical interactions were not apparently influenced. It is concluded that the mechanical properties of biopolymer films were mainly affected by the structural conformation, as indicated by the rheological results. View Full-Tex

Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding

Contrastive learning, especially self-supervised contrastive learning (SSCL), has achieved great success in extracting powerful features from unlabeled data. In this work, we contribute to the theoretical understanding of SSCL and uncover its connection to the classic data visualization method, stochastic neighbor embedding (SNE), whose goal is to preserve pairwise distances. From the perspective of preserving neighboring information, SSCL can be viewed as a special case of SNE with the input space pairwise similarities specified by data augmentation. The established correspondence facilitates deeper theoretical understanding of learned features of SSCL, as well as methodological guidelines for practical improvement. Specifically, through the lens of SNE, we provide novel analysis on domain-agnostic augmentations, implicit bias and robustness of learned features. To illustrate the practical advantage, we demonstrate that the modifications from SNE to $t$-SNE can also be adopted in the SSCL setting, achieving significant improvement in both in-distribution and out-of-distribution generalization.Comment: Accepted by ICLR 202

Thermal behaviour of high amylose cornstarch studied by DSC

The thermal behaviour of high amylose cornstarches (80% amylose content) was studied by DSC using high pressure stainless steel pans in the temperature range between 0-350 degrees C. The number of endotherms and the enthalpy of gelatinization were found to depend on moisture content. Up to four endotherms and one exotherm were determined when the moisture content was above 40%. The meaning of each endotherm has been discussed. The enthalpy of gelatinization was calculated based on the summation of all the gelatinization endotherms and found to increase with increasing water content

In the process of polysaccharide gel formation:A review of the role of competitive relationship between water and alcohol molecules

Polysaccharides have emerged as versatile materials capable of forming gels through diverse induction methods, with alcohol-induced polysaccharide gels demonstrating significant potential across food, medicinal, and other domains. The existing research mainly focused on the phenomena and mechanisms of alcohol-induced gel formation in specific polysaccharides. Therefore, this review provides a comprehensive overview of the intricate mechanisms underpinning alcohol-triggered gelation of different polysaccharides and surveys their prominent application potentials through rheological, mechanical, and other characterizations. The mechanism underlying the enhancement of polysaccharide network structures by alcohol is elucidated, where alcohol displaces water to establish hydrogen bonding and hydrophobic interactions with polysaccharide chains. Specifically, alcohols change the arrangement of water molecules, and the partial hydration shell surrounding polysaccharide molecules is disrupted, exposing polysaccharides' hydrophobic groups and enhancing hydrophobic interactions. Moreover, the pivotal influences of alcohol concentration and addition method on polysaccharide gelation kinetics are scrutinized, revealing nuanced dependencies such as the different gel-promoting capabilities of polyols versus monohydric alcohols and the critical threshold concentrations dictating gel formation. Notably, immersion of polysaccharide gels in alcohol augments gel strength, while direct alcohol addition to polysaccharide solutions precipitates gel formation. Future investigations are urged to unravel the intricate nexus between the mechanisms underpinning alcohol-induced polysaccharide gelation and their practical utility, thereby paving the path for tailored manipulation of environmental conditions to engineer bespoke alcohol-induced polysaccharide gels.</p

In the process of polysaccharide gel formation:A review of the role of competitive relationship between water and alcohol molecules

Polysaccharides have emerged as versatile materials capable of forming gels through diverse induction methods, with alcohol-induced polysaccharide gels demonstrating significant potential across food, medicinal, and other domains. The existing research mainly focused on the phenomena and mechanisms of alcohol-induced gel formation in specific polysaccharides. Therefore, this review provides a comprehensive overview of the intricate mechanisms underpinning alcohol-triggered gelation of different polysaccharides and surveys their prominent application potentials through rheological, mechanical, and other characterizations. The mechanism underlying the enhancement of polysaccharide network structures by alcohol is elucidated, where alcohol displaces water to establish hydrogen bonding and hydrophobic interactions with polysaccharide chains. Specifically, alcohols change the arrangement of water molecules, and the partial hydration shell surrounding polysaccharide molecules is disrupted, exposing polysaccharides' hydrophobic groups and enhancing hydrophobic interactions. Moreover, the pivotal influences of alcohol concentration and addition method on polysaccharide gelation kinetics are scrutinized, revealing nuanced dependencies such as the different gel-promoting capabilities of polyols versus monohydric alcohols and the critical threshold concentrations dictating gel formation. Notably, immersion of polysaccharide gels in alcohol augments gel strength, while direct alcohol addition to polysaccharide solutions precipitates gel formation. Future investigations are urged to unravel the intricate nexus between the mechanisms underpinning alcohol-induced polysaccharide gelation and their practical utility, thereby paving the path for tailored manipulation of environmental conditions to engineer bespoke alcohol-induced polysaccharide gels.</p

Diagnostic and prognostic value of serum miR-9-5p and miR-128-3p levels in early-stage acute ischemic stroke

OBJECTIVES: To investigate the clinical utility of serum microRNA levels (miR-9-5p and miR-128-3p) in the diagnosis and prognosis of early-stage acute ischemic stroke (AIS). METHODS: We compared the differences in serum miR-9-5p and miR-128-3p levels between patients with AIS and healthy individuals (controls). The serum levels of miR-9-5p and miR-128-3p were quantified using quantitative real-time PCR, and the association of each miRNA with AIS was determined using receiver operator characteristic curve analysis. The predictive value of these indices in the diagnosis of early-stage AIS was evaluated in conjunction with that of computed tomography findings and neuron-specific enolase levels. The prognosis of patients with AIS was evaluated three months after their discharge from hospital using the modified Rankin scale, which classifies the prognosis as either favorable or poor. Logistic regression analysis was used to analyze the correlation between miR-9-5p and miR-128-3p levels and patient prognosis. RESULTS: The serum levels of miR-9-5p and miR-128-3p were upregulated in patients with AIS relative to those in healthy individuals. A pronounced correlation was identified between serum miR-9-5p and miR-128-3p levels and patient prognosis, with high levels of both miRNAs being associated with poor patient outcomes. CONCLUSION: Assessment of serum miR-9-5p and miR-128-3p levels is important for the early diagnosis and prognosis of AIS

Biofunctional chitosan–biopolymer composites for biomedical applications

In light of escalating biomedical demands across diverse diseases, there arises a pressing need for the development of sophisticated biocompatible materials exhibiting augmented biological functionality. Chitosan, a cationic polyelectrolyte copolymer of natural origin, distinguishes itself through its extraordinary biological properties, positioning it as a promising starting material to develop versatile biomedical materials. Tremendous attention has been directed towards the creation of high-performance biocomposites, achieved through the strategic manipulation of chitosan’s structure or its derivative, along with the amalgamation of other biopolymers. This comprehensive review intricately explores recent advancements in chitosan-based biofunctional materials, delving into formulations involving various biopolymers including polysaccharides and proteins. It places specific emphasis on the progress in chitosan chemistry and materials development, encompassing particles, hydrogels, aerogels, membranes, films, and sponges. Also, this review critically evaluates the development and functional properties of biofunctional chitosan–biopolymer composite materials, spotlighting interactions, both dynamic covalent and noncovalent, and their pivotal roles in materials formation. These interactions may either be inherent or realized through chemical modification such as “Click” chemistry, polymer grafts, mussel-inspired chemistry, and selective oxidation. Furthermore, the text illustrates the current and potential biomedical applications of these biofunctional composite materials, spanning from wound dressing to tissue engineering (skin, bone, cartilage, and nerve), the controlled release and targeted delivery of drugs/bioactive compounds, biosensing, and 3D printing. Additionally, it addresses critical challenges within the field, posits potential solutions, and provides a forward-looking perspective on the future directions of functional biomaterials and design strategies

Starch gelatinization under shearless and shear conditions

This article reviews the development of studying starch gelatinization under shear and shearless conditions, in particular the technologies used to detect the degree of gelatinization. Advantages and disadvantages of each technology were discussed and then some examples were presented to demonstrate their application. A new technology RheoScope, an instrument that can measure viscosity under shear stress and simultaneously observes variation of starch particles using a microscope, was also introduced. It was found the definition of "gelatinization" could be different for different detection technologies. Under shearless condition full gelatinization of starch needs about ratio of water 3/starch 1, while the gelatinization under shear condition requires less water content since shear stress enhances the processing. The number of endotherm and enthalpy of gelatinization depends on amylose/amylopectin, moisture and lipid content

Forward and Backward Information Retention for Accurate Binary Neural Networks

Weight and activation binarization is an effective approach to deep neural network compression and can accelerate the inference by leveraging bitwise operations. Although many binarization methods have improved the accuracy of the model by minimizing the quantization error in forward propagation, there remains a noticeable performance gap between the binarized model and the full-precision one. Our empirical study indicates that the quantization brings information loss in both forward and backward propagation, which is the bottleneck of training accurate binary neural networks. To address these issues, we propose an Information Retention Network (IR-Net) to retain the information that consists in the forward activations and backward gradients. IR-Net mainly relies on two technical contributions: (1) Libra Parameter Binarization (Libra-PB): simultaneously minimizing both quantization error and information loss of parameters by balanced and standardized weights in forward propagation; (2) Error Decay Estimator (EDE): minimizing the information loss of gradients by gradually approximating the sign function in backward propagation, jointly considering the updating ability and accurate gradients. We are the first to investigate both forward and backward processes of binary networks from the unified information perspective, which provides new insight into the mechanism of network binarization. Comprehensive experiments with various network structures on CIFAR-10 and ImageNet datasets manifest that the proposed IR-Net can consistently outperform state-of-the-art quantization methods