Analyzing the Impact of Food Safety Information on Food Demand in China

This study analyzed the impact of food safety information on food demand in urban China. The LA/AIDS model was estimated by using national province level food consumption data and quantities of articles about food safety event on public media from 2000 to 2008. The results of the study show that urban Chinese consumer food demand was influenced by food safety information from daily newspapers and GM labeling policy. This paper also indicates food price elasticities, expenditure elasticities by categories and the effect of food safety information.food safety, food demand, Linear Approximated Almost Ideal Demand System( LA/AIDS), Genetically modified( GM), food consumption, price elasticity, expenditure elasticity, Consumer/Household Economics, Demand and Price Analysis, Food Consumption/Nutrition/Food Safety, D12, Q11,

Unveiling the relative efficacy, safety and tolerability of prophylactic medications for migraine: pairwise and network-meta analysis

Ranking of migraine interventions using SUCRA values. (DOCX 17 kb

Photo-Otto engine with quantum correlations

We theoretically prose and investigate a photo-Otto engine that is working with a single-mode radiation field inside an optical cavity and alternatively driven by a hot and a cold reservoir, where the hot reservoir is realized by sending one of a pair of correlated two-level atoms to pass through the optical cavity, and the cold one is made of a collection of noninteracting boson modes. In terms of the quantum discord of the pair of atoms, we derive the analytical expressions for the performance parameters (power and efficiency) and stability measure (coefficient of variation for power). We show that quantum discord boosts the performance and efficiency of the quantum engine, and even may change the operation mode. We also demonstrate that quantum discord improves the stability of machine by decreasing the coefficient of variation for power which satisfies the generalized thermodynamic uncertainty relation. Finally, we find that these results can be transferred to another photo-Otto engine model, where the optical cavity is alternatively coupled to a hot thermal bosonic bath and to a beam of pairs of the two correlated atoms that play the role of a cold reservoir

Model Selection for Topic Models via Spectral Decomposition

Abstract Topic models have achieved significant successes in analyzing large-scale text corpus. In practical applications, we are always confronted with the challenge of model selection, i.e., how to appropriately set the number of topics. Following the recent advances in topic models via tensor decomposition, we make a first attempt to provide theoretical analysis on model selection in latent Dirichlet allocation. With mild conditions, we derive the upper bound and lower bound on the number of topics given a text collection of finite size. Experimental results demonstrate that our bounds are correct and tight. Furthermore, using Gaussian mixture model as an example, we show that our methodology can be easily generalized to model selection analysis in other latent models

Precision Removal of Uneven Skin Tissue at the Micrometer Level via Focus-Corrected Femtosecond-Laser Ablation

From the perspective of aesthetic surgery and regenerative medicine, the precision of surgical instruments is critical for preventing aesthetic complications during procedures such as skin debridement and the removal of unwanted tissues, as well as for better regeneration. Femtosecond lasers (fs-lasers) can achieve micrometer-level tissue removal. However, an uneven skin texture can cause the laser to defocus, leading to iatrogenic injury and hindering clinical application. Overcoming the defocusing tendency of fs-lasers is therefore crucial for their clinical use

NASRec: Weight Sharing Neural Architecture Search for Recommender Systems

The rise of deep neural networks provides an important driver in optimizing recommender systems. However, the success of recommender systems lies in delicate architecture fabrication, and thus calls for Neural Architecture Search (NAS) to further improve its modeling. We propose NASRec, a paradigm that trains a single supernet and efficiently produces abundant models/sub-architectures by weight sharing. To overcome the data multi-modality and architecture heterogeneity challenges in recommendation domain, NASRec establishes a large supernet (i.e., search space) to search the full architectures, with the supernet incorporating versatile operator choices and dense connectivity minimizing human prior for flexibility. The scale and heterogeneity in NASRec impose challenges in search, such as training inefficiency, operator-imbalance, and degraded rank correlation. We tackle these challenges by proposing single-operator any-connection sampling, operator-balancing interaction modules, and post-training fine-tuning. Our results on three Click-Through Rates (CTR) prediction benchmarks show that NASRec can outperform both manually designed models and existing NAS methods, achieving state-of-the-art performance

Molecular basis of ligand recognition and activation of human V2 vasopressin receptor.

Vasopressin type 2 receptor (V2R) belongs to the vasopressin (VP)/oxytocin (OT) receptor subfamily of G protein-coupled receptors (GPCRs), which comprises at least four closely related receptor subtypes: V1aR, V1bR, V2R, and OTR. These receptors are activated by arginine vasopressin (AVP) and OT, two endogenous nine-amino acid neurohypophysial hormones, which are thought to mediate a biologically conserved role in social behavior and sexual reproduction. V2R is mainly expressed in the renal collecting duct principal cells and mediates the antidiuretic action of AVP by accelerating water reabsorption, thereby playing a vital role in controlling water homeostasis. Moreover, numerous gain-of-function and loss-of-function mutations of V2R have been identified and are closely associated with human diseases, including nephrogenic syndrome of inappropriate diuresis (NSIAD) and X-linked congenital nephrogenic diabetes insipidus (NDI). Thus, V2R has attracted intense interest as a drug target. However, due to a lack of structural information, how AVP recognizes and activates V2R remains elusive, which hampers the V2R-targeted drug design. Here, we determined a 2.6 Å resolution cryo-EM structure of the full-length, G s -coupled human V2R bound to AVP (Fig. 1a; Supplementary information, Table S1). The G s protein was engineered based on mini-G s that was used in the crystal structure determination of the G s -coupled adenosine A 2A receptor (A 2A R) to stabilize the V2R–G s protein complex (Supplementary information, Data S1). The final structure of the AVP–V2R–G s complex contains all residues of AVP (residues 1–9), the Gα s Ras-like domain, Gβγ subunits, Nb35, scFv16, and the V2R residues from T31 to L339 8.57 (superscripts refer to Ballesteros–Weinstein numbering). The majority of amino acid side chains, including AVP, transmembrane domain (TMD), all flexible intracellular loops (ICLs) and extracellular loops (ECLs) except for ICL3 and G185–G188 in ECL2, were well resolved in the model, refined against the EM density map (Fig. 1a; Supplementary information, Figs. S1–3). The complex structure can provide detailed information on the binding interface between AVP and helix bundle of the receptor, as well as the receptor–G s interface