U.S. HOUSEHOLD CONSUMPTION OF FRESH FRUITS

This study uses the 1987-88 U.S. Department of Agriculture Nationwide Food Consumption Survey data to analyze the impacts of income, prices, and selected socioeconomic characteristics on household consumption of fresh fruits. Results suggest that fresh fruits are considered economic necessities, with own prices significantly influencing consumption. Cross-price effects are generally weak and insignificant, but the number of adults in the age group 18-64 is an important determinant of household consumption of fresh fruits. While nutrition information and household savings have significant, positive influences on most fresh fruit consumption, the presence of a working wife has a significant and negative influence.Food Consumption/Nutrition/Food Safety,

Organic Price Premiums Paid for Fresh Tomatoes and Apples by U.S. Households: Evidence from Nielsen Homescan Data

Using multivariate regression on data composed of prices, produce characteristics, demographics, and interactions, this study investigates organic price premiums paid by U.S. consumers for fresh tomatoes and apples, two of the top organic produce sellers, and identifies factors explaining variation in price premiums. The econometric problem of each buyer having multiple records in the purchase data is addressed in the estimation procedure.Consumer/Household Economics, Food Consumption/Nutrition/Food Safety,

The non-bipartite integral graphs with spectral radius three

In this paper, we classify the connected non-bipartite integral graphs with spectral radius three.Comment: 18 pages, 5 figures, 2 table

Coordinated Replay Sample Selection for Continual Federated Learning

Continual Federated Learning (CFL) combines Federated Learning (FL), the decentralized learning of a central model on a number of client devices that may not communicate their data, and Continual Learning (CL), the learning of a model from a continual stream of data without keeping the entire history. In CL, the main challenge is \textit{forgetting} what was learned from past data. While replay-based algorithms that keep a small pool of past training data are effective to reduce forgetting, only simple replay sample selection strategies have been applied to CFL in prior work, and no previous work has explored coordination among clients for better sample selection. To bridge this gap, we adapt a replay sample selection objective based on loss gradient diversity to CFL and propose a new relaxation-based selection of samples to optimize the objective. Next, we propose a practical algorithm to coordinate gradient-based replay sample selection across clients without communicating private data. We benchmark our coordinated and uncoordinated replay sample selection algorithms against random sampling-based baselines with language models trained on a large scale de-identified real-world text dataset. We show that gradient-based sample selection methods both boost performance and reduce forgetting compared to random sampling methods, with our coordination method showing gains early in the low replay size regime (when the budget for storing past data is small).Comment: 7 pages, 6 figures, accepted to EMNLP (industry track

Reading Books is Great, But Not if You Are Driving! Visually Grounded Reasoning about Defeasible Commonsense Norms

Commonsense norms are defeasible by context: reading books is usually great, but not when driving a car. While contexts can be explicitly described in language, in embodied scenarios, contexts are often provided visually. This type of visually grounded reasoning about defeasible commonsense norms is generally easy for humans, but (as we show) poses a challenge for machines, as it necessitates both visual understanding and reasoning about commonsense norms. We construct a new multimodal benchmark for studying visual-grounded commonsense norms: NORMLENS. NORMLENS consists of 10K human judgments accompanied by free-form explanations covering 2K multimodal situations, and serves as a probe to address two questions: (1) to what extent can models align with average human judgment? and (2) how well can models explain their predicted judgments? We find that state-of-the-art model judgments and explanations are not well-aligned with human annotation. Additionally, we present a new approach to better align models with humans by distilling social commonsense knowledge from large language models. The data and code are released at https://seungjuhan.me/normlens.Comment: Published as a conference paper at EMNLP 2023 (long

Neurophysiological evidence of motor preparation in inner speech and the effect of content predictability

Self-generated overt actions are preceded by a slow negativity as measured by electroencephalogram, which has been associated with motor preparation. Recent studies have shown that this neural activity is modulated by the predictability of action outcomes. It is unclear whether inner speech is also preceded by a motor-related negativity and inf luenced by the same factor. In three experiments, we compared the contingent negative variation elicited in a cue paradigm in an active vs. passive condition. In Experiment 1, participants produced an inner phoneme, at which an audible phoneme whose identity was unpredictable was concurrently presented. We found that while passive listening elicited a late contingent negative variation, inner speech production generated a more negative late contingent negative variation. In Experiment 2, the same pattern of results was found when participants were instead asked to overtly vocalize the phoneme. In Experiment 3, the identity of the audible phoneme was made predictable by establishing probabilistic expectations. We observed a smaller late contingent negative variation in the inner speech condition when the identity of the audible phoneme was predictable, but not in the passive condition. These findings suggest that inner speech is associated with motor preparatory activity that may also represent the predicted action-effects of covert actions

Gauging a Non-Semi-Simple WZW Model

We consider gauged WZW models based on a four dimensional non-semi-simple group. We obtain conformal \s-models in $D=3$ spacetime dimensions (with exact central charge $c=3$) by axially and vectorially gauging a one-dimensional subgroup. The model obtained in the axial gauging is related to the $3D$ black string after a correlated limit is taken in the latter model. By identifying the CFT corresponding to these \s-models we compute the exact expressions for the metric and dilaton fields. All of our models can be mapped to flat spacetimes with zero antisymmetric tensor and dilaton fields via duality transformations.Comment: 17 pages, harvmac, THU-93/30 (The discussion and reference sections are expanded

The Impact of Heterozygous KCNK3 Mutations Associated With Pulmonary Arterial Hypertension on Channel Function and Pharmacological Recovery

Background-Heterozygous loss of function mutations in the KCNK3 gene cause hereditary pulmonary arterial hypertension (PAH). KCNK3 encodes an acid-sensitive potassium channel, which contributes to the resting potential of human pulmonary artery smooth muscle cells. KCNK3 is widely expressed in the body, and dimerizes with other KCNK3 subunits, or the closely related, acid-sensitive KCNK9 channel. Methods and Results-We engineered homomeric and heterodimeric mutant and nonmutant KCNK3 channels associated with PAH. Using whole-cell patch-clamp electrophysiology in human pulmonary artery smooth muscle and COS7 cell lines, we determined that homomeric and heterodimeric mutant channels in heterozygous KCNK3 conditions lead to mutation-specific severity of channel dysfunction. Both wildtype and mutant KCNK3 channels were activated by ONO-RS-082 (10 mu mol/L), causing cell hyperpolarization. We observed robust gene expression of KCNK3 in healthy and familial PAH patient lungs, but no quantifiable expression of KCNK9, and demonstrated in functional studies that KCNK9 minimizes the impact of select KCNK3 mutations when the 2 channel subunits co-assemble. Conclusions-Heterozygous KCNK3 mutations in PAH lead to variable loss of channel function via distinct mechanisms. Homomeric and heterodimeric mutant KCNK3 channels represent novel therapeutic substrates in PAH. Pharmacological and pH-dependent activation of wildtype and mutant KCNK3 channels in pulmonary artery smooth muscle cells leads to membrane hyperpolarization. Co-assembly of KCNK3 with KCNK9 subunits may provide protection against KCNK3 loss of function in tissues where both KCNK9 and KCNK3 are expressed, contributing to the lung-specific phenotype observed clinically in patients with PAH because of KCNK3 mutations.National Heart, Lung, and Blood Institute (NHLBI)Cardiovascular Medical Research and Education Fund (CMREF)Columbia Univ, Coll Phys & Surg, Dept Pharmacol, New York, NY USAColumbia Univ, Dept Pediat, Coll Phys & Surg, New York, NY 10027 USAUniv Fed São Paulo, Paulista Sch Med, Dept Biophys, São Paulo, BrazilNew York Stem Cell Fdn, Res Inst, New York, NY USAUniv Fed São Paulo, Paulista Sch Med, Dept Biophys, São Paulo, BrazilNHLBI: F30 HL129656NHLBI R24 grant: R24HL123767Web of Scienc