In this paper we study one-sided hypothesis testing under random sampling without replacement, which frequently appears in the cryptographic problem setting, including the verification of measurement-based quantum computation. Suppose that $n+1$ binary random variables $X_1,\ldots, X_{n+1}$ follow a permutation invariant distribution and n binary random variables $X_1,\ldots, X_{n}$ are observed. Then, we propose randomized tests with a randomization parameter for the expectation of the $(n+1)$th random variable $X_{n+1}$ under a given significance level $\delta>0$. Our randomized tests significantly improve the upper confidence limit over deterministic tests. Our problem setting commonly appears in machine learning in addition to cryptographic scenarios by considering adversarial examples. Such studies are essential for expanding the applicable area of statistics. Although this paper addresses only binary random variables, a similar significant improvement by randomized tests can be expected for general non-binary random variables.

Which stories of conflict we hear, and who gets to narrate future visions for peace matters. Nearly a decade ago, I published an article in International Affairs (Hagen 2016) highlighting the need to challenge cisgender and heteronormative assumptions embedded within the Women, Peace, and Security (WPS) agenda. Since then, I have had the opportunity to speak widely about what motivated me to write on the topic: a lack of attention to lesbian, bisexual, and transgender women in what at that time was 15 years of work on WPS. As a queer feminist lesbian I am emotionally and intellectually invested in transnational women’s rights organizing. I was perplexed by the near absence of sexuality as an intersectional dimension of gender justice, despite the prominent role lesbians have always played in the movement globally. This weakness within the women’s peace movement’s coalitional organizing is now under significant strain amid growing anti-trans attacks with governments turning to securitizing responses to moral panic over trans rights (Leigh 2025, Currah 2022). Still, queer and trans organizers like Amani in Tunisia persist in working for their own visions of a peaceful future, taking advantage of opportunities for allyship where possible.

Previous studies suggest a link between protein intake and diabetes,(1,2) but little is known about whether protein intake timing across the day (i.e. temporal protein patterns) is associated with diabetes. This study aimed to examine temporal protein patterns in American adults and their associations with diabetes, BMI and glycemic measures.

Total protein intake at eating occasions was estimated from the National Health and Nutrition Examination Survey 2017-2020 dietary recall data (≥20 y; n=7625). Latent variable mixture models were used to identify temporal patterns based on hourly protein intake (g). Adults with fasting glucose ≥7.0 mmol/L, poor glycemic control (HbA1c ≥6.5%), taking diabetic medications, or previous diabetes diagnosis were classified as having diabetes. Insulin ≥72 pmol/L and HOMA-IR ≥2.5 were used to determine hyperinsulinemia and insulin-resistance, respectively. Regression models were used to examine associations for temporal protein patterns with diabetes prevalence, BMI and glycemic measures (fasting glucose, HbA1c, insulin, Homeostatic Model Assessment of Insulin Resistance), adjusted for multiple confounders.

Three latent classes for men’s and women’s temporal protein patterns were identified. Class 1 had higher conditional probabilities of eating protein at 18:00h, while Class 2 tended to eat protein an hour later than Class 1 and had higher overall protein intake (p<0.001). Class 3 was characterised by variable protein intake timing and had lower overall protein intake than the other classes (p<0.001). Men’s Class 1 had lower probabilities for hyperinsulinemia (32.5%) and poor glycemic control (5.9%), but associations were attenuated after adjusting for BMI. There were no associations for temporal protein patterns with diabetes, BMI and other glycemic measures.

Temporal protein patterns were not associated with diabetes. The inverse association with several glycemic measures observed for men in Class 1 may be mediated by BMI. Future prospective studies may better examine the effects of temporal protein patterns on diabetes by considering different protein food sources.

We prove that for every locally stable and tempered pair potential $\phi$ with bounded range, there exists a unique infinite-volume Gibbs point process on $\mathbb{R}^{d}$ for every activity $\lambda < ({e}^{L} \hat{C}_{\phi})^{-1}$, where L is the local stability constant and $\hat{C}_{\phi} \,:\!=\, \sup_{x \in \mathbb{R}^{d}} \int_{\mathbb{R}^{d}} 1 - {e}^{-\left\lvert \phi(x, y) \right\rvert} \mathrm{d} y$ is the (weak) temperedness constant. Our result extends the uniqueness regime that is given by the classical Ruelle–Penrose bound by a factor of at least ${e}$, where the improvements become larger as the negative parts of the potential become more prominent (i.e. for attractive interactions at low temperature). Our technique is based on the approach of Dyer et al. (2004 Random Structures & Algorithms 24, 461–479): We show that for any bounded region and any boundary condition, we can construct a Markov process (in our case spatial birth–death dynamics) that converges rapidly to the finite-volume Gibbs point process while the effects of the boundary condition propagate sufficiently slowly. As a result, we obtain a spatial mixing property that implies uniqueness of the infinite-volume Gibbs measure.