Pomona College

Abstract It is widely believed that the ultraviolet background produced during the epoch of reionization conspires against the formation of low-mass galaxies. Indeed, this mechanism is often invoked as part of the solution to the so-called “missing satellites problem.” In this paper we employ FIREbox , a large-volume cosmological simulation based on the Feedback In Realistic Environments physics model, to characterize the mechanisms governing galaxy ignition in the postreionization era. By carefully matching recently ignited halos (with stellar ages below 100 Myr at the time of selection) to halos that failed to form any stars, we conclude that the presence of cold dense gas and halo concentration helps incite the process of galaxy formation. Concretely, we find that 100% of recently ignited halos experience cold dense gas enhancements relative to their matched failed counterparts. Likewise, approximately 83% display enhancements in both cold dense gas and Navarro–Frenk–White concentration ( c NFW ), while the remaining ∼17% exhibit enhanced cold dense gas content and suppressed c NFW values. Lastly, our simulation suggests that galaxy ignition can occur as late as z = 2, potentially allowing us to observationally catch this process “in the act” in the foreseeable future.

ABSTRACT This research investigated whether sequence effects, or facilitation from two consecutive trials that share incongruency, reduce taboo interference during speech production. Participants named pictures accompanied by distractor words that were congruent with (i.e. identical to) or incongruent with (different from) the name of the picture. Incongruent distractors also varied in emotion (taboo or neutral). Similar to pictures with incongruent-neutral distractors, pictures with incongruent-taboo distractors were named faster when preceded by a trial with an incongruent-neutral distractor relative to a congruent-neutral distractor. These results demonstrate that robust taboo interference can be reduced through adjustments to attentional control. However, naming on incongruent-taboo trials did not differ as a function of whether the preceding incongruent trial’s emotion was taboo or neutral, suggesting limitations in attentional mechanisms beyond those employed to control incongruency. Implications of these findings for attentional control accounts of sequence effects are discussed.

We introduce and study a directed analogue of the weighted Tree Augmentation Problem (WTAP). In the weighted Directed Tree Augmentation Problem (WDTAP), we are given an oriented tree \(T = (V,A)\) and a set of directed links \(L \subseteq V \times V\) with positive costs. The goal is to select a minimum cost set of links which enters each fundamental dicut of \(T\) (cuts with one leaving and no entering tree arc). WDTAP captures the problem of covering a cross-free set family with directed links. It can also be used to solve weighted multi 2-TAP, in which we must cover the edges of an undirected tree at least twice. WDTAP can be approximated to within a factor of 2 using standard techniques. We provide an improved (\(1.75 + \varepsilon\))-approximation algorithm for WDTAP in the case where the links have bounded costs, a setting that has received significant attention forWTAP. To obtain this result, we discover a class of instances, called “willows”, for which the natural set covering LP is an integral formulation. We further introduce the notion of “visibly \(k\)-wide” instances which can be solved exactly using dynamic programming. Finally, we show how to leverage these tractable cases to obtain an improved approximation ratio via an elaborate structural analysis of the tree.

Cytoreductive surgery with hyperthermic intraperitoneal chemotherapy (CRS/HIPEC) is often associated with extensive surgical resection and has traditionally been performed via laparotomy. Data on minimally invasive robotic approaches remain limited. We evaluated surgical safety and survival outcomes of robotic CRS/HIPEC for peritoneal surface malignancies (PSM). A single-center propensity score-matched study was conducted using a prospectively collected database (2018-2025). PSM patients treated with robotic CRS/HIPEC were matched 1:1 to open CRS/HIPEC controls using propensity scores based on age, sex, BMI, histology, and PCI. Of 99 cases, 15 robotic and 71 open CRS/HIPECs were identified. After matching, 15 robotic and 15 open cases were balanced by age, sex, BMI, diagnosis, prior surgical score, and PCI. CC-0/1 rate was 100.0% in robotic and 93.3% in open CRS/HIPEC (p = 1.00). Median blood loss was lower in the robotic group (100mL vs 250mL, p = 0.04). Median hospital stay was shorter after robotic CRS/HIPEC (6 vs 9days, p = 0.05). No differences were observed in major complications (26.7% vs 33.3%, p = 1.00) and reoperation (0.0% vs 6.7%, p = 1.00). No 90-day mortality was observed in either group. Median follow-up was 58months. Median overall survival (not reached vs 52months, p = 0.20) and progression-free survival (not reached vs 42months, p = 0.19) did not differ between robotic and open CRS/HIPEC. In PSM patients with low tumor burden, robotic CRS/HIPEC is not associated with increased morbidity or worse survival. It may offer benefits such as reduced blood loss and shorter hospitalization. Multicenter studies are warranted to optimize patient selection.

The topological symmetry group $\mathrm{TSG}(Γ)$ of an embedding $Γ$ of a graph in $S^3$ is the subgroup of the automorphism group of the graph which is induced by homeomorphisms of $(S^3,Γ)$. If we restrict to orientation preserving homeomorphisms then we obtain the orientation preserving topological symmetry group $\mathrm{TSG}_+(Γ)$. In this paper we determine all groups that can be $\mathrm{TSG}(Γ)$ or $\mathrm{TSG}_+(Γ)$ for some embedding $Γ$ of a generalized Petersen graph other than the exceptional graphs $P(12,5)$ and $P(24, 5)$ (which will be addressed in a separate paper.

Drones have become essential tools in applications ranging from surveillance to disaster management, but their misuse poses significant security threats that require effective detection and classification techniques. While various detection methods exist, RF-based approaches offer high accuracy by using the unique spectral signatures emitted during drone communication, avoiding common issues found in visual or audio systems. However, there is significant lack of formatting and organization in public and private datasets for RF-based signals, which can hinder the use of said datasets for further research.This paper presents a comparative analysis of four RF-based drone detection datasets: DroneRF, CardRF, VTI_DroneSET_FFT, and Drone-Remote-Controller-RF-Signal-Dataset. We evaluated the experimental methodologies, including the number and types of drones used, signal features extracted, the data collection environment, the use of the RF chamber, noise mitigation techniques and classification models used. Additionally, we replicated the DroneRF analysis using CardRF data and vice versa to assess cross-dataset reproducibility, as well as investigate the robustness of the datasets concerning different RF channel conditions, variations in training and testing environments, and the overall classification accuracy. This process also revealed key challenges that hindered reproducibility and interoperability between datasets, such as inconsistent and insufficient documentation, hard-coded local file paths, and language-specific dependencies. Our study provides insight into the impact of these methodological differences on drone detection and classification performance in the real world and the importance of standardized data formats and well-documented workflows to enable consistent cross-platform RF-based drone detection research.