General Setting Research Articles

On Optimal Tradeoffs between EFX and Nash Welfare

A major problem in fair division is how to allocate a set of indivisible resources among agents fairly and efficiently. The goal of this work is to characterize the tradeoffs between two well-studied measures of fairness and efficiency --- envy freeness up to any item (EFX) for fairness, and Nash welfare for efficiency --- by saying, for given constants α and β, whether there exists an α-EFX allocation that guarantees a β-fraction of the maximum Nash welfare (β-MNW). For additive valuations, we show that for any α ∈ [0,1], there exists a partial allocation that is α-EFX and 1/(α+1)-MNW. This tradeoff turns out to be tight (for every α) as demonstrated by an impossibility result that we give. We also show that for α ∈ [0, φ-1 ≃ 0.618] these partial allocations can be turned into complete allocations where all items are assigned. Furthermore, for any α ∈ [0, 1/2], we show that the tight tradeoff of α-EFX and 1/(α+1)-MNW with complete allocations holds for the more general setting of subadditive valuations. Our results improve upon the current state of the art, for both additive and subadditive valuations, and match the best-known approximations of EFX under complete allocations, regardless of Nash welfare guarantees. Notably, our constructions for additive valuations also provide EF1 and constant approximations for maximin share guarantees.

ViLT-CLIP: Video and Language Tuning CLIP with Multimodal Prompt Learning and Scenario-Guided Optimization

Pre-trained vision-language(V-L) models such as CLIP have demonstrated impressive Zero-Shot performance in many downstream tasks. Since adopting contrastive video-text pairs methods like CLIP to video tasks is limited by its high cost and scale, recent approaches focus on efficiently transferring the image-based CLIP to the video domain. A major finding is that fine-tuning the pre-trained model to achieve strong fully supervised performance leads to low zero shot, few shot, and base to novel generalization. Instead, freezing the backbone network to maintain generalization ability weakens fully supervised performance. Otherwise, no single prompt tuning branch consistently performs optimally. In this work, we proposed a multimodal prompt learning scheme that balances supervised and generalized performance. Our prompting approach contains three sections: 1) Independent prompt on both the vision and text branches to learn the language and visual contexts. 2) Inter-modal prompt mapping to ensure mutual synergy. 3) Reducing the discrepancy between the hand-crafted prompt (a video of a person doing [CLS]) and the learnable prompt, to alleviate the forgetting about essential video scenarios. Extensive validation of fully supervised, zero-shot, few-shot, base-to-novel generalization settings for video recognition indicates that the proposed approach achieves competitive performance with less commute cost.

Learning Generalized Segmentation for Foggy-Scenes by Bi-directional Wavelet Guidance

Learning scene semantics that can be well generalized to foggy conditions is important for safety-crucial applications such as autonomous driving. Existing methods need both annotated clear images and foggy images to train a curriculum domain adaptation model. Unfortunately, these methods can only generalize to the target foggy domain that has seen in the training stage, but the foggy domains vary a lot in both urban-scene styles and fog styles. In this paper, we propose to learn scene segmentation well generalized to foggy-scenes under the domain generalization setting, which does not involve any foggy images in the training stage and can generalize to any arbitrary unseen foggy scenes. We argue that an ideal segmentation model that can be well generalized to foggy-scenes need to simultaneously enhance the content, de-correlate the urban-scene style and de-correlate the fog style. As the content (e.g., scene semantic) rests more in low-frequency features while the style of urban-scene and fog rests more in high-frequency features, we propose a novel bi-directional wavelet guidance (BWG) mechanism to realize the above three objectives in a divide-and-conquer manner. With the aid of Haar wavelet transformation, the low frequency component is concentrated on the content enhancement self-attention, while the high frequency component is shifted to the style and fog self-attention for de-correlation purpose. It is integrated into existing mask-level Transformer segmentation pipelines in a learnable fashion. Large-scale experiments are conducted on four foggy-scene segmentation datasets under a variety of interesting settings. The proposed method significantly outperforms existing directly-supervised, curriculum domain adaptation and domain generalization segmentation methods. Source code is available at https://github.com/BiQiWHU/BWG.

Adaptive Uncertainty-Based Learning for Text-Based Person Retrieval

Text-based person retrieval aims at retrieving a specific pedestrian image from a gallery based on textual descriptions. The primary challenge is how to overcome the inherent heterogeneous modality gap in the situation of significant intra-class variation and minimal inter-class variation. Existing approaches commonly employ vision-language pre-training or attention mechanisms to learn appropriate cross-modal alignments from noise inputs. Despite commendable progress, current methods inevitably suffer from two defects: 1) Matching ambiguity, which mainly derives from unreliable matching pairs; 2) One-sided cross-modal alignments, stemming from the absence of exploring one-to-many correspondence, i.e., coarse-grained semantic alignment. These critical issues significantly deteriorate retrieval performance. To this end, we propose a novel framework termed Adaptive Uncertainty-based Learning (AUL) for text-based person retrieval from the uncertainty perspective. Specifically, our AUL framework consists of three key components: 1) Uncertainty-aware Matching Filtration that leverages Subjective Logic to effectively mitigate the disturbance of unreliable matching pairs and select high-confidence cross-modal matches for training; 2) Uncertainty-based Alignment Refinement, which not only simulates coarse-grained alignments by constructing uncertainty representations but also performs progressive learning to incorporate coarse- and fine-grained alignments properly; 3) Cross-modal Masked Modeling that aims at exploring more comprehensive relations between vision and language. Extensive experiments demonstrate that our AUL method consistently achieves state-of-the-art performance on three benchmark datasets in supervised, weakly supervised, and domain generalization settings. Our code is available at https://github.com/CFM-MSG/Code-AUL.

Coverage-Guaranteed Prediction Sets for Out-of-Distribution Data

Out-of-distribution (OOD) generalization has attracted increasing research attention in recent years, due to its promising experimental results in real-world applications. In this paper, we study the confidence set prediction problem in the OOD generalization setting. Split conformal prediction (SCP) is an efficient framework for handling the confidence set prediction problem. However, the validity of SCP requires the examples to be exchangeable, which is violated in the OOD setting. Empirically, we show that trivially applying SCP results in a failure to maintain the marginal coverage when the unseen target domain is different from the source domain. To address this issue, we develop a method for forming confident prediction sets in the OOD setting and theoretically prove the validity of our method. Finally, we conduct experiments on simulated data to empirically verify the correctness of our theory and the validity of our proposed method.

Like cheese and chalk or cross-fertilization? A qualitative exploration of how addiction patients perceive treatment in a general psychiatry ward

Background Addiction has historically been conceptualized and treated differently to other conditions. Studies suggest that healthcare staff perceive patients with substance use disorders (SUD) as a specific subgroup with distinct and challenging needs yet SUD patients frequently receive treatment in general psychiatry settings. Notwithstanding, knowledge of how SUD patients view themselves compared to other psychiatric patients and how they experience treatment in general psychiatry settings is lacking. Methods We conducted semi-structured interviews with 22 SUD patients voluntarily hospitalized in the acute psychiatric unit of a general hospital to explore the lived experiences of SUD patients receiving detoxification in an acute psychiatry ward. Data were analyzed using Thematic Content Analysis. Results Two primary themes and five subthemes emerged: (A) Patient perceptions of the problem and its consequences’, which includes the subcategories (i) Patient views of addiction, (ii) Staff perception of the patients; and (B) Lived experiences within the specific setting with subthemes (i) Interaction with the specific setting, (ii) Interaction with fellow patients, and (iii) Perception of staff by patients. Conclusions Overall, SUD patients had mixed perceptions; while many appreciated aspects of their hospitalization, others faced challenges in having all their needs met. Implementing policy-level interventions, like integrating SUD patient needs into psychiatry ward design and ensuring adequate resource allocation and staff training, could improve care quality for addiction patients in general psychiatry settings.

Paleoenvironmental variations during the Late Cambrian: Implications from Zn isotopes, I/(Ca+Mg) ratios, and other elemental proxies

The Upper Cambrian at the Martin Point section (∼110 m-thick) in western Newfoundland is a part of the Cow Head Group and partially spans the coeval Tuckers Cove and the Martin Point members of the Shallow Bay and Green Point formations, respectively. These units comprise alternating shale, minor conglomerate beds, and limestone rhythmites of a toe-of-slope apron. Earlier studies of the C-isotope profile, based on the lime mudstone interbeds, documented global negative δ13Ccarb shifts (from old to young: NL1, NL2, HERB) correlated with the lowermost Proconodontus posterocostatus, Proconodontus muelleri and base of Eoconodontus notchpeakensis conodont zones, respectively (post-Steptoean Positive Carbon Isotope Excursion NL1 and NL2 and Hellnmaria-Red Tops Boundary-HERB). Samples were extracted from the most preserved spots of micritic to near-micritic grain size (≤4 μm−10 μm). Fabric retention confirms petrographic preservation and insignificant correlations (R2 ≤ 0.1) of diagenetic proxies (e.g., Sr) with their environmental counterparts support the preservation of at least near-primary geochemical signatures. The paleoenvironmental proxies (TOC, Zn, P, Cu, Al/Ti, Mn, Fe, V, Mo) support dominant dysoxic conditions. The δ66Zn values (0.09–0.73 ‰ JMC Lyon) and (I/(Ca + Mg)) ratios (0.02–0.48 μmol/mol) vary consistently throughout the studied events. The minor decreases in δ66Zn values seem to denote inhibition of bioproductivity in a dysoxic water column, consistent with warm and humid climate during general transgressive settings and shoaling of organic-rich water into the shallow environment. The low I/(Ca + Mg) ratios (<0.5 μmol/mol) reinforce this interpretation, suggesting general dysoxic settings throughout the entire section.

Scheduling policies to minimize abandonment costs in infomercial call centers

Infomercial call centers answer calls in an order that reduces the number of abandoned calls to minimize lost revenue. We study a multi-class queuing system with a single server and customer abandonment, motivated by the case of infomercial call centers. We fully characterize the structure of the server’s optimal scheduling policy that minimizes the long-run average customer abandonment cost. We show that the optimal service policy is a static priority policy. We derive sufficient conditions under which the so-called b μ –rule is optimal. Under the b μ –rule, it is optimal to give priority to the customer type that has a higher service rate ( μ ) and higher abandonment cost (b), i.e., higher index b μ . We numerically test the robustness of our proposed policy in more general settings, including multi-server infomercial call centers.

Global Mapping Properties of Some Functions of Class S

The Lemma of Schwarz is one of the most surprising results in complex analysis in the sense that some very weak conditions on an analytic function in the unit disk |z| &lt; 1 imply a very strict behavior of that function in the respective disk. What about the behavior of the function outside the unit disk? This is the question we deal with in this paper. The theory we presented in some previous publications was about univalent functions, not necessarily in the unit disk, but in the most general setting, namely in the fundamental domains of arbitrary analytic functions. Naturally, connections can be expected between the two fields of complex analysis. The purpose of this paper is to explore these connections and take advantage of the well established theory of univalent functions in order to advance the theory of fundamental domains.

Abstract 2565: Vitamin D deficiency and outcomes in prostate cancer patients: A real-world database

Abstract Introduction: Vitamin D is essential for many bodily functions, including bone health and the prevention of osteoporosis and rickets. In recent years, the importance of vitamin D metabolism in immune system regulation and cancer prevention has been studied with increased focus. With the advent of cancer immunotherapies this has become more important. Multiple recent publications document that vitamin D deficiency is prevalent in cancer patients. This has also been observed specifically in prostate cancer patients, with a high percentage of these deficient patients being of African- American ancestry. It has been theorized that high levels of vitamin D deficiency among African American prostate cancer patients could contribute to worse cancer outcomes and increased health disparities. However, routine vitamin D testing has not been commonly performed in the oncologic community. We hypothesized that deficient levels of vitamin D could lead to inferior prostate cancer outcomes in men with a wide range of ethnic and socio-economic backgrounds. In this project we recorded vitamin D levels in prostate cancer patients at a large community oncology group and evaluated them by stage, pathologic data, survival, race/ethnicity, and other clinical features. Methods: This study is a retrospective, observational study of the data from the electronic medical records of patients with prostate cancer who received vitamin D level testing at Florida Cancer Specialists &amp; Research Institute from 2008- 2023, throughout the state of Florida. All data used in this study will constitute secondary data, it will have been collected originally for clinical use in the general oncology practice setting. No date parameters or patient limits will be applied to this study, and all eligible patients are included. Results: 451 patients with prostate cancer had determination of vitamin D levels, out of a total of 27,772 prostate cancer patients in the database. 38% of the prostate cancer patients analyzed had low 25-OH vitamin D levels (&amp;lt;32 ng/ml). Patients with low vitamin D levels had an average Gleason score of 7.46. Patients with low vitamin D levels who died had an average survival of 144 months. Patients with low vitamin D levels who presented with localized disease had a 35% chance of eventually developing castrate-resistant disease. 45% of the low vitamin D group developed metastatic disease during their course of treatment. Further comparisons of vitamin D levels with pathologic data, survival/longevity, race/ethnicity, and clinical course will be evaluated and presented. Citation Format: Lowell L. Hart, James Reeves, Stacey Garofalo, William Amick. Vitamin D deficiency and outcomes in prostate cancer patients: A real-world database [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2565.

Gauging non-invertible symmetries: topological interfaces and generalized orbifold groupoid in 2d QFT

Gauging is a powerful operation on symmetries in quantum field theory (QFT), as it connects distinct theories and also reveals hidden structures in a given theory. We initiate a systematic investigation of gauging discrete generalized symmetries in two-dimensional QFT. Such symmetries are described by topological defect lines (TDLs) which obey fusion rules that are non-invertible in general. Despite this seemingly exotic feature, all well-known properties in gauging invertible symmetries carry over to this general setting, which greatly enhances both the scope and the power of gauging. This is established by formulating generalized gauging in terms of topological interfaces between QFTs, which explains the physical picture for the mathematical concept of algebra objects and associated module categories over fusion categories that encapsulate the algebraic properties of generalized symmetries and their gaugings. This perspective also provides simple physical derivations of well-known mathematical theorems in category theory from basic axiomatic properties of QFT in the presence of such interfaces. We discuss a bootstrap-type analysis to classify such topological interfaces and thus the possible generalized gaugings and demonstrate the procedure in concrete examples of fusion categories. Moreover we present a number of examples to illustrate generalized gauging and its properties in concrete conformal field theories (CFTs). In particular, we identify the generalized orbifold groupoid that captures the structure of fusion between topological interfaces (equivalently sequential gaugings) as well as a plethora of new self-dualities in CFTs under generalized gaugings.

The Big Three diagnostic errors through reflections of Japanese internists.

To analyze the Big Three diagnostic errors (malignant neoplasms, cardiovascular diseases, and infectious diseases) through internists' self-reflection on their most memorable diagnostic errors. This secondary analysis study, based on a web-based cross-sectional survey, recruited participants from January 21 to 31, 2019. The participants were asked to recall the most memorable diagnostic error cases in which they were primarily involved. We gathered data on internists' demographics, time to error recognition, and error location. Factors causing diagnostic errors included environmental conditions, information processing, and cognitive bias. Participants scored the significance of each contributing factor on a Likert scale (0, unimportant; 10, extremely important). The Big Three comprised 54.1 % (n=372) of the 687 cases reviewed. The median physician age was 51.5 years (interquartile range, 42-58 years); 65.6 % of physicians worked in hospital settings. Delayed diagnoses were the most common among malignancies (n=64, 46 %). Diagnostic errors related to malignancy were frequent in general outpatient settings on weekdays and in the mornings and were not identified for several months following the event. Environmental factors often contributed to cardiovascular disease-related errors, which were typically identified within days in emergency departments, during night shifts, and on holidays. Information gathering and interpretation significantly impacted infectious disease diagnoses. The Big Three accounted for the majority of cases recalled by Japanese internists. The most relevant contributing factors were different for each of the three categories. Addressing these errors may require a unique approach based on the disease associations.

Generalized Inversion of Nonlinear Operators

AbstractInversion of operators is a fundamental concept in data processing. Inversion of linear operators is well studied, supported by established theory. When an inverse either does not exist or is not unique, generalized inverses are used. Most notable is the Moore–Penrose inverse, widely used in physics, statistics, and various fields of engineering. This work investigates generalized inversion of nonlinear operators. We first address broadly the desired properties of generalized inverses, guided by the Moore–Penrose axioms. We define the notion for general sets and then a refinement, termed pseudo-inverse, for normed spaces. We present conditions for existence and uniqueness of a pseudo-inverse and establish theoretical results investigating its properties, such as continuity, its value for operator compositions and projection operators, and others. Analytic expressions are given for the pseudo-inverse of some well-known, non-invertible, nonlinear operators, such as hard- or soft-thresholding and ReLU. We analyze a neural layer and discuss relations to wavelet thresholding. Next, the Drazin inverse, and a relaxation, are investigated for operators with equal domain and range. We present scenarios where inversion is expressible as a linear combination of forward applications of the operator. Such scenarios arise for classes of nonlinear operators with vanishing polynomials, similar to the minimal or characteristic polynomials for matrices. Inversion using forward applications may facilitate the development of new efficient algorithms for approximating generalized inversion of complex nonlinear operators.

Hausdorff dimension of certain sets arising by the maximal run-length function over factorial language

Let A be a language with infinite number of words over the alphabet Σ={0,1} and let (xi)i=1+∞ be the digits sequence in the unique terminating dyadic expansion of x∈[0,1). The maximal run-length function ln(x,A) of x over A is defined byln(x,A)=max⁡{k:xi+1xi+2⋯xi+k∈Afor some0≤i≤n−k}. In a general setting, Wu (2024) [18] proved a metrical property on the asymptotic behavior of ln(x,A), which extends the famous Erdős-Rényi limit theorem that represents for the special case A={1k:k≥1}. Under the assumption that A is factorial (i.e. the language A is closed under subword), Wu studied the exceptional setE={x∈[0,1):limn→∞⁡ln(x,A)mn=0andlimn→∞⁡ln(x,A)=∞}, and he obtained a lower bound of the Hausdorff dimension of E with some conditions on mn. In this paper, we determine the Hausdorff dimension of E without any additional assumption on mn and we obtain the Hausdorff dimension of two other kinds of exceptional sets of elements whose maximal run-length functions have different growth rates. Our results significantly extend the existing dimension results in this topic.

Linear limit continuation: Theory and an application to two-dimensional Bose–Einstein condensates

We present a coherent and effective theoretical framework to systematically construct numerically exact nonlinear solitary waves from their respective linear limits. First, all possible linear degenerate sets are classified for a harmonic potential using lattice planes. For a generic linear degenerate set, distinct wave patterns are identified in the near-linear regime using a random searching algorithm by suitably mixing the linear degenerate states, followed by a numerical continuation in the chemical potential extending the waves into the Thomas–Fermi regime. The method is applied to the two-dimensional, one-component Bose–Einstein condensates, yielding a spectacular set of waveforms. Our method opens a remarkably large program, and many more solitary waves are expected. Finally, the method can be readily generalized to three dimensions, and also multi-component condensates, providing a highly powerful technique for investigating solitary waves in future works.

A Clinical Guide to Support the Implementation of Addiction Consult Services and the Value of Teaching and Technical Assistance.

People with substance use disorders (SUDs) are increasingly admitted to general hospitals; however, many hospital systems lack both formal structures and skilled staff to provide high-quality care for inpatients with SUDs. Inpatient addiction consult services (ACSs), which are increasingly being implemented around the country, are an evidence-based strategy to add focused care for people with SUDs into the general medical setting. In 2018, New York City Health + Hospitals (H + H) launched an ACS program called Consult for Addiction Care and Treatment in Hospitals in six hospitals, supported by a team of addiction consult experts to deliver teaching and technical assistance (TTA) for the Consult for Addiction Care and Treatment in Hospitals ACSs. This commentary describes the TTA, which included site visits, introductory educational lectures, case conferences, ad hoc support, implementation assistance, and the creation of an addiction care guide. Similar TTA services could be used in the future when hospitals or systems want to launch novel clinical programs.

Promoting mental well-being among parents in the neonatal intensive care unit: a perspective on the role of Physician Associates.

Emotional disorders in parents of infants admitted to the neonatal intensive care unit (NICU) carry the potential for serious ramifications in neonatal and childhood outcomes. Despite this, current NICU mental health supports are less than optimum; postpartum mental health screening is limited, often missed in parents of inpatient infants, and may not be applicable to all family structures. Current evidence demonstrates improved outcomes in neonates and family members with early identification and multidisciplinary approaches to managing mental health problems. Physician Associates/Assistants (PAs) are a skilled group of advanced practice providers who are often a point of first contact for parents in the NICU, helping maintain continuity of care. In this perspective, we underscore leveraging the skills of PAs to promote the emotional wellbeing of parents in the NICU by way of practice and policy involvement. We also included a generic set of recommendations to equip PAs in this role.

Boolean Function Analysis on High-Dimensional Expanders

AbstractWe initiate the study of Boolean function analysis on high-dimensional expanders. We give a random-walk based definition of high-dimensional expansion, which coincides with the earlier definition in terms of two-sided link expanders. Using this definition, we describe an analog of the Fourier expansion and the Fourier levels of the Boolean hypercube for simplicial complexes. Our analog is a decomposition into approximate eigenspaces of random walks associated with the simplicial complexes. Our random-walk definition and the decomposition have the additional advantage that they extend to the more general setting of posets, encompassing both high-dimensional expanders and the Grassmann poset, which appears in recent work on the unique games conjecture. We then use this decomposition to extend the Friedgut–Kalai–Naor theorem to high-dimensional expanders. Our results demonstrate that a constant-degree high-dimensional expander can sometimes serve as a sparse model for the Boolean slice or hypercube, and quite possibly additional results from Boolean function analysis can be carried over to this sparse model. Therefore, this model can be viewed as a derandomization of the Boolean slice, containing only $$|X(k-1)|=O(n)$$ | X ( k - 1 ) | = O ( n ) points in contrast to $$\left( {\begin{array}{c}n\\ k\end{array}}\right) $$ n k points in the (k)-slice (which consists of all n-bit strings with exactly k ones).

Measures of kurtosis: inadmissible for asymmetric distributions?

AbstractSkewness and kurtosis are natural characteristics of a distribution. While it has long been recognized that they are more intrinsically entangled than other characteristics like location and dispersion, this has recently been made more explicit by Eberl and Klar (Stat Papers 65:415–433, 2024) with regard to orders of kurtosis. In this paper, we analyze the implications of this entanglement on kurtosis measures in general and for several specific examples. As a key finding, we show that kurtosis measures that are defined in the classical order-based way, which is analogous to measures of location, dispersion and skewness, do not exist. This raises serious doubts about the frequent application of such measures to skewed data. We then consider old and new proposals for kurtosis measures and evaluate under which additional conditions they measure kurtosis in a meaningful way. Some measures also allow more specific representations of the influence of skewness on the measurement of kurtosis than are available in a general setting. This works particularly well for a family of newly introduced density-based kurtosis measures.

A universal system for boosting gene expression in eukaryotic cell-lines

We demonstrate a transcriptional regulatory design algorithm that can boost expression in yeast and mammalian cell lines. The system consists of a simplified transcriptional architecture composed of a minimal core promoter and a synthetic upstream regulatory region (sURS) composed of up to three motifs selected from a list of 41 motifs conserved in the eukaryotic lineage. The sURS system was first characterized using an oligo-library containing 189,990 variants. We validate the resultant expression model using a set of 43 unseen sURS designs. The validation sURS experiments indicate that a generic set of grammar rules for boosting and attenuation may exist in yeast cells. Finally, we demonstrate that this generic set of grammar rules functions similarly in mammalian CHO-K1 and HeLa cells. Consequently, our work provides a design algorithm for boosting the expression of promoters used for expressing industrially relevant proteins in yeast and mammalian cell lines.