DePaul University

An nth Riemann derivative of a function f at a point x is a limit of the form $D_{\mathcal {A}}f(x)=\lim _{h\rightarrow 0}\sum _{i=0}^na_if(x+b_ih)/h^n,$ where the coefficients $a_i$ and nodes $b_i$ satisfy the Vandermonde linear system $\sum _i a_ib_i^j=n!\cdot \delta _{nj}$ for $j=0,1,\ldots ,n$. The function f is n times Peano differentiable at x if it is approximated to order n near x by its nth Taylor polynomial. In 1936, Marcinkiewicz and Zygmund proved that the nth Riemann differentiability $\widetilde{D}_n$ with nodes $0,1,2,2^2,\ldots ,2^{n-1}$ makes up the difference between the $n-1$st and nth Peano differentiabilities for all functions f at x. Call each $D_{\mathcal {A}}$ with the same property an MZ-differentiation. A number of recent results on MZ-differentiation have opened this subject of classical analysis to ideas from linear and abstract algebra, number theory, or combinatorics. This largely expository article outlines many of these results using numerous examples and counterexamples to illustrate the theorems and give insight into some of the harder proofs. The topics include first order MZ-differentiations, Gaussian differentiations, symmetric and forward Riemann differentiations, the special third Riemann differentiation with nodes $-1,0,1,2$, Riemann differentiations with geometric nodes, and the connection with the classification of generalized Riemann derivatives.

Seasonal influenza remains a persistent public health threat in the United States, causing tens of thousands of deaths and hospitalizations each year despite the availability of effective vaccines. Ongoing challenges—including low vaccination uptake, health inequities, and declining trust in public health institutions—have hindered prevention efforts and left vulnerable populations at heightened risk. The Society of Behavioral Medicine calls for maintaining Medicaid funding, investing in vaccination promotion, and restoring public health data sources to mitigate the impact of influenza. During the 2024–25 flu season, the United States experienced its highest flu case numbers since 2009, with low vaccination uptake and deepening public mistrust in health institutions. Flu-related mortality remains substantial, disproportionately affecting older adults and Black Americans, while proposed federal funding cuts to Medicaid, Medicare, and biomedical research threaten the nation’s epidemic response capacity. Sustained investment in Medicaid, vaccination promotion, and data-driven research is essential to protect vulnerable populations, reduce flu-related illness and death, and strengthen public health preparedness.

The last two decades have seen exponential growth in the number of US and Canadian health humanities programs. As an evolving field, there is significant variation across the structures and educational content of health humanities programs. This study was designed to solicit views from self-identified North American health humanities educators from academic programs. The primary aim was to garner broad perspectives on what distinguishes health humanities academic programs from other academic programs and what content programs should deliver to students. The goal was to distill defining features and parameters of a high-quality health humanities educational program, inquiring in particular about knowledge, skills, and values. Using Participatory Action Research methods, we conducted 14 focus group interviews composed of 89 participants. During phase one analysis, we applied 199 codes to interview transcripts, from which we identified 41 themes across seven domains: (1) Knowledge, (2) Education/Pedagogy, (3) Methodologic Approaches, (4) Skills, (5) Values, (6) Disciplinarity, and (7) Institutional Limitations/External Restrictions. Phase two analysis discerned that these themes inform five overarching themes that cross domains and educational levels: (1) Interdisciplinarity, (2) Internal Inquiry, (3) External Examination, (4) Praxis, and (5) Transformative Education. Our findings suggest that even though health humanities may have neither canonical knowledge bases nor universal methodologies, overarching themes speak to a consensus of field-level priorities that transcend programmatic variation. Further research is needed to improve tools and standards to aid in the growth, assessment, and evaluation of health humanities educational programs.

This qualitative study examined what medical advocates do that is helpful and unhelpful in their interactions with sexual assault survivors from the perspective of nurses. Data were N = 22 semistructured interviews with sexual assault nurse examiners (SANEs) and non-SANEs. Inductive thematic analysis was used. Helpful ways advocates worked with survivors included providing emotional support , caring for tangible needs , providing information , supporting patient choice , staying with and focusing on the patient , and facilitating follow-up care . Unhelpful ways advocates worked with survivors included poor patient service and not respecting patient wishes. SANE training did not influence nurses’ perceptions of advocate helpfulness.

Despite the increasing application of the Sustainable Livelihoods Framework (SLF) in rural and agrarian contexts, a critical lack of empirical analysis persists, particularly in urban informal economies, including among waste picker communities. Addressing this gap, this study examines the impact of livelihood assets on the livelihood security of waste picker households residing near the Putri Cempo Landfill in Surakarta, Indonesia. Grounded in the SLF and employing an expanded asset hexagon model, this research incorporates information capital as a novel dimension in addition to the traditional five capitals (human, physical, natural, financial, and social). Data were collected from 85 households through structured questionnaires, followed by descriptive statistics, asset hexagon visualisation, and binary logistic regression analysis. The results reveal that only 36.5% of households achieved livelihood security, reflecting multidimensional vulnerabilities, particularly in the areas of housing, health, and education. Financial, human, and informational capital emerged as statistically significant determinants of livelihood security, with financial capital exerting the strongest influence. In contrast, natural and social capital showed no significant impact. The findings underscore the importance of enhancing financial inclusion, improving human development, and strengthening access to information to build resilience among informal urban waste workers. This novel inclusion of information capital represents a key theoretical and empirical advancement to the SLF, offering a more comprehensive understanding of urban livelihood dynamics and informing targeted policy and social protection strategies.

Several works have recently investigated the parameterized complexity of data completion problems, motivated by their applications in machine learning, and clustering in particular. Interestingly, these problems can be equivalently formulated as classical graph problems on induced subgraphs of powers of partially-defined hypercubes. In this paper, we follow up on this recent direction by investigating the Independent Set problem on this graph class, which has been studied in the data science setting under the name Diversity. We obtain a comprehensive picture of the problem’s parameterized complexity and establish its fixed-parameter tractability w.r.t. the solution size plus the power of the hypercube. Given that several such First Order Logic (FO) definable problems have been shown to be fixed-parameter tractable on the considered graph class, one may ask whether fixed-parameter tractability could be extended to capture all FO-definable problems. We answer this question in the negative by showing that FO model checking on induced subgraphs of hypercubes is as difficult as FO model checking on general graphs.

Introduction Washington state's adult use cannabis market operates under regulations by the Washington State Liquor and Cannabis Board to restrict access and promotion among young people. Cannabis edibles sold in the state are required to contain specific labels that inform consumers that the product contains cannabis and provide contact information for Poison Control. However, it is unclear how teens perceive such labels. Methods Ten focus groups were conducted with a diverse sample of 28 teens ( M = 15.93, SD = 1.25) in Washington state, United States. After viewing images of cannabis edible products available in Washington state, participants shared their thoughts and opinions about the packaging, warning labels and nutrition information. Results Through a thematic analysis, we noted that teens may be misinterpreting warning labels, and they think warning labels are hidden or unnoticeable. Most teens paid little attention to nutrition labels and often found serving size information confusing. Teens said if an edible product looked similar to snack products they know, they might perceive them as less risky and more enticing. Knowledge of cannabis products also impacted teens' understanding of edible product packaging. Discussion and Conclusions Labels alert teens to the fact that products contain cannabis. However, teens often feel such labels apply to younger children and would not keep teens from using a product. Youth might benefit from additional guidance around interpreting cannabis packaging and labels.

Accurate registration of liver computed tomography (CT) and ultra‐sound (US) images is crucial for image‐guided interventions, enabling precise navigation and treatment planning. However, aligning these multimodal images is challenging due to differences in imaging characteristics, patient positioning, and organ deformation. This paper proposes a novel biomechanically regularized deep deformable registration framework for liver CT and US fusion. Our approach leverages deep learning to model complex deformation fields while incorporating biomechanical priors derived from liver anatomy and tissue properties to enhance the physical plausibility and robustness of the registration process. We utilize a convolutional neural network to predict the deformation field between the CT and US images, guided by a biomechanical regularization term that penalizes unrealistic deformations. The framework is trained on a dataset of paired liver CT and US images, incorporating both synthetic and real‐world deformation scenarios. The results show that the values of mean square error, normalized cross‐correlation, structural similarity, mutual information, feature similarity index, and mean absolute error are 1.2132, 0.9932, 0.9907, 0.913, 0.9971 and 1.39 ±$\pm$ 1.02, respectively. This work represents a step forward in bridging the gap between multimodal image registration and biomechanically informed modelling, advancing precision in image‐guided liver interventions.

The National Institutes of Health (NIH) supports critical biomedical and behavioral health research conducted in the United States through grant funding every year. Recently, several NIH grants that had been awarded and passed full scientific peer review were suspended or canceled with little scientific or performance rationale. As a result of the NIH grant suspensions, important research related to Cancer, COVID-19, and mental health, among others, have been affected, with a loss of at least $643 million in funding. The grant suspensions have halted clinical trials in progress, and could be setting back important biomedical trials and research related to chronic disease, including cardiovascular disease and diabetes, which could benefit the public. While the grant cuts have been claimed to be due to a lack of scientific validity, rigor, or public benefit, these assertions are contrary to the findings of the NIH, researchers, and experts in the field who were initially involved in evaluating and awarding the grants. In order to prevent further unwarranted grant cancellations, we ask congress to consider holding oversight hearings regarding the NIH grant suspensions. Additionally, we ask that they introduce or support legislation that would help to prevent further unjustified grant suspensions and secure predictable funding for biomedical and behavioral health research. Congress must prevent the termination of NIH research grants that have already been awarded through lawful, competitive processes. Legislators must use their constitutional spending authority to ensure agencies execute appropriated funds, to ensure funding efficiency, life-saving medical innovation, and US scientific competitiveness globally. Lay summary Grants awarded by the National Institutes of Health (NIH) for health research, including research on vaccines and health disparities, have been suspended after going through the process of peer review and being awarded a grant. The reasons for the grant suspensions go against the findings of the NIH on the scientific validity, importance, and benefit to the public of the research being conducted, with a lack of justification being given to congress, the researchers, or the public. To address the NIH grant cancellations and try to prevent further suspensions, we ask congress to initiate hearings focused on the grant cancellations and introduce legislation to prevent unwarranted grant cancellations in the future.

Synchrotrons provide a variety of X-ray techniques for fast, high-resolution structural, compositional, and functional analysis of biological tissues. Micro- and nano-CT enable ultra-fast high-resolution 3D imaging of relatively large samples, while X-ray fluorescence provides elemental composition of fixed biological samples with highest sensitivity. X-ray fiber diffraction allows to push resolution limit even further and analyze partially-ordered and disordered biological composites, such as bones, muscles, spider silk, and connective tissues. Collagen fibrils are key components of ligaments, tendons, cartilage, intervertebral discs, cardiac valves and chordae tendineae. Complex architecture, cellular activity, and performance of these tissues strongly depend on proper collagen fiber assembly, governed by proteoglycans. X-ray microdiffraction study of collagenous tissues, such as bone, cardiac tissues, tendons, and cartilage, revealed different fibril distribution patterns and detected presence of different collagen types in these samples. Multimodal x-ray and electron microscopy imaging will shine the light on correlation of collagen fibril structure with its macromolecular ligands and their role in proper tissue functioning, as well as in pathological cases of trauma and disease.

Considering instances of police brutality against people experiencing homelessness (PEH) and subsequent calls for changes to policing, it is important to understand how police and PEH interact. However, this literature in the US context has not been synthesized. This review aims to summarize: (a) the extent to which PEH have contact with police; and the (b) nature and (c) outcomes of these interactions. A PRISMA‐aligned scoping review identified relevant scholarly articles on empirical studies published in a recent 20‐year period in the United States. After screening, 26 relevant articles were analyzed utilizing thematic analysis. Rates of contact were disproportionately high among PEH. Contact was often the result of code enforcement, racial profiling, or notification by housed people, and consisted of harassment and abuse towards PEH. Finally, proximal (i.e., move‐along orders, citation, arrest) and distal (i.e., perpetuating homelessness, lack of service provision, conflict, distrust and avoidance of police, and stress) outcomes emerged.

This study proposes DMCIE (diffusion model with concatenation of inputs and errors) to enhance binary brain tumor segmentation from multimodal MRI scans. Accurate voxel-wise tumor localization remains challenging due to variability in tumor size, shape, and imaging conditions, impacting clinical diagnosis and treatment planning. DMCIE employs a two-stage framework: a 3D U-Net first predicts an initial tumor mask from multimodal MRI inputs (T1, T1ce, T2, FLAIR), and an error map highlighting discrepancies with the ground truth is generated. This error map, concatenated with the original inputs, is refined through a diffusion model that iteratively corrects misclassified and boundary regions. The proposed DMCIE method was evaluated on the BraTS2020 dataset. Compared to the initial U-Net segmentation, DMCIE improved segmentation performance by +5.18% Dice and $-$2.07 mm HD95 compared to the initial U-Net segmentation. It shows improvements in boundary accuracy and segmentation across diverse tumor shapes, and maintains spatial coherence, even in fragmented cases. DMCIE introduces an effective error-guided correction mechanism for binary brain tumor segmentation, using multimodal MRI data to enhance segmentation accuracy. By modeling and correcting segmentation errors during diffusion, DMCIE achieves anatomically precise and well-localized tumor segmentation.

Rooted in the freedom dreams of Black political movements across diasporas, abolition has emerged as a framework for the study and practice of building a world without captivity. Anthropologists of social movements have attended to the dreamers and destroyers doing this work, turning an analytic eye to the practice of abolition among community organizers, high school students, immigrant rights advocates, and queer activists. As the discipline flails for relevance, anthropologists writing from some of the most prestigious enclaves have called for its destruction. Both abolitionist anthropology and the abolition of anthropology itself have surfaced as rejoinders to the deraced humanism that dominated the last century of American anthropology. In this review, we engage abolition as a political horizon, a targeted decarceration movement, an ecological struggle, a mode of healing, and a pedagogical framework. Ultimately, we conceptualize abolition as an ecumenical imperative that both exceeds and inspires anthropological practice.

Mentoring programs are a popular approach for supporting youth through relationships with adult mentors, but few mentoring studies have included the mentor perspective. The present study comprised 80 undergraduate mentors (M age = 19.83, 52.5% White, 76.3% female) and elementary‐aged mentees (M age = 10.61, 91.3% Black, 53.8% female). Mentee and mentor perceptions of the mentoring relationship and their other adult social supports were assessed over an academic year, in addition to mentor internalizing problems. It was hypothesized that mentor and mentee mentoring relationship quality would both be predicted by and predict the other variables of interest. For mentees, cross‐lagged panel models indicated pre‐existing adult social supports were positively associated with perception of the mentoring relationship, while for mentors, multiple regression highlighted the negative association of mentor internalizing problems with perceived mentoring relationship quality. These findings highlight the need for dyadic perspectives in future mentoring research.