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A Parallel Interval Modeling Framework for Nonlinear Systems: Application to a Modified Duffing Oscillator
No full textThe paper presents a mathematical framework for converting nonlinear dynamical systems into parallel forms. This framework replaces the exact system motion equations with interval equations, enabling the representation of nonlinear functions over piecewise linear domains. Such representation enables the description of system motions using linear-like differential equations, which can be analyzed and manipulated using well-known control methods. One such method is eigenvalue analysis, a powerful tool in classical control theory since many techniques rely on the system’s characteristic polynomial and its eigenvalues. We apply this method to define interval system eigenvalues and track their variation during system operation. These eigenvalues serve as the basis for partial fraction decomposition, transforming the series system model into a parallel structure. This transformation incorporates both real and complex-conjugate eigenvalues. Unlike classical approaches, our method accounts for subsystems with complex components, producing complex vector signals. We demonstrate the approach by converting a modified Duffing oscillator into parallel form and analyzing its outputs. The contribution is primarily conceptual and methodological, providing a decomposition framework rather than a performance-optimized numerical scheme
Porous Triboelectric Nanogenerator for Load Sensing of Total Knee Replacement
No full textThis study addresses the critical need for self-powered, durable pressure sensors in Total Knee Replacement (TKR) implants to enable the collection of post-operative information. The scope of this research encompasses the design, development, and testing of a triboelectric nanogenerator (TENG) integrated into an instrumented knee implant for energy harvesting and pressure sensing. The authors’ unique approach involves utilizing a porous silicone rubber as a dielectric material. This allows the TENG to withstand forces up to 2000 N and generate a maximum power output of 18 μW. Theoretical modeling combined with experimental validation provides deeper insight into the fundamental operating principles. We elucidate the TENG output performance under an MTS servo-hydraulic load frame compared with a VIVO joint simulator. Other important characteristics, such as load sensitivity and the influence of porosity, are also presented. The proposed TENG shows great potential as a pressure sensor in TKR applications, offering high sensitivity, stability, and low cost
Data Please!: Expanding the Role of Libraries in Data Science through Digital Scholarship
Get PDFObjective: As data science becomes more integrated into research and teaching, libraries are well-positioned to support this work. This study examines how a digital scholarship team at Binghamton University enhanced engagement with data science by assessing faculty, staff, and graduate student needs. Through focus group interviews, the study identifies key support gaps and outlines strategic initiatives to strengthen interdisciplinary data science programming within the library.
Methods: A qualitative approach was used, involving 26 focus group interviews with faculty, staff, and graduate students across STEM and related fields. Participants discussed their data science work, tools, training, and perceived resource gaps. Qualitative coding analysis identified key areas for library support.
Results: The study revealed three primary areas for library expansion in data science: (1) fostering interdisciplinary collaboration through outreach, (2) developing structured data science programming aligned with campus needs, and (3) establishing physical and digital infrastructure for data-intensive research. In response, the Digital Scholarship team implemented a three-semester data science programming plan, enhanced research community engagement, and contributed to a dedicated data science space in the upcoming Digital Scholarship Center.
Conclusions: Findings support the library’s role as a vital hub for data science. By aligning digital scholarship services with campus needs, the library can bridge gaps in data literacy, tool accessibility, and collaborative opportunities. While initial implementations show promising engagement, ongoing assessment will be necessary to refine services, particularly for undergraduates and emerging technologies. This study provides a model for other libraries to expand data science programming effectively
Energy burden: Exploring the intersection of race, income, and community characteristics across the United States
Get PDFHousehold energy burden is a simple concept with complicated causes. Energy burden measures the percentage of income spent by a household on energy for heating, lighting, air conditioning, cooking, etc. Households with greater energy burdens may have to make tradeoffs between paying utility bills and medical, housing, or other expenses. Some limited quantitative and case study research indicates that underprivileged groups suffer larger energy burdens, often attributed to lower income levels. Our study is the first to examine the phenomenon nationally as well as investigate the drivers of energy burden on households across the United States. Our examination of energy burden across all measurable census tracts in the United States (n = 64,835) finds that even when accounting for income, majority African American census tracts face significantly increased average energy burden with largely Latinx census tracts less challenged. To explore this social occurrence, we examine the intersectionality of race, income, and structural challenges in these neighborhoods. We find that average building age and homeownership rates impact energy burden and are two factors that overburden African American households. We discuss some historical and programmatic factors that our analysis points to as potential causal mechanisms for the higher energy burden in African American communities. The goal of a just energy transition to lower carbon emissions requires that policymakers understand that energy burden is not simply a matter of income, but a complex set of historical and structural causes that face households with multiple vulnerabilities
The Walking Moai Hypothesis: Archaeological Evidence, Experimental Validation, and Response to Critics
Get PDFThe transport of Rapa Nui\u27s (Easter Island) monumental moai statues has been debated for over a century. Based on a systematic analysis of 962 moai, with a focus on 62 road statues, combined with 3D modeling and experimental trials, we demonstrate that these multi-ton megaliths were designed for transport vertically in a controlled walking motion facilitated by their carved shapes. Our evidence includes distinctive morphological features of road moai (wide, D-shaped bases and forward lean), archaeological road characteristics (4.5m wide, concave cross-sections), non-random breakage patterns, and successful experimental validation using a precisely-scaled 4.35 metric ton replica based on road moai morphology. Our experiments revealed that the forward-leaning design enabled efficient transport, covering 100 meters in 40 minutes with a team of 18 people—a significant improvement over earlier vertical transport attempts that used incorrectly proportioned ahu moai forms. Statistical analysis of the road moai distribution reveals patterns that are strongly consistent with transport failure: 51.6% concentrate within 2 km of the Rano Raraku quarry, following an exponential decay pattern expected from mechanical failure processes rather than deliberate ceremonial placement. Despite empirical support, several scholars have challenged the walking hypothesis. We systematically address critiques regarding terrain constraints, rope availability, weathering patterns, and alternative transport mechanisms, demonstrating how objections fail to account for the comprehensive archaeological evidence supporting vertical transport. The walking method required minimal resources and labor compared to horizontal transport hypotheses, revealing sophisticated engineering rather than environmental destruction, and aligning with Rapa Nui oral traditions that describe moai walking from the quarry
Targeting Wnt-driven metabolic adaptations in cancer: integrating glycolysis, glutaminolysis, IDO1-mediated immune evasion, and therapeutic delivery strategies
Get PDFThe Wnt pathway is an evolutionarily conserved signaling cascade that regulates a wide range of fundamental cellular processes, including proliferation, differentiation, polarity, migration, metabolism, and survival. Due to its central regulatory roles, Wnt signaling is critically involved in the pathophysiology of numerous human diseases. Aberrant activation or insufficient inhibition of this pathway has been causally linked to cancer, degenerative disorders, metabolic syndromes, and developmental abnormalities. Wnt signaling drives cancer progression by reprogramming metabolism and promoting immune evasion. Wnt-driven tumors exhibit enhanced aerobic glycolysis (the Warburg effect), glutaminolysis, and macropinocytosis, which support rapid proliferation and help maintain redox homeostasis under nutrient-limited or nutrient-deprived conditions. These metabolic adaptations sustain tumor survival and contribute to immune suppression, as seen in the Wnt5a-indoleamine 2,3-dioxygenase 1 (IDO1) axis, which fosters regulatory T-cell expansion and an immunosuppressive microenvironment. The interplay among glycolysis, glutamine metabolism, and immune escape renders Wnt-driven cancers highly adaptable and resistant to conventional therapies. Targeting metabolic enzymes, such as pyruvate dehydrogenase kinase 1 (PDK1), lactate dehydrogenase A (LDHA), glutaminase (GLS), and monocarboxylate transporters (MCT-1), alongside immune checkpoint inhibitors or IDO1 blockade, presents a promising strategy for overcoming metabolic plasticity and immune evasion in Wnt-driven malignancies, thereby enhancing therapeutic efficacy and improving patient survival in otherwise refractory tumor types. Combining glycolysis and glutaminolysis inhibitors with T-cell activating therapies may disrupt tumor metabolic plasticity and restore anti-tumor immunity. Additionally, advanced drug delivery systems, including lipid nanoparticles (LNPs), polymeric nanocarriers, and exosome-based platforms, enhance the targeted accumulation of metabolic inhibitors and immunomodulatory agents while minimizing systemic toxicity. This review examines the metabolic and immune adaptations of Wnt-driven cancers, with a focus on glycolysis, glutaminolysis, and macropinocytosis. We highlight emerging therapeutic targets and nanomedicine-based delivery strategies to counteract metabolic adaptation and immune suppression. By integrating metabolic and immune-targeting with precision nano-delivery platforms, future treatment paradigms may improve outcomes for aggressive and therapy-resistant Wnt-driven cancers
α-Amylase-Mediated Antibiotic Degradation and Sequestration in Pseudomonas aeruginosa Biofilm Therapy
Get PDFBackground: As of 2022, 80% of all documented microbial infections are biofilm-associated: communities of microorganisms adhered to a surface and enclosed in a complex extracellular polymeric substance (EPS). The EPS acts as a physical barrier protecting the bacteria from antimicrobial agents and host immune responses. To combat this hurdle, the application of glycoside hydrolases (GH) has been investigated due to their ability to cleave particular structural polysaccharides within the EPS, thus breaking down the protective barrier and improving antibiotic clearance. While various studies demonstrate the capacity of GHs to improve antibiotic efficacy against biofilms in combination, there is clear differential success between these treatments depending on the GH and antibiotic chosen. Due to the overlap of GH targets and antibiotic structures, it is imperative to ensure that the antibiotics in combinatorial treatments are not degraded by the GH. Methods: This study aimed to screen the GH α-amylase produced from Aspergillus oryzae (AO) and Bacillus subtilis (BS), combined with various antibiotics from different classes, charges, and mode of actions by determining MICs. against the bacterium Pseudomonas aeruginosa (PA) of 6 antibiotics with or without α-amylase and treat 2-day PA biofilms with antibiotics with or without GHs. Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS) stability assays and Differential Scanning Fluorimetry (DSF) were conducted to determine antibiotic and GH degradation as well as antibiotic sequestration. Results: Increased MICs in the presence of GHs as well as decreased antibiotic clearance against 2-day biofilms were suggestive of antibiotic degradation. LC-MS/MS stability assays of tetracycline and ciprofloxacin in the presence and absence of α-amylase further demonstrated the α-amylase-mediated antibiotic sequestration. Differential scanning fluorimetry (DSF) assays confirmed α-amylase-antibiotic interactions. Conclusions: This study suggests that α-amylase is capable of degrading and sequestering a variety of antibiotics, and the degree to which these phenomena occur varies depending upon the source of the GH. As a potential treatment for biofilm-associated infections, it is imperative that the GH + antibiotic combinations are determined compatible prior to clinical use
Understanding initial capacity loss in substituted layered oxide cathodes for lithium-ion batteries
Get PDFLayered oxide LiCoO₂ (LCO) pioneered the commercialization of lithium-ion batteries (LIBs) in 1991, yet the growing demand for higher energy density has driven the development of substituted layered oxides, including LiNiᵧMnCo₁₋ᵧ₋O₂ (NMC) and LiNiᵧCo₁₋ᵧ₋AlO₂ (NCA). Despite the increased energy density, achieving full lithium reversibility during the first charge-discharge cycle remains a critical challenge: approximately 0.08–0.11 Li is “irreversibly” lost after delithiation, resulting in a substantial capacity loss of 10–15%. This loss is conventionally attributed to bulk lithium transport limitations arising from three interrelated factors: (1) contraction of the c-axis lattice during lithiation, (2) reduced rate of tetrahedral site hopping (TSH) at high lithium concentrations, and (3) localized charge accumulation near low-valent transition metal (TM) ions. This work challenges this view, demonstrating that initial capacity loss (ICL) stems from a complex interplay of bulk, surface, and interfacial kinetics rather than bulk transport alone. Electrochemical analysis of LiNiᵧCo₁₋ᵧO₂ (0 ≤ y ≤ 0.80) and ternary NMC variants (NMC111, NMC525, NMC811) identifies compositional thresholds: systems with y ≤ 0.60 retain low ICL of 0.014–0.037 Li at a delithiation limit of 0.4 Li, whereas at y = 0.80, ICL surges to 0.081 Li. In ternary systems, simultaneous incorporation of Mn and Ni maintains low ICL, with no measurable influence of Mn on the observed capacity loss. Furthermore, increasing the delithiation limit in NMC811 from 0.4 Li to 0.8 Li reduces ICL by over 30%—from 0.137 Li to 0.094 Li—likely driven by decomposition of the surface impurity layer at high voltages. These findings refine our understanding of ICL in layered oxide cathodes and emphasize the need for holistic kinetic optimization across bulk, surface, and interfacial domains for maximizing first cycle performance
The Association of Circulating Immune Cells with Cognitive Function, Brain Imaging, and Incident all-cause and Alzheimer\u27s Dementia: The Framingham Offspring Study.
Get PDFBackground: Emerging evidence supports the central role of the immune system in brain health, yet little is known about the role of circulating immune cells and cognitive function or brain health in dementia-free populations. We investigated the association of 43 immune cells with cognitive function, structural brain imaging, and incident dementia in Framingham Heart Study Offspring participants. Methods: Immune cells were phenotyped by flow cytometry. Linear mixed effects models were used for cross-sectional associations between immune cells and four cognitive domain scores and 13 brain MRI measurements. Cox proportional hazards regression models tested the relationship between immune cells and time to dementia. Models were adjusted for age, sex, education, CMV status, and APOE genotype, with further adjustment for cardiovascular risk factors. Data was further stratified by CMV status. Results: Among 795 participants with cellular phenotyping, cognitive testing and brain imaging data (mean age 61, 52% women), there were no associations between immune cells and cognitive test scores. Several significant associations between immune cells and regional brain MRI measurements were observed. Higher CD8+ cells [CD8+CD45RO-CCR7-CD27-(Teff), CD8+CD45RA+CD28-CD57+(TEMRA), CD8+CD27-CD28-] associated with greater cerebrum gray and frontal gray matter volumes and inclusion of cardiovascular risk factors strengthened the association. Among CMV+ participants, CD8+TEMRA and CD8+Teff cells were significantly associated with higher total gray and frontal gray matter volumes. No significant associations were observed between immune cells and incident all-cause or Alzheimer’s disease dementia. Conclusion: The pathobiology underpinning the associations between immune cells and brain volumes require further study and validation in diverse samples
Evaluation of shorter versus longer antifungal treatment durations for Candida spp. urinary tract infections among hospitalized adults.
Get PDFInfectious Diseases Society of America guidelines recommend 14 days of treatment for Candida spp. urinary tract infections (UTIs). To our knowledge, no data are available to compare \u3c14 days for Candida spp. UTI. This was a\u3esingle-center, retrospective cohort study between 01 January 2015 and 01 January 2024. Hospitalized adults with \u3e1 urine culture with Candida spp. and symptoms who initiated \u3e1 antifungal dose within 96 hours were included. Multiple exclusion criteria existed, including but not limited to if Candida spp. were isolated from another site, antifungals were received for another indication, or the participant was asymptomatic. The primary outcome was clinical treatment success. Binary logistic regression was performed to further assess the relationship between fluconazole duration and clinical treatment success. Among 2,400 patients with candiduria, 45 and 58 in the 14-day and \u3c14-day cohorts were assessed after exclusion criteria were applied, respectively. Median (interquartile range) fluconazole duration was 14 (14–14) days in the 14-day cohort and 7 (5–7) in the \u3c14-day cohort. There was no difference in clinical treatment success in patients treated for 14 days vs \u3c14 days (14 days: 93.3% (42/45) vs \u3c14 days: 93.1% (54/58), P = 1.000; between-group difference (95% CI: 0.02 [−9.6 to 10]). Fluconazole duration did not have a significant association with clinical treatment success on binary logistic regression (P = 0.503; odds ratio 0.917 [95% CI: 0.712–1.181]). There was no statistically significant difference in clinical treatment success in patients treated with fluconazole for a median of 14 days vs a median of 7 days for symptomatic Candida spp. UTI. These data support the potential utility of shorter antifungal durations for Candida spp. UTI