bluuebunny/crossref_metadata_2025 huggingface dataset:
Bioactive fiber-reinforced hydrogel to tailor cell microenvironment for structural and functional regeneration of myotendinous junction
Authors: Sun Yuzhi , Sheng Renwang , Cao Zhicheng , Liu Chuanquan , Li Jiaxiang , Zhang Po , Du Yan , Mo Qingyun , Yao Qingqiang , Chen Jialin , Zhang Wei
Published: April 2024

Myotendinous junction (MTJ) injuries are prevalent in clinical practice, yet the treatment approaches are limited to surgical suturing and conservative therapy, exhibiting a high recurrence rate. Current research on MTJ tissue engineering is scarce and lacks in vivo evaluation of repair efficacy. Here, we developed a three-dimensional–printed bioactive fiber-reinforced hydrogel containing mesenchymal stem cells (MSCs) and Klotho for structural and functional MTJ regeneration. In a rat MTJ defect model, the bioactive fiber-reinforced hydrogel promoted the structural restoration of muscle, tendon, and muscle-tendon interface and enhanced the functional recovery of injured MTJ. In vivo proteomics and in vitro cell cultures elucidated the regenerative mechanisms of the bioactive fiber-reinforced hydrogel by modulating oxidative stress and inflammation, thus engineering an optimized microenvironment to support the survival and differentiation of transplanted MSCs and maintain the functional phenotype of resident cells within MTJ tissues, including tendon/muscle cells and macrophages. This strategy provides a promising treatment for MTJ injuries.
A variational reformulation of molecular properties in electronic-structure theory
Authors: Jørgensen Poul , Olsen Jeppe , Johansen Magnus Bukhave , von Buchwald Theo Juncker , Hillers-Bendtsen Andreas Erbs , Mikkelsen Kurt V. , Helgaker Trygve
Published: April 2024

Conventional quantum-mechanical calculations of molecular properties, such as dipole moments and electronic excitation energies, give errors that depend linearly on the error in the wave function. An exception is the electronic energy, whose error depends quadratically on the error in wave function. We here describe how all properties may be calculated with a quadratic error, by setting up a variational Lagrangian for the property of interest. Because the construction of the Lagrangian is less expensive than the calculation of the wave function, this approach substantially improves the accuracy of quantum-chemical calculations without increasing cost. As illustrated for excitation energies, this approach enables the accurate calculation of molecular properties for larger systems, with a short time-to-solution and in a manner well suited for modern computer architectures.
Loureirin A is a narrow-spectrum antimicrobial agent against
Helicobacter pylori
Authors: Tong Qian , Yin Chengqiang , Hang Xudong , Bai Yuefan , Zhang Chongwen , Xu Jingcheng , Huang Yan , Ge Yixin , Chen Tianyu , Zeng Liping , Jia Jia , Bi Hongkai
Published: April 2024

Currently,
Helicobacter pylori
eradication by antibiotic therapy faces various challenges, including antibiotic resistance, side effects on intestinal commensal bacteria, and patient compliance. In this study, loureirin A (LrA), a traditional Chinese medicine monomer extracted from Sanguis Draconis flavones, was found to possess specific antibacterial activity against
H. pylori
without the bacteria displaying a tendency to develop resistance
in vitro
. LrA demonstrated a synergistic or additive effect when combined with omeprazole (a proton pump inhibitor) against
H. pylori
. The combination of LrA and omeprazole showed promising anti-
H
.
pylori
potential, exhibiting notable
in vivo
efficacy comparable to standard triple therapy in mouse models infected with both drug-sensitive and drug-resistant
H. pylori
strains. Moreover, the narrow-spectrum antibacterial profile of LrA is reflected in its minimal effect on the diversity and composition of the mouse gut microbiota. The underlying mechanism of action of LrA against
H. pylori
involves the generation of bactericidal levels of reactive oxygen species, resulting in apoptosis-like cell death. These findings indicate that LrA is a promising lead compound targeting
H. pylori
without harming the commensal bacteria.
Gut microbiota intervention alleviates pulmonary inflammation in broilers exposed to fine particulate matter from broiler house
Authors: Liu Junze , Li Yuan , Shen Dan , Li Xiaoqing , Wang Kai , Nagaoka Kentaro , Li Chunmei
Published: April 2024

The gut microbiota of poultry is influenced by a variety of factors, including feed, drinking water, airborne dust, and footpads, among others. Gut microbiota can affect the immune reaction and inflammation in the lungs. To investigate the effect of gut microbiota variation on lung inflammation induced by PM
2.5
(fine particulate matter) in broilers, 36 Arbor Acres (AA) broilers were randomly assigned to three groups: control group (CON), PM
2.5
exposure group (PM), and PM
2.5
exposure plus oral antibiotics group (PMA). We used non-absorbable antibiotics (ABX: neomycin and amikacin) to modify the microbiota composition in the PMA group. The intervention was conducted from the 18th to the 28th day of age. Broilers in the PM and PMA groups were exposed to PM by a systemic exposure method from 21 to 28 days old, and the concentration of PM
2.5
was controlled at 2 mg/m
3
. At 28 days old, the lung injury score, relative mRNA expression of inflammatory factors, T-cell differentiation, and dendritic cell function were significantly increased in the PM group compared to the CON group, and those of the PMA group were significantly decreased compared to the PM group. There were significant differences in both α and β diversity of cecal microbiota among these three groups. Numerous bacterial genera showed significant differences in relative abundance among the three groups. In conclusion, gut microbiota could affect PM
2.5
-induced lung inflammation in broilers by adjusting the capacity of antigen-presenting cells to activate T-cell differentiation.

IMPORTANCE

Gut microbes can influence the development of lung inflammation, and fine particulate matter collected from broiler houses can lead to lung inflammation in broilers. In this study, we explored the effect of gut microbes modified by intestinal non-absorbable antibiotics on particulate matter-induced lung inflammation. The results showed that modification in the composition of gut microbiota could alleviate lung inflammation by attenuating the ability of dendritic cells to stimulate T-cell differentiation, which provides a new way to protect lung health in poultry farms.
Deciphering
Staphylococcus aureus–
host dynamics using dual activity-based protein profiling of ATP-interacting proteins
Authors: Ahator Stephen Dela , Hegstad Kristin , Lentz Christian S. , Johannessen Mona
Published: April 2024

The utilization of ATP within cells plays a fundamental role in cellular processes that are essential for the regulation of host–pathogen dynamics and the subsequent immune response. This study focuses on ATP-binding proteins to dissect the complex interplay between
Staphylococcus aureus
and human cells, particularly macrophages (THP-1) and keratinocytes (HaCaT), during an intracellular infection. A snapshot of the various protein activity and function is provided using a desthiobiotin-ATP probe, which targets ATP-interacting proteins. In
S. aureus
, we observe enrichment in pathways required for nutrient acquisition, biosynthesis and metabolism of amino acids, and energy metabolism when located inside human cells. Additionally, the direct profiling of the protein activity revealed specific adaptations of
S. aureus
to the keratinocytes and macrophages. Mapping the differentially activated proteins to biochemical pathways in the human cells with intracellular bacteria revealed cell-type-specific adaptations to bacterial challenges where THP-1 cells prioritized immune defenses, autophagic cell death, and inflammation. In contrast, HaCaT cells emphasized barrier integrity and immune activation. We also observe bacterial modulation of host processes and metabolic shifts. These findings offer valuable insights into the dynamics of
S. aureus
–host cell interactions, shedding light on modulating host immune responses to
S. aureus
, which could involve developing immunomodulatory therapies.

IMPORTANCE

This study uses a chemoproteomic approach to target active ATP-interacting proteins and examines the dynamic proteomic interactions between
Staphylococcus aureus
and human cell lines THP-1 and HaCaT. It uncovers the distinct responses of macrophages and keratinocytes during bacterial infection.
S. aureus
demonstrated a tailored response to the intracellular environment of each cell type and adaptation during exposure to professional and non-professional phagocytes. It also highlights strategies employed by
S. aureus
to persist within host cells. This study offers significant insights into the human cell response to
S. aureus
infection, illuminating the complex proteomic shifts that underlie the defense mechanisms of macrophages and keratinocytes. Notably, the study underscores the nuanced interplay between the host’s metabolic reprogramming and immune strategy, suggesting potential therapeutic targets for enhancing host defense and inhibiting bacterial survival. The findings enhance our understanding of host–pathogen interactions and can inform the development of targeted therapies against
S. aureus
infections.
Microbiological diagnosis of pleural infections: a comparative evaluation of a novel syndromic real-time PCR panel
Authors: Kommedal Øyvind , Eagan Tomas Mikal , Fløtten Øystein , Leegaard Truls Michael , Siljan William , Fardal Hilde , Bø Bjørnar , Grøvan Fredrik , Larssen Kjersti Wik , Kildahl-Andersen Arne , Hjetland Reidar , Tilseth Rune , Hareide Sølvi Kristine Øyen , Tellevik Marit , Dyrhovden Ruben
Published: April 2024

Current microbial diagnostics for pleural infections are insufficient. Studies using 16S targeted next-generation sequencing report that only 10%–16% of bacteria present are cultured and that 50%–78% of pleural fluids containing relevant microbial DNA remain culture negative. As a rapid diagnostic alternative suitable for clinical laboratories, we wanted to explore a PCR-based approach. Based on the identification of key pathogens, we developed a syndromic PCR panel for community-acquired pleural infections (CAPIs). This was a pragmatic PCR panel, meaning that it was not designed for detecting all possibly involved bacterial species but for confirming the diagnosis of CAPI, and for detecting bacteria that might influence choice of antimicrobial treatment. We evaluated the PCR panel on 109 confirmed CAPIs previously characterized using culture and 16S targeted next-generation sequencing. The PCR secured the diagnosis of CAPI in 107/109 (98.2%) and detected all present pathogens in 69/109 (63.3%). Culture secured the diagnosis in 54/109 (49.5%) and detected all pathogens in 31/109 (28.4%). Corresponding results for 16S targeted next-generation sequencing were 109/109 (100%) and 98/109 (89.9%). For bacterial species included in the PCR panel, PCR had a sensitivity of 99.5% (184/185), culture of 21.6% (40/185), and 16S targeted next-generation sequencing of 92.4% (171/185). None of the bacterial species present not covered by the PCR panel were judged to impact antimicrobial therapy. A syndromic PCR panel represents a rapid and sensitive alternative to current diagnostic approaches for the microbiological diagnosis of CAPI.

IMPORTANCE

Pleural empyema is a severe infection with high mortality and increasing incidence. Long hospital admissions and long courses of antimicrobial treatment drive healthcare and ecological costs. Current methods for microbiological diagnostics of pleural infections are inadequate. Recent studies using 16S targeted next-generation sequencing as a reference standard find culture to recover only 10%–16% of bacteria present and that 50%–78% of samples containing relevant bacterial DNA remain culture negative. To confirm the diagnosis of pleural infection and define optimal antimicrobial therapy while limiting unnecessary use of broad-spectrum antibiotics, there is a need for rapid and sensitive diagnostic approaches. PCR is a rapid method well suited for clinical laboratories. In this paper we show that a novel syndromic PCR panel can secure the diagnosis of pleural infection and detect all bacteria relevant for choice of antimicrobial treatment with a high sensitivity.
Ophiolite of the Buck Creek/Chunky Gal Mountain area, North Carolina, USA
Authors: Maliner-Colvin* Steven
Published: April 2024

The ophiolite of the Buck Creek and Chunky Gal Mountain areas (North Carolina, USA) consist of very high-temperature mafic and ultramafic units. These mafic and ultramafic rocks were once part of the oceanic lithosphere before being subducted and then thrust into continental rock by the Taconic orogeny, which took place during the Paleozoic era. The thrusting of these mafic and ultramafic rocks into nearby metasedimentary rock was controlled by the Chunky Gal thrust fault. Studies on this ophiolite were mainly petrological, geochemical, and structural in nature. The main rocks of interest within this area are dunite, metatroctolite, and amphibolite. The dunite mostly consists of olivine and minor chromite spinels. Hydrous altered dunite may also consist of antigorite, chlorite, talc, and anthophyllite. This dunite is associated with minor scattered lenses of metatroctolite. The metatroctolite is dominated by plagioclase and olivine, which have symplectites and/or coronas of prograde minerals such as pyroxene, spinel, and sapphirine. Some of this metatroctolite was altered via hydration into chlorite schist and edenite-margarite schist, some of which is corundum-bearing. The dunite and metatroctolite are separated from the surrounding metasedimentary units by the surrounding Chunky Gal Amphibolite. This amphibolite, whose protolith is basaltic/gabbroic, is dominated by hornblende and plagioclase.
Conditions of Recrystallization of Ores of the Ozernoe Polymetallic Deposit (Western Transbaikalia, Russia)
Authors: Damdinova L. B. , Damdinov B. B. , Vikentyev I. V. , Reutsky V. N.
Published: April 2024

The Ozernoe lead–zinc deposit is the largest in Russia in terms of zinc reserves. It has been established that primary layered–banded, massive and brecciated sulfide ores were subject to intensive post-ore deformation and recrystallization, which accompanied dynamic and contact metamorphism. The transformations are expressed in the increase in the size of mineral aggregates and formation of carbonate–quartz–sulfide veins and veinlets with different ratios of constituent minerals. Ore minerals in veins and veinlets are represented by sphalerite, galena, and pyrite in different proportions; chalcopyrite, pyrrhotite, arsenopyrite, and marcasite occur in smaller quantities; and Ag sulfides and sulfosols are rare. The vein minerals are quartz, siderite, and manganese siderite (oligonite); Ba-bearing muscovite (ellacherite) and chlorite are also present. It was established that recrystallization of ores occurred at elevated PT-parameters—up to 535°C and up to 2 kbar—in the presence of relatively highly concentrated fluid phase (salinity up to 21.5 wt % eq. NaCl). Ore transformations are mainly caused by processes of dynamometamorphism. There is still uncertainty both with the age of ore mineralization of the Ozernoe deposit and with the development time of metamorphic processes. This does not allow linking these processes with the stages of geodynamic evolution in the region.
Feasibility of application-based psychomotor vigilance testing to assess fatigue in doctors working night shifts and correlation with smartwatch assessed shift intensity
Authors: Weetman Stefan , Roche Matthew , Leckie Todd , Samuels Theophilus , Hodgson Luke
Published: April 2024

Objectives

To assess: (1) the feasibility of novel data collection methods (wearable technology and an application-based psychomotor vigilance test (PVT)), (2) the impact of night shift working on fatigue, both objective and perceived, for doctors working night shifts in acute hospital specialties and (3) the effects of shift intensity and naps obtained on participant fatigue.

Methods

We adopted an innovative, multimodal approach to data collection allowing assessment of objective and perceived measures of fatigue, in addition to markers of shift intensity. This comprised 5 min PVT for objective quantification of fatigue (via the validated, smartphone-based NASA PVT+ application), wearable electronic devices (Fitbit Versa2) for assessment of shift intensity (step counts and active minutes) and questionnaires to elicit perceptions of fatigue and shift intensity.

Results

Data was collected from 25 participants for a total of 145 night shifts. Objective fatigue (assessed by PVT performance) was significantly increased post night shift, with a PVT mean reaction time 257 ms pre shift versus 283 ms post shift (p<0.0001). However, differences in PVT pre and post shift were not affected by night shift intensity, nor breaks or naps taken on shift. Differences in psychomotor performance between doctors working in different specialties were also observed.

Conclusions

The data collection methods used were found to be feasible with good participant engagement. Findings support existing evidence that night shift working in healthcare workers is associated with fatigue, with psychomotor impairment observed post shift. Lower shift intensity and napping did not appear to mitigate this effect.
Rapid estimates of leaf litter chemistry using reflectance spectroscopy
Authors: Kothari Shan , Hobbie Sarah E. , Cavender-Bares Jeannine
Published: April 2024

Measuring the chemical traits of leaf litter is important for understanding plants’ influence on nutrient cycles, including through nutrient resorption and litter decomposition, but conventional leaf trait measurements are often destructive and labor-intensive. Here, we develop and evaluate the performance of partial least-squares regression models that use reflectance spectra of intact or ground leaves to estimate leaf litter traits, including carbon and nitrogen concentration, carbon fractions, and leaf mass per area (LMA). Our analyses included more than 300 samples of senesced foliage from 11 species of temperate trees, including both needleleaf and broadleaf species. Across all samples, we could predict each trait with moderate-to-high accuracy from both intact-leaf litter spectra (validation R2 = 0.543–0.941; %root mean squared error (RMSE) = 7.49–18.5) and ground-leaf litter spectra (validation R2 = 0.491–0.946; %RMSE = 7.00–19.5). Notably, intact-leaf spectra yielded better predictions of LMA. Our results support the feasibility of building models to estimate multiple chemical traits from leaf litter of a range of species. In particular, intact-leaf spectral models allow non-destructive trait estimation in a matter of seconds, which could enable researchers to measure the same leaves over time in studies of nutrient resorption.
Multiple herbicide-resistant kochia (Bassia scoparia) control in glufosinate-resistant canola
Authors: Torbiak Alysha T. , Blackshaw Robert E. , Brandt Randall N. , Hamman Bill , Geddes Charles M.
Published: April 2024

Multiple herbicide-resistant kochia ( Bassia scoparia (L.) A.J. Scott) has grown in prevalence in the canola ( Brassica napus L.) production region of North America. Glufosinate-resistant canola facilitates kochia management since glufosinate-resistant kochia is not known to occur. Field experiments were conducted from 2013 to 2015 in five environments near Lethbridge and Coalhurst, Alberta, to identify herbicide strategies targeting acetolactate synthase inhibitor-resistant kochia with and without glyphosate resistance in glufosinate-resistant canola. Sequential glufosinate treatments (500 g ai ha−1) postemergence (POST) caused excellent (≥90%) kochia control and biomass reduction across environments. Preplant (PP) carfentrazone + sulfentrazone (9 + 105 g ai ha−1) alone or followed by (fb) POST glufosinate (9 + 27 fb 500 or 9 + 105 fb 500 g ai ha−1) resulted in excellent kochia control in all environments tested. PP carfentrazone + sulfentrazone (9 + 53 g ai ha−1) alone, and a single POST treatment with glufosinate (500 or 590 g ai ha−1) alone or preceded by fall-applied ethalfluralin (1100 fb 500 g ai ha−1) with or without PP carfentrazone (1100 fb 9 fb 500 g ai ha−1) caused ≥80% kochia control and biomass reduction in all environments tested. However, treatments containing PP carfentrazone + sulfentrazone caused unacceptable canola injury or yield loss in at least one environment. In conclusion, single or sequential treatments of glufosinate POST managed multiple herbicide-resistant kochia effectively in canola. Layering fall-applied/PP ethalfluralin and/or PP carfentrazone with glufosinate POST may help alleviate resistance selection pressure placed on glufosinate in canola.
Quantum cosmology in teleparallel gravity with a boundary term
Authors: Amiri H. , Atazadeh K. , Hadi H.
Published: April 2024

We quantize a homogeneous and isotropic universe for two models of modified teleparallel gravity: one wherein an arbitrary function of the boundary term, namely B, is present in the action, and in the other model, a scalar field that is non-minimally coupled to both the torsion and boundary term. In this regard, we study exact solutions of both the classical and quantum frameworks by utilizing the corresponding Wheeler–DeWitt (WDW) equations of the models. To correspond to the comprehensive classical and quantum levels, in the second model, we propose an appropriate initial condition for the wave packets and observe that they closely adhere to the classical trajectories and reach their peak. We quantify this correspondence using the de Broglie–Bohm interpretation of quantum mechanics. According to this proposal, the classical and Bohmian trajectories coincide when the quantum potential vanishes along the Bohmian paths. Furthermore, we apply the de-parameterization technique to our model in the realm of the problem of time in quantum cosmological models based on the WDW equation, utilizing the global internal time denoted as $$\chi $$
χ
, which represents a scalar field.
Ginkgo biloba and Its Chemical Components in the Management of Alzheimer’s Disease
Authors: Peng Yong , Chen Quan , Xue Ya-Hui , Jin Hong , Liu Shu , Du Miao-Qiao , Yao Shun-Yu
Published: April 2024

The pathogenesis of Alzheimer’s disease (AD), a degenerative disease of the central nervous system, remains unclear. The main manifestations of AD include cognitive and behavioral disorders, neuropsychiatric symptoms, neuroinflammation, amyloid plaques, and neurofibrillary tangles. However, current drugs for AD once the dementia stage has been reached only treat symptoms and do not delay progression, and the research and development of targeted drugs for AD have reached a bottleneck. Thus, other treatment options are needed. Bioactive ingredients derived from plants are promising therapeutic agents. Specifically, Ginkgo biloba (Gb) extracts exert anti-oxidant, anticancer, neuroplastic, neurotransmitter-modulating, blood fluidity, and anti-inflammatory effects, offering alternative options in the treatment of cardiovascular, metabolic, and neurodegenerative diseases. The main chemical components of Gb include flavonoids, terpene lactones, proanthocyanidins, organic acids, polysaccharides, and amino acids. Gb and its extracts have shown remarkable therapeutic effects on various neurodegenerative diseases, including AD, with few adverse reactions. Thus, high-quality Gb extracts are a well-established treatment option for AD. In this review, we summarize the insights derived from traditional Chinese medicine, experimental models, and emerging clinical trials on the role of Gb and its chemical components in the treatment of the main clinical manifestations of AD.
Thermal Safe Power Constrained Dynamic Mapping for Heterogeneous Multicore System
Authors: Wang Ling , Wei Huayong , Qi Yun , Li Jianhua
Published: April 2024

Heterogeneous multicore system could provide high flexibility for applications through integrating different types of cores. As the number of cores increases, more and more transistors are integrated which could lead to the rise of chip temperature, thus have a negative impact on the system performance. At present, the typical method to tackle this problem is dynamic voltage and frequency scaling (DVFS) which reduces the voltage and frequency to achieve cooling. However, DVFS will make the heterogeneous multicore system unable to take full advantage of its performance. This paper proposes a dynamic mapping method called TspDM which maximizes the system performance target under the premise of satisfying the temperature safety power. TspDM exploits the runtime performance counters of running threads to dynamically adjust thread mapping. Specifically, a lightweight Artificial Neural Network (ANN) model is proposed to obtain the thread-to-core type mapping when a remapping process is activated. Subsequently, TspDM determines the specific core locations of threads according to the number of threads mapped to a certain core type and the thermal safety power computation. The experimental results show that the proposed method is 21% better than that of PCMig while ensuring the thermal safety of heterogeneous platform. In addition, TspDM outperforms recent performance constrained and power constrained literature in terms of system throughput.
Advances in Explainable, Fair, and Trustworthy AI
Authors: Islam Sheikh Rabiul , Russell Ingrid , Eberle William , Talbert Douglas , Hasan Md Golam Moula Mehedi
Published: April 2024

This special issue encapsulates the multifaceted landscape of contemporary challenges and innovations in Artificial Intelligence (AI) and Machine Learning (ML), with a particular focus on issues related to explainability, fairness, and trustworthiness. The exploration begins with the computational intricacies of understanding and explaining the behavior of binary neurons within neural networks. Simultaneously, ethical dimensions in AI are scrutinized, emphasizing the nuanced considerations required in defining autonomous ethical agents. The pursuit of fairness is exemplified through frameworks and methodologies in machine learning, addressing biases and promoting trust, particularly in predictive policing systems. Human-agent interaction dynamics are elucidated, revealing the nuanced relationship between task allocation, performance, and user satisfaction. The imperative of interpretability in complex predictive models is highlighted, emphasizing a query-driven methodology. Lastly, in the context of trauma triage, the study underscores the delicate trade-off between model accuracy and practitioner-friendly interpretability, introducing innovative strategies to address biases and trust-related metrics.
On Bounding the Behavior of Neurons
Authors: Borowski Richard , Choi Arthur
Published: April 2024

A neuron with binary inputs and a binary output represents a Boolean function. Our goal is to extract this Boolean function into a tractable representation that will facilitate the explanation and formal verification of a neuron’s behavior. Unfortunately, extracting a neuron’s Boolean function is in general an NP-hard problem. However, it was recently shown that prime implicants of this Boolean function can be enumerated efficiently, with only polynomial time delay. Building on this result, we first propose a best-first search algorithm that is able to incrementally tighten the inner and outer bounds of a neuron’s Boolean function. Second, we show that these bounds correspond to truncated prime-implicant covers of the Boolean function. Next, we show how these bounds can be propagated in an elementary class of neural networks. Finally, we provide case studies that highlight our ability to bound the behavior of neurons.
Predictive Policing: A Fairness-aware Approach
Authors: Downey Ava , Islam Sheikh Rabiul , Sarker Md Kamruzzman
Published: April 2024

As Artificial Intelligence (AI) systems become increasingly embedded in our daily lives, it is of utmost importance to ensure that they are both fair and reliable. Regrettably, this is not always the case for predictive policing systems, as evidence shows biases based on age, race, and sex, leading to wrongful identifications of individuals as potential criminals. Given the existing criticism of the system’s unjust treatment of minority groups, it becomes essential to address and mitigate this concerning trend. This study delved into the infusion of domain knowledge in the predictive policing system, aiming to minimize prevailing fairness issues. The experimental results indicate a considerable increase in fairness across all metrics for all protected classes, thus fostering greater trust in the predictive policing system by reducing the unfair treatment of individuals.
Assessing and Addressing Model Trustworthiness Trade-offs in Trauma Triage
Authors: Talbert Douglas A. , Phillips Katherine L. , Brown Katherine E. , Talbert Steve
Published: April 2024

Trauma triage occurs in suboptimal environments for making consequential decisions. Published triage studies demonstrate the extremes of the complexity/accuracy trade-off, either studying simple models with poor accuracy or very complex models with accuracies nearing published goals. Using a Level I Trauma Center’s registry cases (n = 50 644), this study describes, uses, and derives observations from a methodology to more thoroughly examine this trade-off. This or similar methods can provide the insight needed for practitioners to balance understandability with accuracy. Additionally, this study incorporates an evaluation of group-based fairness into this trade-off analysis to provide an additional dimension of insight into model selection. Lastly, this paper proposes and analyzes a multi-model approach to mitigating trust-related trade-offs. The experiments allow us to draw several conclusions regarding the machine learning models in the domain of trauma triage and demonstrate the value of our trade-off analysis to provide insight into choices regarding model complexity, model accuracy, and model fairness.
Forecasting Volatility in the EUR/USD Exchange Rate Utilizing Fractional Autoregressive Models
Authors: Benzid Lamia , Saâdaoui Foued
Published: April 2024

This study investigates the volatility of the Euro-to-US Dollar exchange rate, specifically focusing on identifying long-memory characteristics. Through the analysis of daily data spanning from January 1, 2018, to January 10, 2023, the study uncovers a robust long-memory feature. Supporting this exploration, the study endorses the use of sophisticated models such as Fractionally Integrated Generalized Autoregressive Conditionally Heteroskedastic (FIGARCH) and Hyperbolic Generalized Autoregressive Conditionally Heteroskedastic (HYGARCH), incorporating both student and skewed student innovation distributions. The results underscore the superior performance of FIGARCH and HYGARCH models, particularly when coupled with a skewed student distribution. This collaborative approach enhances the predictability of crucial financial metrics, including Value at Risk (VaR) and Expected Shortfall (ESF), for both long and short trading positions. Significantly, the FIGARCH model, when utilizing a skewed student distribution, demonstrates exceptional predictive power. This outcome challenges the efficient market hypothesis and suggests the potential for generating outstanding returns. In light of these findings, this research contributes valuable insights for comprehending and navigating the intricacies of the Euro-to-US Dollar exchange rate, providing a forward-looking perspective for financial practitioners and researchers alike.
A stochastic epidemic model with individual heterogeneity and mean-reverting Ornstein–Uhlenbeck process
Authors: Song Jiacheng , Lv Wangyong , Yang Xiaofeng , Zhang Ce
Published: April 2024

The objective of this study is to investigate a stochastic SIR epidemic model incorporating a mean-reverting Ornstein–Uhlenbeck process and individual heterogeneity. Initially, we establish the global existence and positivity of a solution within the model through the application of Lyapunov functions. Subsequently, we delve into the dynamical behavior of the SIR model. Our research reveals that increased noise intensity, a slower reversion rate, and positive individual behavior collaboratively contribute to the mitigation of infection outbreaks.
Optimal control and bifurcation analysis of a delayed fractional-order epidemic model for the COVID-19 pandemic
Authors: Xu Conghui , Yu Yongguang , Ren Guojian , Si Xinhui
Published: April 2024

In this paper, a delayed fractional-order epidemic model with general incidence rate and incubation period is proposed for the Corona Virus Disease 2019 (COVID-19) pandemic. The corresponding sufficient conditions are established to analyze the existence and stability of disease-free equilibrium and endemic equilibrium of the proposed model. The conditions for the existence of Hopf bifurcation are obtained by selecting the time delay as the bifurcation parameter. The control strategies for the COVID-19 pandemic are designed, and the corresponding delay fractional order optimal control problem (DFOCP) is analyzed based on the generalized Euler–Lagrange equation. The parameters of the model are identified based on the data of multiple types of the COVID-19 pandemic. Further, the effectiveness of the model in describing the trend of the COVID-19 pandemic is verified. Based on the results of parameter identification, the influence of incubation period on the COVID-19 pandemic is discussed. The forward–backward sweep method (FBSM) is adopted to numerically solve DFOCP, and the control effects under different control measures are analyzed.
Spatial patterns of a reaction–diffusion population system with cross-diffusion and habitat complexity
Authors: Li Weiyu , Li Yanfeng , Yang Ruizhi
Published: April 2024

In this paper, a population system with cross-diffusion and habitat complexity is selected as study object. We investigate that how cross-diffusion and habitat complexity destabilize the otherwise stable periodic solutions of the ODEs to generate the new abundant spatial Turing patterns. By utilizing the local Hopf bifurcation theorem and perturbation theory, we establish a formula to determine the Turing instability of periodic solutions of the population system with cross-diffusion and habitat complexity. Finally, numerical simulations are performed to verify theoretical analysis, simultaneously, we verify the formation process of spatial Turing patterns when the cross-diffusion coefficients and habitat complexity change.
Complex dynamics of a discrete-time Leslie–Gower predator–prey system with herd behavior and slow–fast effect on predator population
Authors: Tahir Naheed , Ahmed Rizwan , Shah Nehad Ali
Published: April 2024

This work examines a discrete Leslie–Gower predator–prey system with herd behavior, focusing on the influence of the slow–fast effect on predator dynamics. We analyze the presence and stability of fixed points, investigating period-doubling and Neimark–Sacker bifurcations at the positive fixed point. A hybrid control technique is implemented to successfully handle chaotic dynamics. Numerical simulations validate the theoretical findings, supporting our analysis. The parameter [Formula: see text] in the predator–prey system has a significant impact on system dynamics due to the slow–fast effect it represents. A stable positive fixed point signifies a lasting and balanced coexistence of predator and prey populations within a certain [Formula: see text] interval. Deviation from this range results in period-doubling and Neimark–Sacker bifurcations, increasing both unpredictability and instability in the system.
A new COVID-19 variant Kraken: The modeling and analysis of the XBB.1.5 with treatment and immunization control factors
Authors: Singh Jaskirat Pal , Kumar Sachin , Gómez-Aguilar J. F.
Published: April 2024

Recent SARS-CoV-2 XBB and BQ subvariants exhibit noticeably enhanced resistance to neutralizing antibodies, including in those persons who are vaccinated and have had breakthrough Omicron infection or who have received the bivalent mRNA booster. Nonlinear dynamics is an intriguing technique for explaining the dynamical behaviors of COVID-19 illness. The goal of this study is to create a novel compartment mathematical model that takes into account populations that have received immunizations against new COVID-19 variants, particularly Omicron. The foundational characteristics of the model, including boundedness and positivity of solutions are established. Following that, the reproduction number has been used to illustrate the equilibrium analysis of steady states. The numerical design of the model has been introduced to assess how various control regimes affect COVID-19 dynamics. All control techniques have been found to have a positive effect on COVID-19 reduction.
Theoretical Characterization of Liquid Crystalline Mesophases: Analysis with Its Link to Phase Transition Temperature
Authors: Pradhan Anup Kumar , Praveen P. Lakshmi
Published: April 2024

An estimation of category of liquid crystalline (LC) phase based on composite lattices using linear algebra and lattice parameters is proposed. The vector space in three dimensions [Formula: see text] is dissolved in the initial phase into two dimensions [Formula: see text], and one dimension [Formula: see text] subspace in a 3D crystal, respectively, rotate and/or slide between each other during thermal process. In linear algebra, this state is designated as [Formula: see text] composite subspaces of vector. As per linear algebraic approach, [Formula: see text] is not identical with 3D, and the mathematical sign ⊕ indicates addition directly. The phase is represented as [Formula: see text] lattice-based composite phase. Apart from the [Formula: see text] phase, two more mixed phases with [Formula: see text] and [Formula: see text] may also be theoretically studied using linear algebra. Finally, the category of phase is proposed to be analyzed with link to its transition temperature.
Dealloyed Pt74Ni26 and Pt26Ni74 Electrodeposited Thin Film Electrocatalysts for Oxygen Reduction
Authors: Hangarter C. M. , Rus E. D. , Liu Y. , Shin J. W. , Oleshko V. P. , Ro H. W. , Composto R. J. , Soles C. , Dura J. A. , Stafford G. , Bendersky L. A. , Moffat T. P.
Published: April 2024

Electrodeposition and microstructure of thin films close to Pt75Ni25 and Pt25Ni75 stoichiometry are described and their catalytic oxygen reduction reaction performance, dealloying, and strain evolution detailed. Multiple techniques are used to characterize the morphology, crystalline structure, and chemical homogeneity of the as-deposited and dealloyed films. A fine-scale percolating network of lower-density regions is evident in the as-deposited Pt74Ni26 films while the as-deposited Pt26Ni74 films are more homogenous and compact. Electrodeposition is accompanied by development of significant in-plane tensile stress that increases at more negative growth potentials to reach 1.28 GPa for as-deposited Pt26Ni74. Dealloying of the near-surface regions of Pt74Ni26 is accompanied by limited expansion or opening of the low-density regions while massive dealloying of the highly stressed Pt26Ni74 results in shrinkage, extensive cracking, and formation of a bi-continuous nanoporous structure with an average pore diameter close to 5 nm. Relative to electrodeposited Pt, the alloy films exhibit enhanced area-specific oxygen reduction reaction activity (at 0.95 V vs RHE, iR-corrected) that amounts to a factor of 3.4 for dealloyed Pt74Ni26 and 5.1 for dealloyed Pt26Ni74 while the Pt-based mass activity increased by a factor of 5.1 and 12.3, for the respective films.
Phosphorylation of AS160-serine 704 is not essential for exercise-increase in insulin-stimulated glucose uptake by skeletal muscles from female or male rats
Authors: Wang Haiyan , Kwak Seong Eun , Zheng Amy , Arias Edward B. , Pan Xiufang , Duan Dongsheng , Cartee Gregory D.
Published: April 2024

The current study evaluated the role of Akt substrate of 160 kDa (AS160) phosphorylation on Ser704 in increased insulin-stimulated glucose uptake by skeletal muscle after exercise. Adeno-associated virus vectors were engineered to express either wild-type-AS160 or AS160 mutated so that it could not be phosphorylated on Ser704 in paired muscles from AS160-knockout rats. The results demonstrated that AS160 phosphorylation on Ser704 was not essential for exercise-induced elevation in insulin-stimulated glucose uptake by rats of either sex.
Optimal Operation of Cogeneration Power Plant Integrated with Solar Photovoltaics Using DLS‐WMA and ANN
Authors: Reddy Butukuri Koti , Giri Nimay Chandra , Yemula Pradeep Kumar , Agyekum Ephraim Bonah , Arya Yogendra
Published: April 2024

Focusing on mitigating global challenges arising from hydrocarbon‐based sources, the integration of cogeneration power plants with solar photovoltaics offers a viable solution. The intermittent nature of renewable resources presents a challenge to the consistent performance of cogeneration systems. To address these issues, this work introduces a novel framework for integrating cogeneration power plants (CGPPs) with solar photovoltaic systems. The key innovation of this research lies in its dual‐algorithm approach that seamlessly blends cogeneration power plants with solar photovoltaic. This study proposed an integrated approach, employing the Derivative Log Sigmoid‐Woodpecker Mating Algorithm (DLS‐WMA) and Optimized Artificial Neural Networks (O‐ANN), to combine cogeneration power plants with solar photovoltaics in industrial distribution systems. The methodology is aimed at achieving a cost‐effective, efficient system design, enhancing the efficiency of cogeneration power plants, and introducing energy storage batteries for uninterrupted power generation under diverse atmospheric conditions and loads. Additionally, the proposed system includes rechargeable batteries for energy storage to support critical services when the solar plant is offline and the CGPP cannot meet the power demand. The industrial system’s photovoltaic component is tuned using the DLS‐WMA for cost minimization and O‐ANN for solar irradiance prediction, ensuring continuous power flow by optimizing both the photovoltaic system and the cogeneration power plant (CGPP) system. Real‐time datasets are used to compare the results obtained by this new approach with those of the previous state‐of‐the‐art algorithms. The error with O‐ANN prediction is 1.2%, compared to 4.1% with the existing WMA‐ANN technique, while the cost‐benefit with DLS‐WMA shows a 9% improvement over the WMA‐ANN technique. The experimental outcomes demonstrate the efficiency of this new approach. Collaboration with industry stakeholders and policymakers is crucial for the large‐scale deployment of this system, facilitating the adoption of sustainable energy practices in industrial distribution systems.
Anxiolytic and Antidepressant Effect of Phaseolus vulgaris on Animal Models
Authors: Munawwar Rabia , Sarfaraz Sana , Ikram Rahila , Zehra Talat , Anser Humaira , Ali Huma
Published: April 2024

An experimental study was conducted using rodents at different doses to evaluate the effect of Phaseolus vulgaris (red beans) on cage crossing, head dip, open field, elevated plus maze, and light and dark apparatus for anxiety and forced swim test for depression. The corticosterone level and histopathological evaluation was also done to correlate the antidepressive impact of the red beans. The study also identified the components responsible for the effect using GCMS. Based on the findings, red beans could be a potential non-pharmacological therapy for mild to moderate depressive patients. The anxiety model was conducted on mice weighing 20–25 gms. Group I was taken as control, group II as 500 mg/kg and group III as administered 1000 mg/kg. The tests were performed on 0th, 7th, 15th, 30th, 45th, and 60th day. The depression model research was conducted on albino rats weighing between 180 and 200 g, divided into four groups: a control group, a 500 mg/kg Phaseolus vulgaris group, a 1000 mg/kg Phaseolus vulgaris group, and a standard group treated with fluoxetine. The forced swimming test was performed on days 0, 7, 15, 30, 45, and 60, after which histopathological evaluations were conducted and blood samples were taken to assess corticosterone levels. GCMS was used to identify the constituents present in red beans, while optical spectroscopy was used to detect minerals and ions. Results showed that both doses of Phaseolus vulgaris possess anxiolytic effect and increased the struggling time of rats in depression model significantly, with the 1000 mg/kg dose showing more significant results than the 500 mg/kg dose. The GCMS results identified the presence of erucic acid, which causes an increase in α-amylase, thus reducing depression. Optical spectroscopy also showed that red beans contain zinc, which may increase BDNF and help in treating depression.
Experimental Study of Macro‐ and Micro‐Scopic Damage in Red Sandstone under Dry and Wet Cycling
Authors: Chen Xiangmei , Ren Yongqiang , Tang Baoli , Li Guojin , Zhang Feitian , Liu Yunfei
Published: April 2024

The high‐strength red sandstone in its natural state is subjected to significant strength deterioration under alternating wet and dry conditions, which can cause many catastrophic problems in the process of engineering construction. It is important to deeply understand the damage mechanism of red sandstone under the action of dry and wet cycles. Therefore, this paper explores the mechanism of red sandstone’s uniaxial deformation and failure through indoor uniaxial compression tests, studies the damage to the microstructure of red sandstone under wet–dry cycles using scanning electron microscopy, and establishes a damage variable based on fractal dimension. The results show that with the increase of wet–dry cycles, the peak stress of red sandstone shows a decreasing trend, and the minimum peak stress is 17.3 MPa, which is a 46.62% decrease compared to the sample with 0 wet–dry cycles. During the wet–dry cycle process, there are four deformation characteristics of red sandstone samples, namely, crack compression, crack extension, progressive fracture, and crack penetration. SEM images show that the porosity, pore area, and fractal dimension all show a nonlinear increase, and the maximum damage variable can reach 10.41%. The research results can provide guidance for engineering design and slope failure mechanism research in red sandstone areas.