Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural controllability of temporal networks

The control of complex systems is an ongoing challenge of complexity research. Recent advances using concepts of structural control deduce a wide range of control related properties from the network representation of complex systems. Here, we examine the controllability of systems for which the timescale of the dynamics we control and the timescale of changes in the network are comparable. We provide analytical and computational tools to study controllability based on temporal network characteristics. We apply these results to investigate the controllable subnetwork using a single input. For a generic class of model networks, we witness a phase transition depending upon the density of the interactions, describing the emergence of a giant controllable subspace. We show the existence of the two phases in real-world networks. Using randomization procedures, we find that the overall activity and the degree distribution of the underlying network are the main features influencing controllability.
The Energy Equation for the Navier–Stokes System

It is shown that a weak solution of the Navier–Stokes equations lying in a space $L^q (0,T;L^p )$, where $1/p+1/q\leqq 1/2$ and $p \geqq 4$, satisfies an energy equality rather than the usual energy inequality. This is true regardless of the dimension of the underlying space.
The electronic structure of CeCoIn5 from angle-resolved photoemission spectroscopy II: Hybridization effects

We have investigated the low-energy electronic structure of the heavy fermion superconductor CeCoIn5 by angle-resolved photoemission. We focus on the dispersion and the peak width of the prominent quasi-two-dimensional Fermi surface sheet at the corner of the Brillouin zone as a function of temperature along certain k-directions with a photon energy of hn = 100 eV. We find slight changes of the Fermi vector and an anomalous broadening of the peak width when the Fermi energy is approached. Additionally we performed resonant ARPES experiments with hn = 121 eV. A flat f-derived band is observed with a distinct temperature dependence and a k-dependent spectral weight. These results, including both off- and on-resonant measurements, fit qualitatively to a two level mixing model derived from the Periodic Anderson Model.
Electron source at the outer boundary of the radiation belts: Storm time case

We examine the strength of the electron source at the outer boundary of the radiation belts using multisatellite observations from Time History of Events and Macroscale Interactions during Substorms during one moderate geomagnetic storm. The electron phase space density (PSD) as a function of the first adiabatic invariant for an equatorially mirroring population over a broad energy range is used to determine the source strength. It is found that the source strength from dipolarization at the outer boundary of the radiation belts during this storm period is well above the observed phase space densities of relativistic electrons inside the outer radiation belt, indicating that the inward radial transport can be a potential source of the relativistic electrons within the radiation belts, even in the strong pitch angle diffusion limit.
Nine New Pregnane Glycosides from the Cultivated Medicinal Plant Marsdenia tenacissima

The ethnobotanical plant Marsdenia tenacissima has been used for hundreds of years for Dai people in Yunnan Province, China. Previously, chemical investigations on this plant have revealed that pregnane glycosides were the main biological constituents. Nine new pregnane glycosides, marsdeosides A–I (1–9), were isolated from cultivated dried stems of the medicinal plant Marsdenia tenacissima in this study. The structures were analyzed by extensive spectroscopic analysis, including 1D, 2D NMR, HRESIMS, and IR spectroscopic analysis. The absolute configurations of the sugar moieties were identified by comparing the Rf values and specific optical rotations with those of the commercially available standard samples and the data reported in the literature. Marsdeosides A (1) featured an unusual 8,14-seco-pregnane skeleton. Compounds 1, 8, and 9 showed activity against nitric oxide production in lipopolysaccharide-activated macrophage RAW264.7, with IC50 values of 37.5, 38.8, and 42.8 μM (L-NMMA was used as a positive control, IC50 39.3 μM), respectively. This study puts the knowledge of the chemical profile of the botanical plant M. tenacissima one step forward and, thereby, promotes the sustainable utilization of the resources of traditional folk medicinal plants.
An assessment of the average nodal volume formulation for the analysis of nearly incompressible solids under finite strains

This paper provides an assessment of the average nodal volume methodology originally proposed by Bonet and Burton (Commun. Numer. Meth. Engng. 1998; 14:437–449) for the analysis of finitely strained nearly incompressible solids. An implicit version of the average nodal pressure formulation is derived by re-casting the original concept in terms of average nodal volume change ratio within the framework of the F-bar method proposed by de Souza Neto et al. (Int. J. Solids Struct. 1996; 33: 3277–3296). In this context, a linear triangle for implicit plane strain and axisymmetric analysis of nearly incompressible solids under finite strains is obtained. An exact expression for the corresponding element stiffness matrix is presented. This allows the use of the full Newton–Raphson algorithm, ensuring quadratic rates of asymptotic convergence in the global equilibrium iterations. The performance of the procedure is thoroughly assessed by means of numerical examples. The results show that the nodal averaging technique substantially reduces the volumetric locking tendency of the linear triangle and allows an accurate prediction of deformed shapes and reaction forces in situations of practical interest. However, the formulation is found to produce considerable checkerboard-type hydrostatic pressure fluctuations which poses severe limitations on its range of applicability. Copyright © 2004 John Wiley & Sons, Ltd.
Comparative Analysis of Qualitative and Bioactive Compounds of Whole and Refined Flours in Durum Wheat Grains with Different Year of Release and Yield Potential

Durum wheat varieties are important sources of nutrients and provide remarkable amounts of phytochemicals. Especially, phenolics, which are mostly located in external layers of grains, have recently gained increased interest due to their high antioxidant power. This study aimed to evaluate the differences in the quality traits and phenolic compounds’ concentration (e.g., phenolic acids) of different durum wheat genotypes, namely four Italian durum wheat cultivars and a USA elite variety, in relation to their yield potential and year of release. Phenolic acids were extracted both from wholemeal flour and semolina and analysed through HPLC-DAD analysis. Ferulic acid was the most represented phenolic acid, both in the wholemeal flour (438.3 µg g−1 dry matter) and in semolina (57.6 µg g−1 dry matter) across all cultivars, followed by p-coumaric acid, sinapic acid, vanillin, vanillic acid, syringic acid, and p-hydroxybenzoic acid. Among the cultivars, Cappelli showed the highest phenolic acid content, whilst Kronos had the lowest one. Negative correlations occurred between some phenolic acids and morphological and yield-related traits, especially for Nadif and Sfinge varieties. On the contrary, durum wheat genotypes with low yield potential such as Cappelli accumulated higher concentrations of phenolic acids under the same growing conditions, thereby significantly contributing to the health-promoting purposes.
Impact of finite temperatures and correlations on the anomalous Hall conductivity from ab initio theory

Finite-temperature effects in the first-principles calculations of electronic transport up to now include almost exclusively only electronic temperatures by means of the Fermi-distribution function neglecting the influence of lattice vibrations. Here, employing the linear response Kubo formalism as implemented in a fully relativistic multiple-scattering Korringa–Kohn–Rostoker Green function method a systematic first-principles study of the anomalous Hall conductivity (AHC) of the 3d-transition metals Fe, Co and Ni is presented. It is shown that the inclusion of both correlations and thermal lattice vibrations is needed to give a material-specific description of the AHC in transition metals. The employed general framework will allow a first-principles description of other transverse transport phenomena treating correlations, finite temperatures and disorder on the same footing, giving valuable insights for experiments.
Modelling collective cell behaviour

The classical mean-field approach to modelling biological systems makes a number of simplifying assumptions which typically lead to coupled systems of reaction-diffusion partial differential equations. While these models have been very useful in allowing us to gain important insights into the behaviour of many biological systems, recent experimental advances in our ability to track and quantify cell behaviour now allow us to build more realistic models which relax some of the assumptions previously made. This brief review aims to illustrate the type of models obtained using this approach.
Simulating Probability Distributions in the Coalescent

Abstract We describe some computational algorithms for computing probability distributions for sample configurations from the finite-sites models in population genetics. One particular interest is the development of computational methods for estimating substitution rates for DNA sequence data using likelihood techniques. The approach uses a recursion satisfied by the sampling probabilities to construct a Markov chain with a set of absorbing states in such a way that the required sampling distribution is the mean of a functional of the process up to the absorption time. This provides a conceptually simple framework for simulating the likelihood of the data for a set of parameter values. The method is particularly attractive in practice: it is simple to program and can be extended to cover other features of interest such as the infinitely-many-sites process, recombination, selection, and variable population size.
Combining Historical and Randomized Controls for Assessing Trends in Proportions

Abstract A statistical method for incorporating historical control data in the analysis of proportions is proposed and illustrated. The method has as its extremes logistic regressions completely pooling and completely ignoring historical controls. The degree of pooling used is determined by the variability from experiment to experiment in the control incidences. The fit of historical control groups to an assumed normal logistic model is assessed using probability plotting techniques. Monte Carlo studies evaluate the adequacy of the asymptotic approximation used. Sensitivity analyses show that results are insensitive to alternative priors. The method is applied to several sets of tumor data from animal experiments.
Olfaction and Anxiety Are Differently Associated in Men and Women in Cognitive Physiological and Pathological Aging

Olfactory and affective factors are associated in a complex way, likely due to partial overlap in brain regions involved. Although the role of olfaction in disorders such as Parkinson Disease (PD) is documented, less clear is the association between olfaction and psychological symptoms, such as anxiety, in Mild Cognitive Impairment (MCI) and elderly cognitively healthy controls (HCs). Also, the role of sex differences in olfaction and psychological symptoms in healthy and pathological aging is poorly understood.
Evolutionary Optimization of an Ice Accretion Forecasting System

The ability to model and forecast accretion of ice on structures is very important for many industrial sectors. For example, studies conducted by the power transmission industry indicate that the majority of failures are caused by icing on overhead conductors and other components of power networks. This paper presents an extension to the ice accretion forecasting system (IAFS) that is comprised of a numerical weather prediction model, a precipitation-type algorithm, and an ice accretion model. To optimize the performance of IAFS, the parameters of the precipitation-type algorithm are estimated using a genetic algorithm. The system is developed by hindcasting a well-documented freezing-rain event and calibrated using four additional ice storms. Subsequently, the system is tested using three independent storms. The results show a significant improvement in consistency, accuracy, and skill of IAFS. The methodology described in this contribution is not limited to ice accretion modeling—it provides a general approach for setting operational parameters of data-processing algorithms to achieve interoperability of numerical weather prediction models with add-on applications based on empirical observations.
The Hochschild cohomology ring modulo nilpotence of a stacked monomial algebra

This paper studies the Hochschild cohomology of finite-dimensional monomial algebras. If Λ = KQ/I with I an admissible monomial ideal, then we give sufficient conditions for the existence of an embedding of K[x1, . , xr]/〈xaxb for a 6= b〉 into the Hochschild cohomology ring HH∗(Λ). We also introduce stacked algebras, a new class of monomial algebras which includes Koszul and D-Koszul monomial algebras. If Λ is a stacked algebra, we prove that HH∗(Λ)/N ∼= K[x1, . , xr]/〈xaxb for a 6= b〉, where N is the ideal in HH∗(Λ) generated by the homogeneous nilpotent elements. In particular, this shows that the Hochschild cohomology ring of Λ modulo nilpotence is finitely generated as an algebra. Introduction. Let K be a field and let Λ = KQ/I be a finite-dimensional K-algebra where Q is a quiver and I is an admissible ideal. We assume that Λ is a monomial algebra, that is, the ideal I is generated by a finite set of paths ̺. We take the set ̺ to be a minimal generating set for I. The Hochschild cohomology ring HH(Λ) is given by HH(Λ) = Ext∗Λe(Λ, Λ) = ⊕
Fueling the flames of colon cancer – does CRP play a direct pro-inflammatory role?

Background Systemic inflammation, diagnostically ascribed by measuring serum levels of the acute phase reactant C-reactive protein (CRP), has consistently been correlated with poor outcomes across cancer types. CRP exists in two structurally and functionally distinct isoforms, circulating pentameric CRP (pCRP) and the highly pro-inflammatory monomeric isoform (mCRP). The aim of this pilot study was to map the pattern of mCRP distribution in a previously immunologically well-defined colon cancer (CC) cohort and explore possible functional roles of mCRP within the tumor microenvironment (TME). Methods Formalin-fixed, paraffin-embedded (FFPE) tissue samples from 43 stage II and III CC patients, including 20 patients with serum CRP 0-1 mg/L and 23 patients with serum CRP >30 mg/L were immunohistochemically (IHC) stained with a conformation-specific mCRP antibody and selected immune and stromal markers. A digital analysis algorithm was developed for evaluating mCRP distribution within the primary tumors and adjacent normal colon mucosa. Results mCRP was abundantly present within tumors from patients with high serum CRP (>30 mg/L) diagnostically interpreted as being systemically inflamed, whereas patients with CRP 0-1 mg/L exhibited only modest mCRP positivity (median mCRP per area 5.07‰ (95%CI:1.32-6.85) vs. 0.02‰ (95%CI:0.01-0.04), p<0.001). Similarly, tissue-expressed mCRP correlated strongly with circulating pCRP (Spearman correlation 0.81, p<0.001). Importantly, mCRP was detected exclusively within tumors, whereas adjacent normal colon mucosa showed no mCRP expression. Double IHC staining revealed colocalization of mCRP with endothelial cells and neutrophils. Intriguingly, some tumor cells also colocalized with mCRP, suggesting a direct interaction or mCRP expression by the tumor itself. Conclusion Our data show that the pro-inflammatory mCRP isoform is expressed in the TME of CC, primarily in patients with high systemic pCRP values. This strengthens the hypothesis that CRP might not only be an inflammatory marker but also an active mediator within tumors.
Rural implementation of the perioperative surgical home: A case-control study

BACKGROUND Perioperative surgical home (PSH) is a novel patient-centric surgical system developed by American Society of Anesthesiologist to improve outcomes and patient satisfaction. PSH has proven success in large urban health centers by reducing surgery cancellation, operating room time, length of stay (LOS), and readmission rates. Yet, only limited studies have assessed the impact of PSH on surgical outcomes in rural areas. AIM To evaluate the newly implemented PSH system at a community hospital by comparing the surgical outcomes using a longitudinal case-control study. METHODS The research study was conducted at an 83-bed, licensed level-III trauma rural community hospital. A total of 3096 TJR procedures were collected retrospectively between January 2016 and December 2021 and were categorized as PSH and non-PSH cohorts (n = 2305). To evaluate the importance of PSH in the rural surgical system, a case-control study was performed to compare TJR surgical outcomes (LOS, discharge disposition, and 90-d readmission) of the PSH cohort against two control cohorts [Control-1 PSH (C1-PSH) (n = 1413) and Control-2 PSH (C2-PSH) (n = 892)]. Statistical tests including Chi-square test or Fischer’s exact test were performed for categorical variables and Mann-Whitney test or Student’s t-test were performed for continuous variables. The general linear models (Poisson regression and binomial logistic regression) were performed to fit adjusted models. RESULTS The LOS was significantly shorter in PSH cohort compared to two control cohorts (median PSH = 34 h, C1-PSH = 53 h, C2-PSH = 35 h) (P value < 0.05). Similarly, the PSH cohort had lower percentages of discharges to other facilities (PSH = 3.5%, C1-PSH = 15.5%, C2-PSH = 6.7%) (P value < 0.05). There was no statistical difference observed in 90-d readmission between control and PSH cohorts. However, the PSH implementation reduced the 90-d readmission percentage (PSH = 4.7%, C1-PSH = 6.1%, C2-PSH = 3.6%) lower than the national average 30-d readmission percentage which is 5.5%. The PSH system was effectively established at the rural community hospital with the help of team-based coordinated multi-disciplinary clinicians or physician co-management. The elements of PSH including preoperative assessment, patient education and optimization, and longitudinal digital engagement were vital for improving the TJR surgical outcomes at the community hospital. CONCLUSION Implementation of the PSH system in a rural community hospital reduced LOS, increased direct-to-home discharge, and reduced 90-d readmission percentages.
Prevalence and associated factors of medication adherence among infertile women undergoing frozen-thawed embryo transfer cycle: A cross-sectional study

Objective: This study aimed to explore the prevalence and associated factors of medication adherence among infertile women undergoing frozen-thawed embryo transfer (FET) cycle. Methods: A cross-sectional study was conducted with 556 infertile women undergoing FET cycle in total. The Self-efficacy for Appropriate Medication Use Scale (SEAMS), Herth Hope Index (HHI) scale, and Social Support Rating Scale (SSRS) were used to evaluate the patients. Data were described by univariate and multivariate analyses. Logistic regression method was performed to analyse the factors potentially associated with medication adherence. Results: The average score of Self-efficacy for Appropriate Medication Use Scale (SEAMS) was 30.38 ± 6.65, and 65.3% of participants showed non-adherence. Multiple regression analysis indicated that first-time FET cycle, treatment stage, methods of daily medication, social support and hope level were the main associated factors of the medication adherence among infertile women undergoing FET cycle (p < 0.001). Conclusion: This study revealed the medication adherence is at medium level among infertile women undergoing FET cycle, especially in patients with repeated FET cycles. The study also suggested that improving the hope level and social support of infertile women undergoing FET cycle may increase medication adherence.
Thermo-Responsive Injectable Hydrogels Formed by Self-Assembly of Alginate-Based Heterograft Copolymers

Polysaccharide-based graft copolymers bearing thermo-responsive grafting chains, exhibiting LCST, have been designed to afford thermo-responsive injectable hydrogels. The good performance of the hydrogel requires control of the critical gelation temperature, Tgel. In the present article, we wish to show an alternative method to tune Tgel using an alginate-based thermo-responsive gelator bearing two kinds of grafting chains (heterograft copolymer topology) of P(NIPAM86-co-NtBAM14) random copolymers and pure PNIPAM, differing in their lower critical solution temperature (LCST) about 10 °C. Interestingly, the Tgel of the heterograft copolymer is controlled from the overall hydrophobic content, NtBAM, of both grafts, implying the formation of blended side chains in the crosslinked nanodomains of the formed network. Rheological investigation of the hydrogel showed excellent responsiveness to temperature and shear. Thus, a combination of shear-thinning and thermo-thickening effects provides the hydrogel with injectability and self-healing properties, making it a good candidate for biomedical applications.
Automated Detection of Corneal Edema With Deep Learning-Assisted Second Harmonic Generation Microscopy

Second Harmonic Generation Microscopy (SHG) is widely acknowledged as a valuable non-linear optical imaging tool, its contrast mechanism providing the premises to non-invasively identify, characterize, and monitor changes in the collagen architecture of tissues. However, the interpretation of SHG data can pose difficulties even for experts histopathologists, which represents a bottleneck for the translation of SHG-based diagnostic frameworks to clinical settings. The use of artificial intelligence methods for automated SHG analysis is still in an early stage, with only few studies having been reported to date, none addressing ocular tissues yet. In this work we explore the use of three Deep Learning models, the highly popular InceptionV3 and ResNet50, alongside FLIMBA, a custom developed architecture, requiring no pre-training, to automatically detect corneal edema in SHG images of porcine cornea. We observe that Deep Learning models building on different architectures provide complementary results for the classification of cornea SHG images and demonstrate an AU-ROC = 0.98 for their joint use. These results have potential to be extrapolated to other diagnostics scenarios, such as automated extraction of hydration level of cornea, or identification of corneal edema causes, and thus pave the way for novel methods for precision diagnostics of the cornea with Deep-Learning assisted SHG imaging.