Alternative Models Research Articles

Populism and alternative models to representative democracy

ABSTRACT This introduction to the special issue provides an overview of the state of the art in the study of populism and democracy. It outlines the current debates and identifies several questions that remain unexplored or underexplored. It elaborates on how the different articles in this special issue address these gaps in the literature in order to advance and consolidate our knowledge about the relationship between populism and alternatives to representative democracy. Those articles make a significant contribution to this debate and open important avenues for future research.

Metaheuristic-Driven Optimization for Complex Multidimensional Decision-Making:

Effective management accounting procedures necessitate a thorough evaluation of discrepancies and variability in decision-making processes. However, conventional statistical measures often generate misleading results. In this research, we present the Mean Squares of Criteria and Alternatives (MESCA) metaheuristic approach to multifaceted decision-making. MESCA is specially designed to tackle intricate, multidimensional dilemmas, making it exceptionally suitable for scenarios involving conflicting or competing constraints. This, in turn bolsters the confidence levels of decision-makers, ultimately fostering more informed and enhanced decision-making processes. In this case study, we employ a metaheuristic approach to determine the optimal airport location, contrasting it with the established Simultaneous Evaluation of Criteria and Alternatives (SECA) model. Our research follows a deductive, survey-based methodology, with a focus on prioritizing cities within East Azerbaijan province for airport placement. We consider ten indicators, including economic factors and safety standards, to evaluate the suitability of alternative locations. The comparative analysis between the MESCA method and the SECA model accentuates the advantages of metaheuristic approach over the SECA model, offering valuable insights for effective management decisions. Our findings confirm that both approaches concur in identifying the same city as the most favorable alternative based on the established criteria. Moreover, our research demonstrates that the MESCA method surpasses the SECA model in terms of simplicity, flexibility, and cost-effectiveness, crucial considerations in the realm of management accounting. These revelations provide essential guidance to airport specialists and decision-makers when navigating constraints and selecting optimal airport locations.

Instructional Coaching Personnel and Program Scalability

Abstract Instructional coaching is an attractive alternative to one-size-fits-all teacher training and development in part because it is purposefully differentiated: Programming is aligned to individual teachers’ needs and implemented by an individual coach. But, how much of the benefit of coaching as an instructional improvement model depends on the specific coach with whom a teacher works? Collaborating with a national teacher training and development organization, TNTP, we find substantial variability in effectiveness across coaches in terms of changes in preservice teachers’ instructional practice (roughly 0.25 to 0.3 standard deviation from our preferred sample and models). The magnitude of coach effectiveness heterogeneity is quite similar to average coaching program effects on teaching practice identified in other research. Through a set of alternative model specifications and permutation tests, we rule out the possibility that our estimates of coach effectiveness heterogeneity are driven by nonrandom sorting of coaches to teachers, at least on observable characteristics available in our data, as well as the possibility that these estimates are simply statistical noise. These findings suggest that identifying, recruiting, and supporting highly skilled coaches will be key to scaling instructional coaching programs.

Reversions mask the contribution of adaptive evolution in microbiomes.

When examining bacterial genomes for evidence of past selection, the results obtained depend heavily on the mutational distance between chosen genomes. Even within a bacterial species, genomes separated by larger mutational distances exhibit stronger evidence of purifying selection as assessed by , the normalized ratio of nonsynonymous to synonymous mutations. Here, we show that the classical interpretation of this scale-dependence, weak purifying selection, leads to problematic mutation accumulation when applied to available gut microbiome data. We propose an alternative, adaptive reversion model with exactly opposite implications for dynamical intuition and applications of . Reversions that occur and sweep within-host populations are nearly guaranteed in microbiomes due to large population sizes, short generation times, and variable environments. Using analytical and simulation approaches, we show that adaptive reversion can explain the decay given only dozens of locally-fluctuating selective pressures, which is realistic in the context of Bacteroides genomes. The success of the adaptive reversion model argues for interpreting low values of obtained from long-time scales with caution, as they may emerge even when adaptive sweeps are frequent. Our work thus inverts the interpretation of an old observation in bacterial evolution, illustrates the potential of mutational reversions to shape genomic landscapes over time, and highlights the importance of studying bacterial genomic evolution on short time scales.

A Comprehensive Review of Preclinical Models for Polycystic Ovary Syndrome

Background: Polycystic ovary syndrome (PCOS) is a reproductive, metabolic, and endocrine disorder with unclear aetiology. PCOS, the most common cause of female reproductive and metabolic disorders, is known to affect more than one in ten women globally. PCOS and associated clinical manifestations are probably underdiagnosed despite their high occurrence. Objective: Alternative animal models have been employed to investigate the causes of PCOS or assess potential treatments. In light of this piece of information, it is challenging to create an animal model that accurately captures all components of this condition; nonetheless, the resemblance of an animal model's biology and/or biochemical characteristics to the phenotypes of PCOS in humans may boost its applicability. Result: The key characteristics of these models are closer to human situations when compared to women with PCOS, as shown by this comparison. The creation and testing of drugs for the treatment of PCOS are necessary. Conclusion:: The overview of PCOS, current preclinical models, and appropriate models chosen in different studies to mimic various phenotypes in PCOS studies are all covered in this review paper. Additionally, we have outlined the benefits and drawbacks of PCOS animal models.

Regional Evaluation Study of VFTO Interference to Secondary Side Cables Based on Cloud Model and MARCOS.

With the advent of the data era, most power secondary side equipment tends to be digitized. The power system needs more accurate numerical results to further improve its operating efficiency. Therefore, it is important to study the electromagnetic interferences of very fast transient overvoltage (VFTO) generated by gas-insulated switchgear (GIS). To protect the secondary side cable from interferences, the secondary side cable is wrapped with an outer shield and the shield is grounded. When the interference of VFTO comes, it will couple the interference current and interference voltage on the shield of the cable. By grounding, the interference is greatly discharged. However, due to the grounding resistance, there will be a potential difference between the grounding points at the two ends of the shield of the cable. This causes a corresponding interference current to flow through the shield, which will affect the transmission of signals inside the cable. In the actual substation, the resistivity of the soil, the ambient temperature and humidity of the area, and so on will have impacts on the grounding resistance. In addition, the irregularity of the cable arrangement and the time of the use of the cable will have impacts on the signal transmission of the cable. Based on the abovementioned issues, this article proposed a comprehensive assessment method based on the combination of the cloud model and measurement of alternatives and ranking according to compromise solution (MARCOS). The method brings the cloud model into MARCOS by the algorithm of the contribution of the cloud droplets. It overcomes the difficulty of cloud model quantification. By comparing the results of the proposed method with the actual conditions at the substation and the results of the common MARCOS assessment method, the validity of the method is verified, and a reference scheme is provided for substation optimization.

Non-thermal emission in M31 and M33

Context. Spiral galaxies M31 and M33 are among the γ-ray sources detected by the Fermi Large Area Telescope (LAT). Aims. We aim to model the broadband non-thermal emission of the central region of M31 (a LAT point source) and of the disk of M33 (a LAT extended source), as part of our continued survey of non-thermal properties of local galaxies that includes the Magellanic Clouds. Methods. We analysed the observed emission from the central region of M31 (R < 5.5 kpc) and the disk-sized emission from M33 (R ∼ 9 kpc). For each galaxy, we self-consistently modelled the broadband spectral energy distribution of the diffuse non-thermal emission based on published radio and γ-ray data. All relevant radiative processes involving relativistic and thermal electrons (synchrotron, Compton scattering, bremsstrahlung, and free–free emission and absorption), along with relativistic protons (π0 decay following interaction with thermal protons), were considered, using exact emissivity formulae. We also used the Fermi-LAT-validated γ-ray emissivities for pulsars. Results. Joint spectral analyses of the emission from the central region of M31 and the extended disk of M33 indicate that the radio emission is composed of both primary and secondary electron synchrotron and thermal bremsstrahlung, whereas the γ-ray emission may be explained as a combination of diffuse pionic, pulsar, and nuclear-BH-related emissions in M31 and plain diffuse pionic emission (with an average proton energy density of 0.5 eV cm−3) in M33. Conclusions. The observed γ-ray emission from M33 appears to be mainly hadronic. This situation is similar to other local galaxies, namely, the Magellanic Clouds. In contrast, we have found suggestions of a more complex situation in the central region of M31, whose emission could be an admixture of pulsar emission and hadronic emission, with the latter possibly originating from both the disk and the vicinity of the nuclear black hole. The alternative modelling of the spectra of M31 and M33 is motivated by the different hydrogen distribution in the two galaxies: The hydrogen deficiency in the central region of M31 partially unveils emissions from the nuclear BH and the pulsar population in the bulge and inner disk. If this were to be the case in M33 as well, these emissions would be outshined by diffuse pionic emission originating within the flat central-peak gas distribution in M33.

TeV pion bumps in the gamma-ray spectra of flaring blazars

Context. Very high-energy (VHE, E > 100 GeV) observations of the blazar Mrk 501 with MAGIC in 2014 provided evidence for an unusual narrow spectral feature at about 3 TeV during an extreme X-ray flaring activity. The one-zone synchrotron-self Compton scenario, widely used in blazar broadband spectral modeling, fails to explain the narrow TeV component. Aims. Motivated by this rare observation, we propose an alternative model for the production of narrow features in the VHE spectra of flaring blazars. These spectral features may result from the decay of neutral pions (π0 bumps) that are in turn produced via interactions of protons (of tens of TeV energy) with energetic photons, whose density increases during hard X-ray flares. Methods. We explored the conditions needed for the emergence of narrow π0 bumps in VHE blazar spectra during X-ray flares reaching synchrotron energies ∼100 keV using time-dependent radiative transfer calculations. We focused on high-synchrotron peaked (HSP) blazars, which comprise the majority of VHE-detected extragalactic sources. Results. We find that synchrotron-dominated flares with peak energies ≳100 keV can be ideal periods for the search of π0 bumps in the VHE spectra of HSP blazars. The flaring region is optically thin to photopion production, its energy content is dominated by the relativistic proton population, and the inferred jet power is highly super-Eddington. Application of the model to the spectral energy distribution of Mrk 501 on MJD 56857.98 shows that the VHE spectrum of the flare is described well by the sum of a synchrotron self-Compton (SSC) component and a distinct π0 bump centered at 3 TeV. Spectral fitting of simulated SSC+π0 spectra for the Cherenkov Telescope Array (CTA) show that a π0 bump could be detected at a 5σ significance level with a 30-min exposure. Conclusions. A harder VHE γ-ray spectrum than the usual SSC prediction or, more occasionally, a distinct narrow bump at VHE energies during hard X-ray flares, can be suggestive of a relativistic hadronic component in blazar jets that otherwise would remain hidden. The production of narrow features or spectral hardenings due to π0 decay in the VHE spectra of blazars is testable with the advent of CTA.

A theoretical framework for the analysis of an opposed piston linear engine design

Traditional crank-based engines face limitations due to mechanical, thermal, and combustion inefficiencies. In contrast, the opposed piston design of a linear engine generator mitigates frictional losses by eliminating rotational motion and crankshaft linkages. Instead, electrical power is generated through the oscillation of a translator within a linear stator. However, the lack of geometric constraints in the free piston design leads to uncertainties regarding dead center positions, resulting in challenges such as misfire, stall, over-fueling, and rapid load changes.This study aims to fill this gap by reviewing existing modeling literature and advancing the fundamental understanding of opposed piston linear engines (OPLE) with springs through the development of an idealized, nondimensional model. A combination of analytical and numerical models was developed to better understand the behavior of the OPLE. The model introduces a streamlined symmetric analytical solution, succeeded by a broader general analytical resolution, with careful attention to the significant influence of thermodynamic effects at each phase, offering insights into the engine's dynamic performance. Limitations inherent to the analytical solutions are addressed by a numerical scheme utilizing the Runge-Kutta technique. This approach guarantees swift and dependable computational outcomes, which captures cyclic variation. The alternator model amalgamates both linear and sinusoidal work profiles, adjusting the magnetic work output in response to fluctuations in the compression ratio relative to the Top Dead Center (TDC) clearance distance. This adjustment dictates the generator load for each translator.The proposed model integrates the dynamics of a damped spring-mass system with thermodynamic expressions representing in-cylinder processes. Simplifications are made assuming perfect springs, ideal gases, instantaneous heat transfer, and an average friction force dependent on stroke length for work output. Selected cases are analyzed to elucidate the system's fundamental behavior, both within and outside the context of the Otto cycle, showcasing natural and forced stability over multiple operation cycles. Notably, enhancing the baseline cylinder pressure, or input heat relative to spring stiffness can elevate the work-to-heat ratio values. The attained work-to-heat ratio within compression ratio window of 16 is approximately 28 %. While this percentage may fluctuate in the context of general FPLE designs, the model developed for OPLE in this work plays a crucial role in maintaining the engine within this narrowly defined efficiency range, without compromising the potential performance demonstrated in this study. Differences in compression ratios provided intriguing insights into the dynamics of the translator and the in-cylinder thermodynamics of the interconnected system. Lower TDC clearance resulted in high translator displacement, velocity, and enhanced thermal efficiency.

Convnext-Eesnn: An effective deep learning based malware detection in edge based IIOT

A rising number of edge devices, like controllers, sensors, and robots, are crucial for Industrial Internet of Things (IIoT) networks for collecting data for communication, storage, and processing. The security of the IIoT could be compromised by any malicious or unusual behavior on the part of any of these devices. They may also make it possible for malicious software placed on end nodes to enter the network and perform unauthorized activities. Existing anomaly detection techniques are less effective due to the increasing diversity of the network and the complexity of cyberattacks. In addition, most strategies are ineffective for devices with limited resources. Therefore, this work presents an effective deep learning based Malware Detection framework to make the edge based IIoT network more secure. This multi-stage system begins with the Deep Convolutional Generative Adversarial Networks (DCGAN) based data augmentation method to overcome the issue of data imbalance. Next, a ConvNeXt-based method extracts the features from the input data. Finally, an optimized Enhanced Elman Spike Neural Network (EESNN) based deep learning is utilized for malware recognition and classification. Using two distinct datasets— MaleVis and Malimg— the generalizability of the suggested model is clearly demonstrated. With an accuracy of 99.24% for MaleVis and 99.31% for the Malimg dataset, the suggested strategy demonstrated excellent results and surpassed all other existing methods. It illustrates how the suggested strategy outperforms alternative models and offers numerous benefits.

Single administration of a psychedelic [(R)-DOI] influences coping strategies to an escapable social stress

Psychedelic compounds have potentially rapid, long-lasting anxiolytic, antidepressive and anti-inflammatory effects. We investigated whether the psychedelic compound (R)-2,5-dimethoxy-4-iodoamphetamine [(R)-DOI], a selective 5-HT2A receptor partial agonist, decreases stress-related behavior in male mice exposed to repeated social aggression. Additionally, we explored the likelihood that these behavioral changes are related to anti-inflammatory properties of [(R)-DOI]. Animals were subjected to the Stress Alternatives Model (SAM), an escapable social stress paradigm in which animals develop reactive coping strategies - remaining in the SAM arena (Stay) with a social aggressor, or dynamically initiated stress coping strategies that involve utilizing the escape holes (Escape) to avoid aggression. Mice expressing these behavioral phenotypes display behaviors like those in other social aggression models that separate animals into stress-vulnerable (as for Stay) or stress-resilient (as for Escape) groups, which have been shown to have distinct inflammatory responses to social stress. These results show that Stay animals have heightened cytokine gene expression, and both Stay and Escape mice exhibit plasma and neural concentrations of the inflammatory cytokine tumor necrosis factor-α (TNFα) compared to unstressed control mice. Additionally, these results suggest that a single administration of (R)-DOI to Stay animals in low doses, can increase stress coping strategies such as increasing attention to the escape route, promoting escape behavior, and reducing freezing during socially aggressive interaction in the SAM. Lower single doses of (R)-DOI, in addition to shifting behavior to suggest anxiolytic effects, also concomitantly reduce plasma and limbic brain levels of the inflammatory cytokine TNFα.

Estimating the Allocation of the Economic Value Generated by Utilization of All-Oral Direct-Acting Antivirals for Hepatitis C in the United States, 2015 to 2019

ObjectivesBetween 2013 to 2019, several all-oral direct-acting antivirals (DAAs) were launched with the potential to cure patients with hepatitis C virus (HCV). They generated economic value in terms of the health gains for patients and cost-savings for the US healthcare system. We estimated the share of this value allocated to 4 manufacturers vs society. MethodsFor 2015 to 2019, we estimated the incremental impact of DAAs on HCV health outcomes and costs. We used the Center for Disease Analysis Foundation Polaris Observatory database to estimate utilization. Per-patient projections of lifetime quality-adjusted life-years (QALYs) gained and medical costs avoided were based on a standard 9-state HCV disease-progression model for DAA treatment vs alternatives. Annual QALY gains were valued at $114 000 per QALY. Outcomes and costs were discounted at 3%. Estimated revenues were based on reported sales. ResultsAn estimated 1 080 000 patients received DAAs: 81.5% would not have received the pre-DAA standard of care. On average, these patients were projected to gain 4.4 QALYs and save $104 400 in lifetime healthcare costs, generating $531.8 billion in value. Those who would have received treatment gained 1.7 QALYs and saved $41 500 in lifetime costs, generating $47.4 billion in economic value. As treatment costs fell nearly 75%, the 4 manufacturers reported $37.4 billion from DAA sales—an allocation of 6.5% of the total value. ConclusionsThe significant majority (∼90%) of the economic value of curing HCV with DAAs were health benefits to patients and net cost-savings to society. DAA manufacturers received a minority share (6.5%) of the aggregate economic value generated.

Skull-Derived Myeloid Cells Augment T Cell Responses and Suppress Glioblastoma Growth

INTRODUCTION: Recent studies have implicated skull marrow as a functional myeloid reservoir in CNS pathology. However, its contribution to malignancy remains unexplored. METHODS: Fluorescently labeled calvarial flaps were transplanted onto syngeneic glioblastoma-bearing mice, followed by flow cytometric profiling of tumor-infiltrative leukocytes. To assay the functional relevance of SDMCs, tumor-bearing C57BL/6 mice were treated with preemptive calvarial ablation (13 Gy irradiation), or conversely intracalvarial AMD3100 to augment myeloid egress from marrow niches. Tumor burden was monitored via survival and bioluminescent imaging. RESULTS: 72 h following CMFDA-stained calvarial transplantation into tumor-bearing Balb/C mice, 40.3% of tumor-infiltrative myeloid cells were fluorescent and thus skull-derived; transplantation in an alternative longitudinal model (GFP+ flaps, C57BL/6) validated that SDMCs were robust and viable at 3 weeks post-operatively. As MHCII+ cells were disproportionately enriched among SDMCs (87.9% vs 67.3%, p = 0.012), we interrogated the immunogenicity of these cells through targeted ablation. Skull-ablated mice had reduced infiltration by antigen-presenting cells than controls (cDCs: 1.1% vs 4.5%, p = 0.002; macrophages: 14.4% vs 36.6%, p < 0.001) and 6-fold greater necrosis (67.7% vs 13.5% apoptotic, p < 0.001), suggesting an impaired ability to mount a controlled, adaptive immune response. The stimulatory role of SDMCs was further demonstrated via intracalvarial AMD3100 administration, which through its promotion of myeloid precursor egress (0.26% vs 0.02%, p < 0.001) and cDC2 infiltration (10.4% vs 3.0%, p = 0.003) yielded robust CD4+ T cell activation and effector memory differentiation. These differences were clinically meaningful, as skull irradiation accelerated tumor growth and attenuated survival compared to controls, while AMD3100 treatment accomplished the opposite (median OS: 17d vs 22d, p < 0.001; 26.5d vs 22d, p = 0.006). CONCLUSIONS: The preferential polarization of SDMCs into immunostimulatory APCs warrants the continued exploration of local marrow-targeting agents (e.g., AMD3100) as therapeutic modalities.

Improving student higher order thinking skills using SynecticHOTS-oriented learning model

The achievement of students’ learning outcomes in physics lessons has a low tendency, this is due to various factors, one of which is higher-order thinking skills (HOTS) based learning that has not been fully implemented in the learning process and assessment. This study aimed to determine the differences in the Synectic-HOTS learning model in physics compared to conventional learning models. This study used a quasi-experimental study with a pre-test–post-test nonequivalent control group design. The instrument used in this study is a two-tier test question that contains 20 items of HOTS aspect. The prerequisite test showed that the data was not homogeneous, while the results of the data homogeneity test were stated to be homogeneous. Therefore, a non-parametric test was carried out using the Mann-Whitney U-test. Based on the results of the data analysis, the Asymp. Sig. (2-tailed) for the pre-test was 0.111 and the post-test was 0.001 (p=.000<05). The effect size calculation shows that the Synectic learning model is effective in the medium category. These results indicate that the application of the SynecticHOTS model significantly improves HOTS when compared to conventional learning models. This work can open up insights to teachers about alternative, creative, and effective learning models to improve higher-order thinking skills and student learning outcomes.

Cultural mechanisms linking mothers' familism values to externalizing behaviors among Midwest U.S. Latinx adolescents.

This study was designed to examine associations among parents' familism values, adolescents' cultural resources, and externalizing behavior among Latinx youth in the Midwestern United States. Participants were 267 Latinx adolescents (M age = 15.58 years; SD = 1.28 years; 45% girls; 82.8% Mexican American) and their mothers/mother figures who completed individually administered interviews comprised of standardized measures. Structural equation modeling was used to test several alternative mediational models in which youth ethnic identity and familism values served as potential cultural mechanisms linking parents' familism values to lower levels of youth externalizing behavior. Results showed that mothers' familism values were positively associated with youth ethnic identity which was positively associated with youth familism values; in turn, youth familism values were inversely associated with externalizing behavior. The findings did not differ by youth gender or nativity (U.S.-born vs. foreign-born youth). These findings provide support for cultural resilience perspectives by highlighting the protective role of ethnic identity and familism values among U.S. Latinx adolescents. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Wisdom predicts emotional intelligence and wise reasoning

ABSTRACT In a recent article in The Journal of Positive Psychology, Schneider et al. (2023) examined the relations of emotional intelligence (EI) on wise reasoning and three-dimensional wisdom. They concluded that only the managing emotions branch of EI predicted wise reasoning, contingent upon epistemic humility and need for cognition in Study 1 (N = 99) and epistemic humility, empathic concern, and perspective taking in Study 2 (N = 150). Unfortunately, this article has several problems, including (a) the mischaracterization of three-dimensional wisdom as knowledge rather than personality qualities, (b) mediating variables whose concepts and measures partially overlapped with wise reasoning and wisdom, and (c) some problems with computing the three-dimensional wisdom scale (3D-WS) in Study 2. I tested alternative path models, which showed that three-dimensional wisdom predicted EI and wise reasoning, whereas EI by itself did not predict wise reasoning. Wise reasoning might depend more on personal wisdom than EI.

Two-sample test for stochastic block models via the largest singular value

The stochastic block model is widely used for detecting community structures in network data. However, the research interest in much of the literature focuses on the study of one sample of stochastic block models. Detecting the difference between the two community structures is a less studied issue for stochastic block models. In this article, we propose a novel test statistic based on the largest singular value of a residual matrix obtained by subtracting the geometric mean of two estimated block mean effects from the sum of two observed adjacency matrices. We prove that the null distribution of the proposed test statistic converges in distribution to the Tracy-Widom distribution with index 1, and we show the difference between the two samples for stochastic block models can be tested via the proposed method. We show that the proposed test is asymptotically powerful against alternative models. Further, we extend the proposed method to the degree-corrected stochastic block model. Both simulation studies and real-world data examples indicate that the proposed method works well.

Embodied and embedded mindfulness: a mindful path to well-being

ABSTRACT While there is a growing interest in mindfulness as an intrapersonal trait, only a limited number of studies have investigated interpersonal mindfulness, and no study has examined the interaction between both concepts. This paper aims to evaluate a path model that depicts the role of both intrapersonal and interpersonal mindfulness in facilitating emotion regulation and improving well-being by mitigating the effects of psychological symptoms and enhancing social connectedness and safeness. Additionally, this study aims to compare the results obtained using different measures of intrapersonal and interpersonal mindfulness. Moreover, the study evaluates an alternative path model. A sample of 353 participants completed various measures of intrapersonal and interpersonal mindfulness, emotion dysregulation, psychological symptoms (stress, anxiety, and depression), social connectedness, social safeness, satisfaction with life, and happiness. The findings supported the proposed path model, indicating that emotion regulation mediated the relationship between intrapersonal and interpersonal mindfulness on one side and psychological symptoms and social connectedness and social safeness on the other side. Furthermore, the findings suggested that psychological symptoms and social related measures mediated the associations between emotion regulation and well-being. The same path model was supported when using different sets of mindfulness measures. The alternative path was not supported. This study enhances our understanding of how intrapersonal and interpersonal mindfulness interact together to promote emotion regulation, improve well-being, mitigate psychological symptoms, and foster social relatedness and safeness. The findings highlight the importance of training both intrapersonal and interpersonal mindfulness skills to enhance well-being. Implications and limitations are thoroughly discussed.

New reimbursement models to promote better patient outcomes and overall value in laboratory medicine and healthcare.

The most widespread healthcare reimbursement models, including diagnostic laboratory services, are Fee-for-Service, Reference Pricing and Diagnosis-Related Groups. Within these models healthcare providers are remunerated for each specific service or procedure they operate. Healthcare payers are increasingly exploring alternative models, such as bundled payments or value-based reimbursement to encourage value of patient care rather than the simple amount of delivered services. These alternative models are advised, as they are more efficient in promoting cost-effective, high-quality laboratory testing, thereby improving patient health outcomes. If outcomes-based evaluation is a pillar in a new vision of "Value-Based Healthcare", an active policy of Value-Based Reimbursement in laboratory medicine will assure both an efficiency-based sustainability and a high-quality effectiveness-based diagnostic activity. This review aims to evaluate current and alternative reimbursement models, to support a wider agenda in encouraging more Value-Based Healthcare and Value-Based Reimbursement in laboratory medicine.

A finite volume scheme for solving an alternative morphodynamic model with porosity

AbstractThis work proposes an extended numerical scheme based on the finite volume method that is intended to solve a new morphodynamic model with porosity. The St-Venant equations and the Exner equation are coupled in this model, accounting for the variation of the porosity function . In the morphodynamic system, the Jacobian matrix's sign is taken into account when reconstructing the numerical fluxes using an improved Roe's approach to assure correct numerical computations.