Miracle-dz/UniFAR-FTUs huggingface dataset:
Sustainability of Leisure Tourism Events from a Destination Social Responsibility Perspective: Do Attribution Theory Dimensions Matter?

Although Destination Sustainable Responsibility (DSR) has become a critical factor in upholding tourists’ satisfaction and positive behavioral outcomes, research on how tourists perceive different attributional dimensions (e.g., controllability, stability) about the existing information adequacy on tourists’ behavior is limited. Additionally, no study has investigated how DSR influences leisure tourists’ satisfaction across various characteristics. Therefore, the current research has the novelty of examining the effects of Destination Sustainable Responsibility (DSR) on leisure tourists’ satisfaction. The study reveals two attribution theory dimensions, controllability, and stability, as mediators and information adequacy as a moderated mediation. Additionally, the study investigates how tourists’ personalities (extroverted, conscientious, neurotic, open, and agreeable) affect their perceptions of attribution dimensions. A quantitative analysis of 464 tourists who experienced leisure activities in sustainability resorts in the Red Sea was conducted to explore these relationships. The results provide a better understanding of how DSR affects leisure tourists’ satisfaction and how different personalities influence their perceptions. Our research findings demonstrate that tourists’ perceptions of destination sustainability initiatives (DSR) are contingent upon the controllability and stability of events and that extraverted and conscientious tourists reach different attributions on DSR than those with neuroticism and openness levels and agreeableness. Additionally, it appears that information adequacy concerning the controllability of events is privileged over the event’s stability about informant amount with DSR. We explore the implications of our conclusions from both theoretical and management perspectives.
What entails risk management maturity in public organisations?

Abstract This article investigates which attributes and contingent factors are crucial to develop a public sector risk management maturity model (PSRMMM). The purpose of this study is not to provide a PSRMMM per se, but to be a scientific reference in the creation of future models to better guide public organisations. Accordingly, enterprise risk management literature and specific public sector factors were analysed to build a questionnaire that was carried out in Brazilian federal and state public organisations. Next, a path of multivariate statistical techniques (CATPCA, K-modes, and multinomial logistic regression analysis) was used to analyse the data collected from 330 survey responses. Results reveal that 12 statistically significant variables explain 5 different levels of public sector risk management maturity. This study stands out for its originality in indicating the main contingent factors and attributes a PSRMMM must have per level of maturity, facilitating the development of prescriptions to guide implementation improvements. Moreover, this study has practical implications to government policymakers who use PSRMMM to assess the performance of public organizations in implementing risk management frameworks.
Pocket ACEs: Discovering new function within an old player

Angiotensin-converting enzyme (ACE) is canonically known for its role in the renin-angiotensin system (RAS) where its conversion of angiotensin I (Ang I) to the bioactive peptide angiotensin II (Ang II) helps to regulate blood pressure, electrolyte, and volume homeostasis. Further studies on ACE have shown that its enzymatic activity is relatively non-specific and functions outside of the RAS axis. Of the multiple systems it has been implicated in, ACE has been found to play an important role in the development and modulation of hematopoiesis and the immune system, both through the RAS and independently of the RAS axis.
Stochastic dynamics of the midlatitude atmospheric jet

Abstract The innate tendency of the background straining field of the midlatitude atmospheric jet to preferentially amplify a subset of disturbances produces a characteristic response to stochastic perturbation whether the perturbations are internally generated by nonlinear processes or externally imposed. This physical property of enhanced response to a subset of perturbations is expressed analytically through the nonnormality of the linearized dynamical operator, which can be studied to determine the transient growth of particular disturbances over time through solution of the initial value problem or, alternatively, to determine the stationary response to continual excitation through solution of the related stochastic problem. Making use of the fact that the background flow dominates the strain rate field, a theory for the turbulent state can be constructed based on the nonnormality of the dynamical operator linearized about the background flow. While the initial value problem provides an explanation f.
Analysis of laminar mixed convection in inclined semicircular ducts under buoyancy-assisted and -opposed conditions

Several practical applications involve mixed convection in ducts of various cross sections and orientations. These applications include solar energy systems, cooling of electronic devices, compact heat exchangers, and cooling cores of nuclear reactors. Full understanding or the prevailing velocity and temperature fields, as well as the pressure drop and heat transfer characteristics, is necessary for the proper design of such systems. Here, laminate, fully developed mixed convection is inclined semicircular ducts is investigated theoretically under buoyancy-assisted and buoyancy-opposed conditions. A numerical, finite control volume approach was adopted in solving the governing equations, and results were obtained for the two limiting boundary conditions H1 and H2. These results include velocity and temperature distributions, a map for the onset of flow reversal, and data for the friction factor and Nusselt number. The results are presented with a detailed assessment of the effects of inclination, Reynolds number, Grashof number, and the thermal boundary conditions.
An Improved Canny Algorithm for Edge Detection

Because of the high similarity between the gradient magnitudes of low-contrast edge and noise,the conventional Canny algorithm for detection,which is based on the double-threshold to detect and connect edges,damages partly the low-contrast edge though it suppresses noise.An improved Canny algorithm is therefore proposed instead of the double-threshold one,which detects and connects the edges in accordance to the difference of the gradient direction between the edge and the noise,so as to protect efficiently the details of all low-contrast edges with the noise suppressed simultaneously.The new approach is thus superior to the conventional one.Simulation tests have verified the effectiveness of the improved Canny algorithm for edge detection.
Comparison of Cloud Cover from All-Sky Imager and Meteorological Observer

AbstractNaked-eye observation of cloud cover has widely resisted automation. Replacement of human observation by instruments is an inexorable trend for the development of ground-based macroscopic cloud observation. In this paper, cloud covers from an all-sky imager (ASI) are compared with those from a meteorological observer (MO) through field experiments performed at three sites in China. The correlation coefficient between ASI and MO is 0.77 for all cases. The ASI cloud fractions have great agreement with MO for clear sky, overcast sky, and sky loaded with low- and middle-level clouds. About 78% of the ASI cases had deviations between ±1 tenth compared to MO cloud cover. High-level cloud (or aerosol) is the main reason causing this difference. It is partially due to MO, who takes aerosol as high, thin cloud. Another reason might be that ASI made a wrong estimation for high-level cloud (or aerosol) because of its detector and the cloud-determination algorithm. Distinguishing high, thin cloud from aerosol.
Ultramicro Interdigitated Array Electrode Chip with Optimized Construction for Detection of Ammonia Nitrogen in Water

Ammonia nitrogen is a common contaminant in water and its determination is important for environmental protection. In this paper, an electrochemical sensor based on an ultramicro interdigitated array electrode (UIAE) chip with optimized construction was fabricated with Micro-Electro-Mechanical System (MEMS) technology and developed to realize the detection of ammonia nitrogen in water. The effects of spacing-to-width ratio and width of the working electrode on UIAE’s electrochemical characteristics and its ammonia nitrogen detection performance were studied by finite element simulation and experiment. The results demonstrated that the smaller the spacing-to-width ratio, the stronger generation–collection effect, and the smaller the electrode width, the stronger the edge effect, which led to an easier steady-state reach, a higher response current, and better ammonia nitrogen determination performance. The fabricated UIAE chip with optimized construction showed the linear detection range of 0.15 mg/L~2.0 mg/L (calculated as N), the sensitivity of 0.4181 μA·L·mg−1, and good anti-interference performance, as well as a long lifetime. UIAE based on bare Pt was successfully applied to ammonia nitrogen detection in water by optimizing structure, which might broaden the methods of ammonia nitrogen detection in water.
Marcadores FGF-23 y klotho en enfermedad renal crónica y su implicación cardiovascular, una revisión sistemática

La principal causa de mortalidad en enfermedad renal crónica (ERC), en el 80% de pacientes se da por enfermedad cardiovascular asociada, los parámetros bioquímicos clásicos del metabolismo óseomineral aún no logran explicar la progresión patológica por tanto, se ha empezado a estudiar nuevos marcadores con relación al daño cardiovascular, donde se ha encontrado al marcador FGF-23 y su correceptor Klotho, implicados en la génesis del daño cardiovascular y enfermedad óseomineral asociada al fosforo, que en conjunto causan remodelamiento cardiovascular, lo que ha empezado aclarecer aún más esta dinámica fisiopatológica. Esta revision busca conocer la implicación de los marcadores FGF-23 y Klotho en ERC y el riesgo cardiovascular asociado y para ello realizó una revision sistemática de literatura, indagando en bases biomédicas como COCHRANE, Embase, LILACS, Scielo, Pub-Med, EBSCO, Hinari, Sociedades médicas, así como tesauros MeSH propios de esta investigación
Enhanced mid-to-near-infrared second harmonic generation in silicon plasmonic microring resonators with low pump power

We propose an efficient and low-power second harmonic generation (SHG) process in a silicon-compatible hybrid plasmonic microring resonator. By making the microring resonator doubly resonant at the fundamental wavelength of 3.1 μm and second harmonic wavelength of 1.55 μm, the SHG efficiency is enhanced by almost two orders of magnitude when compared to the previous result induced in a straight plasmonic waveguide. A SHG efficiency of 13.71% is predicted for a low pump power of 20 mW in a ring with radius of 2.325 μm. This device provides a potential route for realizing efficient frequency conversion between mid-infrared and near-infrared wavebands on a chip.
Optimal Selection of an Inertial Sensor for Cycle Slip Detection Considering Single-frequency RTK/INS Integrated Navigation

This paper suggests a methodology for the selection of an inertial sensor for cycle slip detection. The satellitedifference and time-difference residual between the predicted and measured carrier phases is defined as the monitoring value for cycle slip detection. The inertial navigation system (INS) position is used to calculate the predicted observation, and its error mainly contributes to the residual. For one cycle slip detection, the monitoring value residual should be smaller than the threshold. Based on this approach, we derive the maximum permissible position estimation error of the INS to detect one cycle slip. An Earth-centered, Earth-fixed (ECEF) frame-based INS is used for the derivations. Then, we formulate the position estimation error as a function of the inertial sensor specifications using suitable assumptions. Using resulting equation, the optimal inertial sensor can be selected based on the required cycle slip detection performance. To verify the process of optimal IMU selection, simulation data is used. The derived position estimation error of the INS is analyzed carefully, and the monitoring value elicited by the INS error is also investigated. As a result, the selected IMU satisfies the designed cycle slip detection performance within the microelectromechanical systems (MEMS) grade.
Freezing of dipole dynamics in relaxor ferroelectric Pb(Mg1/3Nb2/3)O3-PbTiO3 as evidenced by dielectric spectroscopy

Complex dielectric susceptibility (χ' + jχ'') has been studied at f = 10-2-105 Hz in the relaxor ferroelectric 0.75Pb(Mg1/3Nb2/3)O3-0.25PbTiO3. In addition to the well known relaxor dispersion observed at temperatures around and below the temperature of permittivity maximum Tm, a new and comparatively weak dispersion has been disclosed at T>Tm. It is described by the `universal relaxation law', χ'' = cot(np/2)χ'fn-1. The temperature dependence of the exponent n follows the Vogel-Fulcher relation, indicating a process of freezing into the nonergodic state.
Therapeutic effects of CD133 + Exosomes on liver function after stroke in type 2 diabetic mice

Background and purpose Non-alcoholic fatty liver disease (NAFLD) is known to adversely affect stroke recovery. However, few studies investigate how stroke elicits liver dysfunction, particularly, how stroke in type 2 diabetes mellitus (T2DM) exacerbates progression of NAFLD. In this study, we test whether exosomes harvested from human umbilical cord blood (HUCBC) derived CD133 + cells (CD133 + Exo) improves neuro-cognitive outcome as well as reduces liver dysfunction in T2DM female mice. Methods Female, adult non-DM and T2DM mice subjected to stroke presence or absence were considered. T2DM-stroke mice were randomly assigned to receive PBS or Exosome treatment group. CD133 + Exo (20 μg/200 μl PBS, i.v.) was administered once at 3 days after stroke. Evaluation of neurological (mNSS, adhesive removal test) and cognitive function [novel object recognition (NOR) test, odor test] was performed. Mice were sacrificed at 28 days after stroke and brain, liver, and serum were harvested. Results Stroke induces severe and significant short-term and long-term neurological and cognitive deficits which were worse in T2DM mice compared to non-DM mice. CD133 + Exo treatment of T2DM-stroke mice significantly improved neurological function and cognitive outcome indicated by improved discrimination index in the NOR and odor tests compared to control T2DM-stroke mice. CD133 + Exo treatment of T2DM stroke significantly increased vascular and white matter/axon remodeling in the ischemic brain compared to T2DM-stroke mice. However, there were no differences in the lesion volume between non-DM stroke, T2DM-stroke and CD133 + Exo treated T2DM-stroke mice. In T2DM mice, stroke induced earlier and higher TLR4, NLRP3, and cytokine expression (SAA, IL1β, IL6, TNFα) in the liver compared to heart and kidney, as measured by Western blot. T2DM-stroke mice exhibited worse NAFLD progression with increased liver steatosis, hepatocellular ballooning, fibrosis, serum ALT activity, and higher NAFLD Activity Score compared to T2DM mice and non-DM-stroke mice, while CD133 + Exo treatment significantly attenuated the progression of NAFLD in T2DM stroke mice. Conclusion Treatment of female T2DM-stroke mice with CD133 + Exo significantly reduces the progression of NAFLD/NASH and improves neurological and cognitive function compared to control T2DM-stroke mice.
LSD1 inhibition modulates transcription factor networks in myeloid malignancies

Acute Myeloid Leukemia (AML) is a type of cancer of the blood system that is characterized by an accumulation of immature hematopoietic cells in the bone marrow and blood. Its pathogenesis is characterized by an increase in self-renewal and block in differentiation in hematopoietic stem and progenitor cells. Underlying its pathogenesis is the acquisition of mutations in these cells. As there are many different mutations found in AML that can occur in different combinations the disease is very heterogeneous. There has been some progress in the treatment of AML through the introduction of targeted therapies and a broader application of the stem cell transplantation in its treatment. However, many mutations found in AML are still lacking defined interventions. These are in particular mutations and dysregulation in important myeloid transcription factors and epigenetic regulators that also play a crucial role in normal hematopoietic differentiation. While a direct targeting of the partial loss-of-function or change in function observed in these factors is very difficult to imagine, recent data suggests that the inhibition of LSD1, an important epigenetic regulator, can modulate interactions in the network of myeloid transcription factors and restore differentiation in AML. Interestingly, the impact of LSD1 inhibition in this regard is quite different between normal and malignant hematopoiesis. The effect of LSD1 inhibition involves transcription factors that directly interact with LSD1 such as GFI1 and GFI1B, but also transcription factors that bind to enhancers that are modulated by LSD1 such as PU.1 and C/EBPα as well as transcription factors that are regulated downstream of LSD1 such as IRF8. In this review, we are summarizing the current literature on the impact of LSD1 modulation in normal and malignant hematopoietic cells and the current knowledge how the involved transcription factor networks are altered. We are also exploring how these modulation of transcription factors play into the rational selection of combination partners with LSD1 inhibitors, which is an intense area of clinical investigation.
Biopigments of Microbial Origin and Their Application in the Cosmetic Industry

Along with serving as a source of color, many microbial pigments have gained attention as interesting bioactive molecules with potential health advantages. These pigments have several applications in the food, agrochemical, medicine, and cosmetic industries. They have attracted the attention of these industries due to their high production value, low cost, stability, and biodegradability. Recently, many consumers worldwide have noted the impact of synthetic dyes; thus, natural pigments are more in demand than synthetic colors. On the other hand, the cosmetic industry has been moving toward greener manufacturing, from the formulation to the packaging material. Microbial pigments have several applications in the field of cosmetics due to their photoprotection, antioxidant, and antiaging properties, including inhibiting melanogenesis and acting as natural colorants for cosmetics, as some microorganisms are rich in pigments. More investigations are required to estimate the safety and efficacy of employing microbial pigments in cosmetic products. Furthermore, it is necessary to obtain information about DNA sequencing, metabolic pathways, and genetic engineering. In addition, unique habitats should be explored for novel pigments and new producing strains. Thus, new microbial pigments could be of consideration to the cosmetic industry, as they are ideal for future cosmetics with positive health effects.
On the variances of asymptotically normal estimators from complex surveys

Summary The problem of specifying and estimating the variance of estimated parameters based on complex sample designs from finite populations is considered. The results of this paper are particularly useful when the parameter estimators cannot be defined explicitly as a function of other statistics from the sample. It is shown how these results can be applied to linear regression, logistic regression and log linear contingency table models. An example of the application of the technique to the Canada Health Survey is given.
Multi-Modal Interaction-Aware Motion Prediction at Unsignalized Intersections

Autonomous vehicle technologies have evolved quickly over the last few years, with safety being one of the key requirements for their full deployment. However, ensuring their safety while navigating through highly interactive and complex scenarios remains a critical challenge. To tackle this problem, intention estimation and motion prediction are fundamental. In this work, a method to infer the intentions, based on a Dynamic Bayesian Network (DBN), and predict the motion, using Markov Chains, of the nearby vehicles at unsignalized intersections is proposed. This approach considers all possible corridors of the surrounding traffic participants and takes into account their interactions to infer the probabilities of stopping or crossing the intersection, as well as the probability of being in each of the possible navigable corridors. To achieve this, the DBN is used to model the relationships between the observed states and the unobserved intentions of the nearby agents. The Markov Chain model, obtained from a kinematic model, is used to predict the future motions of the vehicles, taking into account their current state, their inferred intentions, and the uncertainty associated with the prediction. The resulting multi-modal motion predictions are sent to the ego vehicle to navigate through the scene. The proposed method is evaluated in 6 real situations extracted from publicly available datasets and is compared with a model-based and a learn-based baseline models. The results showed that the proposed method outperformed both baselines in terms of accuracy considering the metrics ADE and FDE.
Epistatic effects of Siglec-G and DNase1 or DNase1l3 deficiencies in the development of systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a severe autoimmune disease that displays considerable heterogeneity not only in its symptoms, but also in its environmental and genetic causes. Studies in SLE patients have revealed that many genetic variants contribute to disease development. However, often its etiology remains unknown. Existing efforts to determine this etiology have focused on SLE in mouse models revealing not only that mutations in specific genes lead to SLE development, but also that epistatic effects of several gene mutations significantly amplify disease manifestation. Genome-wide association studies for SLE have identified loci involved in the two biological processes of immune complex clearance and lymphocyte signaling. Deficiency in an inhibitory receptor expressed on B lymphocytes, Siglec-G, has been shown to trigger SLE development in aging mice, as have mutations in DNA degrading DNase1 and DNase1l3, that are involved in clearance of DNA-containing immune complexes. Here, we analyze the development of SLE-like symptoms in mice deficient in either Siglecg and DNase1 or Siglecg and DNase1l3 to evaluate potential epistatic effects of these genes. We found that germinal center B cells and follicular helper T cells were increased in aging Siglecg -/- x Dnase1 -/- mice. In contrast, anti-dsDNA antibodies and anti-nuclear antibodies were strongly increased in aging Siglecg-/- x Dnase1l3-/- mice, when compared to single-deficient mice. Histological analysis of the kidneys revealed glomerulonephritis in both Siglecg -/- x Dnase1 -/- and Siglecg-/- x Dnase1l3-/- mice, but with a stronger glomerular damage in the latter. Collectively, these findings underscore the impact of the epistatic effects of Siglecg with DNase1 and Dnase1l3 on disease manifestation and highlight the potential combinatory effects of other gene mutations in SLE.