Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Customer Engagement in Mediating the Influence of Brand Experience and Customer Satisfaction on the Customer Loyalty of Full-Service Airline in Indonesia

The Corona Virus Disease-19 (COVID-19) pandemic, which is currently engulfing the entire world, has significantly reduced the number of air travel passengers worldwide. However, the decline in air travel passengers on domestic routes in Indonesia occurred in 2019, one year before the COVID-19 pandemic hit the aviation industry worldwide. The decline in passengers in 2019 can be taken as a signal of weakening demand in the aviation industry in Indonesia. This research was conducted on 233 respondents from the airline "X" as one of the full-service in Indonesia, which has also been affected by the decline in passengers since 2019. The strategy to increase customer retention during the COVID-19 pandemic and the post-pandemic period is an important thing to study, considering that the existing literature on airline customer loyalty has never been carried out under the conditions of the COVID-19 pandemic. Therefore, this study examines customer satisfaction, customer engagement, and brand experience as a combination of antecedent constructs of customer loyalty based on the perception of Indonesian passengers traveling with full-service airlines. The research shows that brand experience has no positive and significant effect on customer loyalty. Meanwhile, customer satisfaction and customer engagement positively and significantly impact customer loyalty. Furthermore, customer engagement can fully mediate the relationship between brand experience and customer loyalty of airline "X". In contrast, customer engagement can partially mediate the relationship between customer satisfaction and customer loyalty.
Effects of Systematic Diet Education Combined with Multidisciplinary Nursing on Nutritional Status and Calcium and Phosphorus Metabolism in Patients with Diabetic Kidney Disease in Uremic Phase after Treatment with Alogliptin

Objective To explore the effects of systematic diet education combined with multidisciplinary nursing on nutritional status and calcium and phosphorus metabolism in patients with diabetic kidney disease (DKD) in uremic phase after treatment with alogliptin. Methods A total of 90 DKD patients with uremia admitted to our hospital from January 2020 to January 2021 were selected as the research objects. The subjects were divided into combined group and routine group by random number table method. All patients received alogliptin medication. The combination group received systematic dietary education combined with multidisciplinary nursing after the medication, and the conventional group received conventional intervention. Serum albumin, blood calcium, and other indexes were detected between both groups after intervention. Results After intervention, compared with the conventional group, all nutritional indexes of the combined group were obviously higher, levels of serum phosphorus and calcium-phosphorus product of the combined group were obviously lower (P < 0.001), the incidence of hypoglycemia and hyperglycemia of the combined group was obviously lower (P < 0.05), the total compliance rate of the combined group was obviously higher (P < 0.05), and the SAS score of the combined group was obviously lower (P < 0.001). Conclusion With conspicuous intervention effect, systematic diet education combined with multidisciplinary nursing is a reliable method that can improve the nutritional status and levels of calcium and phosphorus metabolism, enhance treatment compliance, and reduce anxiety. Further research will help to provide a better solution for patients. This trial is registered with ChiCTR2200057011.
Wind Power Project Repowering: Financial Feasibility, Decision Drivers, and Supply Chain Effects

As wind power facilities age, project owners are faced with plant end of life decisions. This report is intended to inform policymakers and the business community regarding the history, opportunities, and challenges associated with plant end of life actions, in particular repowering. Specifically, the report details the history of repowering, examines the plant age at which repowering becomes financially attractive, and estimates the incremental market investment and supply chain demand that might result from future U.S. repowering activities.
Genome-Wide Survey and Development of the First Microsatellite Markers Database (AnCorDB) in Anemone coronaria L.

Anemone coronaria L. (2n = 2x = 16) is a perennial, allogamous, highly heterozygous plant marketed as a cut flower or in gardens. Due to its large genome size, limited efforts have been made in order to develop species-specific molecular markers. We obtained the first draft genome of the species by Illumina sequencing an androgenetic haploid plant of the commercial line “MISTRAL® Magenta”. The genome assembly was obtained by applying the MEGAHIT pipeline and consisted of 2 × 106 scaffolds. The SciRoKo SSR (Simple Sequence Repeats)-search module identified 401.822 perfect and 188.987 imperfect microsatellites motifs. Following, we developed a user-friendly “Anemone coronaria Microsatellite DataBase” (AnCorDB), which incorporates the Primer3 script, making it possible to design couples of primers for downstream application of the identified SSR markers. Eight genotypes belonging to eight cultivars were used to validate 62 SSRs and a subset of markers was applied for fingerprinting each cultivar, as well as to assess their intra-cultivar variability. The newly developed microsatellite markers will find application in Breeding Rights disputes, developing genetic maps, marker assisted breeding (MAS) strategies, as well as phylogenetic studies.
Swift Weathering Response on Floodplains During the Paleocene‐Eocene Thermal Maximum

Silicate weathering is thought to increase and offset the rapid, massive input of CO2 into the atmosphere and ocean during the Paleocene‐Eocene Thermal Maximum (PETM), but few nonmarine records have been used to quantify this. We probe changes in silicate weathering intensity by measuring Li isotope ratios of bedrock and ancient floodplain deposits spanning the PETM in the Bighorn Basin, Wyoming (USA). Our results reveal a rapid increase in silicate weathering intensity during the PETM that remained high during at least the initial stage of climate recovery. Additionally, we determine that soils that formed farthest from ancient river channels underwent larger weathering changes than near‐channel soils. Alongside increased temperatures and pCO2, the simplest explanation for this response relates to increased seasonal fluctuations in water table height in the floodplain that promote dissolution and precipitation reactions. These findings newly demonstrate that weathering on floodplains, like mountain hillslopes, responds to climate change.
LIMIT EQUILIBRIUM METHOD BASED ON RATIO OF FACTOR OF SAFETY FOR SLOPE STABILITY OF UNSATURATED SOILS

The relationship between the factor of safety of unsaturated soils slope and the stability is proposed for a given unsaturated soil slice.If the minimum factor of safety is greater than or equals to the allowable factor of safety,the slice is safe.The general limit equilibrium methods for stability analysis,Swedish slice method and Bishop method,are conducted based on the ratio of factor of safety and the improved Mohr-Coulomb failure theory.Several special formulas are achieved when the pore pressure is 0.The minimum factor of safety of an unsaturated soil slope is analyzed with the changes of different parameters.Some results show that with the increase of the ratio of factor of safety,the minimum factor of safety significantly decreases,yet the density has little effect on the minimum factor of safety.
Using a System Pharmacology Method to Search for the Potential Targets and Pathways of Yinqiaosan against COVID-19

The first reported case of coronavirus disease 2019 (COVID-19) occurred in Wuhan, Hubei, China. Thereafter, it spread through China and worldwide in only a few months, reaching a pandemic level. It can cause severe respiratory illnesses such as pneumonia and lung failure. Since the onset of the disease, the rapid response and intervention of traditional Chinese medicine (TCM) have played a significant role in the effective control of the epidemic. Yinqiaosan (YQS) was used to treat COVID-19 pneumonia, with good curative effects. However, a systematic overview of its active compounds and the therapeutic mechanisms underlying its action has yet to be performed. The purpose of the current study is to explore the compounds and mechanism of YQS in treating COVID-19 pneumonia using system pharmacology. A system pharmacology method involving drug-likeness assessment, oral bioavailability forecasting, virtual docking, and network analysis was applied to estimate the active compounds, hub targets, and key pathways of YQS in the treatment of COVID-19 pneumonia. With this method, 117 active compounds were successfully identified in YQS, and 77 potential targets were obtained from the targets of 95 compounds and COVID-19 pneumonia. The results show that YQS may act in treating COVID-19 pneumonia and its complications (atherosclerosis and nephropathy) through Kaposi sarcoma-related herpesvirus infection and the AGE-RAGE signaling pathway in diabetic complications and pathways in cancer. We distinguished the hub molecular targets within pathways such as TNF, GAPDH, MAPK3, MAPK1, EGFR, CASP3, MAPK8, mTOR, IL-2, and MAPK14. Five of the more highly active compounds (acacetin, kaempferol, luteolin, naringenin, and quercetin) have anti-inflammatory and antioxidative properties. In summary, by introducing a systematic network pharmacology method, our research perfectly forecasts the active compounds, potential targets, and key pathways of YQS applied to COVID-19 and helps to comprehensively clarify its mechanism of action.
Nomograms for Death from Pneumocystis jirovecii Pneumonia in HIV-Uninfected and HIV-Infected Patients

Purpose Pneumocystis jirovecii pneumonia (PCP) is a major cause of death in immunocompromised patients. Many risk factors for poor prognosis have been reported, but few studies have created predictive models with these variables to calculate the death rate accurately. This study created nomogram models for the precise prediction of mortality risk in human immunodeficiency virus (HIV) uninfected and HIV-infected patients with PCP. Patients and Methods A retrospective study was performed over a 10-year period to evaluate the clinical characteristics and outcomes of PCP in HIV-uninfected and HIV-infected adults treated in Beijing, China from 2010 to 2019. Univariate and multivariate logistic regression analyses were used to identify mortality risk factors to create the nomograms. Nomogram models were evaluated by using a bootstrapped concordance index, calibration plots and receiver operating characteristic (ROC) curves. Results A total of 167 HIV-uninfected and 193 HIV-infected PCP patients were included in the study. Pneumothorax, duration of fever after admission, CD4+ T cells ≤100/µL and trimethoprim-sulfamethoxazole (TMP-SMX) combined with caspofungin (CAS) treatment were independent risk factors for death in HIV-uninfected PCP patients. We derived a well calibrated nomogram for mortality by using these variables. The area under the curve was 0.865 (95% confidence interval 0.799–0.931). Independent risk factors for death in HIV-infected PCP patients were pneumothorax, platelet (PLT) ≤80×109/L, haemoglobin (HGB) ≤90 g/L, albumin (ALB), cytomegalovirus (CMV) coinfection and TMP-SMX combined with CAS treatment. The nomogram showed good discrimination, with a C-index of 0.904 and excellent calibration. Conclusion The nomograms which were derived may be useful tools for the precise prediction of mortality in HIV-uninfected and HIV-infected patients, but require validation in clinical practice.
Improving Peary Caribou Presence Predictions in MaxEnt Using Spatialized Snow Simulations

The Arctic has warmed at twice the global average over recent decades, which has led to a reduction in the spatial extent and mass balance of snow. The increase in occurrence of winter extreme events such as rain-on-snow, blizzards, and heat waves has a significant impact on snow thickness and density. Dense snowpack conditions can decrease or completely prevent foraging by Peary caribou (Rangifer tarandus pearyi) by creating “locked pastures,” a situation where forage is present but not accessible under snow or ice. Prolonged and severe weather events have been linked to poor body condition, malnutrition, high adult mortality, calf losses, and major population die-offs in Peary caribou. Previous work has established the link between declines in Peary caribou numbers in the Canadian Arctic Archipelago and snow conditions, however these efforts have been limited by the quality and resolution of data describing snow physical properties in the Arctic. Here, we 1) investigate whether a snow model adapted for the Antarctic (SNOWPACK) can produce snow simulations relevant to Canadian High Arctic conditions, and 2) test snow model outputs to determine their utility in predicting Peary caribou occurrence with MaxEnt modelling software. We model Peary caribou occurrence across three seasons: July – October (summer forage and rut), November – March (fall movement and winter forage), and April – June (spring movement and calving). Results of snow simulations using the Antarctic SNOWPACK model demonstrated that both top and bottom density values were greatly improved when compared to simulations using the original version developed for alpine conditions. Results were also more consistent with field measurements using the Antarctic model, though it underestimated the top layer density compared to on-site measurements. Modelled outputs including snow depth and CT350 (cumulative thickness of snow layers surpassing the critical density value of 350 kg·m-3; a density threshold relevant to caribou) proved to be important predictors of Peary caribou space use in each of the top seasonal models along with vegetation and elevation. All seasonal models were robust in that they were able to predict reasonably well the occurrence of Peary caribou outside the period used to develop the models. This work highlights the need for continued monitoring of snow conditions with climate change to understand potential impacts to the species’ distribution.
Endocannabinoid Modulation in Neurodegenerative Diseases: In Pursuit of Certainty

Simple Summary Neurodegenerative diseases represent an important cause of morbidity and mortality worldwide. Existing therapeutic options are limited and focus mostly on improving symptoms and reducing exacerbations. The endocannabinoid system is involved in the pathophysiology of such disorders, an idea which has been highlighted by recent scientific work. The current work focusses its attention on the importance and implications of this system and its synthetic and natural ligands in disorders such as Alzheimer’s, Parkinson’s, Huntington’s and multiple sclerosis. Abstract Neurodegenerative diseases are an increasing cause of global morbidity and mortality. They occur in the central nervous system (CNS) and lead to functional and mental impairment due to loss of neurons. Recent evidence highlights the link between neurodegenerative and inflammatory diseases of the CNS. These are typically associated with several neurological disorders. These diseases have fundamental differences regarding their underlying physiology and clinical manifestations, although there are aspects that overlap. The endocannabinoid system (ECS) is comprised of receptors (type-1 (CB1R) and type-2 (CB2R) cannabinoid-receptors, as well as transient receptor potential vanilloid 1 (TRPV1)), endogenous ligands and enzymes that synthesize and degrade endocannabinoids (ECBs). Recent studies revealed the involvement of the ECS in different pathological aspects of these neurodegenerative disorders. The present review will explore the roles of cannabinoid receptors (CBRs) and pharmacological agents that modulate CBRs or ECS activity with reference to Alzheimer’s Disease (AD), Parkinson’s Disease (PD), Huntington’s Disease (HD) and multiple sclerosis (MS).
Democracy and Health in Developing Countries: New Cross-National Evidence, 1990–2016

Scholars have long investigated the factors that affect health outcomes in less-developed countries. One debate that has increasingly intensified in recent years is the democracy and health relationship in comparative international context. Scholars argue that democracy does affect country-level health outcomes in less-developed countries, while others argue democracy does not affect country-level health outcomes. I estimate the effect of numerous democracy indexes on child mortality and infant mortality in developing countries using fixed effects regression models with heteroskedasticity-robust standard errors clustered by country. I find that multiple aspects of democracy exert significant beneficial effects on child mortality and infant mortality in less-developed countries.
The Effect of Distributive Justice and Situational Leadership on Job Satisfaction through Work Family Conflict (Case Study of Full-time Working Women in the Banking Sector in Jakarta)

Work Family conflict is a phenomenon that is experienced by most people in big cities, where working women are a demand of the times as an effort to support the family economy. This study aims to analyze the effect of distributive justice and situational leadership on job satisfaction through work family conflict. The object of this research is women who work full-time in the banking sector in Jakarta. A total of 100 respondents filled out the questionnaire, the sample was taken using the purposive sampling technique. Data were analyzed using PLS (Partial Least Square analysis). The results of this study indicate that distributive justice has no impact on job satisfaction and situational leadership has a positive effect on job satisfaction. Work family conflict has no impact on job satisfaction. Distributive justice through work family conflict has no effect on job satisfaction. Situational leadership through work family conflict has no impact on job satisfaction.
Difference Set Based Methods for Optimal Thinned Circular Arrays in Aperture Synthesis Radiometers

Sparse antenna array design is of great importance in aperture synthesis radiometers(ASR). For non-redundant baseline distribution and the simplicity of mechanical structure and instrumental manufacture,the circular array,as a promising configuration of ASR,has received more and more attention.Two methods for optimal thinned circular arrays are proposed to achieve the least redundancy in baseline length(modulus of baseline vector). One is half-circle thinning based on restricted difference set(RDS),the other is full-circle thinning based on cyclic difference set(CDS). Both methods can greatly reduce the numbers of the elements and channels and provide analytical solutions for the element positions of thinned circular arrays.With the rotation of the array and time-shared measurement,the thinned circular arrays resulting for both methods can obtain the same spatial frequency coverage as that of UCA.
Risk Appetite Fluctuations in the Insurance Industry

The risk appetite of insurance companies ﬂ uctuates over time in a quasi cyclical fashion. When their capitalization is high (low), companies choose portfolios with a high (small) share of risky assets. We show that this phenomenon may have the same source as the underwriting cycle, namely recapitalization costs. We build a simple dynamic model of the insurance sector where ﬁ nancial frictions prevent companies from maintaining a target leverage. Portfolio decisions of insurers ﬂ uctuate with their aggregate capitalization. The model rationalizes two apparently disjoint pieces of evidence: long-standing Elisa empirical evidence on underwriting cycles and more recent evidence on the ﬂ uctuations of insurance companies’ risk appetite.
Time Parameter Mapping and Contour Error Precompensation for Multiaxis Input Shaping

When the trajectory with high speed and high acceleration contains frequency contents matching with the structure mode, the inertial vibration of the structure is easily excited, reducing machining accuracy and surface finish. Input shaping can avoid vibration, but it introduces time-delay that causes multiaxis trajectory distortion and affects the accuracy of contour error estimation. This article presents time parameter mapping and contour error precompensation for multiaxis input shaping to suppress vibration. The mapping of time parameter domain of trajectories is established by deducing the relation between the local curvature extremums of the trajectories before and after shaping, which provides reference points for contour error estimation. The actual trajectory is predicted by the closed-loop servo dynamics model and reference trajectory, and then the Newton iterative algorithm based on time parameter mapping is used to seek the contour error point. Finally, the calculated contour error is low-pass filtered and projected to each axis, and then the shaped trajectory is precompensated to simultaneously reduce the contour error and avoid structural vibration. Comparative experiments are conducted to validate the effectiveness of the proposed method. Experimental results illustrate that the proposed method not only suppresses structural vibration, but also significantly improves the estimation accuracy and contouring performance by time parameter mapping.
Non-Orthogonal Multiple Access-Based Average Age of Information Minimization in LEO Satellite-Terrestrial Integrated Networks

In this paper, we investigate non-orthogonal multiple access (NOMA) based average age of information (AoI) in LEO satellite-terrestrial integrated networks. Two-user NOMA scheme is used in terrestrial networks and several satellites provide orthogonal access for the rest of users to update status packets. Firstly, the closed-form expressions of average AoI in terrestrial networks and satellite channels are derived with average block error rate. Then, the average AoI minimization problem is decomposed into two parts: 1) average AoI minimization in terrestrial networks and 2) average AoI minimization among satellites. In the first part, a base station-terrestrial user selection and transmit power optimization algorithm is proposed for choosing the optimal NOMA pair and transmit power to minimize average AoI in each BS. A coalition formation game (CFG) is formulated to minimize average AoI among satellites in second part. With the proposed Min-AoI order, the CFG is theoretically proven to be an exact potential game, which can achieve total average AoI minimization of all satellite users. A distributed CFG-based algorithm is proposed for SUs grouping with low complexity. Finally, numerical results are provided to verify the correctness of theoretical analysis and evaluate our proposed algorithms, compared with other schemes.