Miracle-dz/UniFAR-FTUs huggingface dataset:
CCAM: China Catchment Attributes and Meteorology dataset

Abstract. The absence of a compiled large-scale catchment characteristics dataset is a key obstacle limiting the development of large-sample hydrology research in China. We introduce the first large-scale catchment attribute dataset in China. We compiled diverse data sources, including soil, land cover, climate, topography, and geology, to develop the dataset. The dataset also includes catchment-scale 31-year meteorological time series from 1990 to 2020 for each basin. Potential evapotranspiration time series based on Penman's equation are derived for each basin. The 4911 catchments included in the dataset cover all of China. We introduced several new indicators that describe the catchment geography and the underlying surface differently from previously proposed datasets. The resulting dataset has a total of 125 catchment attributes and includes a separate HydroMLYR (hydrology dataset for machine learning in the Yellow River Basin) dataset containing standardized weekly averaged streamflow for 102 basins in the Yellow River Basin. The standardized streamflow data should be able to support machine learning hydrology research in the Yellow River Basin. The dataset is freely available at https://doi.org/10.5281/zenodo.5729444 (Zhen et al., 2021). In addition, the accompanying code used to generate the dataset is freely available at https://github.com/haozhen315/CCAM-China-Catchment-Attributes-and-Meteorology-dataset (last access: 26 November 2021) and supports the generation of catchment characteristics for any custom basin boundaries. Compiled data for the 4911 basins covering all of China and the open-source code should be able to support the study of any selected basins rather than being limited to only a few basins.
Implementation of CPG based locomotion controller on Minimule Robot

Creating effective locomotion for legged robots is a very challenging task especially in an unknown environment. Currently, most research works on locomotion control are focused on the trajectory based method. Here we are implementing a biologically inspired Central Pattern Generator(CPG) based controller for a quadruped Minimule robot. This local control system of quadruped animals is modelled through an artificial neural oscillator based structure. The robot was first modelled using MSC ADAMS and integrated with MATLAB for simulation. This paper deals with parameter modulation of the CPG network, the gait transition for the robot and environment adaptability through limit cycle stability. Various parameters for locomotion like frequency, velocity and gait can be obtained just by changing a single parameter, the duty factor. The CPG based Minimule robot can achieve both trot and walk gait by varying the phase relationship between the limbs and is stable due to the inherent property of CPG.
Expected Extinction Times of Epidemics With State-Dependent Infectiousness

We model an epidemic where the per-person infectiousness in a network of geographic localities changes with the total number of active cases. This would happen as people adopt more stringent non-pharmaceutical precautions when the population has a larger number of active cases. We show that there exists a sharp threshold such that when the curing rate for the infection is above this threshold, the expected time for the epidemic to die out is logarithmic in the initial infection size, whereas when the curing rate is below this threshold, the expected time for epidemic extinction is infinite. We also show that when the per-person infectiousness goes to zero asymptotically as a function of the number of active cases, the expected extinction times all have the same asymptote independent of network structure. We make no mean-field assumption while deriving these results. Simulations on real-world network topologies bear out these results, while also demonstrating that if the per-person infectiousness is large when the epidemic size is small (i.e., the precautions are lax when the epidemic is small and only get stringent after the epidemic has become large), it might take a very long time for the epidemic to die out. We also provide some analytical insight into these observations.
International Business Decision-Making in Family Small and-Medium-Sized Enterprises

Family firm internationalization has become a topic of interest over the last few decades. However, there has been surprisingly little research about the actual international business decision-making in the family firm literature. The purpose of this article is to highlight specific family firm factors which affect the international business decision-making. Based on examples on international market entry, target market choice, entry mode choice, and entry timing decisions, it is suggested that long-term and regional orientation, knowledge-base and its transfer, bifurcation-bias, and perseverance of family managers are important factors affecting international business decision-making among family SMEs.
Time perspective as predictor of perceived stress in managers

The aim of this study was to determine relation between dimensions of time perspective and perceived stress among managers, who have one to three years of working experience as managers. The basic assumption was that dimensions of time perspective are empirically confirmed correlates of numerous psychic functions, thus they can also be correlates of perceived stress. Therefore, we set hypothesis that dimensions of time perspective are significant predictors of perceived stress in managers. The study was conducted on the sample of 92 managers of both genders (37% of men and 63% of women). Average age of examinees was 36.58 years. Selective variable for formation of the sample was the length of working experience in management - from minimum one up to maximum three years. The assumption for the sample justification was that managers-beginners experience bigger number of stimuli from the environment as stressors. An adapted version of Zimbardo's time perspective questionnaire (ZTPI, Zimbardo & Boyd, 1999, adaptation of Kostić & Nedeljković, 2013) was used to operationalize the time perspective. The questionnaire with 52 items determines five dimensions of time perspective - negative and positivie past, hedonistic and fatalistic present and future. Perceived stress is determined by score on Cohen's questionnaire for perceived stress (The Perceived Stress Scale, PSS-10, Cohen et al, 1983). Significant regression model was obtained, which explains 17,6% variance in perception of stress in managers. As the only independently significant predictor in the group of dimensions of time perspective, future was highlighted (b = 0,416). Managers who are turned towards the future have higher scores of the perceived stress. The results confirmed the initial assumption on predictor power of dimensions of time perspective in predicting intensity of the perceived stress. The results represent contribution to understanding the relationship between dimensions of time perspective and stress perception during the first years of management and may be the starting point for future research of those constructs.
Electromyographic study assessing swallowing function in subacute stroke patients with respiratory muscle weakness

Abstract Background: Dysphagia has been reported to be associated with the descent of the hyolaryngeal complex. Further, suprahyoid muscles play a greater role than infrahyoid muscles in elevation of the hyolarngeal complex. Respiratory muscle training (RMT) can improve lung function, and expiratory muscle strength training can facilitate elevation of the hyoid bone and increase the motor unit recruitment of submental muscles during normal swallowing. This study aimed to investigate the surface electromyography (sEMG) of the swallowing muscles, bilaterally, and the effect of RMT on swallowing muscles in stroke patients with respiratory muscle weakness. Methods: Forty patients with first episode of unilateral stroke were included in this retrospective controlled trial. After exclusion of 11 patients with respiratory muscle strength stronger than 70% of the predicted value, 15 were allocated to the RMT group and 14 to the control group. However, eventually, 11 patients in RMT group and 11 patients in control group completed the study. The sEMG of the orbicularis oris, masseter, submental, and infrahyoid muscles were recorded during dry swallowing, water swallowing (2 mL), and forced exhalation against a threshold breathing trainer set at different intensities, at baseline and after 6-week RMT. Results: Regarding the sEMG of submental muscles, there were significant between-group differences on the latency of the unaffected side (P = .048), significant change from baseline force on the unaffected side (P = .035), and significant between-side difference (P = .011) in the RMT group during dry swallowing. Significant change in the duration from baseline was observed on the affected side of the RMT group when blowing was set at 50% maximal expiratory pressure (MEP; P = .015), and on the unaffected side of the control group when blowing set at 15% MEP (P = .005). Significant difference was observed in the duration between 50% MEP and 15% MEP after 6-week program in the control group (P = .049). Conclusions: A 6-week RMT can improve the electric signal of the affected swallowing muscles with more effect on the unaffected side than on the affected side during dry swallowing. Furthermore, RMT with 50% MEP rather than 15% MEP can facilitate greater submental muscle activity on the affected side in stroke patients with respiratory muscle weakness.
Sustainable Stabilizer-Free Nanoparticle Formulations of Valsartan Using Eudragit® RLPO

The bioavailability of the antihypertensive drug valsartan can be enhanced by various microencapsulation methods. In the present investigation, valsartan-loaded polymeric nanoparticles were manufactured from Eudragit® RLPO using an emulsion–solvent evaporation method. Polyvinyl alcohol (PVA) was found to be a suitable stabilizer for the nanoparticles, resulting in a monodisperse colloid system ranging in size between 148 nm and 162 nm. Additionally, a high encapsulation efficiency (96.4%) was observed. However, due to the quaternary ammonium groups of Eudragit® RLPO, the stabilization of the dispersion could be achieved in the absence of PVA as well. The nanoparticles were reduced in size (by 22%) and exhibited similar encapsulation efficiencies (96.4%). This more cost-effective and sustainable production method reduces the use of excipients and their expected emission into the environment. The drug release from valsartan-loaded nanoparticles was evaluated in a two-stage biorelevant dissolution set-up, leading to the rapid dissolution of valsartan in a simulated intestinal medium. In silico simulations using a model validated previously indicate a potential dose reduction of 60–70% compared to existing drug products. This further reduces the expected emission of the ecotoxic compound into the environment.
Hemodynamics Challenges for the Navigation of Medical Microbots for the Treatment of CVDs

Microbots have been considered powerful tools in minimally invasive medicine. In the last few years, the topic has been highly studied by researchers across the globe to further develop the capabilities of microbots in medicine. One of many applications of these devices is performing surgical procedures inside the human circulatory system. It is expected that these microdevices traveling along the microvascular system can remove clots, deliver drugs, or even look for specific cells or regions to diagnose and treat. Although many studies have been published about this subject, the experimental influence of microbot morphology in hemodynamics of specific sites of the human circulatory system is yet to be explored. There are numerical studies already considering some of human physiological conditions, however, experimental validation is vital and demands further investigations. The roles of specific hemodynamic variables, the non-Newtonian behavior of blood and its particulate nature at small scales, the flow disturbances caused by the heart cycle, and the anatomy of certain arteries (i.e., bifurcations and tortuosity of vessels of some regions) in the determination of the dynamic performance of microbots are of paramount importance. This paper presents a critical analysis of the state-of-the-art literature related to pulsatile blood flow around microbots.
Predicting Movie Success: Review of Existing Literature

Indian Hindi Cinema industry popularly known as Bollywood has reached staggering proportions in terms of volume of business (184.3 billion), manpower employment (over 6 million workers), movies produced (more than 100 in a year) and its reach (exported to more than 100 countries worldwide). With so much at stake and highly uncertain nature of returns, it is of commercial interest to develop a model which can predict success of a movie. This however, is not an easy work, since movies have been described as experience goods with very less shelf life; it is difficult to forecast demand for a movie. There are number of parameters that may influence success of a movie like - time of its release, marketing gimmicks, lead actor, lead actress, director, producer, writer, music director - being some of the factors. The present study aims to develop a model based upon neural networks that may help in predicting the success of a movie in advance thereby reducing certain level of uncertainty.
Acute Myocardial Infarction in Young Men Under 50 Years of Age: Clinical Characteristics, Treatment, and Long-Term Prognosis

Aim The prevalence of acute myocardial infarction (AMI) is increasing in young adults, especially in men. This study aims to compare the characteristics and explore the association between age and clinical outcomes in male adults who first experienced AMI. Methods A total of 2737 male patients with AMI were divided into three groups by age: <50, 50–65, and ≥65 years. Clinical characteristics and long-term results (all-cause and cardiac deaths, nonfatal MI, revascularization, nonfatal stroke, cardiac rehospitalization) were identified across different age subgroups. The association between age and the outcomes was assessed by Cox proportional hazard models. Results This population was followed up for a median of 36.7 months. Patients <50 years had a lower prevalence of diabetes (19.4%) and previous stroke (1.8%), while they were more often to be smokers (77.1%), obese (26%), dyslipidemia (74.7%), and with the single-vessel disease (16.2%). The risk of cardiovascular and all-cause death in patients ≥65 years was higher than patients <50 years, which was noticed through competing risk regression analysis after adjusting for confounding factors (adjusted HR 3.24; 95% CI 2.26–4.22, p=0.020 for cardiovascular death, adjusted HR 4.17; 95% CI 1.91–9.10, p<0.001 for all-cause death). Conclusion In conclusion, although men who suffered from first AMI under the age of 50 had lower mortality, they had a higher burden of modifiable traditional risk factors. The management of modifiable lifestyles should be addressed to all young AMI patients.
Generating Synthetic Receiver Functions Using Seismic Interferometry

Receiver functions have a wealth of crustal information and are useful to study the lithosphere. They require a powerful impulsive source like earthquakes and must be a teleseismic event from the receiver station. Such requirements does not always guarantee a good azimuthal coverage from the station which is essential to get good accurate results. Seismic interferometry is used to generate virtual impulsive sources of energy and synthesize synthetic receiver functions which provides additional azimuthal coverage. Such receiver functions can be stacked with other receiver functions having the same back azimuthal characteristics to obtain better crustal information.
Prognostic Factors and Clinical Considerations for Iron Chelation Therapy in Myelodysplastic Syndrome Patients

Abstract Iron chelation therapy (ICT) is an important tool in the treatment of transfusion-dependent lower-risk myelodysplastic syndrome (MDS) patients. ICT is effective in decreasing iron overload and consequently in limiting its detrimental effects on several organs, such as the heart, liver, and endocrine glands. Besides this effect, ICT also proved to be effective in improving peripheral cytopenia in a significant number of MDS patients, thus further increasing the clinical interest of this therapeutic tool. In the first part of the review, we will analyze the toxic effect of iron overload and its mechanism. Subsequently, we will revise the clinical role of ICT in various subsets of MDS patients (low, intermediate, and high risk MDS, patients who are candidates for allogeneic stem cell transplantation).
Inner Properties Estimation of Gala Apple Using Spectral Data and Two Statistical and Artificial Intelligence Based Methods

Fruits provide various vitamins to the human body. The chemical properties of fruits provide useful information to researchers, including determining the ripening time of fruits and the lack of nutrients in them. Conventional methods for determining the chemical properties of fruits are destructive and time-consuming methods that have no application for online operations. For that, various researchers have conducted various studies on non-destructive methods, which are currently in the research and development stage. Thus, the present paper focusses on a non-destructive method based on spectral data in the 200–1100-nm region for estimation of total soluble solids and BrimA in Gala apples. The work steps included: (1) collecting different samples of Gala apples at different stages of maturity; (2) extracting spectral data of samples and pre-preprocessing them; (3) measuring the chemical properties of TSS and BrimA; (4) selecting optimal (effective) wavelengths using artificial neural network-simulated annealing algorithm (ANN-SA); and (5) estimating chemical properties based on partial least squares regression (PLSR) and hybrid artificial neural network known as the imperialist competitive algorithm (ANN-ICA). It should be noted that, in order to investigate the validity of the methods, the estimation algorithm was repeated 500 times. In the end, the results displayed that, in the best training, the ANN-ICA predicted the TSS and BrimA with correlation coefficients of 0.963 and 0.965 and root mean squared error of 0.167% and 0.596%, respectively.
Synthesis of the unmanned aerial vehicle remote control augmentation system

Medium size Unmanned Aerial Vehicle (UAV) usually flies as an autonomous aircraft including automatic take-off and landing phases. However in the case of the on-board control system failure, the remote steering is using as an emergency procedure. In this reason, remote manual control of unmanned aerial vehicle is used more often during take-of and landing phases. Depends on UAV take-off mass and speed (total energy) the potential crash can be very danger for airplane and environment. So, handling qualities of UAV is important from pilot-operator point of view. In many cases the dynamic properties of remote controlling UAV are not suitable for obtaining the desired properties of the handling qualities. In this case the control augmentation system (CAS) should be applied. Because the potential failure of the on-board control system, the better solution is that the CAS algorithms are placed on the ground station computers. The method of UAV handling qualities shaping in the case of basic control system failure is presented in this paper. The main idea of this method is that UAV reaction on the operator steering signals should be similar - almost the same - as reaction of the "ideal" remote control aircraft. The model following method was used for controller parameters calculations. The numerical example concerns the medium size MP-02A UAV applied as an aerial observer system.Medium size Unmanned Aerial Vehicle (UAV) usually flies as an autonomous aircraft including automatic take-off and landing phases. However in the case of the on-board control system failure, the remote steering is using as an emergency procedure. In this reason, remote manual control of unmanned aerial vehicle is used more often during take-of and landing phases. Depends on UAV take-off mass and speed (total energy) the potential crash can be very danger for airplane and environment. So, handling qualities of UAV is important from pilot-operator point of view. In many cases the dynamic properties of remote controlling UAV are not suitable for obtaining the desired properties of the handling qualities. In this case the control augmentation system (CAS) should be applied. Because the potential failure of the on-board control system, the better solution is that the CAS algorithms are placed on the ground station computers. The method of UAV handling qualities shaping in the case of basic control system failu.
A simple tree planting framework to improve climate, air pollution, health, and urban heat in vulnerable locations using non‐traditional partners

Correspondence Deborah J. January-Bevers, Houston Wilderness, 1334 Brittmoore Rd, Suite 2804, Houston, TX 77043, USA. Email: deborah@houstonwilderness.org Societal Impact Statement Planting trees is considered an effective method for climate change adaptation and mitigation. This framework provides a replicable blueprint to improve health, urban heat, flooding, and air pollution via a multisectoral, collaborative, environmental datadriven approach. Native tree species with targeted ecosystem services are selected, and sites are strategically identified based on environmental and health benefits, with the intent of engaging community involvement through education and large-scale tree plantings. Including non-traditional partners in the framework provides heightened awareness of the relationship between climate change and health, thus catalyzing decision-making regarding sustainable actions that reduce effects of climate change. This native tree planting framework is highly adaptable in other cities. Summary • A multidisciplinary framework is presented for a data-driven, climate change adaptation and climate change and air pollution mitigation project. This framework leverages heightened awareness of the connections between climate change, air pollution, and health to expand the cadre and societal impacts of those working to intervene in resilience planning and implementation. • The framework, implemented in Houston, Texas, USA, beginning in 2019, consists of three parts: (1) identification of optimal native tree species for climate change adaptations and air pollution mitigation around variables important locally; (2) selection of large-scale native tree planting locations where populations are already disproportionately experiencing flooding, increased heat, and air pollution-related health effects that could be further exacerbated from climate change; and (3) engagement of multisectoral leadership broadened beyond those traditionally working on climate change resilience through heightening awareness of the link to human health. • Native tree species were identified that had the highest combination of absorption of carbon dioxide, other air pollutants, and water absorption (aiding in flood adaptation and air pollution/heat mitigation). Thousands of the top tree species were planted in locations that experience substantial flooding during large rain events, Received: 26 June 2021 Revised: 5 October 2021 Accepted: 22 October 2021 DOI: 10.1002/ppp3.10245