Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting a Responsible Ecotourist Behaviour: Pilot Study

In sustainable ecotourism, responsible ecotourist behaviour towards purchasing local products and services is vital to alleviate poverty in local communities and help wildlife conservation. Using an extended Theory of Planned Behaviour, this study investigates the relationship between attitude, anticipated emotion, and environmental concern. This pilot study was conducted to test the reliability of the questionnaire instrument before conducting the actual research. Data collection was conducted in Penang National Park, and questionnaires were distributed face to face among the ecotourist. Samples were obtained using the purposive sampling method. Statistical Software Packages, namely SPSS version 26.0, were used to perform data analysis. The high internal consistency of items among the constructs shows that the questionnaires are reliable in conducting actual research in predicting responsible ecotourist behaviour (Cronbach Alpha value ranges from 0.883 to 0.604).
Fixed-time flocking formation of nonlinear multi-agent system with uncertain state perturbation

ABSTRACT This paper aims to solve the control problem of fixed-time rigid formation for a class of nonlinear multi-agent systems with uncertain state perturbation and external disturbance. Firstly, in order to compensate the system uncertainty with uncertain dynamics and disturbances in fixed-time, an adaptive disturbance state observer independent of the initial state is therefore designed. Secondly, a fixed-time flocking control strategy is proposed by combining backstepping control method with fixed time control. It is strictly proved that the designed controller realises the fixed-time boundedness of the closed-loop error system independent of the initial state based on the rigidity theory and Lyapunov framework. Finally, the performance of the observer and controller is verified by numerical simulation, and the flocking formation control of a class of UAV group is realised on the simulation platform based on UE4.
Critical PDT Theory III: Events at the Molecular and Cellular Level

Photodynamic therapy (PDT) is capable of eradicating neoplastic cells that are accessible to sufficient light and oxygen. There is adequate information now available for assessing conditions where PDT might be the therapy of choice, but limited access to clinical facilities and impediments to regulatory approval of new agents have limited clinical usage. Early reports mainly involved clinical data with few thoughts towards finding death pathways. In 2022, there is a clear understanding of the determinants of successful tumor eradication. While PDT may be the optimal method for many clinical indications, support for this approach has lagged. This report provides a commentary on some elements of recent progress in PDT at the molecular and cellular levels, along with a discussion of some of the limitations in current research efforts.
Influence of sensory integration training on sensory motor functions in patients with thalamic syndrome

Introduction. Thalamic stroke causes impairment in sensory motor functions; these changes in perception lead to pain and deteriorate postural stability. The goal of this study was to investigate the influence of sensory integration training on pain and posture stability in patients with thalamic syndrome. Methods. overall, 30 patients of both sexes, aged 45–65 years, diagnosed with a thalamic stroke were randomly allocated into 2 groups. The control group received selected sensory training of the conventional physical therapy program and the study group received sensory integration training with the Biodex Balance System beside the conventional physical therapy program. Results. The intra-group comparisons with MANoVA revealed statistically insignificant differences in pain, as well as overall, anteroposterior (forward and backward), and mediolateral (right and left) limits of stability after the treatment in the control group (p-value of 0.180, 0.301, 0.792, 0.247, 0.381, and 0.847, respectively). in the study group, there was a statistically significant decrease in pain and improvement in overall, anteroposterior (forward and backward), and mediolateral (right and left) limits of stability after the treatment (p-value of 0.01 for pain and 0.000 for each of the 5 limit of stability variables, respectively). The inter-group comparisons showed statistically significant differences in favour of the study group (p = 0.000). Conclusions. Adding the sensory integration training program was effective to decrease pain and improve posture stability in patients with thalamic syndrome.
Development of low-cost heterodyne interferometer with virtual electronic phasemeter

Commercial laser interferometers are conventionally used to measure the positioning error of a long linear stage in multiaxis computer numerical control machine tools. However, commercial laser interferometers are costly and difficult to use. Therefore, a low-cost photodetector-based heterodyne interferometer combined with an electronic phasemeter module was proposed for precise measurement of the positioning error of a long linear stage. The proposed heterodyne interferometer was combined with a virtual electronic phasemeter that employs a self-developed signal-processing technique. Our core algorithm and proposed photoelectric-signal-processing technique were developed using the LabVIEW human–machine interface. Moreover, to verify the performance of the proposed heterodyne interferometer, a laboratory-built prototype was constructed and used to measure the positioning error of a long linear stage. The experimental results indicated that the positioning accuracy of the proposed interferometer was ±4.5 μm for a linear stage with a displacement of 250 mm; the results obtained were comparable to those obtained with a commercially available laser interferometer. The proposed heterodyne interferometer can thus be used in other applications related to precision engineering.
A Hybrid Material Generation Algorithm with Probabilistic Neural Networks for Solving Classification Problems

—Classification is based on machine learning, in which each element in a set of data is classified into one of a predetermined set of groups. In data mining, an artificial neural network (ANN) is the most significant methodology because of the exact results obtained through this algorithm and applied in solving many classification problems. ANN consists of a group of types of feed-forward networks, feed-back network, RFB networks, and the probabilistic neural networks (PNN). For classification issues, the PNN is frequently utilized. The primary goals of this research are to fine-tune the weights of neural networks to enhance the classiﬁcation accuracy. To accomplish this goal, the Material Generation Algorithm (MGA) was investigated with PNN in a hybrid model. Newly, the hybridization of algorithms is ubiquitous and it has led to the development of unique procedures that outperform those that use a single algorithm. Several distinct classification tasks are used to test the efficiency of the suggested (MGA-PNN) approach. The MGA algorithm's efficiency is evaluated using the PNN training outcomes generated, and its outcomes are compared to that of other optimization strategies. By 11 benchmark datasets, the suggested algorithm's performance in terms of classification accuracy is evaluated. The outcomes display that the MGA outperforms the biogeography based optimization, firefly method in terms of classification accuracy.
Exploratory Investigation of the Plasma Proteome Associated with the Endotheliopathy of Trauma

Background: The endotheliopathy of trauma (EoT) is associated with increased mortality following injury. Herein, we describe the plasma proteome related to EoT in order to provide insight into the role of the endothelium within the systemic response to trauma. Methods: 99 subjects requiring the highest level of trauma activation were included in the study. Enzyme-linked immunosorbent assays of endothelial and catecholamine biomarkers were performed on admission plasma samples, as well as untargeted proteome quantification utilizing high-performance liquid chromatography and tandem mass spectrometry. Results: Plasma endothelial and catecholamine biomarker abundance was elevated in EoT. Patients with EoT (n = 62) had an increased incidence of death within 24 h at 21% compared to 3% for non-EoT (n = 37). Proteomic analysis revealed that 52 out of 290 proteins were differentially expressed between the EoT and non-EoT groups. These proteins are involved in endothelial activation, coagulation, inflammation, and oxidative stress, and include known damage-associated molecular patterns (DAMPs) and intracellular proteins specific to several organs. Conclusions: We report a proteomic profile of EoT suggestive of a surge of DAMPs and inflammation driving nonspecific activation of the endothelial, coagulation, and complement systems with subsequent end-organ damage and poor clinical outcome. These findings support the utility of EoT as an index of cellular injury and delineate protein candidates for therapeutic intervention.
Train Driver Fatigue Detection Using Eye Feature Vector and Support Vector Machine

Fatigue driving is one of the main causes of traffic accidents. The eye features are the important cues of fatigue detection. In order to improve the accuracy and robustness of detection based on a single eye feature, we propose a fatigue detection algorithm based on the eye feature (EFV) vector. Firstly, the coordinates of the eye region were localized with facial landmarks detector and the landmarks geometric relation (LGR) was calculated as a feature value. Secondly, a deep transfer learning network was designed to classify the driver eye state on a small dataset. The probability value of the eyes being open state was calculated. Then an eye feature vector was constructed to overcome the limitations of a single fixed threshold and a support vector machine (SVM) model was trained for eye state classification recognition. Finally, the performance of the proposed detection model was evaluated by the percentage of eyelid closure over time (PERCLOS) criterion. The results show that the accuracy of this model can reach 91.67% on the test database, which is higher than the single-feature-based method. This work lays a foundation for the online fatigue detection of train drivers and the deployment of the train driving monitoring system.
Evidence of regional sea-level rise acceleration for the North Sea

Global mean sea-level rise (SLR) has accelerated since 1900 from less than 2 mm yr−1 during most of the century to more than 3 mm yr−1 since 1993. Decision-makers in coastal countries, however, require information on SLR at the regional scale, where detection of an acceleration in SLR is difficult, because the long-term sea-level signal is obscured by large inter-annual variations with multi-year trends that are easily one order of magnitude larger than global mean values. Here, we developed a time series approach to determine whether regional SLR is accelerating based on tide gauge data. We applied the approach to eight 100-year records in the southern North Sea and detected, for the first time, a common breakpoint in the early 1990s. The mean SLR rate at the eight stations increases from 1.7 ± 0.3 mm yr−1 before the breakpoint to 2.7 ± 0.4 mm yr−1 after the breakpoint (95% confidence interval), which is unprecedented in the regional instrumental record. These findings are robust provided that the record starts before 1970 and ends after 2015. Our method may be applied to any coastal region with tidal records spanning at least 40 years, which means that vulnerable coastal communities still have time to accumulate the required time series as a basis for adaptation decisions in the second half of this century.
Numerical Analysis Of a Falling Circular Particle Passing through a Fluid Channel having Diamond Shaped Obstacles

It has been analyzed that the particle motion inside a vertical channel while passing across diamond shaped obstacles produces severe effects on the fluid. Particle interaction with outer boundary, internal obstacles and with the fluid is inspected. An Eulerian based approach using a computational mesh is used in which solid particles are allowed to move freely in fluid domain. Fluid and particle interaction inside the whole domain is carried using Fictitious boundary method (FBM). A multigrid finite element method combined with the fictitious boundary method (FEM-FBM) is used for the simulation of in-compressible fluid flow along with rigid particle falling and colliding inside a fluid domain. A collision model to treat the Particle-obstacle and particle-wall interactions is used to avoid particle overlapping. The particulate flow is evaluated using an open source multigrid finite element solver FEATFLOW. Numerical investigations are executed in view of different particle positions and different alignment of diamond shaped obstacles. Effects on the movement of the particle and on the interaction of the fluid-particle system due to particle-wall, particle-Obstacle, particle-fluid interactivity has been analyzed.
Genome Sequencing of Amomum tsao-ko Provides Novel Insight Into Its Volatile Component Biosynthesis

As an important economic and medicinal crop, Amomum tsao-ko is rich in volatile oils and widely used in food additives, essential oils, and traditional Chinese medicine. However, the lack of the genome remains a limiting factor for understanding its medicinal properties at the molecular level. Here, based on 288.72 Gb of PacBio long reads and 105.45 Gb of Illumina paired-end short reads, we assembled a draft genome for A. tsao-ko (2.70 Gb in size, contig N50 of 2.45 Mb). Approximately 90.07% of the predicted genes were annotated in public databases. Based on comparative genomic analysis, genes involved in secondary metabolite biosynthesis, flavonoid metabolism, and terpenoid biosynthesis showed significant expansion. Notably, the DXS, GGPPS, and CYP450 genes, which participate in rate-limiting steps for terpenoid backbone biosynthesis and modification, may form the genetic basis for essential oil formation in A. tsao-ko. The assembled A. tsao-ko draft genome provides a valuable genetic resource for understanding the unique features of this plant and for further evolutionary and agronomic studies of Zingiberaceae species.
Neighbouring countries and bilateral remittances: a global study

ABSTRACT We measure to what extent neighbouring countries affect the amount of remittances between a source and a recipient country, controlling for the commonly used macro determinants of remittances. We provide novel evidence on the importance of neighbouring countries, with the parameter estimates capturing origin and destination spatial dependence being positive and significant. Disregarding the role of neighbouring countries leads to biased estimates and misprediction. Indeed, when we correctly account for the role of neighbouring countries, prediction errors decrease by 44% when we express bilateral remittances in nominal terms and by 31% when remittances are in logarithm. Next, we present evidence supporting the altruism, the investment and the financial friction motives to remit, with the altruism motive being the one that contributes the most to explain expected remittances. As an application of our model, we show that, following the Covid-19 shock, remittances are expected to decrease less in countries with smaller income per capita. This is good news for low- to middle-income countries.
Scistarter 2.0: A digital platform to foster and study sustained engagement in citizen science

In this chapter, the authors focus on how SciStarter has developed a new digital infrastructure to support sustained engagement in citizen science, and research into the behaviors and motivations of participants. The new digital infrastructure of SciStarter includes integrated registration and contribution tracking tools to make it easier to participate in multiple projects, enhanced GIS information to promote locally relevant projects, an online personal dashboard to keep track of contributions, and the use of these tools (integrated registration, GIS, dashboard) by project owners and researchers to better understand and respond to the needs and interests of citizen-science participants. In this chapter, the authors explore how these new tools build pathways to participatory policymaking, expand access to informal STEM experiences, and lower barriers to citizen science. The chapter concludes with a design for a citizen-science future with increased access to tools, trackable participation, and integrated competencies.
Studies of Phytochemicals, Antioxidant, and Antibacterial Activities of Pinus gerardiana and Pinus roxburghii Seed Extracts

Pine seeds are considered as nonwood forest products (NWFP) with regularly increasing market's demand. They can be eaten in various ways such as roasted or raw. In addition, they are included in various traditional dishes like in cookies, sauces, candies, cakes, breads, and other bakery items and, moreover, for medicinal purposes. GC-MS study is performed to analyze the phytochemical compounds present in the seed extracts of Pinus roxburghii (Chir) and Pinus gerardiana (Chilgoza). In total, 25 compounds were identified each in Chir and Chilgoza. In Chir seeds, abundantly present compounds were 2,4-di-tert-butylphenol (16.6%), followed by ç-Terpinene (9.9%) and cyclohexanol, 4-ethenyl-4-methyl-3-(1-methylethenyl)-, (1à,3à,4á) (9.8%), whereas in Chilgoza seeds, the maximum amount of compound was 1-hexyl-1-nitrocyclohexane (17.3%), followed by phenol, 2,6-bis(1,1-dimethylethyl) (15.4%), and heptadecane, 2-methyl (8.4%). The total phenolic content of Chir seed sample was 1536 ± 4.35 (mg GAE/100 g), whereas in the Chilgoza seed extract was 642.66 ± 2.08 (mg GAE/100 g). The application of RP-HPLC-DAD system revealed that Chir and Chilgoza seeds have maximum quantity of catechin (15.77 ± 0.16 μg/mg and 17.49 ± 0.32 μg/mg, respectively). Both Chir and Chilgoza seed extracts exhibited significant antioxidant (radical scavenging) potential, through H2O2 (618.94 ± 21.45 μg/mL and 575.16 ± 19.88 μg/mL) and DPPH (552.60 ± 13.03 μg/mL and 429.15 ± 3.80 μg/mL) assays, respectively. Additionally, a well-known antibacterial potential was also found in both plants' dichloromethane extracts, with 64 to 256 μg/mL of minimum inhibitory concentrations. As a whole, result shows the importance of both plants as a naturally occurring phytochemical source with significant antibacterial and antioxidant activity.
Phylogenetic Analysis of the Complete Mitochondrial Genomes in the Ten Rupicapra Subspecies and Implications for the Existence of Multiple Glacial Refugia in Europe

Simple Summary The successive glaciations that took place during the Pleistocene shaped de distribution of temperate species in Europe, both plants and animals. Traditionally, it has been hypothesized that during the coldest periods, species took refuge in three areas of southern Europe (Iberian, Italian and Balkan peninsulas) and then recolonized the north when temperatures rose and conditions were more favorable. In the present work, the complete mitochondrial sequences of the ten described chamois populations have been analyzed to identify which areas of the continent have served as refuges for the species during the glaciations. The results of the present work are consistent with the existence of multiple glacial refugia across Europe, revealing a much more complex picture of the effect of glaciations on the genetics of temperate species than is commonly accepted, giving us a better understanding of how past events determine the present species. Abstract The current distribution of populations in Europe is marked by the effects of glaciations that occurred during the Pleistocene. Temperate species were isolated in glacial refugia that were the sources of postglacial recolonization. The traditional glacial refuge areas were the Iberian, the Italian and the Balkan peninsulas. Here we revisit the evolutionary history of chamois (Rupicapra genus) to evaluate other sites in continental Europe and Anatolia that have been suggested as potential refuges. We have obtained the complete mitochondrial sequence of seven chamois, including the subspecies parva, carpatica, caucasica, and asiatica whose mitochondrial genome had not been yet reported. These, together with the other fourteen sequences already in the GenBank, represent the different geographical populations of the Rupicapra genus. The phylogenetic analysis showed the three old clades, dating from the early Pleistocene, already reported: mtW in the Iberian Peninsula, mtC in the Appenines and the Massif of Chartreuse, and mtE comprising all the population from the Alps to the east. The genomes within each of the clades mtW and mtE, showed divergence times larger than 300 thousand years. From here, it can be argued that the present-day lineages across Europe are very old and their split dates back to the middle Pleistocene.
Ontology Extraction from Software Requirements Using Named-Entity Recognition

With the software playing a key role in most of the modern, complex systems it is extremely important to create and keep the software requirements precise and non-ambiguous. One of the key elements to achieve such a goal is to define the terms used in a requirement in a precise way. The aim of this study is to verify if the commercially available tools for natural language processing (NLP) can be used to create an automated process to identify whether the term used in a requirement is linked with a proper definition. We found out, that with a relatively small effort it is possible to create a model that detects the domain specific terms in the software requirements with a precision of 87%. Using such model it is possible to determine if the term is followed by a link to a definition.
Population aging and medical cost growth—From the perspective of medical cost concentration and Sustainability

This paper examines the causes of increasing medical expenses caused by population aging from the aspects of concentration and sustainability. Counterfactual calculation shows that the important fact that population aging increases medical expenses at different quantiles and reduces the distribution gap of medical expenses is rooted in the high concentration and strong sustainability of medical expenses of the elderly population. The medical expenses of the elderly population not only have the characteristics of high single hospitalization expenses, large proportion of continuous hospitalization and strong dispersion of medical expenses, but also have a heavier expenditure burden in the five medical expense levels. The influence of population aging on the growth of medical expenses is lower than that of the change of age structure of the whole population. The influence of endowment effect increases with time, and the increase of high score medical expenses is the most obvious. In addition, the improvement of health awareness plays a leading role in the structural effect affecting the growth of medical expenses. By constructing the theoretical logic that the medical needs of the elderly population affect the medical expenses, this paper strongly explains the reality of the rapid growth of medical expenses under the background of China’s aging population.