Miracle-dz/UniFAR-FTUs huggingface dataset:
Better, quicker, together : enabling public transport service quality co-monitoring through a smartphone-based platform

Public transport system is an important part of cities, and the quality of public transport service – passengers’ perceived performance – is a key urban indicator. Customer satisfaction surveys has been the traditional methods and metrics for monitoring and evaluating public transport service quality, but they come with a number of weaknesses. They are administered too infrequently and ask subjects to provide only general ratings. The infrequency results in potential delay for agencies to receive feedback, and the abstractness reduces the possibilities of associating satisfaction levels to specific trips and their attributes, as well as using the data to inform service improvement decisions. Given these shortcomings with conventional surveying practices, there is great value in engaging riders as additional sources of information. This reflects the concept of “comonitoring” – agencies using public feedback to supplement the official monitoring and regulation. This is aided by the growing ubiquity of Internet-connected mobile devices, which enables citizens to generate and submit feedback without time or geographic constraints. From the data collection perspective, this would make the process more dynamic, low-cost, and in real-time. Equally importantly, it is poised to enhance public transport agencies’ relationship with their customers – conveying to customers that their experience and feedback are valued. The service sector today is increasingly striving to be more responsive to the customers’ needs and experiences, seeking to strengthen the relationships with customers. The benefits of co-monitoring may help public transport agencies adapt to these current service paradigm shifts towards “real-time” and “ondemand. ” This thesis documents the creation and piloting of a smartphone-based platform for engaging customers in becoming co-monitors of the local bus service quality. Working with
Hazard Analysis Critical Control Points (HACCP) - Prerequisite Programs 1

The Institute of Food and Agricultural Sciences (IFAS) is an Equal Opportunity Institution authorized to provide research, educational information and other services only to individuals and institutions that function with non-discrimination with respect to race, creed, color, religion, age, disability, sex, sexual orientation, marital status, national origin, political opinions or affiliations. U.S. Department of Agriculture, Cooperative Extension Service, University of Florida, IFAS, Florida A&M University Cooperative Extension Program, and Boards of County Commissioners Cooperating. Nick T. Place , Dean In addition to the preliminary steps that should be followed when putting together a HACCP plan, there are certain programs that help provide a solid foundation for the plan. Some of these programs are required for certain food processing segments under HACCP regulations under the Food and Drug Administration (FDA) and the U.S. Department of Agriculture (USDA)/Food Safety and Inspection Service (FSIS). With the advent of HACCP regulations, some HACCP experts have suggested that the phrase “Prerequisite Programs” be used only for those programs required under regulation, in order to distinguish them from “Precursory Programs,” which are programs that have been deemed necessary, but are not required under regulation. In this discussion, however, the term Prerequisite Programs will be used to designate programs specified under regulations, as well as others deemed important to the HACCP system.
Applying multiple linear regression and quadratic curve fitting to predict Beijing's housing prices

This paper constructs a statistical model that could predict housing prices in Beijing. With the fast development of China's society, the real estate market has shown an incredible growth rate. For Beijing, as the capital of China, the housing market would be the most specific example for research. Thus, we gathered about 20 years of housing data from the official site to construct a statistical model to predict housing prices. Furthermore, we use predicted data compared with real data. Since China has strong central control, the market is most affected by policies, and we cannot quantify it. However, we chose several factors that could be put into the model, including income, GDP, population, consumption level, and GDP from construction. These factors are considered the most important elements that will affect housing prices and are the factors we use in our prediction model. In the end, we make the predictions for values in 2019 and 2020, and the predicted price has little difference from the actual data, which could demonstrate our model's accuracy. However, our model is built ideally, and for real-word prediction it needs to consider more unpredictable factors, such as central policies, social change, and so on.
Toxoplasmosis and Schizophrenia: A Systematic Review and Meta‐Analysis of Prevalence and Associations and Future Directions

Background A potential link between toxoplasmosis with schizophrenia (SCZ) has been extensively studied over the past 2 decades. Our study was aimed to determine whether, beyond an association, the field is primed for randomized clinical trials of anti‐Toxoplasma prophylaxis in Toxoplasma seropositive patients with SCZ. Methods We performed a methodological appraisal of toxoplasmosis‐SCZ association studies, a meta‐analysis, and a compilation of claims and pathophysiologic hypotheses. Results We analyzed 66 studies with 11,540 patients with SCZ and 69,491 controls. For patients with SCZ, 54 studies targeted Toxoplasma‐IgG seropositivity, 18 targeted Toxoplasma‐IgG serointensity, and 17 targeted Toxoplasma‐IgM seropositivity. For SCZ‐phenotypes, 26 targeted Toxoplasma‐IgG seropositivity, six targeted Toxoplasma‐IgG serointensity, and three targeted Toxoplasma‐IgM seropositivity. Two‐thirds of these studies reported a positive association. Statistically significant associations with SCZ were reported in 31/54 studies, 11/18 studies, and 3/17 studies. Significant associations with SCZ‐phenotypes were reported in 20/26 studies, 2/6 studies, and 0/3 studies, respectively. Toxoplasma‐IgG seropositivity increased the odds of SCZ (OR = 1.91; 95% CI: 1.61–2.27). Heterogeneity across studies was large (I 2 = 80.03%). Adjusted analyses for at least age and socioeconomic status/place of residence were done in 17 studies; temporality was addressed only in 4. Conclusion A large number of observational studies revealed a modest to large association between toxoplasmosis and SCZ. Although important methodological biases were identified, further association studies are unlikely to change this association and are not justified. It is time to test this association in randomized double‐blind placebo‐controlled clinical trials of first line anti‐Toxoplasma prophylaxis in Toxoplasma seropositive patients with SCZ.
A Qualitative Exploration into Beliefs of Pre-service EFL Teachers about School Experience

This qualitative study aims to explore the beliefs of Turkish pre-service EFL teachers about their school experiences and any change in their beliefs during this experience to identify their professional development as prospective teachers. For this purpose, ten Turkish pre-service EFL teachers at a state university in central Turkey reflected their experiences for one semester in the process of their teaching practice period for 14 weeks. The results reveal that pre-service teachers hold different beliefs about overall approaches to teaching and learning a foreign language, language use in the classroom, classroom management, and teaching grammar. The results also indicate a change in their beliefs related to questioning selves as teachers, teaching profession in general, use of technology in the classroom, using teaching techniques, and classroom management. The findings of this study also have implications for teacher education programs, particularly for the school experience component.
Trajectory Clustering for Air Traffic Categorisation

Availability of different types of data and advances in data-driven techniques open the path to more detailed analyses of various phenomena. Here, we examine the insights that can be gained through the analysis of historical flight trajectories, using data mining techniques. The goal is to learn about usual (or nominal) choices airlines make in terms of routing, and their relation with aircraft types and operational flight costs. The clustering is applied to intra-European trajectories during one entire summer season, and a statistical test of independence is used to evaluate the relations between the variables of interest. Even though about half of all flights are less than 1000 km long, and mostly operated by one airline, along one trajectory, the analysis shows that, for longer flights, there exists a clear relation between the trajectory clusters and the operating airlines (in about 49% of city pairs) and/or the aircraft types (30%), and/or the flight costs (45%).
Motion Planning of the Citrus-Picking Manipulator Based on the TO-RRT Algorithm

The working environment of a picking robot is complex, and the motion-planning algorithm of the picking manipulator will directly affect the obstacle avoidance effect and picking efficiency of the manipulator. In this study, a time-optimal rapidly-exploring random tree (TO-RRT) algorithm is proposed. First, this algorithm controls the target offset probability of the random tree through the potential field and introduces a node-first search strategy to make the random tree quickly escape from the repulsive potential field. Second, an attractive step size and a “step-size dichotomy” are proposed to improve the directional search ability of the random tree outside the repulsive potential field and solve the problem of an excessively large step size in extreme cases. Finally, a regression superposition algorithm is used to enhance the ability of the random tree to explore unknown space in the repulsive potential field. In this paper, independent experiments were carried out in MATLAB, MoveIt! , and real environments. The path-planning speed was increased by 99.73%, the path length was decreased by 17.88%, and the number of collision detections was reduced by 99.08%. The TO-RRT algorithm can be used to provide key technical support for the subsequent design of picking robots.
Study on the deployment of national top-level nodes

The status of national top-level nodes in the industrial internet are similar to the roots of the Domain Name System (DNS) of the Internet. With the increasingly mature development of the industrial Internet, the resolution pressure borne by national top-level nodes will be far greater than that of the root in DNS. It is very important for the identification and parsing system of industrial Internet to choose the appropriate deployment location for the national top-level node. This paper puts forward a set of research theory and model to determine the deployment position of national top-level node, which can be used to guide the construction of national top-level nodes of industrial Internet in the future.
Human-in-the-Loop Control of Soft Exosuits Using Impedance Learning on Different Terrains

Many previous works of soft wearable exoskeletons (exosuit) target at improving the human locomotion assistance, without considering the impedance adaption to interact with the unpredictable dynamics and external environment, preferably outside the laboratory environments. This article proposes a novel hierarchical human-in-the-loop paradigm that aims to produce suitable assistance powers for cable-driven lower limb exosuits to aid the ankle joint in pushing off the ground. It includes two primary loop layers: impedance learning in the external loop and human-in-the-loop adaptive management in the inner loop. Considering unknown terrains, its impedance model can be transferred to a quadratic programming problem with specified constraints, which a designed primal-dual optimization prototype then solves. Then, the presented impedance learning strategy is introduced to regulate the impedance model with the adaptive assistant powers for humans on different terrains. An adaptive controller is designed in the inner loop to balance the nonlinearities and compliance existing in the human-exosuit coexistence, while the robust mechanism compensates for disturbances to facilitate trajectory management without employing the general regressor. The advantage of the proposed technique over conventional solutions with fixed impedance parameters is that it can improve human walking performance over different terrains. Experiments demonstrate the significance of the approach.
Compressive full-waveform LIDAR with low-cost sensor

Full-waveform LiDAR is a method that digitizes the complete waveform of backscattered pulses to obtain range information of multi-targets. To avoid expensive sensors in conventional full-waveform LiDAR system, a new system based on compressive sensing method is presented in this paper. The non-coherent continuous-wave laser is modulated by electro-optical modulator with pseudo-random sequences. A low-bandwidth detector and a low-bandwidth analog-digital converter are used to acquire the returned signal. OMP algorithm is employed to reconstruct the high resolution range information.
Single Bounce Air to Ground Communication Channel Capacity for MIMO Applications

This paper addresses the air-to-ground communication problem, where multiple transmit antennas are used on the aircraft to combat multi-path interference. The channel is assumed to have a line-of-sight component and a single ground reflection. Multiple input multiple output (MIMO) techniques can be used in this situation, to increase the reliability and data rate. In this paper we discuss how the MIMO channel capacity changes, with the aircraft antenna configuration, altitude, velocity, range, and a number of other parameters. For comparison, the MIMO results are compared to systems which have single antennas at the transmitter, at the receiver, or at both ends.
Improved fuzzy sliding mode control in flexible manipulator actuated by PMAs

Abstract Pneumatic muscle actuator (PMA) similar to biological muscle is a new type of pneumatic actuator. The flexible manipulator based on PMAs was constructed to simulate the actual movement of the human upper arm. Considering the model errors and external disturbances, the fuzzing sliding mode control based on the saturation function was proposed. Compared with other fuzzy control methods, fuzzy control and saturation function are used to adjust the robust terms to improve the tracking accuracy and reduce the high-frequency chattering.
Research and Application on Reverse Engineering Used in NURBS Surface Modeling

The development situations of vane modeling in home and abroad are introduced.Due to the problem of different required data to vane shape and vane modeling,the surface data conversion from 2D to 3D is deduced.A reverse engineering method that uses NURBS to realize vane modeling is brought forward,which enhances the surface precision effectively.
The The dialogic nature of regulation in collaborative digital argumentative writing practices

This article discusses the dialogic nature of regulating perspectives on a controversial topic during students’ argumentative writing in remote teaching. The emerging collaborative writing processes mediated by digital technology are importantly changed as responses to physical distancing in education, as demanded by the measures of biosecurity established by the national government to prevent the transmission of COVID-19. Our analysis is framed in a sociocultural perspective, which contributes to our understanding of the concepts related to dialogism, regulation, positionings on a topic, collaborative writing, and digital technology as a tool for dialogic interaction. Our qualitative, idiographic study analyzes the argumentative utterances produced by a dyad of students enrolled in a Textual Production course at a Colombian public university who write a critical commentary over four (4) weeks using Google Docs application. The findings indicate that the participants discuss and negotiate decisions in the group writing situation and that during this dialogic interaction, the ideas are influenced by the thoughts of the other. When they communicate with each other, their discourses regulate their positionings on the social situation that is the subject of the dialogue. It is also possible to identify both the possibilities of the pedagogical mode and its potential limitations for dialogic interaction, which synchronously and asynchronously facilitate or restrict the performance of the joint writing activity. It can be concluded that within the framework of remote teaching, digital technology has become a flexible mode of pedagogical practice that supports dialogic interaction, enables regulation among peers for discussion, negotiation, and positioning on a topic, and facilitates the construction of collective knowledge that emerges in argumentative collaborative writing.
The complete chloroplast genome sequence of Convallaria majalis L.

Abstract The complete chloroplast genome of an important medicinal plant, Convallaria majalis Linnaeus, was sequenced for the first time. The entire circular genome is 162,218 bp in length, with 37.9% GC contents. The genome has consisted of a large single-copy region (LSC) with a length of 85,417 bp, a small single-copy region (SSC) with a length of 18,495 bp, and two inverted repeat regions (IRs) with a length of 29,153 bp each. The genome harbored 133 genes, including 87 protein coding genes, 38 tRNA genes, and eight rRNA genes. The phylogenetic tree of 24 plant species was constructed based on the maximum-likelihood method. This study will provide theoretical basis for further study on plant genetics phylogenetic research.
Evaluating observed and future spatiotemporal changes in precipitation and temperature across China based on CMIP6‐GCMs

The present study aimed to evaluate the performance of 46 global climate models (GCMs) from the newly released Coupled Model Intercomparison Project Phase 6 (CMIP6) in the historical simulation of precipitation and temperature, and select the best performing GCMs for future projection across China and three major river basins. This study uses four shared socioeconomic pathways (SSPs), namely SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5 relative to the base period (1961–2014). Initially, 46 models were evaluated across China employing an improved Taylor diagram method. Based on relatively better performance, 10 best‐performing models (TBMs) were selected out of 46 models for further evaluation. The results show that historical temperature was well reproduced by CMIP6 over the study regions with a high correlation coefficient (CC). All the TBMs produced good CC ranging from 0.8 to 0.99 presenting the precipitation and temperature distribution well. Meanwhile, EC‐Earth3 and EC‐Earth3‐Veg well simulated the precipitation and temperature amounts as well as trends over selected three river basins. The multimodel ensemble mean (MME) underestimates temperature over China and selected three basins with bias values of −0.53, −0.21, −0.91, and −0.68°C, respectively. In contrast, MEM overestimated the simulated precipitation with the amount of 27.7, 32.4, 21.0, and 104.6% across China and selected three basins. During future projections, increased precipitation and temperature trends are projected over three selected river basins as well as all across China. The increasing trend of future precipitation over China under SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5 scenarios are 0.65, 0.86, 1.29, and 0.76 mm·a−1, whereas, the increasing trend of temperature is 0.008, 0.028, 0.050, and 0.065°C·a−1, respectively. Comparatively, the greater the radiation force, the higher projected increases in precipitation and temperature across China and three major river basins were observed. The extent of CMIP6 models over the target region and its river basins calls for further deep assessment of the attribution and possible implementation of robust methods that can accurately simulate the observed patterns for future practice.
Trace H2S Promotes Organic Aerosol Production and Organosulfur Compound Formation in Archean Analog Haze Photochemistry Experiments

Organic haze and sulfur gases are ubiquitous in planetary atmospheres and were likely present in Earth's Archean atmosphere. Currently, there are few experiments investigating how H2S influences organic haze chemistry on Archean Earth. Here, we present results from laboratory haze‐analog experiments probing the role of H2S in the composition and total mass of aerosol produced from precursor mixtures of Archean‐like gas fluxes (e.g., pCO2 ∼3–50xPAL). We show that trace H2S enhances organic aerosol production at all carbon dioxide mixing ratios studied, and we observe both organic and inorganic sulfur aerosol products. Our finding challenges predictions that H2SO4 and S8 were the primary sulfur reservoirs in Earth's Archean atmosphere, and these results suggest that inorganic sulfur and organic haze chemistry are tightly coupled during the formation of organic hazes in the atmospheres of the Archean Earth and likely Archean‐like exoplanets.
Pahicmetria, a Model of Metric in Environmental Hydric Planning

This paper considers the abstraction of a parametric model of environmental planning in a watershed (expressed in processes, complex patterns, and UML diagrams), as an element for decision-making using tools ORs, which facilitates the model and implements an environmental planning water. This management strategy set during the planning of water resources, represented in ArchiMate, offers a model of integrated metric parameters and elements for proper planning that make up the actors in a watershed. KeywordsSoftware Engineering; Environmental Planning; Treatment Plants; Municipal Wastewater; Life Cycle Analysis
Lyso-IP: Uncovering Pathogenic Mechanisms of Lysosomal Dysfunction

Lysosomes are ubiquitous membrane-bound organelles found in all eukaryotic cells. Outside of their well-known degradative function, lysosomes are integral in maintaining cellular homeostasis. Growing evidence has shown that lysosomal dysfunction plays an important role not only in the rare group of lysosomal storage diseases but also in a host of others, including common neurodegenerative disorders, such as Alzheimer disease and Parkinson disease. New technological advances have significantly increased our ability to rapidly isolate lysosomes from cells in recent years. The development of the Lyso-IP approach and similar methods now allow for lysosomal purification within ten minutes. Multiple studies using the Lyso-IP approach have revealed novel insights into the pathogenic mechanisms of lysosomal disorders, including Niemann-Pick type C disease, showing the immense potential for this technique. Future applications of rapid lysosomal isolation techniques are likely to greatly enhance our understanding of lysosomal dysfunction in rare and common neurodegeneration causes.